TY - JOUR A1 - Sedova, Barbora A1 - Kalkuhl, Matthias A1 - Mendelsohn, Robert T1 - Distributional impacts of weather and climate in rural India JF - Economics of disasters and climate change N2 - Climate-related costs and benefits may not be evenly distributed across the population. We study distributional implications of seasonal weather and climate on within-country inequality in rural India. Utilizing a first difference approach, we find that the poor are more sensitive to weather variations than the non-poor. The poor respond more strongly to (seasonal) temperature changes: negatively in the (warm) spring season, more positively in the (cold) rabi season. Less precipitation is harmful to the poor in the monsoon kharif season and beneficial in the winter and spring seasons. We show that adverse weather aggravates inequality by reducing consumption of the poor farming households. Future global warming predicted under RCP8.5 is likely to exacerbate these effects, reducing consumption of poor farming households by one third until the year 2100. We also find inequality in consumption across seasons with higher consumption during the harvest and lower consumption during the sowing seasons. KW - climate change KW - weather KW - inequality KW - household analysis KW - India KW - econometrics Y1 - 2019 U6 - https://doi.org/10.1007/s41885-019-00051-1 SN - 2511-1280 SN - 2511-1299 VL - 4 IS - 1 SP - 5 EP - 44 PB - Springer CY - Cham ER - TY - JOUR A1 - Cervantes, Sebastian A1 - Shprits, Yuri Y. A1 - Aseev, Nikita A1 - Drozdov, Alexander A1 - Castillo Tibocha, Angelica Maria A1 - Stolle, Claudia T1 - Identifying radiation belt electron source and loss processes by assimilating spacecraft data in a three-dimensional diffusion model JF - Journal of geophysical research : Space physics N2 - Data assimilation aims to blend incomplete and inaccurate data with physics-based dynamical models. In the Earth's radiation belts, it is used to reconstruct electron phase space density, and it has become an increasingly important tool in validating our current understanding of radiation belt dynamics, identifying new physical processes, and predicting the near-Earth hazardous radiation environment. In this study, we perform reanalysis of the sparse measurements from four spacecraft using the three-dimensional Versatile Electron Radiation Belt diffusion model and a split-operator Kalman filter over a 6-month period from 1 October 2012 to 1 April 2013. In comparison to previous works, our 3-D model accounts for more physical processes, namely, mixed pitch angle-energy diffusion, scattering by Electromagnetic Ion Cyclotron waves, and magnetopause shadowing. We describe how data assimilation, by means of the innovation vector, can be used to account for missing physics in the model. We use this method to identify the radial distances from the Earth and the geomagnetic conditions where our model is inconsistent with the measured phase space density for different values of the invariants mu and K. As a result, the Kalman filter adjusts the predictions in order to match the observations, and we interpret this as evidence of where and when additional source or loss processes are active. The current work demonstrates that 3-D data assimilation provides a comprehensive picture of the radiation belt electrons and is a crucial step toward performing reanalysis using measurements from ongoing and future missions. KW - acceleration KW - code KW - density KW - emic waves KW - energetic particle KW - mechanisms KW - reanalysis KW - ultrarelativistic electrons KW - weather Y1 - 2019 U6 - https://doi.org/10.1029/2019JA027514 SN - 2169-9380 SN - 2169-9402 VL - 125 IS - 1 PB - American Geophysical Union CY - Washington ER - TY - THES A1 - Šedová, Barbora T1 - Heterogeneous effects of weather and climate change on human migration T1 - Heterogene Auswirkungen von Wetter und Klimawandel auf menschliche Migration N2 - While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices. N2 - Während die geschätzten Zahlen zukünftiger Klimamigranten alarmierend sind, deuten die wachsenden empirischen Belege darauf hin, dass der Klimawandel nicht automatisch zu mehr Migration führt. Denn auch wenn klimabezogene Einflüsse die Entscheidung zur Migration zunehmend beeinflussen, wird diese durch eine Vielzahl von Faktoren, wie beispielsweise den sozioökonomischen und politischen Bedingungen, beeinflusst. Der Zusammenhang zwischen Klimawandel und Migration ist also stark kontextabhängig. Diese Dissertation besteht aus fünf Artikeln und zeigt, wann und wie Klimamigration entsteht, indem sie die heterogenen klimatischen Einflüsse in Entwicklungsländern untersucht. Gestützt auf ökonomische Migrationstheorien analysiere ich Datensätze aus den Natur- und Sozialwissenschaften mithilfe von Methodiken der ökonometrischen Kausalanalyse, der Geoinformationssysteme und der systematischen Literatursynthese. In drei von fünf Kapiteln schätze ich die kausalen Auswirkungen des Klimawandels auf Ungleichheit und Migration in Indien und Subsahara Afrika. Durch die Verwendung von Interaktionstermen und die Analyse von Teilstichproben untersuche ich in Regressionsmodellen, wie sich diese Beziehungen für verschiedene Bevölkerungsgruppen unterscheiden. In den verbleibenden zwei Kapiteln fasse ich die ökonometrische Literatur zur Klimamigration systematisch zusammen. Zunächst führe ich eine umfassende Meta-Regressionsanalyse durch, um die allgemeine Klimamigrationsmuster zusammenzufassen und die widersprüchliche Evidenz zu erklären. In einem zweiten Schritt untersuche ich die ökonometrische Klimamigrationsliteratur aus einer methodologischen Perspektive, um Best-Practice-Leitlinien für künftige empirische Analysen von Klimamigration bereitzustellen. Insgesamt bestätigen die Ergebnisse dieser Dissertation, dass die klimatischen Einflüsse auf menschliche Migration heterogen sind und von den sozioökonomischen Merkmalen der einzelnen Haushalte wie dem Wohlstand und Bildungsniveau, der Abhängigkeit von der Landwirtschaft oder dem Zugang zu Anpassungstechnologien und Versicherungen, mitbestimmt werden. Ich finde beispielsweise, dass ungünstige klimatische Schocks zu einem Migrationsanstieg im ländlichen Indien führen, sie aber die Migration im landwirtschaftlichen Subsahara Afrika, wo das durchschnittliche Einkommensniveau viel niedriger ist, verhindern. Ich habe zudem herausgefunden, dass im Gegensatz zu lokalen klimatischen Schocks, die in erster Linie die Binnenmigration in die Städte verstärken und damit die Urbanisierung beschleunigen, globale Schocks über landwirtschaftliche Erzeugerpreise die Abwanderung in benachbarte Länder antreiben. Diese Ergebnisse erweitern unser derzeitiges Verständnis, indem sie verdeutlichen, wann und wie Akteure auf unterschiedliche Klimaereignisse mit der Entscheidung zur Migration reagieren. Die daraus resultierenden Erkenntnisse können helfen, Entscheidungsträger auf drei wichtige Arten zu informieren. Erstens, wenn man weiß, wer die Klimamigranten sind und welche Destinationsziele sie wählen, wird Klimamigration vorhersehbarer und damit kontrollierbarer. Dies kann verhindern, dass sie zu einer humanitären Krise wird. Zweitens hilft die Identifizierung von Bevölkerungsgruppen, die nicht in der Lage sind, sich durch Migration an die veränderten klimatischen Bedingungen anzupassen, dabei, unfreiwillige Immobilität zu vermeiden, was wiederum auch eine potenzielle humanitären Krise verhindert. Drittens können all diese Informationen helfen, Kosten und Nutzen der Klima(im)mobilität genauer zu bewerten und so die Social Cost of Carbon genauer einzuschätzen. KW - migration KW - weather KW - climate change KW - agriculture KW - food prices KW - inequality KW - econometrics KW - Landwirtschaft KW - Klimawandel KW - Ökonometrie KW - Lebensmittelpreise KW - Ungleichheit KW - Migration KW - Wetter Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-536733 ER - TY - JOUR A1 - Ungelenk, Johannes T1 - The storm is up and all is on the hazard BT - Shakespeares Tragödien und das Wetter JF - Poetica N2 - The article is dedicated to the role of weather in Shakespeare’s tragedies. It traces a dense net of weather instances – stage weather, narrated weather events, weather imagery – throughout his plays, and attempts to reconstruct the weather’s structural implications for the tragedy genre. The way early modern humoral pathology understood the weather’s influence on the humours of the human body – of which Shakespeare’s plays themselves give evidence – provides the background for reconstructing the function of the weather as a source of tragic force. Its turbulence not only infects the characters in the play and thereby drives the plot, but also transgresses the boundaries of the fictional world and affects spectators in the auditorium. KW - Shakespeare KW - Wetter KW - weather Y1 - 2020 U6 - https://doi.org/10.30965/25890530-05101003 SN - 0303-4178 SN - 2589-0530 VL - 51 IS - 1-2 SP - 119 EP - 147 ER - TY - JOUR A1 - Ayzel, Georgy A1 - Scheffer, Tobias A1 - Heistermann, Maik T1 - RainNet v1.0 BT - a convolutional neural network for radar-based precipitation nowcasting JF - Geoscientific Model Development N2 - In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting. Its design was inspired by the U-Net and SegNet families of deep learning models, which were originally designed for binary segmentation tasks. RainNet was trained to predict continuous precipitation intensities at a lead time of 5min, using several years of quality-controlled weather radar composites provided by the German Weather Service (DWD). That data set covers Germany with a spatial domain of 900km × 900km and has a resolution of 1km in space and 5min in time. Independent verification experiments were carried out on 11 summer precipitation events from 2016 to 2017. In order to achieve a lead time of 1h, a recursive approach was implemented by using RainNet predictions at 5min lead times as model inputs for longer lead times. In the verification experiments, trivial Eulerian persistence and a conventional model based on optical flow served as benchmarks. The latter is available in the rainymotion library and had previously been shown to outperform DWD's operational nowcasting model for the same set of verification events. RainNet significantly outperforms the benchmark models at all lead times up to 60min for the routine verification metrics mean absolute error (MAE) and the critical success index (CSI) at intensity thresholds of 0.125, 1, and 5mm h⁻¹. However, rainymotion turned out to be superior in predicting the exceedance of higher intensity thresholds (here 10 and 15mm h⁻¹). The limited ability of RainNet to predict heavy rainfall intensities is an undesirable property which we attribute to a high level of spatial smoothing introduced by the model. At a lead time of 5min, an analysis of power spectral density confirmed a significant loss of spectral power at length scales of 16km and below. Obviously, RainNet had learned an optimal level of smoothing to produce a nowcast at 5min lead time. In that sense, the loss of spectral power at small scales is informative, too, as it reflects the limits of predictability as a function of spatial scale. Beyond the lead time of 5min, however, the increasing level of smoothing is a mere artifact – an analogue to numerical diffusion – that is not a property of RainNet itself but of its recursive application. In the context of early warning, the smoothing is particularly unfavorable since pronounced features of intense precipitation tend to get lost over longer lead times. Hence, we propose several options to address this issue in prospective research, including an adjustment of the loss function for model training, model training for longer lead times, and the prediction of threshold exceedance in terms of a binary segmentation task. Furthermore, we suggest additional input data that could help to better identify situations with imminent precipitation dynamics. The model code, pretrained weights, and training data are provided in open repositories as an input for such future studies. KW - weather KW - models KW - skill Y1 - 2020 U6 - https://doi.org/10.5194/gmd-13-2631-2020 SN - 1991-959X SN - 1991-9603 VL - 13 IS - 6 SP - 2631 EP - 2644 PB - Copernicus Publ. CY - Göttingen ER - TY - GEN A1 - Ayzel, Georgy A1 - Scheffer, Tobias A1 - Heistermann, Maik T1 - RainNet v1.0 BT - a convolutional neural network for radar-based precipitation nowcasting T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting. Its design was inspired by the U-Net and SegNet families of deep learning models, which were originally designed for binary segmentation tasks. RainNet was trained to predict continuous precipitation intensities at a lead time of 5min, using several years of quality-controlled weather radar composites provided by the German Weather Service (DWD). That data set covers Germany with a spatial domain of 900km × 900km and has a resolution of 1km in space and 5min in time. Independent verification experiments were carried out on 11 summer precipitation events from 2016 to 2017. In order to achieve a lead time of 1h, a recursive approach was implemented by using RainNet predictions at 5min lead times as model inputs for longer lead times. In the verification experiments, trivial Eulerian persistence and a conventional model based on optical flow served as benchmarks. The latter is available in the rainymotion library and had previously been shown to outperform DWD's operational nowcasting model for the same set of verification events. RainNet significantly outperforms the benchmark models at all lead times up to 60min for the routine verification metrics mean absolute error (MAE) and the critical success index (CSI) at intensity thresholds of 0.125, 1, and 5mm h⁻¹. However, rainymotion turned out to be superior in predicting the exceedance of higher intensity thresholds (here 10 and 15mm h⁻¹). The limited ability of RainNet to predict heavy rainfall intensities is an undesirable property which we attribute to a high level of spatial smoothing introduced by the model. At a lead time of 5min, an analysis of power spectral density confirmed a significant loss of spectral power at length scales of 16km and below. Obviously, RainNet had learned an optimal level of smoothing to produce a nowcast at 5min lead time. In that sense, the loss of spectral power at small scales is informative, too, as it reflects the limits of predictability as a function of spatial scale. Beyond the lead time of 5min, however, the increasing level of smoothing is a mere artifact – an analogue to numerical diffusion – that is not a property of RainNet itself but of its recursive application. In the context of early warning, the smoothing is particularly unfavorable since pronounced features of intense precipitation tend to get lost over longer lead times. Hence, we propose several options to address this issue in prospective research, including an adjustment of the loss function for model training, model training for longer lead times, and the prediction of threshold exceedance in terms of a binary segmentation task. Furthermore, we suggest additional input data that could help to better identify situations with imminent precipitation dynamics. The model code, pretrained weights, and training data are provided in open repositories as an input for such future studies. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 964 KW - weather KW - models KW - skill Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-472942 SN - 1866-8372 IS - 964 ER - TY - JOUR A1 - Ungelenk, Johannes T1 - Satyrs, Spirits and Dionysian Intemperance in Shakespeare's 'Tempest' JF - Cahiers Élisabéthains N2 - The article focuses on the rebellious subplot of William Shakespeare’s The Tempest that forms around Caliban, Stephano, and Trinculo, and reads it as a satyr play. Demonstrated is how the Dionysian subplot stands in close analogical connection with the play’s main action. It is also argued that the storyline emphasises a dimension of the play that is of high relevance to the analysis of its metatheatrical implications. The correspondences between the main action and the satyr play elements highlight the important role that intemperance, excess and the suspension of control play in the Shakespearean theatrical setting. N2 - Le présent article s’intéresse à l’intrigue secondaire de La Tempête, de William Shakespeare, qui s’organise autour de la rébellion de Caliban, de Stephano, de Trinculo, abordée comme drame satyrique. Il démontre comment cette intrigue secondaire dionysiaque comporte des liens analogiques étroits avec l’action principale. L’auteur avance également que la trame de l’action souligne une dimension de la pièce qui s’avère importante pour l’analyse des implications métathéâtrales. Les correspondances entre l’action principale et le drame satyrique mettent en relief le rôle important de l’intempérance, de l’excès et du dérèglement dans un contexte dramatique shakespearien. KW - metatheatre KW - alcohol KW - weather KW - satyr play KW - animal Y1 - 2020 U6 - https://doi.org/10.1177/0184767819897082 SN - 0184-7678 SN - 2054-4715 VL - 101 IS - 1 SP - 45 EP - 64 PB - Sage Publications CY - London ER - TY - GEN A1 - Molnos, Sonja A1 - Mamdouh, Tarek A1 - Petri, Stefan A1 - Nocke, Thomas A1 - Weinkauf, Tino A1 - Coumou, Dim T1 - A network-based detection scheme for the jet stream core T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - The polar and subtropical jet streams are strong upper-level winds with a crucial influence on weather throughout the Northern Hemisphere midlatitudes. In particular, the polar jet is located between cold arctic air to the north and warmer subtropical air to the south. Strongly meandering states therefore often lead to extreme surface weather. Some algorithms exist which can detect the 2-D (latitude and longitude) jets' core around the hemisphere, but all of them use a minimal threshold to determine the subtropical and polar jet stream. This is particularly problematic for the polar jet stream, whose wind velocities can change rapidly from very weak to very high values and vice versa. We develop a network-based scheme using Dijkstra's shortest-path algorithm to detect the polar and subtropical jet stream core. This algorithm not only considers the commonly used wind strength for core detection but also takes wind direction and climatological latitudinal position into account. Furthermore, it distinguishes between polar and subtropical jet, and between separate and merged jet states. The parameter values of the detection scheme are optimized using simulated annealing and a skill function that accounts for the zonal-mean jet stream position (Rikus, 2015). After the successful optimization process, we apply our scheme to reanalysis data covering 1979-2015 and calculate seasonal-mean probabilistic maps and trends in wind strength and position of jet streams. We present longitudinally defined probability distributions of the positions for both jets for all on the Northern Hemisphere seasons. This shows that winter is characterized by two well-separated jets over Europe and Asia (ca. 20 degrees W to 140 degrees E). In contrast, summer normally has a single merged jet over the western hemisphere but can have both merged and separated jet states in the eastern hemisphere. With this algorithm it is possible to investigate the position of the jets' cores around the hemisphere and it is therefore very suitable to analyze jet stream patterns in observations and models, enabling more advanced model-validation. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 625 KW - Southern-Hemisphere KW - variability KW - weather KW - driven KW - amplification KW - circulation KW - reanalysis KW - extremes KW - climate KW - summer Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419099 SN - 1866-8372 IS - 625 SP - 75 EP - 89 ER - TY - THES A1 - Barsch, Andreas T1 - Zum Einfluss von Witterung und Klima auf den Landschaftszustand und die Landschaftsentwicklung im Uvs-Nuur-Becken (NW-Mongolei) N2 - Im Landschaftszustand und in der Landschaftsentwicklung kommen funktionale Beziehungen zwischen dem naturbedingten Energie-, Wasser- und Stoffhaushalt einerseits und den Auswirkungen der Landnutzung andererseits zum Ausdruck. Gegenwärtig verändert der globale Anstieg der bodennahen Temperaturen vielerorts den landschaftlichen Energie-, Wasser- und Stoffhaushalt, wobei besonders in Trockengebieten zu erwarten ist, dass dieser Trend in Verbindung mit einer unangepassten Landnutzung das Regenerationsvermögen der Vegetation einschränkt und zur Zerstörung der Bodendecke führt. Für die Mongolei und für benachbarte Gebiete Asiens sind in Szenarien zur globalen Erwärmung hohe Werte des Temperaturanstiegs prognostiziert worden. Eine globale Einschätzung der anthropogen induzierten Bodendegradation hat diese Region als stark oder extrem stark betroffen eingestuft. Vor diesem Hintergrund wurde im Uvs-Nuur-Becken, das im Nordwesten der Mongolei und damit in einer der trockensten Regionen des Landes gelegen ist, untersucht, wie sich der globale Temperaturanstieg auf der lokalen und regionalen Ebene widerspiegelt und wie der Landschaftshaushalt dabei verändert wird. Die Auswirkungen des sommerlichen Witterungsverlaufes auf den Landschaftszustand sind 1997 bis 1999 an einem Transsekt erfasst worden, das sich zwischen dem Kharkhiraa-Gebirge am Westrand des Beckens und dem See Uvs Nuur im Beckeninneren von den Polsterfluren und Matten der alpinen Stufe über die Gebirgswaldsteppe, die Trockensteppe bis zur Halbwüste erstreckt. An neun Messpunkten wurden witterungsklimatische Daten in Verbindung mit Merkmalen der Vegetation, des Bodens und der Bodenfeuchte aufgenommen. Die im Sommer 1998 gewonnenen Messwerte wurden mit Hilfe einer Clusteranalyse gebündelt und verdichtet. Auf dieser Grundlage konnten landschaftliche Zustandsformen inhaltlich gekennzeichnet, zeitlich eingeordnet und durch Zeit-Verhaltens-Modelle (Stacks) abgebildet werden. Aus den Zeit-Verhaltens-Modellen wird ersichtlich, dass man Zustandsformen, in denen die Hitze und die Trockenheit des Sommers 1998 besonders stark zum Ausdruck kommen, an allen Messpunkten beobachten kann, nimmt man die Station auf dem fast 3.000 m hohen Gipfel des Khukh Uul sowie die grundwasserbeeinflusste Station in unmittelbarer Seenähe aus. In ihrer extremen Form sind Trockenperioden jedoch nur im Beckeninneren und am Fuß der Randgebirge, also in der Halbwüste, in der Trockensteppe und in der Wiesensteppe aufgetreten. Im Bergwald sowie im Bereich der alpinen Matten und Polsterfluren fehlen sie. Am stärksten sind die grundwasserfreien Bereiche der Halbwüste von der Hitze und Niederschlagsarmut des Sommers 1998 betroffen. An vier Fünfteln der Tage des Beobachtungszeitraumes herrscht an diesem Messpunkt extreme Trockenheit. Es fällt entweder gar kein Niederschlag oder nur so wenig, dass der seit dem Frühjahr erschöpfte Bodenwasservorrat nicht aufgefüllt wird. Das Verhältnis zwischen Niederschlag und potenzieller Verdunstung liegt hier bei 1:12. In der Halbwüste zeichnet sich eine fortschreitende Desertifikation ab, zumal hier eine nichtangepasste Weidenutzung dominiert, in der Ziegen eine immer größere Rolle spielen. Dies gilt insbesondere für Bereiche in Siedlungsnähe. Örtlich ist auch der Bestand der Trockensteppe gefährdet, die sich an die Halbwüste zum Beckenrand hin anschließt. Hier ist nicht nur die Viehdichte am höchsten, sondern hier werden auch die meisten unbefestigten Fahrwege wild angelegt und die Bodendecke damit zerstört. Dies kann im Endeffekt zu einem Übergreifen von Prozessen der Desertifikation führen. Aus methodischer Sicht zeigt sich, dass die Kennzeichnung landschaftlicher Zustandsformen durch Zeit-Verhaltens-Modelle die Ermittlung der Auswirkungen von Witterung und Klima auf den Landschaftszustand erleichtert, da sie deren Aussage konzentriert. Zur Interpretation der Ergebnisse ist jedoch ein Rückgriff auf die beschreibende Darstellung der Messwerte notwendig. Die im westlichen Uvs-Nuur-Becken und seinen Randgebirgen angewandte Verfahrensweise ermöglicht es, globale Aussagen zur globalen Erwärmung der Kontinente regional oder lokal zu überprüfen und zu untersetzen." N2 - Landscape condition and landscape development express the functional relations between energy balance, water balance and material balance on the one hand and on the other hand they reflect the effects of land use. At present the global increase of near-surface air temperature changes the energy balance, water balance and material balance in many places. Especially in arid regions this trend and an inappropriate land use restrict the regeneration ability of vegetation and lead to the degradation of soil cover. Different scenarios for global warming prognosticate high values of increasing air temperature in Mongolia and its adjacent regions in Asia. A global estimation of anthropogenicly induced soil degradation classifies this region as strongly or extremely strong affected. Against this background a research was carried out in the Uvs Nuur Basin, placed in the northwest of Mongolia and therefore in one of the most arid regions of this country. The object of investigation was the reflection of the global increase of air temperature on a local and regional level and the resulting changes of landscape balance. From 1997 to 1999 the effects of changes in summer weather on the landscape condition were measured on a transect from the Kharkhiraa mountains at the western margin of the basin up to the lake Uvs at the centre of the basin. The transect included alpine mat, mountain steppe, dry steppe and semi desert. Climatic data was collected at 9 transect stations, in addition with characteristics of vegetation, soil and soil moisture. The data of summer 1998 was bundled and consolidated with a cluster analysis. On this basis forms of landscape condition could be evaluated in content, arranged chronologically and characterised by time performance models (stacks). The time performance models prove that forms of landscape condition marking the heat and the drought of summer 1998 can be found at every station of the transect except of the one on the summit of Khukh Uul at almost 3.000 m above sea level and another groundwater-influenced station at the bank of lake Uvs. However, extremely dry periods occur only from the centre of the basin up to the foothills, thus in the semi desert, the dry steppe and the short grass steppe. They do not occur in the mountain forest and in the alpine mat. Areas in the semi desert are most affected by drought and lack of precipitation during the summer 1998. Four fifths of the days in the measurement period are extremely droughty days. Either there is no precipitation at all or it is insufficient to fill up the soil water storage exhausted since spring-time. The relation of precipitation and potential evaporation averages out here at 1:12. A progressive desertification becomes apparent in the semi desert, particularly determined by an inappropriate land use in conjunction with an increasing goat-rearing in the area around the settlements. Partially this trend even affects the dry steppe in adjacency to the semi desert toward the margin of the basin. These areas are characterised not only by the highest stocking rate but also by the largest number of unofficial dirt roads thus leading to the denudation of the soil cover and finally to the spreading of desertification processes. From the methodical point of view it is obvious that the characterisation by time performance models facilitates the determination of weather and climate influence on landscape condition by summarising their information. However, the interpretation of the results has to be accomplished by a describing analysis of the measured data. The procedure applied in the western Uvs Nuur Basin and its adjacent mountains provides the opportunity to examine and substantiate the reports on global warming at regional or local level. KW - Mongolei; Uvs-Nuur-Becken KW - Witterung KW - Klima KW - Landschaftshaushalt KW - Energie- KW - Wasser- und Stoffhaushalt KW - multivariate Statistik KW - Clusteranalyse KW - landsch KW - Mongolia KW - Uvs Nuur Basin KW - weather KW - climate KW - landscape balance KW - energy balance KW - water balance KW - material balance KW - multivariate statistics KW - cluster analy Y1 - 2003 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-0001184 ER -