Institut für Geographie und Geologie
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Der Klimawandel und insbesondere die globale Erwärmung gehören aktuell zu den größten Herausforderungen an Politik und Wissenschaft. Steigende CO2-Emissionen sind hierbei maßgeblich für die Klimaerwärmung verantwortlich. Ein regulierender Faktor beim CO2-Austausch mit der Atmosphäre ist die Vegetation, welche als CO2-Senke aber auch als CO2-Quelle fungieren kann. Diese Funktionen können durch Analysen der Landbedeckungsänderung in Kombination mit Modellierungen der Kohlenstoffbilanz quantifiziert werden, was insbesondere von aktuellen und zukünftigen politischen Instrumenten wie CDM (Clean Development Mechanism) oder REDD (Reducing Emissions from Deforestation and Degradation) gefordert wird. Vor allem in Regionen mit starker Landbedeckungsänderung und hoher Bevölkerungsdichte sowie bei geringem Wissen über die Produktivität und CO2-Speicherpotentiale der Vegetation, bedarf es einer Erforschung und Quantifizierung der terrestrischen Kohlenstoffspeicher. Eine Region, für die dies in besonderem Maße zutrifft, ist Westafrika. Jüngste Studien haben gezeigt, dass sich einerseits die Folgen des Klimawandels und Umweltveränderungen sehr stark in Westafrika auswirken werden und andererseits Bevölkerungswachstum eine starke Änderung der Landbedeckung für die Nutzung als agrarische Fläche bewirkt hat. Folglich sind in dieser Region die terrestrischen Kohlenstoffspeicher durch Ausdehnung der Landwirtschaft und Waldrodung besonders gefährdet. Große Flächen agieren anstelle ihrer ursprünglichen Funktion als CO2-Senke bereits als CO2-Quelle. [...]
Climate change assessment in Southeast Asia and implications for agricultural production in Vietnam
(2011)
For many years, the study of climatic changes and variations has become the main objective of climatic research, as has been appreciated in the IPCC's reports and several publications regarding climatic evolution on different space-time scales. Since the 80's, many research groups have generated the extensive database from which the analysis of temperature, precipitation and other climatic parameters has been performed on a global scale (Jones et al., 1986; Hansen and Lebedeff, 1987, 1988; Vinnikov et al., 1987, 1990). The most important result of these research projects is the evidence of global warming during the 20th century, especially in the last two decades. However, numerous challenges still exist about the structure and dimension of the climatic change on a considerable scale. Therefore, it is necessary to carry out studies on a local and regional scale that allow for a more precise evaluation of the global warming phenomenon. A statistical analysis approach was developed to identify systematic differences between large-scale climatic variable from the General Circulation Models (GCM), NCEP, CRU re-analysis data set and climatic parameters (temperature and precipitation data). Models are able to satisfactorily reproduce the spatial patterns of the regional temperature and precipitation field. The response of the climate system to various emission scenario simulated by the GCM was used to analyze and predict the local climate change. The main objective of this study is to analysis the time evolution of the annual and seasonal temperature and precipitation during the 21st century and in order to contribute to our knowledge of temperature and precipitation trends over the century on a regional scale, not only in Southeast Asia but also in Vietnam; the study focuses to develop a dynamical – statistical model describing the relationship between the major climate variation and agricultural production in Vietnam. This study will be an important contribution to the present-day assessment of climate change impacts in the low latitudes. Regional scenarios of climate change, including both rainfall and mean temperature were then used to assess the impact of climate change on crop production in the region in order to evaluate the vulnerability of the system to global warming. Climate change has adverse impacts on the socio - economic development of all nations. But the degree of the impact will vary across nations. It is expected that changes in the earth's climate will impact on developing countries like Vietnam, in particular, hardest because their economies are strongly dependent on crude forms of natural resources and their economic structure is less flexible to adjust to such drastic changes. In Chapter 1: Introduction and background I describe in general terms climate, climate change, climate change model with benefits and problems. Chapter 2: methodology discusses the methods including interpolation, validation, clustering, correlation and regression which were applied in the study. Chapter 3 and chapter 4 describe the database and study area. The most important is chapter 5 Results. The last is chapter 6 Conclusion and outlook followed by the reference list and an appendix.
BACKGROUND: Climate change will probably alter the spread and transmission intensity of malaria in Africa. OBJECTIVES: In this study, we assessed potential changes in the malaria transmission via an integrated weather disease model.
METHODS: We simulated mosquito biting rates using the Liverpool Malaria Model (LMM). The input data for the LMM were bias-corrected temperature and precipitation data from the regional model (REMO) on a 0.5 degrees latitude longitude grid. A Plasmodium falciparum infection model expands the LMM simulations to incorporate information on the infection rate among children. Malaria projections were carried out with this integrated weather disease model for 2001 to 2050 according to two climate scenarios that include the effect of anthropogenic land-use and land-cover changes on climate.
RESULTS: Model-based estimates for the present climate (1960 to 2000) are consistent with observed data for the spread of malaria in Africa. In the model domain, the regions where malaria is epidemic are located in the Sahel as well as in various highland territories. A decreased spread of malaria over most parts of tropical Africa is projected because of simulated increased surface temperatures and a significant reduction in annual rainfall. However, the likelihood of malaria epidemics is projected to increase in the southern part of the Sahel. In most of East Africa, the intensity of malaria transmission is expected to increase. Projections indicate that highland areas that were formerly unsuitable for malaria will become epidemic, whereas in the lower-altitude regions of the East African highlands, epidemic risk will decrease.
CONCLUSIONS: We project that climate changes driven by greenhouse-gas and land-use changes will significantly affect the spread of malaria in tropical Africa well before 2050. The geographic distribution of areas where malaria is epidemic might have to be significantly altered in the coming decades.
The 2007 flood in the Sahel: causes, characteristics and its presentation in the media and FEWS NET
(2012)
During the rainy season in 2007, reports about exceptional rains and floodings in the Sahel were published in the media, especially in August and September. Institutions and organizations like the World Food Programme (WFP) and FEWS NET put the events on the agenda and released alerts and requested help. The partly controversial picture was that most of the Sahel faced a crisis caused by widespread floodings. Our study shows that the rainy season in 2007 was exceptional with regard to rainfall amount and return periods. In many areas the event had a return period between 1 and 50 yr with high spatial heterogeneity, with the exception of the Upper Volta basin, which yielded return periods of up to 1200 yr. Despite the strong rainfall, the interpretation of satellite images show that the floods were mainly confined to lakes and river beds. However, the study also proves the difficulties in assessing the meteorological processes and the demarcation of flooded areas in satellite images without ground truthing. These facts and the somewhat vague and controversial reports in the media and FEWS NET demonstrate that it is crucial to thoroughly analyze such events at a regional and local scale involving the local population.
The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass.
This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure.
The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.
Klimawandelbedingte bzw. potenziell klimawandelbedingte Umweltmigration ist ein sehr komplexes und breites Feld. Es existiert eine Fülle von Studien, die sich in ihrer Herangehensweise unterscheiden, weshalb hier ein Systematisierungsvorschlag aufgezeigt wird. Mittels einer an den Richtlinien der Grounded Theory orientierten Analyse wurden Studien auf zentrale gemeinsame Kategorien hin untersucht und als Modell präsentiert. Dieses stellt jedoch kein abgeschlossenes System dar, sondern dient durch seine Offenheit als Gerüst, das mit Ergebnissen aus weiteren Fallstudien gefestigt werden kann.
Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation.
The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential.
The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.
Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS) techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI). Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.