@article{SaraviaTrachte2025, author = {Saravia, Christian and Trachte, Katja}, title = {Spatiotemporal analysis of NH³ emission sources and their relation to land use types in the eastern German lowlands}, series = {Atmosphere}, volume = {16}, journal = {Atmosphere}, number = {3}, publisher = {MDPI}, address = {Basel}, issn = {2073-4433}, doi = {10.3390/atmos16030346}, year = {2025}, abstract = {Ammonia (NH³) emissions, which are key precursors of fine particulate matter, pose significant environmental challenges. This study investigated the spatiotemporal variations in NH³ emissions across the eastern German lowlands from 2013 to 2022 using IASI-B satellite data. Five major Land Cover Classes (LCC) -tree, grassland, cropland, built-up areas, and water bodies- were analyzed. The results showed distinct diurnal variations, with nighttime NH³ concentrations exceeding 2.0 × 10¹⁶ molecules cm⁻² in the peak months. Seasonal patterns indicated significant emissions in March (1.2 × 10¹⁶ molecules cm⁻²), April (1.1 × 10¹⁶ molecules cm⁻²), and August (9.6 × 10¹⁵ molecules cm⁻²), while the lowest concentrations occurred in September (0.6 × 10¹⁵ molecules cm⁻²). Persistent hotspots were identified in the northwestern region, where emissions peaked in spring (1.8 × 10¹⁶ molecules cm⁻²) and summer (1.3 × 10¹⁶ molecules cm⁻²), primarily due to agricultural activities. Over the study period, the annual NH³ concentration peaked in 2015, 2018, and 2022. Using k-means clustering, three distinct emission zones were identified, with Cluster 3 showing the highest NH³ emission values, particularly in urban centers, and agricultural zones were identified, covering less than 20\% of the study area, where cropland predominates (8\%). Meteorological factors significantly influenced NH³ levels, with negative correlations obtained for precipitation, wind speed, and evaporation, while solar radiation, boundary layer height, and instantaneous moisture fluxes showed positive correlations. A case study from March 2022, employing the HYSPLIT trajectory model, confirmed that agricultural practices are the dominant NH³ source, with emissions reaching 3.2 × 10¹⁶ molecules cm⁻² in hotspot regions.}, subject = {Ammonia; Remote sensing; Land cover type; Spatiotemporal variability; Cluster k-means}, language = {en} } @phdthesis{An2015, author = {An, Ni}, title = {Statistical analysis of extreme climate events in Brandenburg}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-36117}, school = {BTU Cottbus - Senftenberg}, year = {2015}, abstract = {The main idea of this paper is to evaluate the performance of the fine resolution CLM model in the state of Brandenburg Germany, create a bias correction method and reanalyze the climate signals of the corrected simulations on projections of the 21st century. The bias correction method is a distribution oriented method and the analysis is mainly focused on the extreme events such as 95 and 5 percentile daily temperatures and 95 percentile daily precipitations in a period of 30 years, but also includes seasonal temperature, daily temperature difference and monthly precipitation to demonstrate the effectiveness of the correction method. The results showed that the correction method was very effective on different variables. After correction, the extreme daily temperature bias was reduced from a cold bias of 1-2K to less than 0.1K. The corrected projection simulations suggested that the extreme temperatures were about to increase both in intensity and in frequency. The extreme precipitation after correction was meant to become more severe and frequent as well.}, subject = {Bias correction; Climate simulation; CLM model evaluation; Climate signal analysis; Bias Korrektur; Klima Simulation; CLM Modell Auswertung; Klima Signal Analyse; Brandenburg; Klima; Modell; Statistische Analyse; Simulation}, language = {en} } @phdthesis{Klein2016, author = {Klein, Marten}, title = {Inertial wave attractors, resonances, and wave excitation by libration : direct numerical simulations and theory}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-41712}, school = {BTU Cottbus - Senftenberg}, year = {2016}, abstract = {Resonance phenomena are ubiquitous in Nature. Resonance means that a system can accumulate large amounts of kinetic energy. In rotating flows inertial waves provide a mechanism for resonance by redistributing momentum, kinetic energy and helicity. In order to investigate inertial waves a Taylor-Couette system was investigated which consists of a homogeneous liquid confined between two coaxial cylinders and two rigid lids. The inner cylinder is slightly conical (frustum) to break the vertical mirror symmetry. Inertial waves were excited by two different forcing configurations: the frustum in libration and the lids together with the outer cylinder in libration. Libration means that the rotation rate of the wall is modulated with a fixed amplitude and frequency of the order of the mean rotation rate. Direct numerical simulations (DNS) were conducted with a numerical solver in terrain-following coordinates. DNS results reveal that inertial wave excitation is localised at the edges of the confinement, which is in very good agreement with recent laboratory measurements of Seelig (2014, PhD thesis, BTU Cottbus - Senftenberg). A model of the wave excitation mechanism was developed with the aid of boundary layer theory. The model suggests that a difference in the boundary layer mass flux (Ekman flux) excites the waves by driving an excess Ekman pumping velocity at the edges. The DNS results exhibit this flux difference, and the simulated kinetic energy spectra of the waves exhibit the frequency dependency predicted by the model. However, DNS results also exhibit helical vortices at the edges which are not part of the model. Conservation properties suggest that these vortices are merely a compensating phenomenon which tends to stabilise the boundary layer flow. The details of this flow, however, appear less important for the wave excitation. Response spectra of the kinetic energy, the dissipation rate, the helicity, and the quality factor were computed in order to assess resonance conditions. Simulated resonance peaks have a width of only 1/20th of the mean rotation rate. At these peaks, the kinetic energy was found to increase by a factor 10-50 even though viscous forces were still rather large (Ekman number of the order 1/100,000 with the length scale given by the mean radial gap width). The flow patterns found at those resonances were investigated and found to be in very good agreement with the spatial patterns obtained by laboratory measurements and geometric ray tracing. The DNS results suggest that there are two types of resonance in rotating flows: modes and wave attractors. In contrast to a mode, a wave attractor exhibits net focusing of wave energy and occupies a finite frequency band. DNS results show that the wave attractor resonance frequency adjusts within the frequency band which suggests that wave attractor resonances complement 'classical' mode resonances and may, thus, be relevant in various applications.}, subject = {Direct Numerical Simulations; Rotating flows; Resonance; Inertial waves; Boundary layer theory; Direkte Numerische Simulationen; Rotierende Str{\"o}mungen; Resonanz; Tr{\"a}gheitswellen; Grenzschichttheorie; Direkte numerische Simulation; Rotationsstr{\"o}mung; Tr{\"a}gheitswelle; Taylor-Couette-Str{\"o}mung}, language = {en} } @article{MurkuteSayeedPuchaCofrepetal.2024, author = {Murkute, Charuta and Sayeed, Mostafa and Pucha-Cofrep, Franz and Carrillo-Rojas, Galo and Homeier, J{\"u}rgen and Limberger, Oliver and Fries, Andreas and Bendix, J{\"o}rg and Trachte, Katja}, title = {Turbulent energy and carbon fluxes in an Andean montane forest : energy balance and heat storage}, series = {Forests}, volume = {15}, journal = {Forests}, number = {10}, publisher = {MDPI}, address = {Basel}, issn = {1999-4907}, doi = {10.3390/f15101828}, year = {2024}, abstract = {High mountain rainforests are vital in the global energy and carbon cycle. Understanding the exchange of energy and carbon plays an important role in reflecting responses to climate change. In this study, an eddy covariance (EC) measurement system installed in the high Andean Mountains of southern Ecuador was used. As EC measurements are affected by heterogeneous topography and the vegetation height, the main objective was to estimate the effect of the sloped terrain and the forest on the turbulent energy and carbon fluxes considering the energy balance closure (EBC) and the heat storage. The results showed that the performance of the EBC was generally good and estimated it to be 79.5\%. This could be improved when the heat storage effect was considered. Based on the variability of the residuals in the diel, modifications in the imbalances were highlighted. Particularly, during daytime, the residuals were largest (56.9 W/m2 on average), with a clear overestimation. At nighttime, mean imbalances were rather weak (6.5 W/m2) and mostly positive while strongest underestimations developed in the transition period to morning hours (down to -100 W/m2). With respect to the Monin-Obukhov stability parameter ((z - d)/L) and the friction velocity (u*), it was revealed that the largest overestimations evolved in weak unstable and very stable conditions associated with large u* values. In contrast, underestimation was related to very unstable conditions. The estimated carbon fluxes were independently modelled with a non-linear regression using a light-response relationship and reached a good performance value (R2 = 0.51). All fluxes were additionally examined in the annual course to estimate whether both the energy and carbon fluxes resembled the microclimatological conditions of the study site. This unique study demonstrated that EC measurements provide valuable insights into land-surface-atmosphere interactions and contribute to our understanding of energy and carbon exchanges. Moreover, the flux data provide an important basis to validate coupled atmosphere ecosystem models.}, subject = {Energy balance closure; Heat storage; Carbon fluxes; Eddy covariance; Andes Mountains}, language = {en} } @article{AhmedZaforTrachte2024, author = {Ahmed, Rezwan and Zafor, Md. Abu and Trachte, Katja}, title = {Land-use and land-cover changes in Cottbus city and Spree-Neisse district, Germany, in the last two decades : a study using remote sensing data and Google Earth Engine}, series = {Remote Sensing}, volume = {16}, journal = {Remote Sensing}, number = {15}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs16152773}, year = {2024}, abstract = {Regular detection of land-use and land-cover (LULC) changes with high accuracy is necessary for natural resources management and sustainable urban planning. The produced LULC maps from Google Earth Engine (GEE) also illustrate the transformation of the LULC for the respective landscape over time. The selected study area, Cottbus City and the Spree-Neisse district in northeastern Germany, has undergone significant development over the past decades due to various factors, including urbanization and industrialization; also, the landscape has been converted in some areas for post-mining activities. Detection of LULC changes that have taken place over the last few decades thus plays a vital role in quantifying the impact of these factors while improving the knowledge of these developments and supporting the city planners or urban management officials before implementing further long-term development initiatives for the future. Therefore, the study aims to (i) detect LULC changes for the time slices 2002 and 2022, testing machine learning (ML) algorithms in supervised and unsupervised classification for Landsat satellite imageries, and (ii) validate the newly produced LULC maps with the available regional database (RDB) from the federal and state statistical offices, Germany, and the DynamicWorld (DW) near real-time 10 m global LULC data set powered by artificial intelligence (AI). The results of the Random Forest (RF) and the Smilecart classifiers of supervised classification using Landsat 9 OLI-2/TIRS-2 in 2022 demonstrated a validation accuracy of 88\% for both, with Kappa Index (KI) of 83\% and 84\%, respectively. Moreover, the Training Overall Accuracy (TOA) was 100\% for both years. The wekaKMeans cluster of the unsupervised classification also illustrated a similar transformation pattern in the LULC maps. Overall, the produced LULC maps offered an improved representation of the selected region's various land-cover classes (i.e., vegetation, waterbodies, built areas, and bare ground) in the last two decades (2022 to 2022).}, subject = {LULC; Machine learning; Landsat; Google Earth Engine; Landnutzung; Bodenbedeckung; Landsat; Google Earth; Maschinelles Lernen}, language = {en} } @phdthesis{Block2007, author = {Block, Alexander}, title = {Unsicherheiten in Oberfl{\"a}chen- und Bodenparametern und ihre Auswirkungen auf die Ergebnisse regionaler Klimasimulationen}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus-3636}, school = {BTU Cottbus - Senftenberg}, year = {2007}, abstract = {In regionalen Klimamodellen wird die untere Randbedingung durch Bodenmodelle bereitgestellt. Diese beinhalten Modellformulierungen, die eine große Anzahl an Eingabeparametern ben{\"o}tigen. Die exakte Bestimmung dieser Parameter stellt ein Problem dar, da sie f{\"u}r ein großes Gebiet in hoher r{\"a}umlicher und teilweise zeitlicher Aufl{\"o}sung erfolgen muss. Die unterschiedlichen Bestimmungsmethoden tragen dazu bei, dass f{\"u}r viele Oberfl{\"a}chen- und Bodenparameter nur ein m{\"o}glicher Wertebereich angegeben werden kann. Die Auswirkungen dieser ungenauen Kenntnis der Parameter auf die Ergebnisse regionaler Klimasimulationen mit dem CLM wurden untersucht. F{\"u}r den LAI, den Vegetationsbedeckungsgrad, die Wurzeltiefe, die Vegetationsalbedo, den Stomatawiderstand, die Bodenart und die W{\"a}rmeleitf{\"a}higkeit konnten Ver{\"a}nderungen der Modellergebnisse im Jahresmittel von 2-6 W/m^2 der Energiebilanzgr{\"o}ßen und 0,25 K der 2m-Temperatur nachgewiesen werden. Im Monatsmittel ergeben sich Ver{\"a}nderungen bis 20 W/m^2 f{\"u}r die turbulenten W{\"a}rmefl{\"u}sse und bis 1,5 K f{\"u}r die 2m-Temperatur. Es konnte gezeigt werden, dass die resultierenden Unsicherheiten in den Modellergebnissen dabei r{\"a}umlich und zeitlich variieren und stark vom Bodenwassergehalt beeinflusst werden. Die Benutzung zweier neuer Parameterdatens{\"a}tze f{\"u}hrte in den Simulationen zu einer Erw{\"a}rmung bis 0,5 K im Jahresmittel und konnte damit die gegen{\"u}ber Beobachtungsdaten vorhandene Temperaturabweichung von 1,5 K des Modells reduzieren.}, subject = {Klima / Modell; Boden; Energiebilanz; Regionale Klimamodelle; Bodenmodelle; Unsicherheiten; Regional climate simulation; Soil model; Uncertainties}, language = {de} } @phdthesis{Wilberforce2007, author = {Wilberforce, Nana Takyi}, title = {Climate change detection in Central Africa}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus-3583}, school = {BTU Cottbus - Senftenberg}, year = {2007}, abstract = {Central Africa is a band of land stretching from the Atlantic Ocean to the Horn of Africa between 18º N 0.75º S and 18º W 44º E. The climate of this region shows a transition zone from the Sahara Desert in the north to the wet tropical Guinean coast and equatorial continental interior in its south. In such transition zones, drought is a common occurrence; of great concern is the progressive drying of the region from the 1970s and into the 1980s. This thesis aims to investigate whether climate change has occurred in Central Africa in the 2nd half of the 20th century. The reanalysis data from the National Centres for Environmental Prediction (NCEP) was used to analyse trends of temperature and precipitation over Central Africa with the linear regression model and patterns of precipitation using principal component analysis. The results of the trend analyses revealed an average increase in temperature of 0.15K/ decade and an average decrease in precipitation of -91 mm/decade for the period 1948-2004 over the whole study area. A regional trend analysis of box averaged data (2.5° in latitude and longitude) revealed an increased precipitation over the Northern part," the Sahel", and a marked decrease in precipitation and an increase in temperature over the Eastern parts of the study areas especially in countries such as Somalia, Sudan and Ethiopia. To quantify the changes in temperature and precipitation for different climatic periods (1951-1980, 1961-1990 and 1971-2000), 30-year trend analyses were also performed. Results revealed a relatively stable temperature trend and fluctuations in the precipitation trend over the three 30 year climate periods. Principal component analysis produces a decomposition of the data field into spatial patterns (eigenvectors) and a temporal time series describing the temporal importance of these patterns. For precipitation over Central Africa, three patterns stand out for 60.39\% of the total variance in the precipitation over Central Africa. The individual principal components explain 37.6\%, 12.1\%, and 10.7\% respectively of the total variance. The first principal component captures progressive drying in Central Africa, the second principal component captures the different seasons within Central Africa and the third principal component captures the movement of the Intertropical Convergence Zone over Central Africa. Apart from explaining the current precipitation patterns over Central Africa, the use of principal component analysis in this study has demonstrated that a limited number of spatial patterns are basis for African weather, coordinate system for present day climate with maximum variance contribution along the first axis, maximum of the remaining variance along the second axis with subsequent axes explaining less variance can be used to explain precipitation variability within Central Africa. The same method can be used to explain temporal differences between climate change scenarios and present day climate.}, subject = {Zentralafrika; Klima{\"a}nderung; Wiederschlaf; Temperatur; Zentralafrika; Klimawandel; Precipitation; Temperature; Central Africa; Climate Change}, language = {en} } @phdthesis{Nawdiyal2014, author = {Nawdiyal, Manish}, title = {Effect of mining on regional climate}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-34631}, school = {BTU Cottbus - Senftenberg}, year = {2014}, abstract = {Intensive coal mining over the region of Lusatia covers a large area in southern Brandenburg and Saxony. Post mining this region has been filled with water resulting in lake formation. People living in the vicinity of mining area believe that the lake formation will increase convective precipitation in the neighboring area which shall lead to weathering of their structures. This was the prime reason to investigate the Lusatia region. The study about the impact of lake was carried out using data and CCLM simulation analyses. For data analysis, stations Senftenberg, Cottbus and Elsterheide-Geierswalde were selected. For the analysis, six 10 years running time series, CPDF were analyzed for all the three stations. Last three time series included the period of lake formation at station Elsterheide-Geierswalde. The CPDF time series showed little deviation for station Elsterheide-Geierswalde as compared to that for other two stations during lake formation periods. But in absence of parameters (temperature, wind data) data analysis was inconclusive. To observe effect of LULC (Land use and land cover) change on precipitation, three different simulations have been carried out, 1. VAT010: This simulation represents the potential vegetation of the whole domain. This describes the pre mining stage of the area when there was no mining. 2. VAT020: This simulation represents the introduction of lake points in the model domain. This describes the situation of area post mining, when lakes are formed.}, subject = {Mining effect; Regional climate; CCLM simulation; Data analysis; Bergbaut{\"a}tigkeit; Regionales Klima; CCLM-Simulation; Datenanalyse; Lausitz; Braunkohlenrevier; Rekultivierung; Klimaanalyse}, language = {en} }