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Submitted publications | Articles | Technical reports | Book chapters | Conference contributions

Submitted publications


Anthes K, Peter C, Nauss T, Ammoneit R (submitted)
SSP-Model – A metaconcept of knowledge-reconstruction to promote teachers’ professionalization at university. Journal of International research in geographical and environmental education.

Abstract: Teacher students need to be prepared to deal with topics in a subject related professional, specialised and educational way. They have to reflect their everyday knowledge, their pre-conceptions or (incorrect) beliefs of content knowledge and connect it to the knowledge gained at university, also to understand its complexity. To handle this challenge, a scale-space-place based development model (SSP-Model) containing geographical key concepts for complexity reduction of topics in a sufficient way was created. It is a tool to transfer students’ pre-conceptions into more scientific alternatives, by structuring and grasping the essential geographical content within any topic from a geographical man/environment perspective.


Peter C, Nauss T (submitted)
Nature of models in Geography and Geography education.
Journal of Geography in Higher Education

Abstract: Science and education in Geography heavily depends on models, but in a teaching and hence a professionalization context they are primarily utilized from an application and much less from a development perspective which however is the key for a reflexive evaluation of models communicated as e.g. maps, figures or predictions. To provide a theoretical basis on the nature of models which can subsequently be used for the further professionalization of students, teachers and scientific professionals, we present a working model on modelling which exemplifies the dual dimensions of model development a model application as a basis for knowledge generation and education in Geography.


Woellauer S, Nauss T (submitted)
An on-demand processing database system for climate station data.
Computers and Geosciences

Abstract: Small to medium-scale projects by geographers, ecologists or other environmental scientists are generally not backed-up by dedicated computer scientists although all kinds of sensors with non-continuous measurement options are heavily utilized in many research activities. The Tube Database (TubeDB) is intended to offer an easy to operate software system to archive, quality control, query and retrieve time series data in an efficient way. Data import is realized by using raw formats as recorded by the respective sensors. When a user requests data, a query to an on-demand processing unit is created that builds an individual processing graph with the raw data as a source. The processing graph may consist of typical preparation steps for time series data such as temporal aggregation, quality checks, interpolation of missing values and transformations. The user interface is a desktop or web based application to accomplish easy access and on the visualizations of time series and export functionality. In addition, direct HTTP requests can be sent to the API.






Lehnert LW, Meyer H, Obermeier WA, Silva B, Regeling B, Thies B, Bendix J (2018)
Hyperspectral Data Analysis in R: the hsdar-Package.
Journal of Statistical Software

Abstract: Hyperspectral remote sensing is a promising tool for a variety of applications including ecology and geology but also analytical chemistry and medical research. Here, the new hsdar-package for R statistical software is presented, which allows to perform a large va- riety of analysis steps during a typical hyperspectral remote sensing approach. Therefore, the package introduces a new class to efficiently store even large hyperspectral datasets such as hyperspectral cubes within R. The package includes several important hyperspec- tral analysis tools such as continuum removal, normalized ratio indices and integrates two widely used radiation transfer models. Besides this, the package provides methods to directly use the functionality of the caret-package for machine learning tasks. To demon- strate the range of functions of the hsdar-package, two case studies are included. The first one shows the estimation of plant leaf chlorophyll content and the second one the ability to detect cancer in the human larynx from hyperspectral data.


Higginbottom T, Symeonakis E, Meyer H, van der Linden S. (2018) 
Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data.
ISPRS Journal of Photogrammetry and Remote Sensing 139: 88–102. doi: 10.1016/j.isprsjprs.2018.02.010

Abstract: Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies.
Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.


Meyer N, Meyer H, Welp G, Amelung W (2018) 
Soil respiration and its temperature sensitivity: rapid acquisition using mid-infrared spectroscopy.
Geoderma 323: 31-40. doi: 10.1016/j.geoderma.2018.02.031

Abstract: Spatial patterns of soil respiration (SR) and its sensitivity to temperature (Q10) are one of the key uncertainties in climate change research but since their assessment is very time-consuming, large data sets can still not be provided. Here, we investigated the potential of mid-infrared spectroscopy (MIRS) to predict SR and Q10 values for 124 soil samples of diverse land use types taken from a 2868 km² catchment (Rur catchment, Germany/Belgium/Netherlands). Soil respiration at standardized temperature (25°C) and soil moisture (45% of maximum water holding capacity, WHC) was successfully predicted by MIRS coupled with partial least square regression (PLSR, R² = 0.83). Also the Q10 value was predictable by MIRS-PLSR for a grassland submodel (R² = 0.75) and a cropland submodel (R² = 0.72) but not for forested sites (R² = 0.03). In order to provide soil respiration estimates for arbitrary conditions of temperature and soil moisture, more flexible models are required that can handle nonlinear and interacting relations. Therefore, we applied a random forest model, which includes the MIRS spectra, temperature, soil moisture, and land use as predictor variables. We could show that SR can be simultaneously predicted for any temperature (5-25°C) and soil moisture level (30-75% of WHC), indicated by a high R² of 0.73. We conclude that the combination of MIRS with sophisticated statistical prediction tools allows for a novel, rapid acquisition of SR and Q10 values across landscapes and thus to fill an important data gap in the validation of large scale carbon modeling.


Meyer H, Reudenbach C, Hengl T, Katurji M, Nauß T (2018)
Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation.
Environmental Modelling & Software 101: 1-9. doi: 10.1016/j.envsoft.2017.12.001

Abstract: Importance of target-oriented validation strategies for spatio-temporal prediction models is illustrated using two case studies: (1) modelling of air temperature (Tair) in Antarctica, and (2) modelling of volumetric water content (VW) for the R.J. Cook Agronomy Farm, USA. Performance of a random k-fold cross-validation (CV) was compared to three target-oriented strategies: Leave-Location-Out (LLO), Leave-Time-Out (LTO), and Leave-Location-and-Time-Out (LLTO) CV. Results indicate that considerable differences between random k-fold (R² = 0.9 for Tair and 0.92 for VW) and target-oriented CV (LLO R² = 0.24 for Tair and 0.49 for VW) exist, highlighting the need for target-oriented validation to avoid an overoptimistic view on models. Differences between random k-fold and target-oriented CV indicate spatial over-fitting caused by misleading variables. To decrease over-fitting, a forward feature selection in conjunction with target-oriented CV is proposed. It decreased over-fitting and simultaneously improved target-oriented performances (LLO CV R² = 0.47 for Tair and 0.55 for VW).




Gottwald J, Appelhans T, Adorf F, Hillen J, Nauss T (2017)
High-Resolution MaxEnt Modelling of Habitat Suitability for Maternity Colonies of the Barbastelle Bat Barbastella barbastellus (Schreber, 1774) in Rhineland-Palatinate, Germany.
Acta Chiropterologica 19(2): 389-398. doi: 10.3161/15081109ACC2017.19.2.015

Abstract: The barbastelle bat Barbastella barbastellus (Schreber, 1774), probably one of the rarest of western European bat species, has suffered from substantial population declines over the last several decades. In fact, it was believed to be extinct within the federal state of Rhineland-Palatinate (western Germany) until the discovery of a maternity colony in 2004. More reproduction sites have since been found, which demonstrates a substantial knowledge gap about the actual distribution and abundance of the species in Rhineland-Palatinate. Suitable habitats for maternity colonies are crucial for the survival of a population and knowledge of their location is critical for conservation. We modelled the suitability of habitats for use by maternity colonies in Rhineland-Palatinate based on high-resolution data of the forest structure and roosting sites of maternity colonies, using the presence-only machine learning approach MaxEnt. In addition to statistical tests of the model performance, we analysed general occurrence surveys from the last few years for evidence of barbastelle and conducted an in-situ survey on one of the sites identified as highly suitable by the model, but for which no occurrence records exist. On this site, we discovered a new maternity colony. Analysis of third-party surveys resulted in two recently discovered colonies, which shows the barbastelle's range is not restricted to the area south of the Moselle River. The results of our study along with the scattered pattern of potentially suitable locations for maternity colonies in the region challenge previous assumptions of the geographic distribution of barbastelle in Rhineland-Palatinate. This study demonstrates the potential of habitat suitability modelling in conservation ecology and the results may provide a basis for future preservation strategies in the region.


Gütlein A, Zistl-Schlingmann M, Becker J, Sierra Cornejo N, Detsch F, Dannemann M, Appelhans T, Hertel D, Kuzyakov Y, Kiese R (2017)
Nitrogen turnover and greenhouse gas emissions in a tropical alpine ecosystem, Mt. Kilimanjaro, Tanzania.
Plant and Soil 411: 243-259. doi: 10.1007/s11104-016-3029-4

Abstract: Tropical alpine ecosystems are identified as the most vulnerable to global environmental change, yet despite their sensitivity they are among the least studied ecosystems in the world. Despite its important role in constraining potential changes to the carbon balance, soil nitrogen (N) turnover and plant availability in high latitude and high altitude ecosystems is still poorly understood. Here we present a first time study on a tropical alpine  Helichrysum  ecosystem at Mt. Kilimanjaro, Tanzania, which lies at an altitude of 3880 m. Vegetation composition is characterized and major gross N turnover rates are investigated using the  15N pool dilution method for three different vegetation cover types. In addition greenhouse gas exchange (CO2, N2O and CH4) was manually measured using static chambers. Gross N turnover rates and soil CO2  and N2O emissions were generally lower than values reported for temperate ecosystems, but similar to tundra ecosystems. Gross N mineralization, NH4+  immobilization rates, and CO2  emissions were significantly higher on densely vegetated plots than on sparsely vegetated plots. Relative soil N retention was high and increased with vegetation cover, which suggests high competition for available soil N between microbes and plants. Due to high percolation rates, irrigation/rainfall has no impact on N turnover rates and greenhouse gas (GHG) emissions. While soil N2O fluxes were below the detection limit at all plots, soil respiration rates and CH4  uptake rates were higher at the more densely vegetated plots. Only soil respiration rates followed the pronounced diurnal course of air and soil temperature. Overall, our data show a tight N cycle dominated by closely coupled ammonification-NH4+-immobilization, which is little prone to N losses. Warming could enhance vegetation cover and thus N turnover; however, only narrower C:N ratios due to atmospheric nitrogen deposition may open the N cycle of  Helichrysum  ecosystems.



Detsch F, Otte I, Appelhans T, Nauss T (2017)
A glimpse at short-term controls of evapotranspiration along the southern slopes of Kilimanjaro
Environmental Monitoring and Assessment 189: 465. doi:10.1007/s10661-017-6179-9

Abstract: Future climate characteristics of the southern Kilimanjaro region, Tanzania, are mainly determined by local land-use and global climate change. Reinforcing increasing dryness throughout the twentieth century, ongoing land transformation processes emphasize the need for a proper understanding of the regional-scale water budget and possible implications on related ecosystem functioning and services. Here, we present an analysis of scintillometer-based evapotranspiration (ET) covering seven distinct habitat types across a massive climate gradient from the colline savanna woodlands to the upper-mountain Helichrysum zone (940 to 3960 m.a.s.l.). Random forest-based mean variable importance indicates an outstanding significance of net radiation (Rnet) on the observed ET across all elevation levels. Accordingly, topography and frequent cloud/fog events have a dampening effect at high elevations, whereas no such constraints affect the energy and moisture-rich submontane coffee/grassland level. By contrast, long-term moisture availability is likely to impose restrictions upon evapotranspirative net water loss in savanna, which particularly applies to the pronounced dry season. At plot scale, ET can thereby be approximated reasonably using (Rnet), soil heat flux, and to a lesser degree, vapor pressure deficit and rainfall as predictor variables (R² 0.59 to 1.00). While multivariate regression based on pooled meteorological data from all plots proves itself useful for predicting hourly ET rates across a broader range of ecosystems (R² = 0.71), additional gains in explained variance can be achieved when vegetation characteristics as seen from the NDVI are considered (R² = 0.87). To sum up, our results indicate that valuable insights into land cover-specific ET dynamics, including underlying drivers, may be derived even from explicitly short-term measurements in an ecologically highly diverse landscape.


Otte I, Detsch F, Gütlein A, Scholl M, Kiese R, Appelhans T, Nauss T (2017)
Seasonality of stable isotope composition of atmospheric water input at the southern slopes of Mt. Kilimanjaro, Tanzania.
Hydrological Processes 31, 3932-3947. doi:10.1002/hyp.11311

Abstract:To understand the moisture regime at the southern slopes of Mt. Kilimanjaro, we analyzed the isotopic variability of oxygen (δ18O) and hydrogen (δD) of rainfall, throughfall and fog from a total of 2,140 samples collected weekly over two years at nine study sites along an elevation transect ranging from 950 m a.s.l. to 3,880 m a.s.l.. Precipitation in the Kilimanjaro tropical rainforests consists of a combination of rainfall, throughfall and fog. We defined Local Meteoric Water Lines (LMWL) for all three precipitation types individually and the overall precipitation (δDprec = 7.45(± 0.05) x δ18Oprec + 13.61(± 0.20) (n = 2,140; R² = 0.91, p < 0.001).
We investigated the precipitation type specific stable isotope composition and analyzed effects of amount, altitude and temperature. Aggregated annual mean values revealed isotope composition of rainfall as most depleted and fog water as most enriched in heavy isotopes at the highest elevated research site. We found an altitude effect of δ18Orain = -0.12 ‰ * 100 m-1, which varies according to precipitation type and season. The relatively weak altitude effect may reveal two different moisture sources in the research area: (i) local moisture recycling and (ii) regional moisture sources. Generally, the seasonality of δ18Orain values follows the bimodal rainfall distribution under the influences of south- and northeasterly trade winds. These seasonal patterns of isotopic composition were linked to different regional moisture sources by analyzing HYSPLIT backward trajectories. Seasonality of d excess values revealed evidence of enhanced moisture recycling after the onset of the rainy seasons. This comprehensive dataset is essential for further research using stable isotopes as a hydrological tracer of sources of precipitation that contribute to water resources of the Kilimanjaro region.


Ferger S, Peters M, Appelhans T, Detsch F, Hemp A, Nauss T, Otte I, Böhning-Gaese K,
Schleuning M (2017)
Synergistic effects of climate and land use on avian beta diversity.
Diversity and Distributions. doi:10.1111/ddi.12615

Abstract: Gradients in climate and land use occur simultaneously in many of the Earth’s ecosystems and thus collectively impact most ecological communities. Albeit climate and land use have potentially interacting effects on ecological communities that may exacerbate or ameliorate their individual effects, little is known about the effect of the climate-land use interaction on community composition. A better understanding of the interaction between climate and land use is essential to predict the impacts of environmental change on ecological communities. We quantified the community composition of birds on 64 study plots of 13 different habitat types along an elevational gradient from 870 to 4550 m a.s.l. at Mt. Kilimanjaro in Tanzania. We partitioned the variation in pairwise beta diversity (ßcc) of birds and its two additive components, species richness differences (ßrich) and species replacement (ß-3), among the effects of temperature, land-use intensity and their interaction. Temperature and land use had synergistic effects on beta diversity (ßcc) of birds, i.e. the combination of high temperature and high land-use intensity led to higher beta diversity than expected from the sum of both individual effects. While temperature explained more of the variation in species richness differences(ßrich), land use explained more of the variation in species replacement (ß-3), indicating that different processes drove avian beta diversity along the temperature and land-use gradients. Our results challenge previous studies that investigated the effects of climate and land use in isolation, because disregarding their synergistic interaction underestimates the joint effect of climate and land use on biodiversity. A consideration of the synergy between climate and land use is essential for adequate predictions of the impact of global change on biodiversity.


Meyer H, Drönner J, Nauss T (2017)
Satellite-based high-resolution mapping of rainfall over southern Africa.
Atmospheric Measurement Techniques 10: 2009-2019. doi:  10.5194/amt-10-2009-2017

Abstract: A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Rainfall measurements from about 350 weather stations from 2010–2014 served as ground truth for calibration and validation. SEVIRI and weather station data were used to train neural networks that allowed the estimation of rainfall area and rainfall quantities over all times of the day. The results revealed that 60 % of recorded rainfall events were correctly classified by the model (probability of detection, POD). However, the false alarm ratio (FAR) was high (0.80), leading to a Heidke skill score (HSS) of 0.18. Estimated hourly rainfall quantities were estimated with an average hourly correlation of ρ= 0. 33 and a root mean square error (RMSE) of 0.72. The correlation increased with temporal aggregation to 0.52 (daily), 0.67 (weekly) and 0.71 (monthly). The main weakness was the overestimation of rainfall events. The model results were compared to the Integrated Multi-satellitE Retrievals for GPM (IMERG) of the Global Precipitation Measurement (GPM) mission. Despite being a comparably simple approach, the presented MSG-based rainfall retrieval outperformed GPM IMERG in terms of rainfall area detection: GPM IMERG had a considerably lower POD. The HSS was not significantly different compared to the MSG-based retrieval due to a lower FAR of GPM IMERG. There were no further significant differences between the MSG-based retrieval and GPM IMERG in terms of correlation with the observed rainfall quantities. The MSG-based retrieval, however, provides rainfall in a higher spatial resolution. Though estimating rainfall from satellite data remains challenging, especially at high temporal resolutions, this study showed promising results towards improved spatio-temporal estimates of rainfall over southern Africa.


Meyer H, Kühnlein M, Reudenbach C, Nauss T (2017)
Revealing the potential of spectral and texture predictor variables in a neural network based rainfall retrieval technique.
Remote Sensing Letters 8: 647-656. doi: 10.1080/2150704X.2017.1312026

Abstract: Estimating rainfall areas and rates from geostationary satellite images has the opportunity of both, a high spatial and a high temporal resolution which cannot be achieved by other satellite-based systems until now.
Most recent retrieval techniques are solely based on spectral channels of the satellites. These retrievals can be classified as "purely pixel-based" because no information about the neighbourhood pixels is included. Assuming that precipitation is highly correlated with cloud processes and therefore with cloud texture, textural information derived from the neighbourhood of a pixel might give valuable information about the cloud type and hence about a respective probability of the rainfall rate.
To study the potential of textural variables to improve optical rainfall retrieval techniques, rainfall areas and rainfall rates were estimated over Germany for the year 2010 using a neural network approach. In addition to the spectral predictor variables from Meteosat Second Generation (MSG), different Grey Level Co-occurance Matrix (GLCM) based textural variables were calculated from all MSG channels. Using recursive feature selection, models were trained and their performance was compared to spectral-only models.
Contrary to the expectations, the performance of the models did not increase when textural information was included.


Otte I, Detsch F, Mwangomo E, Hemp A, Appelhans T, Nauss T (2017)
Multidecadal trends and interannual variability of rainfall as observed from five lowland stations at Mt. Kilimanjaro, Tanzania.
Journal of Hydrometeorology 18: 349-361. doi: 10.1175/JHM-D-16-0062.1

Abstract: Future rainfall dynamics in the Kilimanjaro region will mainly be influenced by both global climate and local land-cover change. An increase in rainfall is expected, but also rising temperatures are predicted for the ecosystem. In-situ rainfall of five stations is analyzed to determine seasonal variability and multi-decadal trends in the lowlands and lower elevations of the Kilimanjaro region. Monthly rainfall totals are obtained from the Tanzanian Meteorological Agency, from two mission stations and from a sugar cane plantation. The datasets of the two missions cover a time span of 64 and 62 years, starting in 1940 and 1942, while rainfall data obtained from the Tanzanian Meteorological Agency and from the sugar cane plantation starts in 1973 and 1974 and thus cover 40-41 years. In one out of five stations a significant weak negative linear long-term trend in rainfall is observable, which is also evident in the other locations, although not significant. However, humid and dry decades are evident and seasonality has changed especially during the long rains between March and May. El Niño-Southern Oscillation (ENSO) in combination with positive Indian Ocean Dipole (IOD) leads to enhanced rainfall during the year of ENSO onset and the following year. During La Nin~a years, rainfall increases in the following year, while during the onset year rainfall patterns are more diverse. Positive IOD leads to enhanced rainfall amounts.


Meyer H, Lehnert WL, Wang Y, Reudenbach C, Nauss T, Bendix J (2017)
From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?
International Journal of Applied Earth Observation and Geoinformation 55: 21–31. doi: 10.1016/j.jag.2016.10.001

Abstract: Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the applicability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional scales. Using machine learning techniques, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate pasture degradation proxies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to high resolution multispectral satellite data is assessed. 1183 Hyperspectral measurements and vegetation records were performed at 18 locations on the QTP. Random Forests models with recursive feature selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predictors. Separate models were calculated using NBI from hyperspectral data as well as from the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used (cross validated R2~ 0.89). In contrast, errors in AGB estimations were considerably higher (cross validated R2 ~ 0.32). Only small differences in accuracy were observed between the models based on hyperspectral compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying \textit{in situ} measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP. Thus, this study presents robust methodology to remotely detect and monitor pasture degradation at high spatial resolutions.



Peters MK, Hemp A, Appelhans T, Behler C, Classen A, Detsch F, Ensslin A, Ferger SW, Frederiksen SB, Gebert F, Haas, Helbig-Bonitz M, Hemp C, Kindeketa WJ, Mwangomo E, Ngereza C, Otte I, Röder J, Rutten G, Schellenberger Costa D, Tardanico J, Zancolli G, Deckert J, Eardley CD, Peters RS, Rödel MO, Schleuning M, Ssymank A, Kakengi V, Zhang J, Böhning-Gaese K, Brandl R, Kalko EKV, Kleyer M, Nauss T, Tschapka M, Fischer M, Steffan-Dewenter I (2016)
Predictors of elevational biodiversity gradients change from single taxt to the multi-taxa community level.
Nature Communications 7:13736. doi: 10.1038/ncomms13736

Abstract: The factors determining gradients of biodiversity are a fundamental yet unresolved topic in ecology. While diversity gradients have been analyzed for numerous single taxa, progress toward general explanatory models has been hampered by limitations in the phylogenetic coverage of past studies. By parallel sampling 21 major plant and animal taxa along a 3.7 km elevational gradient at Mount Kilimanjaro we quantify cross-taxon consensus in diversity gradients and evaluate predictors of diversity from single taxa to the multi-taxa community level. While single taxa showed complex distribution patterns and responded to different environmental factors, scaling up diversity to the community level lead to an unambiguous support of mean annual temperature as the main predictor of species richness in both plants and animals. Our findings show the value of multi-taxa studies to identify general explanations of diversity gradients and support the importance of temperature-dependent evolutionary and ecological processes for diversification and species coexistence.


Meyer H, Katurji M, Appelhans T, Müller M, Nauss T, Roudier P, Zawar-Reza P (2016)
Mapping daily air temperature for Antarctica based on MODIS LST.
Remote Sensing, 8, 732. doi:10.3390/rs8090732

Abstract: Spatial predictions of near-surface air temperature ( Tair ) in Antarctica are required as baseline information for a variety of research disciplines. Since the network of weather stations in Antarctica is sparse, remote sensing methods have large potential due to their capabilities and accessibility. Based on the MODIS land surface temperature (LST) data, Tair at the exact time of satellite overpass was modelled at a spatial resolution of 1 km using data from 32 weather stations. The performance of a simple linear regression model to predict Tair from LST was compared to the performance of three machine learning algorithms: Random Forest (RF), generalized boosted regression models (GBM) and Cubist. In addition to LST, auxiliary predictor variables were tested in these models. Their relevance was evaluated by a Cubist-based forward feature selection in conjunction with leave-one-station-out cross-validation to reduce the impact of spatial overfitting. GBM performed best to predict Tair using LST and the month of the year as predictor variables. Using the trained model, Tair could be estimated with a leave-one-station-out cross-validated R2 of 0.71 and a RMSE of 10.51 ° C. However, the machine learning approaches only slightly outperformed the simple linear estimation of Tair from LST ( R2 of 0.64, RMSE of 11.02 ° C). Using the trained model allowed creating time series of Tair over Antarctica for 2013. Extending the training data by including more years will allow developing time series of Tair from 2000 on.


Röder J, Detsch F, Otte I, Appelhans T, Nauss T, Brandl R (2016)
Heterogeneous patterns of abundance of epigeic arthropod lineages along a major elevation gradient.
Biotropica doi: 10.1111/btp.12403

Abstract: Species diversity is the most common variable reported in recent ecological research articles. Ecological processes, however, are driven by individuals. High abundances make arthropods, despite their small body sizes, important actors in food webs. Understanding the variation in animal abundances along climatic gradients is important for predicting changes in ecosystem processes under global warming. Despite this, data on abundance distributions of major arthropod taxa along climatic gradients remains poorly documented. We sampled arthropod assemblages in disturbed and undisturbed vegetation types along an elevation gradient of 860-4550m asl on the southern slopes of Mt. Kilimanjaro, Tanzania. In our analysis, we focused on 13 taxa of arthropods that represented three major functional groups: predators, herbivores and decomposers. Most of the taxa showed unimodal patterns of abundance with peaks at low elevations. When taxa were assigned to functional groups, abundance in undisturbed sites was largest in lower montane forest for all groups. In disturbed sites, abundance declined linearly, except for decomposers, who showed another peak in the land-use zone. When we assigned beetles to functional groups, however, decomposers showed almost linear decline, and predators (ca. 2400m asl) and herbivores (ca. 3000m asl) showed unimodal patterns with peaks a lot further up the slope, at least in undisturbed sites. Temperature, not primary productivity, was the best predictor for abundance for most of the taxa and groups. Disturbance was only of minor importance. In conclusion, we found different trends in the response of arthropod abundance along the elevation gradient which depended on the level of taxonomic and functional resolution. This highlights the need for more comparisons of different taxa along the same climatic gradients.


Messenzehl K, Meyer H, Otto J-C, Hoffmann T, Dikau R (2016)
Regional-scale controls on the spatial activity of rockfalls (Turtmann Valley, Swiss Alps) — A multivariate modeling approach.
Geomorphology doi: http://dx.doi.org/10.1016/j.geomorph.2016.01.008

Abstract: In mountain geosystems, rockfalls are among the most effective sediment transfer processes, reflected in the regional-scale distribution of talus slopes. However, the understanding of the key controlling factors seems to decrease with increasing spatial scale, due to emergent and complex system behavior and not least to recent methodological shortcomings in rockfall modeling research. In this study, we aim (i) to develop a new approach to identify major regional-scale rockfall controls and (ii) to quantify the relative importance of these controls. Using a talus slope inventory in the Turtmann Valley (Swiss Alps), we applied for the first time the decision-tree based random forest algorithm (RF) in combination with a principal component logistic regression (PCLR) to evaluate the spatial distribution of rockfall activity. This study presents new insights into the discussion on whether periglacial rockfall events are controlled more by topo-climatic, cryospheric, paraglacial or/and rock mechanical properties.


Ludwig A, Meyer H, Nauss T (2016)
Automatic classification of Google Earth images for a larger scale monitoring of bush encroachment in South Africa.
International Journal of Applied Earth Observation and Geoinformation 50:89–94. doi: http://dx.doi.org/10.1016/j.jag.2016.03.003

Abstract: Bush encroachment of savannas and grasslands is a common form of land degradation in the rangelands of South Africa. To assess the carrying capacity of the land and to understand underlaying processes of bush encroachment, continuous monitoring of this phenomenon is needed. The aim of this study is to provide training sites for satellite-based monitoring of bush encroachment in South Africa on a medium spatial resolution satellite sensor (e.g. MODIS or Landsat) scale. Since field surveys are time consuming and of limited spatial extent, the satellite based creation of training sites using Google Earth images is intended. Training pixels for woody vegetation and non-woody land cover were manually digitized from 50 sample Google Earth images. A Random Forests model was trained to delineate woody from non-woody pixels. The results indicate a high performance of the model (AUC = 0.97). The model was applied to a further 500 Google Earth images with a spatial extent of 250 m × 250 m. The classified images form the database of training sites which can be used for larger scale monitoring of bush encroachment in South Africa.


Meyer H, Kühnlein M, Appelhans T, Nauss T (2016)
Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals.

Atmospheric Research 169, Part B:424–433. doi: 10.1016/j.atmosres.2015.09.021

Abstract: Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms — random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) — for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.


Detsch F, Otte I, Appelhans T, Nauss T (2016)
A comparative study of cross-product NDVI dynamics in the Kilimanjaro region – a matter of sensor, degradation calibration, and significance.
Remote Sensing 8:159. doi: 10.3390/rs8020159

Abstract: While satellite-based monitoring of vegetation activity at the earth's surface is of vital importance for many eco-climatological applications, the degree of agreement among certain sensors and products providing estimates of the Normalized Difference Vegetation Index (NDVI) has been found to vary considerably. In order to assess the extent of such differences in highly heterogeneous terrain, we analyze and compare intra-annual seasonal fluctuations and long-term monotonic trends (2003–2012) in the Kilimanjaro region, Tanzania. The considered NDVI datasets include the Moderate Resolution Imaging Spectroradiometer (MODIS) products from Terra and Aqua, Collections 5 and 6, and the 3rd Generation Global Inventory Modeling and Mapping Studies (GIMMS) product. The degree of agreement in seasonal fluctuations is assessed by calculating a pairwise Index of Association (IOAs), whereas long-term trends are derived from the trend-free pre-whitened Mann–Kendall test. On the seasonal scale, the two Terra-MODIS products (and, accordingly, the two Aqua-MODIS products) are best associated with each other, indicating that the seasonal signal remained largely unaffected by the new Collection 6 calibration approach. On the long-term scale, we find that the negative impacts of band ageing on Terra-MODIS NDVI have been accounted for in Collection 6, which now distinctly outweighs Aqua-MODIS in terms of greening trends. GIMMS NDVI, by contrast, fails to capture small-scale seasonal and trend patterns that are characteristic for the highly fragmented landscape which is likely owing to the coarse spatial resolution. As a short digression, we also demonstrate that the amount of false discoveries in the determined trend fraction is distinctly higher for p < 0.05 ( 52.6 % ) than for p < 0.001 ( 2.2 % ) which should point the way for any future studies focusing on the reliable deduction of long-term monotonic trends.


Detsch F, Otte I, Appelhans T, Hemp A, Nauss T (2016)
Seasonal and long-term vegetation dynamics from 1-km GIMMS-based NDVI time series at Mt. Kilimanjaro, Tanzania.
Remote Sensing of Environment 178:70–83. doi: 10.1016/j.rse.2016.03.007

Abstract: Vegetation dynamics in the Kilimanjaro region, Tanzania, are subject to (i) global climate change and (ii) local land-cover change resulting from natural or anthropogenic disturbance. While recent climate models predict rising temperatures over East Africa throughout the 21st century, effects of land-use change on the local-scale water budget and, related therewith, on vegetation response are much more diverse. In addition, sea surface temperature anomalies in the Pacific (El Niño Southern Oscillation, ENSO) and Indian Ocean (Indian Ocean Dipole, IOD) are known to severely impact rainfall patterns and vegetation activity in the study area and possibly reinforce each other. Here we present long-term and seasonal vegetation dynamics derived from a GIMMS-based NDVI record resampled to 1 km spatial resolution and covering a 30-year period (1982–2011). In the long term, most of the upper mountain regions showed positive trends which was mainly attributed to vegetation recovery after disastrous fires during the outgoing 20th century. Along the western mountainside, by contrast, strong negative trends emerged as a consequence of fire-driven downward migration of Erica bush along the upper slopes and massive land conversion processes affecting the lower slopes. On the seasonal scale, a strong dependence of the regional vegetation on the effects of ENSO/IOD teleconnections became evident. Similar to previous findings on rainfall, the most beneficial effects occurred during concurrent El Niño/IOD events, while the impacts of La Niña were far less pronounced. To sum up, the newly created 1-km NDVI record proved capable of capturing long-term and seasonal vegetation patterns, which particularly applies for large-scale teleconnections, and thus provides an invaluable archive of decadal-scale vegetation dynamics in the study area.


Appelhans T, Nauss T (2016)
Spatial patterns of sea surface temperature influences on east african precipitation as revealed by empirical orthogonal teleconnections.
Atmospheric Science 3. doi: 10.3389/feart.2016.00003

Abstract: East Africa is characterized by a rather dry annual precipitation climatology with two distinct rainy seasons. In order to investigate sea surface temperature driven precipitation anomalies for the region we use the algorithm of empirical orthogonal teleconnection analysis as a data mining tool. We investigate the entire East African domain as well as 5 smaller sub-regions mainly located in areas of mountainous terrain. In searching for influential sea surface temperature patterns we do not focus any particular season or oceanic region. Furthermore, we investigate different time lags from 0 to 12 months. The strongest influence is identified for the immediate (i.e., non-lagged) influences of the Indian Ocean in close vicinity to the East African coast. None of the most important modes are located in the tropical Pacific Ocean, though the region is sometimes coupled with the Indian Ocean basin. Furthermore, we identify a region in the southern Indian Ocean around the Kerguelen Plateau which has not yet been reported in the literature with regard to precipitation modulation in East Africa. Finally, it is observed that not all regions in East Africa are equally influenced by the identified patterns.




Lehnert LW, Meyer H, Wang Y, Miehe G, Thies B, Reudenbach C, Bendix J (2015)
Retrieval of grassland plant coverage on the Tibetan Plateau based on a multi-scale, multi-sensor and multi-method approach.
Remote Sensing of Environment 164:197–207. doi: http://dx.doi.org/10.1016/j.rse.2015.04.020

Abstract: Plant coverage is a basic indicator of the biomass production in ecosystems. On the Tibetan Plateau, the biomass of grasslands provides major ecosystem services with regard to the predominant transhumance economy. The pastures, however, are threatened by progressive degradation, resulting in a substantial reduction in plant coverage with currently unknown consequences for the hydrological/climate regulation function of the plateau and the major river systems of SE Asia that depend on it and provide water for the adjacent lowlands. Thus, monitoring of changes in plant coverage is of utmost importance, but no reliable tools have been available to date to monitor the changes on the entire plateau. Due to the wide extent and remoteness of the Tibetan Plateau, remote sensing is the only tool that can recurrently provide area-wide data for monitoring purposes. In this study, we develop and present a grassland-cover product based on multi-sensor satellite data that is applicable for monitoring at three spatial resolutions (WorldView type at 2–5 m, Landsat type at 30 m, MODIS at 500 m), where the data of the latter resolution cover the entire plateau. Four different retrieval techniques to derive plant coverage from satellite data in boreal summer (JJA) were tested. The underlying statistical models are derived with the help of field observations of the cover at 640 plots and 14 locations, considering the main grassland vegetation types of the Tibetan Plateau. To provide a product for the entire Tibetan Plateau, plant coverage estimates derived by means of the higher-resolution data were upscaled to MODIS composites acquired between 2011 and 2013. An accuracy assessment of the retrieval methods revealed best results for the retrieval using support vector machine regressions (RMSE: 9.97%, 7.13% and 5.51% from the WorldView to the MODIS scale). The retrieved values coincide well with published coverage data on the different grassland vegetation types.


Classen A, Peters MK, Kindeketa WJ, Appelhans T, Eardley C-D, Gikungu M-W, Hemp A, Nauss T, Steffan-Dewenter I (2015)
Temperature versus resource constraints: which factors determine bee diversity on Mount Kilimanjaro, Tanzania?
Global Ecology and Biogeography 24:642–652. doi: 10.1111/geb.12286

Abstract: Understanding the mechanisms controlling variation in species richness along environmental gradients is one of the most important objectives in ecology. Resource availability is often considered as the major driver of animal diversity. However, in ectotherms, temperature might play a predominant role as it modulates metabolic rates and the access of animals to resources. Here, we investigate the relative importance of resource availability and temperature in determining the diversity pattern of bees along a 3.6-km elevational gradient. We assessed bee species richness and abundance with pan traps and floral resources with transect records on 60 study sites which were equally distributed over six near-natural and six disturbed habitat types along an elevational gradient from 870 to 4550?m a.s.l. We used path analysis to disentangle the effects of temperature, precipitation, floral resource abundance, bee abundance and land use on bee species richness. In addition, we monitored flower visitation rates during transect walks at different elevations to evaluate the temperature dependence of bee–flower interactions. Bee species richness continuously declined with elevation in natural and disturbed habitats. While the abundance of floral resources had a significant but only weak effect on species richness, the effect of temperature was strong. Temperature had a strong positive effect on species richness that was not mediated by bee abundance and an indirect effect via bee abundances. We observed higher levels of bee–flower interactions at higher temperatures, supporting the hypothesis that temperature limits diversity by constraining resource exploitation in ectotherms.


Appelhans T, Mwangomo E, Otte I, Detsch F, Nauss T, Hemp A (2015)
Eco-meteorological characteristics of the southern slopes of Kilimanjaro, Tanzania.
International Journal of Climatology n/a–n/a. doi: 10.1002/joc.4552

Abstract: This study introduces the set-up of a new meteorological station network on the southern slopes of Kilimanjaro, Tanzania, since 2010 and presents the recorded characteristics of air temperature, air humidity and precipitation in both a plot-based and area-wide perspectives. The station set-up follows a hierarchical approach covering an elevational as well as a land-use disturbance gradient. It consists of 52 basic stations measuring ambient air temperature and above-ground air humidity and 11 precipitation measurement sites, with recording intervals of 5?min. With respect to precipitation observations, the network extends the long-term recordings of A. Hemp who has installed and maintained up to 117 multi-month accumulating rainfall buckets in the region since 1997. The meteorological characteristics of the study region based on the derived data since 2010 are mostly in line with previous studies, although we see increased precipitation amounts at higher elevations during these years when compared with long-term means. We furthermore identify a mean annual condensation level at about 2300?m?a.s.l. which has not been reported before. Finally, this is the first study to provide high resolution maps of mean monthly and mean annual temperature, humidity and precipitation for Kilimanjaro, which are of great value for geographically oriented meteorological or ecological investigations. Detailed performance statistics of the geo-statistical and machine learning techniques used for the gap filling of the recorded meteorological time series and their regionalization to the Kilimanjaro region indicate that the presented data sets provide reliable measurements of the meteorological reality at Kilimanjaro.


Appelhans T, Mwangomo E, Hardy D-R, Hemp A, Nauss T (2015)
Evaluating machine learning approaches for the interpolation of monthly air temperature at Mt. Kilimanjaro, Tanzania.
Spatial Statistics 14, Part A:91–113. doi: 10.1016/j.spasta.2015.05.008

Abstract: Spatially high resolution climate information is required for a variety of applications in but not limited to functional biodiversity research. In order to scale the generally plot-based research findings to a landscape level, spatial interpolation methods of meteorological variables are required. Based on a network of temperature observation plots across the southern slopes of Mt. Kilimanjaro, the skill of 14 machine learning algorithms in predicting spatial temperature patterns is tested and evaluated against the heavily utilized kriging approach. Based on a 10-fold cross-validation testing design, regression trees generally perform better than linear and non-linear regression models. The best individual performance has been observed by the stochastic gradient boosting model followed by Cubist, random forest and model averaged neural networks which except for the latter are all regression tree-based algorithms. While these machine learning algorithms perform better than kriging in a quantitative evaluation, the overall visual interpretation of the resulting air temperature maps is ambiguous. Here, a combined Cubist and residual kriging approach can be considered the best solution.


Appelhans T, Detsch F, Nauss T (2015)
remote: Empirical orthogonal teleconnections in R.
Journal of Statistical Software. doi: 10.18637/jss.v065.i10

Abstract: In climate science, teleconnection analysis has a long standing history as a means for describing regions that exhibit above average capability of explaining variance over time within a certain spatial domain (e.g., global). The most prominent example of a global coupled ocean-atmosphere teleconnection is the El Nin ?o Southern Oscillation. There are numerous signal decomposition methods for identifying such regions, the most widely used of which are (rotated) empirical orthogonal functions. First introduced by van den Dool, Saha, and Johansson (2000), empirical orthogonal teleconnections (EOT) denote a regression based approach that allows for straight-forward interpretation of the extracted modes. In this paper we present the R implementation of the original algorithm in the remote package. To highlight its usefulness, we provide three examples of potential use- case scenarios for the method including the replication of one of the original examples from van den Dool et al. (2000). Furthermore, we highlight the algorithms use for cross- correlations between two different geographic fields (identifying sea surface temperature drivers for precipitation), as well as statistical downscaling from coarse to fine grids (using Normalized Difference Vegetation Index fields).


Gasch C.K., Hengl T., Gräler B., Meyer H., Magney T.S., Brown D.J. (2015)
Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D + T: The Cook Agronomy Farm data set. Spatial Statistics 14, Part A, 7

Abstract: The paper describes a framework for modeling dynamic soil properties in 3-dimensions and time (3D + T) using soil data collected with automated sensor networks as a case study. Two approaches to geostatistical modeling and spatio-temporal predictions are described: (1) 3D + T predictive modeling using random forests algorithms, and (2) 3D + T kriging model after detrending the observations for depth-dependent seasonal effects. All the analyses used data from the Cook Agronomy Farm (37 ha), which includes hourly measurements of soil volumetric water content, temperature, and bulk electrical conductivity at 42 stations and five depths (0.3, 0.6, 0.9, 1.2, and 1.5 m), collected over five years. This data set also includes 2- and 3-dimensional, temporal, and spatio-temporal covariates covering the same area. The results of (strict) leave-one-station-out cross-validation indicate that both models accurately predicted soil temperature, while predictive power was lower for water content, and lowest for electrical conductivity. The kriging model explained 37%, 96%, and 18% of the variability in water content, temperature, and electrical conductivity respectively versus 34%, 93%, and 5% explained by the random forests model. A less rigorous simple cross-validation of the random forests model indicated improved predictive power when at least some data were available for each station, explaining 86%, 97%, and 88% of the variability in water content, temperature, and electrical conductivity respectively. The high difference between the strict and simple cross-validation indicates high temporal auto-correlation of values at measurement stations. Temporal model components (i.e. day of the year and seasonal trends) explained most of the variability in observations in both models for all three variables. The seamless predictions of 3D + T data produced from this analysis can assist in understanding soil processes and how they change through a season, under different land management scenarios, and how they relate to other environmental processes.




Lehnert LW, Meyer H, Meyer N, Reudenbach C, Bendix J (2014)
A hyperspectral indicator system for rangeland degradation on the Tibetan Plateau: A case study towards spaceborne monitoring.
Ecological Indicators 39:54–64. doi: http://dx.doi.org/10.1016/j.ecolind.2013.12.005

Abstract: In climate science, teleconnection analysis has a long standing history as a means for describing regions that exhibit above average capability of explaining variance over time within a certain spatial domain (e.g., global). The most prominent example of a global coupled ocean-atmosphere teleconnection is the El Nin ?o Southern Oscillation. There are numerous signal decomposition methods for identifying such regions, the most widely used of which are (rotated) empirical orthogonal functions. First introduced by van den Dool, Saha, and Johansson (2000), empirical orthogonal teleconnections (EOT) denote a regression based approach that allows for straight-forward interpretation of the extracted modes. In this paper we present the R implementation of the original algorithm in the remote package. To highlight its usefulness, we provide three examples of potential use- case scenarios for the method including the replication of one of the original examples from van den Dool et al. (2000). Furthermore, we highlight the algorithms use for cross- correlations between two different geographic fields (identifying sea surface temperature drivers for precipitation), as well as statistical downscaling from coarse to fine grids (using Normalized Difference Vegetation Index fields).


Kühnlein M, Appelhans T, Thies B, Nauss T (2014)
Improving the accuracy of rainfall rates from optical satellite sensors with machine learning – a random forests-based approach applied to MSG SEVIRI.
Remote Sensing of Environment 141:129–143. doi: 10.1016/j.rse.2013.10.026

Abstract: The present study aims to investigate the potential of the random forests ensemble classification and regression technique to improve rainfall rate assignment during day, night and twilight (resulting in 24-hour precipitation estimates) based on cloud physical properties retrieved from Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data. Random forests (RF) models contain a combination of characteristics that make them well suited for its application in precipitation remote sensing. One of the key advantages is the ability to capture non-linear association of patterns between predictors and response which becomes important when dealing with complex non-linear events like precipitation. Due to the deficiencies of existing optical rainfall retrievals, the focus of this study is on assigning rainfall rates to precipitating cloud areas in connection with extra-tropical cyclones in mid-latitudes including both convective and advective-stratiform precipitating cloud areas. Hence, the rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. As predictor variables water vapor-IR differences and IR cloud top temperature are used to incorporate information on cloud top height. ?T8.7–10.8 and ?T10.8–12.1 are considered to supply information about the cloud phase. Furthermore, spectral SEVIRI channels (VIS0.6, VIS0.8, NIR1.6) and cloud properties (cloud effective radius, cloud optical thickness) are used to include information about the cloud water path during daytime, while suitable combinations of temperature differences (?T3.9–10.8, ?T3.9–7.3) are considered during night-time. The development of the rainfall rate retrieval technique is realised in three steps. First, an extensive tuning study is carried out to customise each of the RF models. The daytime, night-time and twilight precipitation events have to be treated separately due to differing information content about the cloud properties between the different times of day. Secondly, the RF models are trained using the optimum values for the number of trees and number of randomly chosen predictor variables found in the tuning study. Finally, the final RF models are used to predict rainfall rates using an independent validation data set and the results are validated against co-located rainfall rates observed by a ground radar network. To train and validate the model, the radar-based RADOLAN RW product from the German Weather Service (DWD) is used which provides area-wide gauge-adjusted hourly precipitation information. Regarding the overall performance, as indicated by the coefficient of determination (Rsq), hourly rainfall rates show already a good correlation with Rsq = 0.5 (day and night) and Rsq = 0.48 (twilight) between the satellite and radar based observations. Higher temporal aggregation leads to better agreement. Rsq rises to 0.78 (day), 0.77 (night) and 0.75 (twilight) for 8-h interval. By comparing day, night and twilight performance it becomes evident that daytime precipitation is generally predicted best by the model. Twilight and night-time predictions are generally less accurate but only by a small margin. This may due to the smaller number of predictor variables during twilight and night-time conditions as well as less favourable radiative transfer conditions to obtain the cloud parameters during these periods. However, the results show that with the newly developed method it is possible to assign rainfall rates with good accuracy even on an hourly basis. Furthermore, the rainfall rates can be assigned during day, night and twilight conditions which enables the estimation of rainfall rates 24 h day.


Thies B, Meyer H, Nauss T, Bendix J (2014)
Projecting land-use and land-cover changes in a tropical mountain forest of Southern Ecuador.
Journal of Land Use Science 9:1–33. doi: 10.1080/1747423X.2012.718378

Abstract: Land-use and land-cover changes (LULCC) affect local climate. Human-induced deforestation is a common phenomenon of LULCC. This also holds true for the biodiversity hotspot in the Andes of Ecuador. This study assesses the possibility to project LULCC to future time steps with a focus on deforestation in the San Francisco valley in South Ecuador. A business-as-usual scenario based on two Landsat scenes from 1987 and 2001 was created to project LULCC until 2006. The uncertainty assessment indicated the difficulty of projecting human impact on the ecosystem since circumstances of LULCC in the study area cannot be assumed to stay invariant. The projection performs better than a naive model relying on slope as its suitability factor.


Kühnlein M, Appelhans T, Thies B, Nauss T (2014)
Precipitation estimates from MSG SEVIRI daytime, nighttime, and twilight data with random forests.
Journal of Applied Meteorology and Climatology 53:2457–2480. doi: 10.1175/JAMC-D-14-0082.1

Abstract: A new rainfall retrieval technique for determining rainfall rates in a continuous manner (day, twilight, and night) resulting in a 24-h estimation applicable to midlatitudes is presented. The approach is based on satellite-derived information on cloud-top height, cloud-top temperature, cloud phase, and cloud water path retrieved from Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and uses the random forests (RF) machine-learning algorithm. The technique is realized in three steps: (i) precipitating cloud areas are identified, (ii) the areas are separated into convective and advective-stratiform precipitating areas, and (iii) rainfall rates are assigned separately to the convective and advective-stratiform precipitating areas. Validation studies were carried out for each individual step as well as for the overall procedure using collocated ground-based radar data. Regarding each individual step, the models for rain area and convective precipitation detection produce good results. Both retrieval steps show a general tendency toward elevated prediction skill during summer months and daytime. The RF models for rainfall-rate assignment exhibit similar performance patterns, yet it is noteworthy how well the model is able to predict rainfall rates during nighttime and twilight. The performance of the overall procedure shows a very promising potential to estimate rainfall rates at high temporal and spatial resolutions in an automated manner. The near-real-time continuous applicability of the technique with acceptable prediction performances at 3–8-hourly intervals is particularly remarkable. This provides a very promising basis for future investigations into precipitation estimation based on machine-learning approaches and MSG SEVIRI data.




Kühnlein M, Appelhans T, Thies B, Kokhanovsky A-A, Nauss T (2013)
An evaluation of a semi-analytical cloud property retrieval using MSG SEVIRI, MODIS and CloudSat.
Atmospheric Research 122:111–135. doi: 10.1016/j.atmosres.2012.10.029

Abstract: Knowledge of cloud properties such as cloud effective radius (aef) and optical thickness (t) is essential to understand their role in the dynamic radiation budget and climate change. The Spinning Enhanced Visible and Infrared Instrument (SEVIRI) on board Meteosat Second Generation (MSG) with its high temporal resolution (15 min), permits a quasi-continuous monitoring of the evolution of cloud properties. This has motivated the adaptation of the SLALOM (SimpLe Approximations for cLOudy Media) algorithm, a semi-analytical cloud property retrieval technique to MSG SEVIRI. The optical properties retrieved by SLALOM are compared against the well known and validated NASA MODIS cloud property product (MODIS 06) as well as the cloud optical depth product (2B-TAU) of CloudSat. The results are shown over the North Atlantic and over the European continent with the intention of determine the relative accuracy between SLALOM and the other retrievals. Over the North Atlantic, SLALOM-based cloud properties retrieved from SEVIRI datasets show a good agreement with the MODIS 06 product with correlation coefficients of 0.93 (t) and 0.82 (aef). The largest deviations were found in less homogeneous cloud areas that are characterized by broken clouds and toward the cloud borders. Moreover, SLALOM optical thickness values are well within the range of corresponding CloudSat 2B-TAU optical thickness values which can be found within a SEVIRI pixel, except for t < 5 where SLALOM tends to overestimate t. Despite the different sensor characteristics and viewing geometries, the retrieved cloud properties compare very well. Over Europe, the evaluation between SLALOM and MODIS 06 showed larger differences. We attribute this to (a) uncertainties related to the surface albedo which is treated differently in the algorithms and is based on different albedo maps and (b) inhomogeneities of clouds which exhibit quite complex structures particularly over land. The latter are detected on different scales by MODIS and SEVIRI because of their different spatial resolutions. Given the demonstrated accuracy of SLALOM using MSG SEVIRI data there is a wide spread of potential applications.




Fries A, Rollenbeck R, Nauss T, Peters T, Bendix J (2012)
Near surface air humidity in a megadiverse Andean mountain ecosystem of southern Ecuador and its regionalization.
Agricultural and Forest Meteorology 152:17–30. doi: 10.1016/j.agrformet.2011.08.004

Abstract: The near surface humidity in a megadiverse mountain ecosystem in southern Ecuador is examined on the basis of Relative Humidity (RH) measurements inside the natural mountain forest and at open sites along an altitudinal gradient from 1700 to 3200 m. The main methodological aim of the current study is to generate a humidity regionalization tool to provide spatial datasets on average monthly mean, minimum and maximum RH, Specific Humidity (q) and Specific Saturation Deficit (DS) by using observation data of RH. The maps based on data of the period 1999–2009 are needed by ecological projects working on various plots where no climate station data are available. The humidity maps are generated by combining a straightforward detrending technique with a Digital Elevation Model and a satellite-based land cover classification which also provides the relative forest cover per pixel. The topical aim of the study is to investigate the humidity distribution and structure of both manifestations of our ecosystem (pastures and natural vegetation) with special considerations to the ecosystem regulation service by converting natural forest into pasture. The results reveal a clear differentiation over the year, partly triggered by the change of synoptic weather situation but also by land cover effects. Humidity amplitudes are particularly low during the main rainy season when cloudiness and rainfall are high, but markedly pronounced in the relative dry season when daily irradiance and outgoing nocturnal radiation causes distinct differences between the land cover units. Particularly the upper pasture areas gained by slash and burn of the natural forest exhibit the lowest humidity values while the humidity inside the mountain forest is significantly higher due to the regulating effects of the dense vegetation. Thus, clearing the forest clearly reduces the regulation function (regulating ecosystem services) of the ecosystem which might become problematic for reforestation under future global warming.


Ayanu YZ, Conrad C, Nauss T,  Wegmann M, Koellner T (2012)
Quantifying and mapping ecosystem services supplies and demands: A review of remote sensing applications.
Environmental Science & Technology 46:8529–8541. doi: 10.1021/es300157u

Abstract: Ecosystems provide services necessary for the livelihoods and well-being of people. Quantifying and mapping supplies and demands of ecosystem services is essential for continuous monitoring of such services to support decision-making. Area-wide and spatially explicit mapping of ecosystem services based on extensive ground surveys is restricted to local scales and limited due to high costs. In contrast, remote sensing provides reliable area-wide data for quantifying and mapping ecosystem services at comparatively low costs, and with the option of fast, frequent, and continuous observations for monitoring. In this paper, we review relevant remote sensing systems, sensor types, and methods applicable in quantifying selected provisioning and regulatory services. Furthermore, opportunities, challenges, and future prospects in using remote sensing for supporting ecosystem services' quantification and mapping are discussed.


Appelhans T, Sturman A, Zawar-Reza P (2012)
Synoptic and climatological controls of particulate matter pollution in a Southern Hemisphere coastal city.
International Journal of Climatology 33:463–479. doi: 10.1002/joc.3439

Abstract: A complex interaction of local meteorology and source characteristics regularly leads to nocturnal smog events during winter in Christchurch, New Zealand. The main focus of this article is on improving understanding of the relationship between atmospheric processes operating at a range of scales that leads to poor air quality in such urban environments. This research therefore aims to provide a quantitative analysis of atmospheric influences on particulate matter pollution in Christchurch across a wide range of spatial and temporal scales, from local to hemispheric and daily to interannual. The probability of exceeding the National Environmental Standard for PM10 for a range of local atmospheric conditions is calculated using the classification and regression trees technique, and links between these probabilities, local meteorology and synoptic weather situations are established. The effect of the transition between synoptic types on local air quality is also examined, and the progression of anticyclones across the country is identified to be the dominant synoptic control mechanism. It is shown that variation in latitudinal location of the path of anticyclones over New Zealand influences the predicted exceedance probability. On interdecadal and hemispheric scales, it is found that the particular combination of local and synoptic atmospheric conditions that favours air quality degradation shows a reoccurring pattern of frequency maxima (and minima) with a periodicity of approximately 14-16 years. In relation to the identified interdecadal variability of synoptic circulation, a close relationship to Southern Hemisphere pressure anomalies at high latitudes is revealed. The results of this research show that, in addition to daily weather variation, air quality in Christchurch is influenced by longer-term climatic processes that operate on interannual hemispheric scales with the implication that, in general, air pollution potential can also be expected to vary on a periodic interdecadal time scale.




Bendix J, Trache K, Palacios E, Rollenbeck R, Göttlicher D, Nauss T, Bendix A (2011)
El Niño meets La Niña – anomalous rainfall patterns in the "traditional" El Niño region of southern Ecuador.
ERDKUNDE 65:151–167. doi: 10.3112/erdkunde.2011.02.04

Abstract: In this paper, the central Pacific cold event of 2008 and its exceptionally warm conditions in the eastern tropical Pacific are analyzed by using rainfall data of south Ecuadorian meteorological stations, sea surface temperatures in the El Niño3 and 1+2 regions, and simulations with the Weather Research and Forecasting (WRF) model. It can be shown that El Niño-like rainfall conditions with severe inundations occur particularly in the coastal plains of southern Ecuador while a central Pacific cold event prevails. In contrary to previous situations, positive rainfall anomalies as a result of El Niño-like conditions in the El Niño1+2 region during the 2008 La Niña event occurred in both regions, the coastal plains and the highlands, for the first time. A detailed analysis of the ocean-atmosphere system during episodes of heavy rainfall reveals typical El Niño circulation and rainfall patterns as observed during previous El Niño events for the coastal area and La Niña-like conditions for the highlands. The spreading of Pacific instability in the Niño1+2 region to the eastern escarpment of the Andes could be the result of a temporary eastward shift of the Walker circulation. The unusual combination of El Niño-like conditions in the eastern tropical Pacific during a La Niña state in the central Pacific is the newest indicator for an impact mode shift regarding severe rainfall anomalies during El Niño/La Niña events in the traditional El Niño area of southern Ecuador since the end of the last century. Since 2000, El Niño events unexpectedly provide below average rainfall while central Pacific La Niña conditions generate exceptional severe flooding in the normally drier coastal plains. The novel sea surface temperature (SST) anomaly dipole structure between the eastern and central/western tropical Pacific and the weakening of El Niño events since 2000 could be due to natural decadal oscillations in the El Niño background state, the Pacific Decadal Oscillation (PDO). However, the observed atmospheric patterns and the recent increase of the SST anomaly difference between the central and the eastern tropical Pacific resemble structures that also result from climate change simulations.


Göttlicher D, Albert J, Nauss T, Bendix J (2011)
Optical properties of selected plants from a tropical mountain ecosystem traits for plant functional types to parametrize a land surface model.
Ecological Modelling 222:493–502. doi: 10.1016/j.ecolmodel.2010.09.021

Abstract: The optical properties (reflectance and transmittance) of selected leaves from a tropical mountain rainforest in southern Ecuador are determined to parametrize optical traits of plant functional types (PFT) of a state of the art land model (Community Land Model, CLM). 46 spatially dominating species are selected from 4 different forest types, the subpáramo and a succession stage of pasture areas representing ecologically predefined functional types within the study area. Measurements are conducted under a standardized experimental setup with a field spectrometer covering the radiation between 305 and 1305 nm. The results of the optical properties of all species are checked for similarity by cluster analysis and are compared to the composition of species of the predefined PFTs. Furthermore the results are compared to other studies, the default values for the globally defined PFT of tropical evergreen trees in the CLM and another forest growth model operated in the same study area. The results show that the clusters aggregated by the reflectance, transmittance or combined properties do not represent the predefined PFTs. The values of the other studies suggest a reassessment of the experimental setup for the transmittance measurements. Nevertheless, new reflectance values for the regionalized PFTs can be determined. The optical values differ from the CLM-PFT of tropical evergreen trees, and new values for the reflectance are recommended.


Nauss T, Kokhanovsky AA (2011)
Retrieval of warm cloud optical properties using simple approximations.
Remote Sensing of Environment 115:1317–1325. doi: 10.1016/j.rse.2011.01.010

Abstract: A new technique relying on SimpLe Approximations for cLOudy Media (SLALOM) for the retrieval of cloud optical and microphysical parameters from optical satellite data during daytime is introduced. The technique is based on simple yet highly accurate approximations of the asymptotic solutions of the radiative transfer theory which have already been implemented in the forward radiative transfer model CLOUD. These approximations enable a solution of the equations of the corresponding backward model during runtime leading to a very fast computation speed. Since these asymptotic solutions are generally applicable to weakly absorbing media only, pre-calculated look-up tables for the reflection function of a semi-infinite cloud (and also the escape function) are used to overcome this restriction within this new retrieval. SLALOM is capable of retrieving the cloud optical thickness, the effective cloud droplet radius, the liquid and ice water paths, the particle absorption length as well as some other properties of water and ice clouds. The comparison of SLALOM with both exact radiative transfer computations and the NASA MODIS cloud property product shows a very good agreement. A Fortran implementation of both CLOUD and SLALOM is available for download under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 license (see http://creativecommons.org/licenses/by-nc-sa/3.0) at http://www.klimatologie.uni-bayreuth.de.




Zawar-Reza P, Appelhans T, Gharaylou M, Shamsipour A (2010)
Mesoscale controls on particulate matter pollution for a mega city in a semi-arid mountainous environment: Tehran, Iran.
International Journal of Environment and Pollution 41:166–183.

Abstract: Tehran, the mega-city capital of Iran, suffers from high concentrations of PM10 throughout the year. Emissions from transport combined with mesoscale atmospheric features related to the mountainous terrain lead to a distinctive diurnal pattern in concentrations. Air quality data from monitoring stations show that the highest concentrations of PM10 are in the morning and evening periods, associated with peak traffic volumes and transition in local meteorology from a stable nocturnal down-slope flow to a daytime upslope regime. There is a clear north-south gradient in PM10 associated with the transport by down-slope winds. A year-long simulation with The Air Pollution Model (TAPM) confirms the mesoscale meteorological regime over Tehran. Simulation results indicate that the peaks in traffic flow and the transition between meteorological regimes contribute to daily PM10 peaks, with the transition playing a relatively minor role.


Thies B, Turek A, Nauss T, Bendix J (2010)
Weather type dependent quality assessment of a satellite-based rainfall detection scheme for the mid-latitudes.
Meteorology and Atmospheric Physics 107:81–89. doi: 10.1007/s00703-010-0076-x

Abstract: The sensitivity of a recently published satellite-based rainfall detection scheme with differing frontal weather regimes is investigated for 676 precipitation scenes between January and August 2004. For this purpose, the rain area classified by the recent Rain Area Delineation Scheme during Night time (RADS-N) was compared to the rain area detected by the radar network of the German Weather Service. The validation results indicate that the rain area detected by RADS-N is highly consistent with the radar network (mean POD: 0.62; mean FAR: 0.52; mean ETS: 0.22). However, the bias indicates a mean overestimation of 42%. The classification results show that the satellite technique performs better in cold frontal situations and thunderstorms. Therefore, further investigations are needed to address the overall performance as well as the dependency on different weather situations and in order to allow reliable rain area detection during night-time, independent of the prevailing weather situation.


Kühnlein M, Thies B, Nauss T, Bendix J (2010)
Rainfall-rate assignment using MSG SEVIRI data — a promising approach to spaceborne rainfall-rate retrieval for midlatitudes.
Journal of Applied Meteorology and Climatology 49:1477–1495. doi: 10.1175/2010JAMC2284.1

Abstract: The potential of rainfall-rate assignment using Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Instrument (SEVIRI) data is investigated. For this purpose, a new conceptual model for precipitation processes in connection with midlatitude cyclones is developed, based on the assumption that high rainfall rates are linked to a high optical thickness and a large effective particle radius, whereas low rainfall rates are linked to a low optical thickness and a small effective particle radius. Reflection values in the 0.56–0.71-µm (VIS0.6) and 1.5–1.78-µm (NIR1.6) channels, which provide information about the optical thickness and the effective radius, are considered in lieu of the optical and microphysical cloud properties. An analysis of the relationship between VIS0.6 and NIR1.6 reflection and the ground-based rainfall rate revealed a high correlation between the sensor signal and the rainfall rate. Based on these findings, a method for rainfall-rate assignment as a function of VIS0.6 and NIR1.6 reflection is proposed. The validation of the proposed technique showed encouraging results, especially for temporal resolutions of 6 and 12 h. This is a significant improvement compared to existing IR retrievals, which obtain comparable results for monthly resolution. The existing relationship between the VIS0.6 and NIR1.6 reflection values and the ground-based rainfall rate is corroborated with the new conceptual model. The good validation results indicate the high potential for rainfall retrieval in the midlatitudes with the high spatial and temporal resolution provided by MSG SEVIRI.


Appelhans T, Sturman A, Zawar-Reza P (2010)
Modelling emission trends from non-constant time series of 10 concentrations in Christchurch, New Zealand.
International Journal of Environment and Pollution 43:354–363.

Abstract: This paper presents an attempt to model the trend of emissions through analysis of a time series of PPM10 concentrations in Christchurch, New Zealand. Emissions are not constant over time, but show high seasonality. Fluctuations are removed by creating a time series in which concentrations do not show dependency on ambient air temperature. Remaining meteorological influences are removed through multiple linear regression. Finally, a moving average filter is applied to reveal the low-frequency trend in the residuals of the meteorologically adjusted time series. The modelled trend shows a peak in emissions in 2001-2002 with a steady decrease thereafter.


Appelhans T, Zawar-Reza P (2010)
A modelling study of particulate matter dispersion under dominant surface wind regime modes in Christchurch, New Zealand.
Air Quality and Climate Change 44:24–29.

Abstract: Prognostic air pollution models such as TAPM are used to study air pollution on multi-day to multi-seasonal scales, driven by daily synoptic forcings. In complex terrain, mesoscale regimes can introduce diurnally reversing wind systems that can be persistent features of low level climatology - especially during stagnant anti-cyclonic conditions that result in deterioration of air quality. In this study, TAPM is modified to ignore synoptic forcings yet still produce terrain induced flows that are common features over the Canterbury Plains in New Zealand. In addition, surface-based climatology for two different regimes is assimilated into the model in order to study their effects on temporal evolution of PM10. Two common modes of surface wind conditions are observed in Christchurch during evenings of high pollution days where the national guideline for PM10 is exceeded. Low level flow during the evening hours with generally low wind speeds is dominated by either a north-westerly or a south-westerly wind direction. Results from TAPM simulations of dispersion indicate north-easterly flow opposes north-westerly to westerly drainage flow from the Southern Alps and traps pollutants over the city for an increased period of time and therewith delays flushing by a few hours. Simulated pollution levels during the evening are close to observed values and indicate that atmospheric control mechanisms are simulated well. This study delivers a viable tool for local environmental monitoring authorities to estimate generalised spatiotemporal pollution behaviour under different low level flow conditions.




Bräuning A, Volland-Voigt F, Burchardt I, Ganzhi O, Nauss T, Peters T (2009)
Climatic control of radial growth of Cedrela montana in a humid mountain rainforest in southern Ecuador.
ERDKUNDE 63:337–345. doi: 10.3112/erdkunde.2009.04.04

Abstract: Cedrela montana is a deciduous broad-leaved tree species growing in the humid mountain rainforests of southern Ecuador. High-resolution dendrometer data indicate a regular seasonal growth rhythm with cambial activity during January to April. Amplitudes of daily radial stem diameter variations are correlated with the amount of the maximum daily vapour pressure deficit. During humid periods, daily stem diameter variations are considerably smaller than during drier periods. This indicates that cambial activity is limited by available moisture even in such a very humid mountain climate. Wood anatomical studies on microcores show the formation of a marginal parenchyma band at the beginning of the growth period. This parenchyma band can be used to delineate annual growth rings. We were able to establish the first ring-width chronology from Cedrela montana which covers the time until 1840. However, the chronology is presently statistically robust back to 1910 only. Correlation functions calculated with NCEP/NCAR data indicate a significantly positive relationship of tree growth with temperatures during the growth period during January to April. However, only 8% of the growth variance is explained by this climatic factor. In the future, this relationship may be useful to reconstruct past temperature conditions of the study area.


Trachte K, Nauss T, Bendix J (2009)
The Impact of different terrain configurations on the formation and dynamics of katabatic flows: idealised case studies.
Boundary-Layer Meteorology 134:307–325. doi: 10.1007/s10546-009-9445-8

Abstract: Impacts of different terrain configurations on the general behaviour of idealised katabatic flows are investigated in a numerical model study. Various simplified terrain models are applied to unveil modifications of the dynamics of nocturnal cold drainage of air as a result of predefined topographical structures. The generated idealised terrain models encompass all major topographical elements of an area in the tropical eastern Andes of southern Ecuador and northern Peru, and the adjacent Amazon. The idealised simulations corroborate that (i) katabatic flows develop over topographical elements (slopes and valleys), that (ii) confluence of katabatic flows in a lowland basin with a concave terrainline occur, and (iii) a complex drainage flow system regime directed into such a basin can sustain the confluence despite varying slope angles and slope distances.


Bendix J, Trachte K, Cermak J, Rollenbeck R, Nauss T (2009)
Formation of convective clouds at the foothills of the tropical eastern Andes (South Ecuador).
Journal of Applied Meteorology and Climatology 48:1682–1695. doi: 10.1175/2009JAMC2078.1

Abstract: This study examines the seasonal and diurnal dynamics of convective cloud entities—small cells and a mesoscale convective complex–like pattern—in the foothills of the tropical eastern Andes. The investigation is based on Geostationary Operational Environmental Satellite-East (GOES-E) satellite imagery (2005–07), images of a scanning X-band rain radar, and data from regular meteorological stations. The work was conducted in the framework of a major ecological research program, the Research Unit 816, in which meteorological instruments are installed in the Rio San Francisco valley, breaching the eastern Andes of south Ecuador. GOES image segmentation to discriminate convective cells and other clouds is performed for a 600 × 600 km2 target area, using the concept of connected component labeling by applying the 8-connectivity scheme as well as thresholds for minimum blackbody temperature, spatial extent, and eccentricity of the extracted components. The results show that the formation of convective clouds in the lowland part of the target area mainly occurs in austral summer during late afternoon. Nocturnal enhancement of cell formation could be observed from October to April (particularly February–April) between 0100 and 0400 LST (LST = UTC - 5 h) in the Andean foothill region of the target area, which is the relatively dry season of the adjacent eastern Andean slopes. Nocturnal cell formation is especially marked southeast of the Rio San Francisco valley in the southeast Andes of Ecuador, where a confluence area of major katabatic outflow systems coincide with a quasi-concave shape of the Andean terrain line. The confluent cold-air drainage flow leads to low-level instability and cellular convection in the warm, moist Amazon air mass. The novel result of the current study is to provide statistical evidence that, under these special topographic situations, katabatic outflow is strong enough to generate mainly mesoscale convective complexes (MCCs) with a great spatial extent. The MCC-like systems often increase in expanse during their mature phase and propagate toward the Andes because of the prevailing upper-air easterlies, causing early morning peaks of rainfall in the valley of the Rio San Francisco. It is striking that MCC formation in the foothill area is clearly reduced during the main rainy season [June–August (JJA)] of the higher eastern Andean slopes. At a first glance, this contradiction can be explained by rainfall persistence in the Rio San Francisco valley, which is clearly lower during the time of convective activity (December–April) in comparison with JJA, during which low-intensity rainfall is released by predominantly advective clouds with greater temporal endurance.


Fries A, Rollenbeck R, Göttlicher D, Nauss T, Homeier J, Peters T, Bendix J (2009)
Thermal structure of a megadiverse Andean mountain ecosystem in southern Ecuador and its regionalization.
ERDKUNDE 63:321–335. doi: 10.3112/erdkunde.2009.04.03

Abstract: The thermal structure of a megadiverse mountain ecosystem in southern Ecuador is examined on the basis of temperature measurements inside the natural mountain forest and at open-sites along an altitudinal gradient from 1600 to 3200 m. The main methodological aim of the current study is to develop an air temperature regionalization tool to provide spatial datasets on average monthly mean, minimum and maximum temperature by using observation data. The maps, based on data of the period 1999–2007, are needed by ecological projects working on various plots where no climate station data are available. The temperature maps are generated by combining a straightforward detrending technique with a Digital Elevation Model and a satellite-based land cover classification which also provides the relative forest cover per pixel. The topical aim of the study is to investigate the thermal structure of both manifestations of our ecosystem (pastures and natural vegetation) with special considerations to the ecosystem temperature regulation service by converting natural forest into pasture. The results reveal a clear thermal differentiation over the year, partly triggered by the change of synoptic weather situation but also by land cover effects. Thermal amplitudes are particularly low during the main rainy season when cloudiness and air humidity are high, but markedly pronounced in the relative dry season when daily irradiance and outgoing nocturnal radiation cause distinct differences between the land cover units. Particularly the lower pasture areas gained by slash and burn of the natural forest exhibit the most extreme thermal conditions while the atmosphere inside the mountain forest is slightly cooler due to the regulating effects of the dense vegetation. Thus, clearing the forest clearly reduces the thermal regulation function (regulating ecosystem services) of the ecosystem which might become problematic under future global warming.


Bendix J, Silva B, Roos K, Göttlicher D-O, Rollenbeck R, Nauss T, Beck E (2009)
Model parameterization to simulate and compare the PAR absorption potential of two competing plant species.
International Journal of Biometeorology 54:283–295. doi: 10.1007/s00484-009-0279-3

Abstract: Mountain pastures dominated by the pasture grass Setaria sphacelata in the Andes of southern Ecuador are heavily infested by southern bracken (Pteridium arachnoideum), a major problem for pasture management. Field observations suggest that bracken might outcompete the grass due to its competitive strength with regard to the absorption of photosynthetically active radiation (PAR). To understand the PAR absorption potential of both species, the aims of the current paper are to (1) parameterize a radiation scheme of a two-big-leaf model by deriving structural (LAI, leaf angle parameter) and optical (leaf albedo, transmittance) plant traits for average individuals from field surveys, (2) to initialize the properly parameterized radiation scheme with realistic global irradiation conditions of the Rio San Francisco Valley in the Andes of southern Ecuador, and (3) to compare the PAR absorption capabilities of both species under typical local weather conditions. Field data show that bracken reveals a slightly higher average leaf area index (LAI) and more horizontally oriented leaves in comparison to Setaria. Spectrometer measurements reveal that bracken and Setaria are characterized by a similar average leaf absorptance. Simulations with the average diurnal course of incoming solar radiation (1998–2005) and the mean leaf–sun geometry reveal that PAR absorption is fairly equal for both species. However, the comparison of typical clear and overcast days show that two parameters, (1) the relation of incoming diffuse and direct irradiance, and (2) the leaf–sun geometry play a major role for PAR absorption in the two-big-leaf approach: Under cloudy sky conditions (mainly diffuse irradiance), PAR absorption is slightly higher for Setaria while under clear sky conditions (mainly direct irradiance), the average bracken individual is characterized by a higher PAR absorption potential. (~74 MJ m-2 year-1). The latter situation which occurs if the maximum daily irradiance exceeds 615 W m-2 is mainly due to the nearly orthogonal incidence of the direct solar beam onto the horizontally oriented frond area which implies a high amount of direct PAR absorption during the noon maximum of direct irradiance. Such situations of solar irradiance favoring a higher PAR absorptance of bracken occur in ~36% of the observation period (1998–2005). By considering the annual course of PAR irradiance in the San Francisco Valley, the clear advantage of bracken on clear days (36% of all days) is completely compensated by the slight but more frequent advantage of Setaria under overcast conditions (64% of all days). This means that neither bracken nor Setaria show a distinct advantage in PAR absorption capability under the current climatic conditions of the study area.


Göttlicher D, Obregon A, Homeier J, Rollenbeck R, Nauss T, Bendix J (2009)
Land-cover classification in the Andes of southern Ecuador using Landsat ETM+ data as a basis for SVAT modelling.
International Journal of Remote Sensing 30:1867–1886. doi: 10.1080/01431160802541531

Abstract: A land-cover classification is needed to deduce surface boundary conditions for a soil–vegetation–atmosphere transfer (SVAT) scheme that is operated by a geoecological research unit working in the Andes of southern Ecuador. Landsat Enhanced Thematic Mapper Plus (ETM+) data are used to classify distinct vegetation types in the tropical mountain forest. Besides a hard classification, a soft classification technique is applied. Dempster–Shafer evidence theory is used to analyse the quality of the spectral training sites and a modified linear spectral unmixing technique is selected to produce abundancies of the spectral endmembers. The hard classification provides very good results, with a Kappa value of 0.86. The Dempster–Shafer ambiguity underlines the good quality of the training sites and the probability guided spectral unmixing is chosen for the determination of plant functional types for the land model. A similar model run with a spatial distribution of land cover from both the hard and the soft classification processes clearly points to more realistic model results by using the land surface based on the probability guided spectral unmixing technique.




Thies B, Nauss T, Bendix J (2008)
Discriminating raining from non-raining cloud areas at mid-latitudes using meteosat second generation SEVIRI night-time data.
Meteorological Applications 15:219–230. doi: 10.1002/met.56

Abstract: A new method for the delineation of precipitation during night-time using multispectral satellite data is proposed. The approach is not only applicable to the detection of mainly convective precipitation by means of the commonly used relation between infrared cloud-top temperature and rainfall probability but enables also the detection of stratiform precipitation (e.g. in connection with mid-latitude frontal systems).
The presented scheme is based on the conceptual model that precipitating clouds are characterized by a combination of particles large enough to fall, an adequate vertical extension [both represented by the cloud water path (CWP)], and the existence of ice particles in the upper part of the cloud. As no operational retrieval exists for Meteosat Second Generation (MSG) to compute the CWP during night-time, suitable combinations of brightness temperature differences (dT) between the thermal bands of Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager (MSG SEVIRI, dT3.9–10.8, dT3.9–7.3, dT8.7–10.8, dT10.8–12.1) are used to infer implicit information about the CWP and to compute a rainfall confidence level. dT8.7–10.8 and dT10.8–12.1 are particularly considered to supply information about the cloud phase. Rain area delineation is realized by using a minimum threshold of the rainfall confidence. To obtain a statistical transfer function between the rainfall confidence and the channel differences, the value combination of the channel differences is compared with ground-based radar data. The retrieval is validated against independent radar data not used for deriving the transfer function and shows an encouraging performance as well as clear improvements compared to existing optical retrieval techniques using only IR thresholds for cloud-top temperature.


Thies B, Nauss T, Bendix J (2008)
Precipitation process and rainfall intensity differentiation using Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager data.
Journal of Geophysical Research: Atmospheres 113:D23206. doi: 10.1029/2008JD010464

Abstract:A new day and night technique for precipitation process separation and rainfall intensity differentiation using the Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager is proposed. It relies on the conceptual design that convective clouds with higher rainfall intensities are characterized by a larger vertical extension and a higher cloud top. For advective-stratiform precipitation areas, it is assumed that areas with a higher cloud water path (CWP) and more ice particles in the upper parts are characterized by higher rainfall intensities. First, the rain area is separated into areas of convective and advective-stratiform precipitation processes. Next, both areas are divided into subareas of differing rainfall intensities. The classification of the convective area relies on information about the cloud top height gained from water vapor-IR differences and the IR cloud top temperature. The subdivision of the advective-stratiform area is based on information about the CWP and the particle phase in the upper parts. Suitable combinations of temperature differences (?T3.9–10.8, ?T3.9–7.3, ?T8.7–10.8, ?T10.8–12.1) are incorporated to infer information about the CWP during nighttime, while a visible and a near-IR channel are considered during the daytime. ?T8.7–10.8 and ?T10.8–12.1 are particularly included to supply information about the cloud phase. Intensity differentiation is realized by using pixel-based confidences for each subarea calculated as a function of the respective value combinations of the previously mentioned variables. For the calculation of the confidences, the value combinations are compared with ground-based radar data. The proposed technique is validated against ground-based radar data and shows an encouraging performance (Heidke skill score 0.07–0.2 for 15-min intervals).


Thies B, Nauss T, Bendix J (2008)
Discriminating raining from non-raining clouds at mid-latitudes using meteosat second generation daytime data.
Atmospheric Chemistry and Physics 8:2341–2349. doi: 10.5194/acp-8-2341-2008

Abstract: A new method for the delineation of precipitation during daytime using multispectral satellite data is proposed. The approach is not only applicable to the detection of mainly convective precipitation by means of the commonly used relation between infrared cloud top temperature and rainfall probability but enables also the detection of stratiform precipitation (e.g. in connection with mid-latitude frontal systems). The presented scheme is based on the conceptual model that precipitating clouds are characterized by a combination of particles large enough to fall, an adequate vertical extension (both represented by the cloud water path; cwp), and the existence of ice particles in the upper part of the cloud. The technique considers the VIS0.6 and the NIR1.6 channel to gain information about the cloud water path. Additionally, the brightness temperature differences ?T8.7-10.8 and ?T10.8-12.1 are considered to supply information about the cloud phase. Rain area delineation is realized by using a minimum threshold of the rainfall confidence. To obtain a statistical transfer function between the rainfall confidence and the four parameters VIS, NIR1.6, ? T8.7-10.8 and ? T10.8-12.1, the value combinations of these four variables are compared to ground based radar data. The retrieval is validated against independent radar data not used for deriving the transfer function and shows an encouraging performance as well as clear improvements compared to existing optical retrieval techniques using only IR thresholds for cloud top temperature.


Bendix J, Rollenbeck R, Göttlicher D, Nauss T, Fabian P (2008)
Seasonality and diurnal pattern of very low clouds in a deeply incised valley of the eastern tropical Andes (South Ecuador) as observed by a cost-effective WebCam system.
Meteorological Applications 15:281–291. doi: 10.1002/met.72

Abstract: To date, the annual and diurnal pattern of low clouds touching the ground in tropical mountains is widely unknown. This holds true for the valley of the Rio San Francisco in southern Ecuador, and is mainly due to a lack of routine cloud observations, which is symptomatic for remote areas in tropical high mountains. A method to use a simple and cost-effective WebCam system for a quantitative analysis of cloud frequency as a proxy for the occurrence of low-cloud bases touching the ground is introduced. An interactive classification tool is developed, which is applied to a comprehensive dataset of 32 452 images (during the years 2002–2004) archived at 5 min intervals. The results point to a rapid increase of cloud frequency at altitudes > 2600 m asl both during the day and the year, mainly caused by advective clouds veiling the crests of the Cordillera del Consuelo. Even if the formation of radiation fog directly at the valley bottom is nearly negligible with regard to the whole dataset, scatterometer measurements suggest that valley fog formation on the slopes is a regular process during the night, causing a clear drop in the cloud base around sunrise. The interaction of low-radiative and high-advective clouds is supposed to be the driving factor for a rainfall maximum at the valley bottom around sunrise. Higher values of cloud frequency still exist at the crest level around noon: these originate from well-developed upslope-breeze systems.




Früh B, Bendix J, Nauss T, Paulat M, Pfeiffer A, Schipper J-W, Thies B, Wernli H (2007)
Verification of precipitation from regional climate simulations and remote-sensing observations with respect to ground-based observations in the upper Danube catchment.
Meteorologische Zeitschrift 16:275–293. doi: 10.1127/0941-2948/2007/0210

Abstract: An evaluation of precipitation fields for four selected months simulated by the regional climate model AtmoMM5 and provided by the satellite retrieval method AtmoSat is presented. As reference, observations at 5 km resolution on a daily and monthly basis are used. We applied conventional verification tools (root mean square error, grid-point based categorical error scores, etc.) as well as the new error score SAL, which separately considers aspects of the structure, amplitude and location of the precipitation field in a predefined area. We also discussed the advantages and disadvantages of each of the scores. The aim of our evaluation was to unfold the strengths and weaknesses of AtmoMM5 and AtmoSat to calculate daily and monthly high resolution precipitation. As a result we found that the catchment averaged monthly mean precipitation is simulated with an acceptable accuracy by both methods. The spatial pattern of the monthly precipitation (typically with a precipitation maximum in the alpine foreland) can only be reproduced by AtmoMM5. Regarding the daily precipitation, our evaluation revealed that both methods still need improvement. The deviations to the observations increase with decreasing precipitation amount resulting in large uncertainties in case of very dry conditions. Overall, we can conclude that AtmoMM5 is better suited to simulate precipitation at 5 km resolution on a daily basis than AtmoSat.


Kokhanovsky AA, Nauss T, Schreier M, Hoyningen-Huene Wv, Burrows J-P (2007)
The Intercomparison of cloud parameters derived using multiple satellite instruments.
IEEE Transactions on Geoscience and Remote Sensing 45:195–200. doi: 10.1109/TGRS.2006.885019

Abstract: Cloud optical thickness (COT) has been retrieved using multiple optical instruments onboard ENVISAT and compared for consistency for a single cloud field over central Europe. To match the spatial resolution of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), the results of retrievals from higher resolution instruments have been averaged on the scale of 30 times 60 km. It was found that the Medium Resolution Imaging Spectrometer (MERIS), Advanced Along Track Scanning Radiometer (AATSR), and SCIAMACHY (all onboard ENVISAT) give close values of COT and, therefore, cloud albedo. Similar results have been obtained for Moderate Resolution Imaging Spectroradiometer onboard the Terra satellite. This suggests that these instruments can be used for synergetic retrievals of cloud properties from space. For instance, the high spectral resolution of SCIAMACHY can be used to enhance MERIS or AATSR retrievals of cloud top height and other cloud characteristics.




Bendix J, Thies B, Nauss T, Cermak J (2006)
A feasibility study of daytime fog and low stratus detection with TERRA/AQUA-MODIS over land.
Meteorological Applications 13:111–125. doi: 10.1017/S1350482706002180

Abstract: A scheme for the detection of fog and low stratus over land during daytime based on data of the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument is presented. The method is based on an initial threshold test procedure in the MODIS solar bands 1–7 (0.62–2.155µm). Fog and low stratus detection generally relies on the definition of minimum and maximum fog and low stratus properties, which are converted to spectral thresholds by means of radiative transfer calculations (RTC). Extended sensitivity studies reveal that thresholds mainly depend on the solar zenith angle and, hence, illumination-dependent threshold functions are developed. Areas covered by snow, ice and mid-/high-level clouds as well as bright/hazy land surfaces are omitted from the initial classification result by means of a subsequent cloud-top height test based on MODIS IR band 31 (at 12 µm) and a NIR/VIS ratio test. The validation of the final fog and low stratus mask generally shows a satisfactory performance of the scheme. Validation problems occur due to the late overpass time of the TERRA platform and the time lag between SYNOP and satellite observations. Apparent misclassifications are mainly found at the edge of the fog layers, probably due to over- or underestimation of fog and low stratus cover in the transition zone from fog to haze.


Nauss T, Kokhanovsky AA (2006)
Discriminating raining from non-raining clouds at mid-latitudes using multispectral satellite data.
Atmospheric Chemistry and Physics 6:5031–5036. doi: 10.5194/acp-6-5031-2006

Abstract: We propose a new method for the delineation of precipitation using cloud properties derived from optical satellite data. This approach is not only sufficient for the detection of mainly convective precipitation by means of the commonly used connection between infrared cloud top temperature and rainfall probability but enables the detection of stratiform precipitation (e.g., in connection with mid-latitude frontal systems). The scheme presented is based on the concept model, that precipitating clouds must have both a sufficient vertical extent and large enough droplets. Therefore, we have analysed MODIS scenes during the severe European summer floods in 2002 and retrieved functions for the computation of an auto-adaptive threshold value of the effective cloud droplet radius with respect to the corresponding optical thickness which links these cloud properties with rainfall areas on a pixel basis.


Kokhanovsky AA, Nauss T (2006)
Reflection and transmission of solar light by clouds: asymptotic theory.
Atmospheric Chemistry and Physics 6:5537–5545. doi: 10.5194/acp-6-5537-2006

Abstract: The authors introduce a radiative transfer model CLOUD for reflection, transmission, and absorption characteristics of terrestrial clouds and discuss the accuracy of the approximations used within the model. A Fortran implementation of CLOUD is available for download. This model is fast, accurate, and capable of calculating multiple radiative characteristics of cloudy media including the spherical and plane albedo, reflection and transmission functions, absorptance as well as global and diffuse transmittance. The approximations are based on the asymptotic solutions of the radiative transfer equations valid at cloud optical thicknesses larger than 5. While the analytic part of the solutions is treated in the code in an approximate way, the correspondent reflection function (RF) of a semi-infinite water cloud R8 is calculated using numerical solutions of the radiative transfer equation in the assumption of Deirmendjian's cloud C1 model. In the case of ice clouds, the fractal ice crystal model is used. The resulting values of R8 with respect to the viewing geometry are stored in a look-up table (LUT).


Kokhanovsky AA, Rozanov VV, Nauss T, Reudenbach C, Daniel J-S, Miller H-L, Burrows J-P (2006)
The semianalytical cloud retrieval algorithm for SCIAMACHY I. The validation.
Atmospheric Chemistry and Physics 6:1905–1911. doi: 10.5194/acp-6-1905-2006

Abstract: A recently developed cloud retrieval algorithm for the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) is briefly presented and validated using independent and well tested cloud retrieval techniques based on the look-up-table approach for MODeration resolutIon Spectrometer (MODIS) data. The results of the cloud top height retrievals using measurements in the oxygen A-band by an airborne crossed Czerny-Turner spectrograph and the Global Ozone Monitoring Experiment (GOME) instrument are compared with those obtained from airborne dual photography and retrievals using data from Along Track Scanning Radiometer (ATSR-2), respectively.




Kokhanovsky AA, Nauss T (2005)
Satellite-based retrieval of ice cloud properties using a semianalytical algorithm.
Journal of Geophysical Research: Atmospheres 110:D19206. doi: 10.1029/2004JD005744

Abstract: A semianalytical algorithm for the retrieval of ice cloud properties from satellite data is presented. The new method is based on the semianalytical cloud retrieval algorithm and uses solutions of the asymptotic radiative transfer theory applicable for optically thick media. Therefore the new method is much less computer time expensive than the commonly used lookup table approaches. Usually, the cloud optical thickness and cloud effective droplet radius are reported for water and ice clouds even though both parameters are dependent on the actual crystal shape assumed in the retrieval procedures. Thus the authors propose to use the reduced optical thickness (ROT) and the particle absorption length (PAL) for the characterization of ice clouds. This implies that no a priori or climatological estimates of the particle shape/size distribution are necessary and increases the comparability of different cloud retrieval algorithms, which are built on many different distribution functions. If still necessary, the retrieved ROT and PAL can easily be transferred to values of the optical thickness and the cloud effective droplet radius by assuming any of those size distribution functions. The developed technique has been applied to data from the NASA EOS Terra Moderate Resolution Imaging Spectroradiometer sensor. The scene shows Hurricane Jeanne just before its landfall near the coast of Florida in September 2004. Both the reduced cloud optical thickness and the particle absorption length have been derived for the eye wall region.


Nauss T, Kokhanovsky AA, Nakajima TY, Reudenbach C, Bendix J (2005)
The intercomparison of selected cloud retrieval algorithms.
Atmospheric Research 78:46–78. doi: 10.1016/j.atmosres.2005.02.005

Abstract: The paper is devoted to the comparison of selected cloud retrieval algorithms. In particular, the authors compare cloud optical thickness, liquid water path and effective droplet size as obtained from the algorithms developed at the Japan Aerospace Exploration Agency (JAXA) and US National Aeronautics and Space Administration (NASA) and a new simplified cloud retrieval algorithm that is based on the analytical solutions of the radiative transfer equations valid for optically thick weakly absorbing cloud layers. Over ocean all three retrievals show very close results but differences increase for a scene over land. This is mainly caused by uncertainties due to the unknown surface albedo, especially for the semi-analytical approach that is based on measurements at 0.86 µm, where the contribution from ground is particularly large. Still, the simplified analytical retrieval technique gives results comparable with much more advanced codes.


Bendix J, Thies B, Cermak J, Nauss T (2005)
Ground fog detection from space based on MODIS daytime data — a feasibility study.
Weather and Forecasting 20:989–1005. doi: 10.1175/WAF886.1

Abstract: The distinction made by satellite data between ground fog and low stratus is still an open problem. A proper detection scheme would need to make a determination between low stratus thickness and top height. Based on this information, stratus base height can be computed and compared with terrain height at a specific picture element. In the current paper, a procedure for making the distinction between ground fog and low-level stratus is proposed based on Moderate Resolution Imaging Spectroradiometer (MODIS, flying on board the NASA Terra and Aqua satellites) daytime data for Germany. Stratus thickness is alternatively derived from either empirical relationships or a newly developed retrieval scheme (lookup table approach), which relies on multiband albedo and radiative transfer calculations. A trispectral visible–near-infrared (VIS–NIR) approach has been proven to give the best results for the calculation of geometrical thickness. The comparison of horizontal visibility data from synoptic observing (SYNOP) stations of the German Weather Service and the results of the ground fog detection schemes reveals that the lookup table approach shows the best performance for both a valley fog situation and an extended layer of low stratus with complex local visibility structures. Even if the results are very encouraging [probability of detection (POD) = 0.76], relatively high percentage errors and false alarm ratios still occur. Uncertainties in the retrieval scheme are mostly due to possible collocation errors and known problems caused by comparing point and pixel data (time lag between satellite overpass and ground observation, etc.). A careful inspection of the pixels that mainly contribute to the false alarm ratio reveals problems with thin cirrus layers and the fog-edge position of the SYNOP stations. Validation results can be improved by removing these suspicious pixels (e.g., percentage error decreases from 28% to 22%).


Nauss T, Bendix J (2005)
An operational MODIS processing scheme for PC dedicated to direct broadcasting applications in meteorology and earth sciences.
Computers & Geosciences 31:804–808. doi: 10.1016/j.cageo.2005.01.003

Abstract: Since late 1999 the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS Terra and Aqua platforms is available (King et al., 1992). NASA has established a Web-Interface for downloading MODIS data from level 1b upward (http://www.daac.gsfc.nasa.gov/) but this data still needs pre- and post-processing. Moreover, research activities focusing on the development of operational product algorithms still rely on the direct broadcast of satellite data since an operational data transfer of level 1b MODIS products from the DAAC (~7.5 GB per day for central Europe) exceeds the intention of the web-interface. Several mostly mixed-language tools are available for single processing steps but there is a lack of comprehensive tools which operationally perform pre- and post-processing of the MODIS data and in addition, allow the implementation of own or third party higher-level products in the same framework. Hence the authors implemented an operational MODIS processing scheme (MOPS) solely based on Fortran and useable on both Linux and MS-Windows platforms with an extendable interface to higher-level products and a user-friendly Java GUI. So far the MODIS cloud mask product ( Ackermann et al., 1998) and two cloud property retrievals (Nakajima and Nakajima, 1995; Kokhanovsky et al., 2003) not available from NASA are implemented. An advanced rainfall retrieval and a fog detection scheme will be available from 2005 on. Moreover the extendable program interface and the dynamically generated Java GUI allows an easy integration of algorithms developed by others.


Technical reports

  • Wilton E, Appelhans T, Baynes M, Zawar-Reza P (2009) Assessing long-term trends in PM10 concentrations in Invercargill. Environet Limited, 11 Lachie Griffin Rise RD1; Lyttelton; Christchurch 8971
  • Appelhans T, Bluett J, Dey K, et al (2007) Using air quality data to track progress toward 10 standards: Case study - Christchurch 1999 - 2006. National Institute of Water & Atmospheric Research Ltd, 10 Kyle Street; PO Box 8602; Christchurch; New Zealand
  • Sturman A, Appelhans T (2006) Estimation of hourly solar radiation from 2nd July to 18th August 2003 in the area between Rangataik and Matea townships, east of Lake Taupo in the central North Island. AgResearch, Ruakura Research Centre; Bisley Road; Private Bag 3115; Hamilton 3240; New Zealand

Book chapters

  • Peters T, Drobnik T, Meyer H, Rankl M, Richter M, Rollenbeck R, Thies B, Bendix J (2013) Environmental Changes Affecting the Andes of Ecuador. In: Bendix J, Beck E, Bräuning A, et al. (eds) Ecosystem Services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador. Springer Berlin Heidelberg, pp 19–29
  • Roos K, Bendix J, Curatola G, Gawlik J, Gerique A, Hamer U, Hildebrandt P, Knoke T, Meyer H, Pohle P, Potthast K, Thies B, Tischer A, Beck E (2013) Current provisioning services: pasture development and use, weeds (bracken) and management. In: Bendix J, Beck E, Bräuning A, et al. (eds) Ecosystem Services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador. Springer, pp 205–218
  • Windhorst D, Silva B, Peters T, Meyer H, Thies B, Bendix J, Frede H-G, Breuer L 2013) Impacts of Local Land-Use Change on Climate and Hydrology. In: Bendix J, Beck E, Bräuning A, et al. (eds) Ecosystem Services, Biodiversity and Environmental Change in a Tropical Mountain Ecosystem of South Ecuador. Springer Berlin Heidelberg, pp 275–286
  • Nauss T, Bendix J (2010) Extreme Windereignisse - Stürme, Hurricans, Tornados. In: Felgentreff C, Glade T (eds) Naturrisiken und Sozialkatastrophen. Springer, pp 181–190
  • Nauss T, Thies B, Turek A, Kokhanovsky AA (2008) Operational discrimination of raining from non-raining clouds in mid-latitudes using multispectral satellite data. In: Michaelides S (eds) Precipitation: Advances in Measurement, Estimation and Prediction. Springer, pp 171-194
  • Reudenbach C, Nauss T, Bendix J (2007) Retrieving precipitation with GOES, Meteosat, and Terra/MSG at the tropics and mid-latitudes. In: Levizzani V, Bauer P, Turk F (eds) Measuring Precipitation from Space. EURAINSAT and the Future. Springer, pp 509-519

Conference contributions (selection)

  • Ludwig A, Meyer H, Higginbottom T, Nauss T (2016) Classifying Google Earth images as training sites for application to a larger scale monitoring of bush encroachment in South Africa. In: EGU General Assembly Conference Abstracts.
  • Meyer H, Lehnert LW, Wang Y, Reudenbach C, Nauss T, Bendix J (2016) Mapping vegetation cover and biomass on the Qinghai-Tibet-Plateau using hyperspectral measurements and multispectral satellite images. In: EGU General Assembly Conference Abstracts.
  • Appelhans T, Mwangomo E, Hardy D-R, Hemp A, Nauss T (2015) Evaluating different machine learning approaches for the interpolation of ambient air temperature at Mt. Kilimajaro, Tanzania. In: EGU General Assembly Conference Abstracts. p 1280
  • Appelhans T, Mwangomo E, Otte I, Detsch F, Nauss T, Hemp A, Ndyamkama J (2015) Extending an operational meteorological monitoring network through machine learning and classical geo-statistical approaches. In: EGU General Assembly Conference Abstracts. pp 1279–1
  • Lehnert L, Meyer H, Bendix J (2015) Hyperspectral Data Analysis in R: The new hsdar-package. In: UseR! 30.06 – 03.07. 2015, Aalborg, Denmark.
  • Messenzehl K, Hoffmann T, Meyer H, Dikau R (2015) Regional-scale controls of periglacial rockfalls (Turtmann valley, Swiss Alps). In: EGU General Assembly Conference Abstracts.
  • Meyer H, Kühnlein M, Appelhans T, Nauss T (2015) Comparison of machine learning algorithms for their applicability in satellite-based optical rainfall retrievals. In: EGU General Assembly Conference Abstracts.
  • Otte I, Detsch Florian, Appelhans T, Nauss T (2015) Quantification and analysis of deuterium and oxygen-18 isotope composition of precipitation at the southern foothills of Mt. Kilimanjaro (Tanzania). In: EGU General Assembly Conference Abstracts.
  • Wöllauer, Stephan; Forteva, Spaska; Nauss, Thomas (2015) On demand processing of climate station sensor data
  • Otte I, Detsch Florian, Nauss T, Appelhans T (2015) Seasonal and long-term rainfall and cloud dynamics in the Mt. Kilimanjaro region as observed from local and remote sensing time series. In: EGU General Assembly Conference Abstracts.
  • Wang Y, Lehnert L, Holzapfel M, Schultz R, Heberling G, Görzen E, Meyer H, Seeber E, Pinkert S, Ritz M, Ansorge H, Bendix J, Seifert B, Miehe G, Long R, Yang Y, Wesche K (2015) Testing congruence among multiple grazing indicators: a multi-site study across the Tibetan plateau. In: EGU General Assembly Conference Abstracts.
  • Lehnert LW, Meyer H, Thies B, Reudenbach C, Bendix J (2014) Monitoring plant cover on the Tibetan Plateau: A multi-scale remote sensing based approach. In: EGU General Assembly Conference Abstracts.
  • Appelhans T, Nauss T (2013) East African rainfall and vegetation dynamics in response to a changing El Nino. In: EGU General Assembly Conference Abstracts. p 12062
  • Lehnert LW, Meyer H, Meyer N, Reudenbach C, Bendix J (2013) Assessing pasture quality and degradation status using hyperspectral imaging: a case study from western Tibet. In: Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 88870I (16 October 2013).
  • Meyer H, Lehnert LW, Wang Y,  Reudenbach C, Bendix J (2013) Measuring pasture degradation on the Qinghai-Tibet Plateau using hyperspectral dissimilarities and indices. In: Proc. SPIE 8893, Earth Resources and Environmental Remote Sensing/GIS Applications IV, 88931F (October 24, 2013). p 88931F–88931F–13
  • Otte I, Appelhans T, Röder J, Nauss T, Brandl R (2013) Monitoring small-scale heterogeneity patterns in a savanna ecosystem at Mt. Kilimanjaro. In: TR32-Hobe Symposium poster presentation.
  • Otte I, Detsch Florian, Appelhans T, Nauss T (2013) Land-cover dynamics in the Mt. Kilimanjaro region as observed from remote sensing time series. In: AK Klima poster presentation.
  • Thies B, Meyer H., Bendix J (2011) Investigating and predicting land use/land cover changes in a tropical mountain forest of southern Ecuador. In: Conference of the society for tropical ecology, Frankfurt.
  • Curatola G, Thies B, Meyer H, Bendix J (2010) Land use change detection with multitemporal satellite data. In: Symposium of the DFG research unit 816 2010, Loja, Ecuador.
  • Göttlicher D, Dobbermann M, Nauss T, Bendix J (2010) Central data services in multidisciplinary environmental research projects - the data-management of the DFG Research Unit 816. In: Curdt C, Bareth G (eds) Proceedings of the Data Management Workshop, 29.-30.10.2009, Cologne. Geographisches Institut der Universität zu Köln, pp 59–64
  • Thies B, Meyer H, Bendix J (2010a) Investigating and predicting land use/land cover changes in a tropical mountain forest of southern Ecuador. In: Jahrestreffen des AK Klima in Würzburg.
  • Appelhans T (2008) East African rainfall and vegetation dynamics in response to a changing El Niño. In: 32nd International Geographical Congress. 26 - 30 August 2012, Cologne, Germany.
  • Appelhans T (2008) Climate dynamics of the Kilimanjaro region: A field measurement campaign to investigate climatological drivers of a tropical montane ecosystem. In: 31st International Conference on Alpine Meteorology. 23 – 27 May 2011, Aviemore, Scotland.

Zuletzt aktualisiert: 09.04.2018 · Thomas Nauss

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