{"id":{"repo_id":"tu-berlin","oai_identifier":"oai:depositonce.tu-berlin.de:11303/25550"},"canonical_url":"https://search.dev.ndltd.org/etd/tu-berlin/oai:depositonce.tu-berlin.de:11303/25550","repository":{"repo_id":"tu-berlin","name":"Technische Universität Berlin","base_url":"https://api-depositonce.tu-berlin.de/server/oai/request"},"display":{"title":"Regional dynamical downscaling and analysis of water balance across different regions and time scales","abstract":"Employing the regional dynamical downscaling (RDD) technique, we can enhance the spatial and temporal resolution of global reanalysis and general circulation model (GCM) data, providing improved data for studying ecological processes. This method ensures physical validity of the data, albeit at high computational costs.This thesis highlights the application and potential added value of RDD in addressing precipitation-related research questions across three distinct regions: the Galápagos Archipelago (GA), the Qaidam Basin (QB), and the Berlin-Brandenburg region in Germany (BB). The studies in these regions, characterised by unique climatic and geographic challenges, demonstrate the ability of RDD to resolve regional- and meso-scale processes and improve data availability in data-scarce region and enhance data-quality over complex terrains. The findings underline the critical role of optimised downscaling approaches in advancing process-based understanding and supporting ecological and climatic research. For the GA, a long-term high-resolution data set Galápagos Refined Analysis (GAR) was developed, by downscaling ERA5 reanalysis data to a grid-spacing of 2 km. The GAR dataset enables detailed analysis of meso-scale atmospheric processes in the GA, validated against in-situ measurements from a network of strategically installed weather stations. The data set is able to reproduce seasonal variability and annual measurement values for precipitation, air temperature at 2 m a.g.l., and mixing ratio at 2 m a.g.l. Further analysis of the GAR data set reveals its ability to reproduce the effects of quasi-periodic El Niño-Southern Oscillation and its extreme states, La Niña and El Niño. We present a spatially explicit analysis of these variables in the GAR dataset, describing their spatial distribution and the impacts of topography and the general wind field. From the GAR, we derive and examine long-term climatic trends in the GA, concluding that over the course of the study period from 1980 to 2023, the GA experienced does not exhibit any significant trends in these variables, but that its climate is dominated by interannual variability. The 3-dimensional data set also allows analysis of trends in the troposphere, where we find increase in layer thickness, induced by a warming trend in the lower and upper troposphere. Regarding the QB, the basin's water balance sensitivity to present-day and mid-Pliocene climate regimes, were examined, demonstrating the potential of RDD in paleoclimatic research. Downscaling of GCM data, to a resolution of 30 km, enabled us to investigate the regional drivers of the basin's water balance, including the influence of the mid-latitude westerlies and the effects of the East Asian Summer Monsoon. We find that the basin's water balance in the mid-Pliocene was influenced by the strengthened mid-latitude westerlies and by the East Asian Summer Monsoon reaching farther west into the QB. For the BB area, we present the Central Europe Refined analysis dataset version 2 (CER v2), building on the first version of the dataset (CER v1) by incorporating higher resolution, improved parameterisations and substituting the ERA-Interim forcing data with ERA5. Through rigorous sensitivity studies, an improved model setup was found, and the resulting data was validated with in-situ measurements from the measurement network of the German Weather Service. Comparison to the CER v1, global gridded data sets and the radar-derived RADOLAN data set, shows the improved performance of the CER v2 and its ability to reproduce monthly, seasonal, and annual precipitation patterns and amounts. This thesis substantiates the ability of RDD to provide deeper insights into regional and meso-scale climatic processes, supporting its application in diverse research contexts across regions, time periods and time-scales.","abstract_html":"Employing the regional dynamical downscaling (RDD) technique, we can enhance the spatial and temporal resolution of global reanalysis and general circulation model (GCM) data, providing improved data for studying ecological processes. This method ensures physical validity of the data, albeit at high computational costs.This thesis highlights the application and potential added value of RDD in addressing precipitation-related research questions across three distinct regions: the Galápagos Archipelago (GA), the Qaidam Basin (QB), and the Berlin-Brandenburg region in Germany (BB). The studies in these regions, characterised by unique climatic and geographic challenges, demonstrate the ability of RDD to resolve regional- and meso-scale processes and improve data availability in data-scarce region and enhance data-quality over complex terrains. The findings underline the critical role of optimised downscaling approaches in advancing process-based understanding and supporting ecological and climatic research. For the GA, a long-term high-resolution data set Galápagos Refined Analysis (GAR) was developed, by downscaling ERA5 reanalysis data to a grid-spacing of 2 km. The GAR dataset enables detailed analysis of meso-scale atmospheric processes in the GA, validated against in-situ measurements from a network of strategically installed weather stations. The data set is able to reproduce seasonal variability and annual measurement values for precipitation, air temperature at 2 m a.g.l., and mixing ratio at 2 m a.g.l. Further analysis of the GAR data set reveals its ability to reproduce the effects of quasi-periodic El Niño-Southern Oscillation and its extreme states, La Niña and El Niño. We present a spatially explicit analysis of these variables in the GAR dataset, describing their spatial distribution and the impacts of topography and the general wind field. From the GAR, we derive and examine long-term climatic trends in the GA, concluding that over the course of the study period from 1980 to 2023, the GA experienced does not exhibit any significant trends in these variables, but that its climate is dominated by interannual variability. The 3-dimensional data set also allows analysis of trends in the troposphere, where we find increase in layer thickness, induced by a warming trend in the lower and upper troposphere. Regarding the QB, the basin's water balance sensitivity to present-day and mid-Pliocene climate regimes, were examined, demonstrating the potential of RDD in paleoclimatic research. Downscaling of GCM data, to a resolution of 30 km, enabled us to investigate the regional drivers of the basin's water balance, including the influence of the mid-latitude westerlies and the effects of the East Asian Summer Monsoon. We find that the basin's water balance in the mid-Pliocene was influenced by the strengthened mid-latitude westerlies and by the East Asian Summer Monsoon reaching farther west into the QB. For the BB area, we present the Central Europe Refined analysis dataset version 2 (CER v2), building on the first version of the dataset (CER v1) by incorporating higher resolution, improved parameterisations and substituting the ERA-Interim forcing data with ERA5. Through rigorous sensitivity studies, an improved model setup was found, and the resulting data was validated with in-situ measurements from the measurement network of the German Weather Service. Comparison to the CER v1, global gridded data sets and the radar-derived RADOLAN data set, shows the improved performance of the CER v2 and its ability to reproduce monthly, seasonal, and annual precipitation patterns and amounts. This thesis substantiates the ability of RDD to provide deeper insights into regional and meso-scale climatic processes, supporting its application in diverse research contexts across regions, time periods and time-scales.","abstract_has_math":false,"creators":["Schmidt, Benjamin Rasmus Leander"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Scherer, Dieter"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-27T21:28:31Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":["https://creativecommons.org/licenses/by-nc/4.0/"],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://doi.org/10.14279/depositonce-24373"],"render_values":[{"text":"https://doi.org/10.14279/depositonce-24373","href":"https://doi.org/10.14279/depositonce-24373","code":true}]}]},"links":{"outbound_url":"https://depositonce.tu-berlin.de/handle/11303/25550","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Scherer, Dieter"]},{"key":"dc:creator","label":"Author","values":["Schmidt, Benjamin Rasmus Leander"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-09-08T15:44:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-09-08T15:44:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:type","label":"Dc Type","values":["Doctoral Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://creativecommons.org/licenses/by-nc/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://depositonce.tu-berlin.de/handle/11303/25550","https://doi.org/10.14279/depositonce-24373"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Employing the regional dynamical downscaling (RDD) technique, we can enhance the spatial and temporal resolution of global reanalysis and general circulation model (GCM) data, providing improved data for studying ecological processes. This method ensures physical validity of the data, albeit at high computational costs.This thesis highlights the application and potential added value of RDD in addressing precipitation-related research questions across three distinct regions: the Galápagos Archipelago (GA), the Qaidam Basin (QB), and the Berlin-Brandenburg region in Germany (BB). The studies in these regions, characterised by unique climatic and geographic challenges, demonstrate the ability of RDD to resolve regional- and meso-scale processes and improve data availability in data-scarce region and enhance data-quality over complex terrains. The findings underline the critical role of optimised downscaling approaches in advancing process-based understanding and supporting ecological and climatic research. For the GA, a long-term high-resolution data set Galápagos Refined Analysis (GAR) was developed, by downscaling ERA5 reanalysis data to a grid-spacing of 2 km. The GAR dataset enables detailed analysis of meso-scale atmospheric processes in the GA, validated against in-situ measurements from a network of strategically installed weather stations. The data set is able to reproduce seasonal variability and annual measurement values for precipitation, air temperature at 2 m a.g.l., and mixing ratio at 2 m a.g.l. Further analysis of the GAR data set reveals its ability to reproduce the effects of quasi-periodic El Niño-Southern Oscillation and its extreme states, La Niña and El Niño. We present a spatially explicit analysis of these variables in the GAR dataset, describing their spatial distribution and the impacts of topography and the general wind field. From the GAR, we derive and examine long-term climatic trends in the GA, concluding that over the course of the study period from 1980 to 2023, the GA experienced does not exhibit any significant trends in these variables, but that its climate is dominated by interannual variability. The 3-dimensional data set also allows analysis of trends in the troposphere, where we find increase in layer thickness, induced by a warming trend in the lower and upper troposphere. Regarding the QB, the basin's water balance sensitivity to present-day and mid-Pliocene climate regimes, were examined, demonstrating the potential of RDD in paleoclimatic research. Downscaling of GCM data, to a resolution of 30 km, enabled us to investigate the regional drivers of the basin's water balance, including the influence of the mid-latitude westerlies and the effects of the East Asian Summer Monsoon. We find that the basin's water balance in the mid-Pliocene was influenced by the strengthened mid-latitude westerlies and by the East Asian Summer Monsoon reaching farther west into the QB. For the BB area, we present the Central Europe Refined analysis dataset version 2 (CER v2), building on the first version of the dataset (CER v1) by incorporating higher resolution, improved parameterisations and substituting the ERA-Interim forcing data with ERA5. Through rigorous sensitivity studies, an improved model setup was found, and the resulting data was validated with in-situ measurements from the measurement network of the German Weather Service. Comparison to the CER v1, global gridded data sets and the radar-derived RADOLAN data set, shows the improved performance of the CER v2 and its ability to reproduce monthly, seasonal, and annual precipitation patterns and amounts. This thesis substantiates the ability of RDD to provide deeper insights into regional and meso-scale climatic processes, supporting its application in diverse research contexts across regions, time periods and time-scales.","Durch die Anwendung des regionalen dynamischen Downscaling (RDD) können die räumliche und zeitliche Auflösung globaler Reanalyse- und Modelldatensätze verbessert und so optimierte Daten zur Untersuchung ökologischer Prozesse führt. Diese Methode gewährleistet die physikalische Konsistenz der Daten, ist jedoch mit hohen Rechenkosten verbunden. In dieser Arbeit wird die Tauglichkeit von RDD zur Beantwortung von niederschlagsbezogenen Forschungsfragen in drei unterschiedlichen Regionen untersucht: dem Galápagos-Archipel (GA), dem Qaidam-Becken (QB) und der Region Berlin-Brandenburg in Deutschland (BB). Die Untersuchungen in den Regionen, mit einzigartigen klimatischen und geografischen Bedingungen, demonstrieren die Fähigkeit von RDD, regionale und mesoskalige atmosphärische Prozesse zu erfassen und so die Datenverfügbarkeit in datenarmen Regionen zu verbessern und die Datenqualität in komplexem Gelände zu steigern. Die Ergebnisse unterstreichen die entscheidende Rolle regional optimierter Datensätze, gewonnen durch dynamisches Downscaling, bei der Verbesserung des Prozessverständnisses und der Beantwortung ökologischer und klimatischer Forschungsfragen. Für das GA wurde ein langfristiger hochauflösender Datensatz, namens Galápagos Refined Analysis (GAR), entwickelt, indem ERA5-Reanalysedaten auf eine Gitterweite von 2 km herunterskaliert wurden. Der GAR-Datensatz ermöglicht detaillierte Analysen mesoskaliger atmosphärischer Prozesse im und um das GA und wurde mit in-situ Messungen eines Netzwerks strategisch installierter Wetterstationen validiert. Der Datensatz ist in der Lage, die saisonale Variabilität und die jährlichen Messwerte für Niederschlag, Lufttemperatur in 2m Höhe über Grund und Mischungsverhältnis in 2m Höhe über Grund abzubilden. Weitere Analysen des GAR-Datensatzes zeigen, dass er die Auswirkungen der quasi-periodischen El-Niño-Southern- Oscillation und deren Extremzustände La Niña und El Niño reproduzieren kann. Die räumlich explizite Analyse der Daten zeigt deren räumliche Verteilung sowie den Einfluss der Topografie und des allgemeinen Windfeldes auf die Werte. Auf Grundlage des GAR-Datensatzes haben wir zusätzlich die langfristigen klimatischen Trends im GA untersucht. Wir kommen zu dem Schluss, dass die untersuchten Variablen im Untersuchungszeitraum von 1980 bis 2023 keine signifikanten Trends aufweisen, sondern dass die Zeitreihen von interannualer Variabilität dominiert sind. Der dreidimensionale Datensatz ermöglicht zudem die Analyse von Trends in der Troposphäre, wo wir eine Zunahme der Schichtdicke feststellen, verursacht durch einen Erwärmungstrend in der unteren und oberen Troposphäre. Im Hinblick auf das QB wurde die Sensitivität des Wasserhaushalts des Beckens gegenüber dem heutigen und dem pliozänen Klima untersucht, was das Potenzial von RDD in der paläoklimatischen Forschung demonstriert. Die Herunterskalierung von GCM-Daten auf eine Auflösung von 30 km ermöglichte es uns, die regionalen Treiber desWasserhaushalts des Beckens zu untersuchen, einschließlich des Einflusses derWestwinde der mittleren Breiten und der Auswirkungen des Ostasiatischen Sommermonsuns. Wir stellen fest, dass der Wasserhaushalt des Beckens im Pliozän durch die verstärkten Westwinde der mittleren Breiten und durch den weiter westlich bis in das QB reichenden Ostasiatischen Sommermonsun beeinflusst wurde. Für die BB-Region präsentieren wir die zweite Version des Central Europe Refined Analysis Datensatzes (CER v2), die auf der ersten Version des Datensatzes (CER v1) aufbaut. Zur Optimierung der Daten wurde die Auflösung erhöht, die physikalische Parametrisierung angepasst und die ERA-Interim-Antriebsdaten durch ERA5-Daten ersetzt. Durch rigorose Sensitivitätsstudien wurde die passende Modellkonfiguration gefunden und der resultierende Datensatz wurde mit in-situ Messungen aus dem Messnetz des Deutschen Wetterdienstes validiert. Vergleiche mit CER v1, globalen Gitterdatensätzen und dem radarbasierten RADOLAN-Datensatz zeigen die hohe Genauigkeit des Datensatzes und seine Fähigkeit, monatliche, saisonale und jährliche Niederschlagsmuster und -mengen abzubilden. Diese Arbeit untermauert die Fähigkeit von RDD, tiefere Einblicke in regionale und mesoskalige klimatische Prozesse zu liefern, und belegt ihre Anwendbarkeit in verschiedenen Forschungskontexten über Regionen, Zeiträume und Zeitskalen hinweg."]},{"key":"dc:title","label":"Title","values":["Regional dynamical downscaling and analysis of water balance across different regions and time scales"]}]}],"canonical_facts":{"dc:contributor.advisor":["Scherer, Dieter"],"dc:creator":["Schmidt, Benjamin Rasmus Leander"],"dc:date.accessioned":["2025-09-08T15:44:12Z"],"dc:date.available":["2025-09-08T15:44:12Z"],"dc:date.issued":["2025"],"dc:description.abstract":["Employing the regional dynamical downscaling (RDD) technique, we can enhance the spatial and temporal resolution of global reanalysis and general circulation model (GCM) data, providing improved data for studying ecological processes. This method ensures physical validity of the data, albeit at high computational costs.This thesis highlights the application and potential added value of RDD in addressing precipitation-related research questions across three distinct regions: the Galápagos Archipelago (GA), the Qaidam Basin (QB), and the Berlin-Brandenburg region in Germany (BB). The studies in these regions, characterised by unique climatic and geographic challenges, demonstrate the ability of RDD to resolve regional- and meso-scale processes and improve data availability in data-scarce region and enhance data-quality over complex terrains. The findings underline the critical role of optimised downscaling approaches in advancing process-based understanding and supporting ecological and climatic research. For the GA, a long-term high-resolution data set Galápagos Refined Analysis (GAR) was developed, by downscaling ERA5 reanalysis data to a grid-spacing of 2 km. The GAR dataset enables detailed analysis of meso-scale atmospheric processes in the GA, validated against in-situ measurements from a network of strategically installed weather stations. The data set is able to reproduce seasonal variability and annual measurement values for precipitation, air temperature at 2 m a.g.l., and mixing ratio at 2 m a.g.l. Further analysis of the GAR data set reveals its ability to reproduce the effects of quasi-periodic El Niño-Southern Oscillation and its extreme states, La Niña and El Niño. We present a spatially explicit analysis of these variables in the GAR dataset, describing their spatial distribution and the impacts of topography and the general wind field. From the GAR, we derive and examine long-term climatic trends in the GA, concluding that over the course of the study period from 1980 to 2023, the GA experienced does not exhibit any significant trends in these variables, but that its climate is dominated by interannual variability. The 3-dimensional data set also allows analysis of trends in the troposphere, where we find increase in layer thickness, induced by a warming trend in the lower and upper troposphere. Regarding the QB, the basin's water balance sensitivity to present-day and mid-Pliocene climate regimes, were examined, demonstrating the potential of RDD in paleoclimatic research. Downscaling of GCM data, to a resolution of 30 km, enabled us to investigate the regional drivers of the basin's water balance, including the influence of the mid-latitude westerlies and the effects of the East Asian Summer Monsoon. We find that the basin's water balance in the mid-Pliocene was influenced by the strengthened mid-latitude westerlies and by the East Asian Summer Monsoon reaching farther west into the QB. For the BB area, we present the Central Europe Refined analysis dataset version 2 (CER v2), building on the first version of the dataset (CER v1) by incorporating higher resolution, improved parameterisations and substituting the ERA-Interim forcing data with ERA5. Through rigorous sensitivity studies, an improved model setup was found, and the resulting data was validated with in-situ measurements from the measurement network of the German Weather Service. Comparison to the CER v1, global gridded data sets and the radar-derived RADOLAN data set, shows the improved performance of the CER v2 and its ability to reproduce monthly, seasonal, and annual precipitation patterns and amounts. This thesis substantiates the ability of RDD to provide deeper insights into regional and meso-scale climatic processes, supporting its application in diverse research contexts across regions, time periods and time-scales.","Durch die Anwendung des regionalen dynamischen Downscaling (RDD) können die räumliche und zeitliche Auflösung globaler Reanalyse- und Modelldatensätze verbessert und so optimierte Daten zur Untersuchung ökologischer Prozesse führt. Diese Methode gewährleistet die physikalische Konsistenz der Daten, ist jedoch mit hohen Rechenkosten verbunden. In dieser Arbeit wird die Tauglichkeit von RDD zur Beantwortung von niederschlagsbezogenen Forschungsfragen in drei unterschiedlichen Regionen untersucht: dem Galápagos-Archipel (GA), dem Qaidam-Becken (QB) und der Region Berlin-Brandenburg in Deutschland (BB). Die Untersuchungen in den Regionen, mit einzigartigen klimatischen und geografischen Bedingungen, demonstrieren die Fähigkeit von RDD, regionale und mesoskalige atmosphärische Prozesse zu erfassen und so die Datenverfügbarkeit in datenarmen Regionen zu verbessern und die Datenqualität in komplexem Gelände zu steigern. Die Ergebnisse unterstreichen die entscheidende Rolle regional optimierter Datensätze, gewonnen durch dynamisches Downscaling, bei der Verbesserung des Prozessverständnisses und der Beantwortung ökologischer und klimatischer Forschungsfragen. Für das GA wurde ein langfristiger hochauflösender Datensatz, namens Galápagos Refined Analysis (GAR), entwickelt, indem ERA5-Reanalysedaten auf eine Gitterweite von 2 km herunterskaliert wurden. Der GAR-Datensatz ermöglicht detaillierte Analysen mesoskaliger atmosphärischer Prozesse im und um das GA und wurde mit in-situ Messungen eines Netzwerks strategisch installierter Wetterstationen validiert. Der Datensatz ist in der Lage, die saisonale Variabilität und die jährlichen Messwerte für Niederschlag, Lufttemperatur in 2m Höhe über Grund und Mischungsverhältnis in 2m Höhe über Grund abzubilden. Weitere Analysen des GAR-Datensatzes zeigen, dass er die Auswirkungen der quasi-periodischen El-Niño-Southern- Oscillation und deren Extremzustände La Niña und El Niño reproduzieren kann. Die räumlich explizite Analyse der Daten zeigt deren räumliche Verteilung sowie den Einfluss der Topografie und des allgemeinen Windfeldes auf die Werte. Auf Grundlage des GAR-Datensatzes haben wir zusätzlich die langfristigen klimatischen Trends im GA untersucht. Wir kommen zu dem Schluss, dass die untersuchten Variablen im Untersuchungszeitraum von 1980 bis 2023 keine signifikanten Trends aufweisen, sondern dass die Zeitreihen von interannualer Variabilität dominiert sind. Der dreidimensionale Datensatz ermöglicht zudem die Analyse von Trends in der Troposphäre, wo wir eine Zunahme der Schichtdicke feststellen, verursacht durch einen Erwärmungstrend in der unteren und oberen Troposphäre. Im Hinblick auf das QB wurde die Sensitivität des Wasserhaushalts des Beckens gegenüber dem heutigen und dem pliozänen Klima untersucht, was das Potenzial von RDD in der paläoklimatischen Forschung demonstriert. Die Herunterskalierung von GCM-Daten auf eine Auflösung von 30 km ermöglichte es uns, die regionalen Treiber desWasserhaushalts des Beckens zu untersuchen, einschließlich des Einflusses derWestwinde der mittleren Breiten und der Auswirkungen des Ostasiatischen Sommermonsuns. Wir stellen fest, dass der Wasserhaushalt des Beckens im Pliozän durch die verstärkten Westwinde der mittleren Breiten und durch den weiter westlich bis in das QB reichenden Ostasiatischen Sommermonsun beeinflusst wurde. Für die BB-Region präsentieren wir die zweite Version des Central Europe Refined Analysis Datensatzes (CER v2), die auf der ersten Version des Datensatzes (CER v1) aufbaut. Zur Optimierung der Daten wurde die Auflösung erhöht, die physikalische Parametrisierung angepasst und die ERA-Interim-Antriebsdaten durch ERA5-Daten ersetzt. Durch rigorose Sensitivitätsstudien wurde die passende Modellkonfiguration gefunden und der resultierende Datensatz wurde mit in-situ Messungen aus dem Messnetz des Deutschen Wetterdienstes validiert. Vergleiche mit CER v1, globalen Gitterdatensätzen und dem radarbasierten RADOLAN-Datensatz zeigen die hohe Genauigkeit des Datensatzes und seine Fähigkeit, monatliche, saisonale und jährliche Niederschlagsmuster und -mengen abzubilden. Diese Arbeit untermauert die Fähigkeit von RDD, tiefere Einblicke in regionale und mesoskalige klimatische Prozesse zu liefern, und belegt ihre Anwendbarkeit in verschiedenen Forschungskontexten über Regionen, Zeiträume und Zeitskalen hinweg."],"dc:identifier.uri":["https://depositonce.tu-berlin.de/handle/11303/25550","https://doi.org/10.14279/depositonce-24373"],"dc:language.iso":["en"],"dc:rights.uri":["https://creativecommons.org/licenses/by-nc/4.0/"],"dc:title":["Regional dynamical downscaling and analysis of water balance across different regions and time scales"],"dc:type":["Doctoral Thesis"]},"updated_at":"2026-07-27T21:28:31Z"}