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  • 1
    Publication Date: 2022-10-13
    Description: Accurate and reliable precipitation data with high spatial and temporal resolution are essential in studying climate variability, water resources management, and hydrological forecasting. A range of global precipitation data are available to this end, but how well these capture actual precipitation remains unknown, particularly for mountain regions where ground stations are sparse. We examined the performance of three global high‐resolution precipitation products for capturing precipitation over Central Asia, a hotspot of climate change, where reliable precipitation data are particularly scarce. Specifically, we evaluated MSWEP, CHIRPS, and GSMAP against independent gauging stations for the period 1985–2015. Our results show that MSWEP and CHIRPS outperformed GSMAP for wetter periods (i.e., winter and spring) and wetter locations (150–600 mm·year−1), lowlands, and mid‐altitudes (0–3,000 m), and regions dominated by winter and spring precipitation. MSWEP performed best in representing temporal precipitation dynamics and CHIRPS excelled in capturing the volume and distribution of precipitation. All precipitation products poorly estimated precipitation at higher elevations (〉3,000 m), in drier areas (〈150 mm), and in regions characterized by summer precipitation. All products accurately detected dry spells, but their performance decreased for wet spells with increasing precipitation intensity. In sum, we find that CHIRPS and MSWEP provide the most reliable high‐resolution precipitation estimates for Central Asia. However, the high spatial and temporal heterogeneity of the performance call for a careful selection of a suitable product for local applications considering the prevailing precipitation dynamics, climatic, and topographic conditions.
    Description: We present the first quantitative evaluation of global high‐resolution (below 12 km) precipitation products against independent ground observations over Central Asia. Our results show that MSWEP was best at representing temporal precipitation dynamics, and CHIRPS was most prominent in representing the volume and distribution of precipitation. This is especially the case of wet seasons, altitudes below 3,000 m, and regions dominated by spring and winter precipitation. Our analysis provides key insights on the precipitation products' suitability for local hydrological applications.
    Description: Leibniz‐Institut für Agrarentwicklung in Transformationsökonomien
    Description: Volkswagen Foundation http://dx.doi.org/10.13039/501100001663
    Keywords: ddc:551.6
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-11-15
    Description: Changes in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.
    Description: BMBF
    Description: BMBF
    Description: ERA.net
    Description: danish ERC program
    Description: Ural Branch, Russian Academy of Sciences https://doi.org/10.13039/501100006422
    Description: BMBF
    Description: Potsdam-Institut für Klimafolgenforschung (PIK) e.V. (3500)
    Keywords: ddc:631.4 ; Carbon emissions ; Soil carbon stocks ; Model simulations ; Steppe region ; Cropland expansion
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2021-03-29
    Description: Forests in lowland Bolivia suffer from severe deforestation caused by different types of agents and land use activities. We identify three major proximate causes of deforestation. The largest share of deforestation is attributable to the expansion of mechanized agriculture, followed by cattle ranching and small-scale agriculture. We utilize a spatially explicit multinomial logit model to analyze the determinants of each of these proximate causes of deforestation between 1992 and 2004. We substantiate the quantitative insights with a qualitative analysis of historical processes that have shaped land use patterns in the Bolivian lowlands to date. Our results suggest that the expansion of mechanized agriculture occurs mainly in response to good access to export markets, fertile soil, and intermediate rainfall conditions. Increases in small-scale agriculture are mainly associated with a humid climate, fertile soil, and proximity to local markets. Forest conversion into pastures for cattle ranching occurs mostly irrespective of environmental determinants and can mainly be explained by access to local markets. Land use restrictions, such as protected areas, seem to prevent the expansion of mechanized agriculture but have little impact on the expansion of small-scale agriculture and cattle ranching. The analysis of future deforestation trends reveals possible hotspots of future expansion for each proximate cause and specifically highlights the possible opening of new frontiers for deforestation due to mechanized agriculture. Whereas the quantitative analysis effectively elucidates the spatial patterns of recent agricultural expansion, the interpretation of long-term historic drivers reveals that the timing and quantity of forest conversion are often triggered by political interventions and historical legacies.
    Keywords: Bolivia; Amazon; Deforestation; Proximate causes; Spatial analysis; Multinomial logistic regression ; 551 ; Environment; Geology; Geography (general); Regional/Spatial Science; Climate Change; Nature Conservation; Oceanography
    Language: English
    Type: article , publishedVersion
    Format: application/pdf
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  • 4
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    Univ. Freiburg (Breisgau)
    Publication Date: 2021-03-29
    Description: Satellite observations with high spatial and temporal resolution have revealed the highly dynamic nature of the solar corona and enabled us to study physical processes in the outer atmosphere of our mother star in great detail. This thesis deals with dynamic processes in coronal loops, i.e. magnetic structures which may be thought of as the elementary building blocks of the solar corona. Using computational fluid dynamics as a tool, I calculate time-dependent models of solar coronal loops in order to address the following questions: Are dynamic processes in coronal loops, such as flows and transient brightenings, necessarily the result of a time-dependent driving mechanism? Can various observations of fast downflows be explained by a common mechanism? Which parameters determine the dynamics of coronal loops? It is found that coronal loops which are predominantly heated around their footpoints can develop a thermal instability in the upper part of the loop. This instability results in a self-amplifying catastrophic cooling process and leads to the formation of dense, cool plasma condensations. The first part of the work focuses on plasma condensations in short cool loops, which presumably constitute the solar transition region, and describes how the catastrophic cooling process leads to transient brightenings in spectral lines formed in the transition region ...
    Description: thesis
    Keywords: 523 ; TGC 765 ; TBI 000 ; Korona {Astronomie: Sonne} ; Ultraviolett-Astronomie
    Language: English
    Type: monograph , publishedVersion
    Format: 161 S.
    Format: application/pdf
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  • 5
    Publication Date: 2021-06-28
    Description: Changes in land management and climate alter vegetation dynamics, but the determinants of vegetation changes often remain elusive, especially in global drylands. Here we assess the determinants of grassland greenness on the Mongolian Plateau, one of the world's largest grassland biomes, which covers Mongolia and the province of Inner Mongolia in China. We use spatial panel regressions to quantify the impact of precipitation, temperature, radiation, and the intensity of livestock grazing on the normalized difference vegetation indices (NDVI) during the growing seasons from 1982 to 2015 at the county level. The results suggest that the Mongolian Plateau experienced vegetation greening from 1982 to 2015. Precipitation and animal density were the most influential factors contributing to higher NDVI on the grasslands of Inner Mongolia and Mongolia. Our results highlight the dominant effect of climate variability, and especially of the precipitation variability, on the grassland greenness in Mongolian drylands. The findings challenge the common belief that higher grazing pressure is the key driver for land degradation. The analysis exemplifies how representative wall‐to‐wall results for large areas can be attained from exploring space–time data and adds empirical insights to the puzzling relationship between grazing intensity and vegetation growth in dryland areas.
    Description: European Union's Framework Programme for Research and Innovation ‐ Horizon 2020 (2014‐2020)
    Description: Alexander von Humboldt Foundation of Germany
    Keywords: 333.7 ; China ; climate change ; grassland ; livestock grazing ; NDVI ; spatial panel regression ; vegetation growth
    Type: article
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