@article{SteiningerAbelZiegleretal.2023, author = {Steininger, Michael and Abel, Daniel and Ziegler, Katrin and Krause, Anna and Paeth, Heiko and Hotho, Andreas}, title = {ConvMOS: climate model output statistics with deep learning}, series = {Data Mining and Knowledge Discovery}, volume = {37}, journal = {Data Mining and Knowledge Discovery}, number = {1}, issn = {1384-5810}, doi = {10.1007/s10618-022-00877-6}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324213}, pages = {136-166}, year = {2023}, abstract = {Climate models are the tool of choice for scientists researching climate change. Like all models they suffer from errors, particularly systematic and location-specific representation errors. One way to reduce these errors is model output statistics (MOS) where the model output is fitted to observational data with machine learning. In this work, we assess the use of convolutional Deep Learning climate MOS approaches and present the ConvMOS architecture which is specifically designed based on the observation that there are systematic and location-specific errors in the precipitation estimates of climate models. We apply ConvMOS models to the simulated precipitation of the regional climate model REMO, showing that a combination of per-location model parameters for reducing location-specific errors and global model parameters for reducing systematic errors is indeed beneficial for MOS performance. We find that ConvMOS models can reduce errors considerably and perform significantly better than three commonly used MOS approaches and plain ResNet and U-Net models in most cases. Our results show that non-linear MOS models underestimate the number of extreme precipitation events, which we alleviate by training models specialized towards extreme precipitation events with the imbalanced regression method DenseLoss. While we consider climate MOS, we argue that aspects of ConvMOS may also be beneficial in other domains with geospatial data, such as air pollution modeling or weather forecasts.}, subject = {Klima}, language = {en} } @phdthesis{Halboth2018, author = {Halboth, Florian}, title = {Building behavior and nest climate control in leaf-cutting ants: How environmental cues affect the building responses of workers of \(Atta\) \(vollenweideri\)}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-161701}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2018}, abstract = {The present work investigates the influence of environmental stimuli on the building behavior of workers of the leaf-cutting ant Atta vollenweideri. It focuses on cues related to the airflow-driven ventilation of their giant underground nests, i.e., air movements and their direction, carbon dioxide concentrations and humidity levels of the nest air. First, it is shown that workers are able to use airflow and its direction as learned orientation cue by performing learning experiments with individual foragers using a classical conditioning paradigm. This ability is expected to allow workers to also navigate inside the nest tunnels using the prevailing airflow directions for orientation, for example during tasks related to nest construction and climate control. Furthermore, the influence of carbon dioxide on the digging behavior of workers is investigated. While elevated CO2 levels hardly affect the digging rate of the ants, workers prefer to excavate at locations with lower concentrations and avoid higher CO2 levels when given a choice. Under natural conditions, shifting their digging activity to soil layers containing lower carbon dioxide levels might help colonies to excavate new or to broaden existing nest openings, if the CO2 concentration in the underground rises. It is also shown that workers preferably transport excavated soil along tunnels containing high CO2 concentrations, when carbon dioxide levels in the underground are elevated as well. In addition, workers prefer to carry soil pellets along outflow tunnels instead of inflow tunnels, at least for high humidity levels of the air. The material transported along tunnels providing outflow of CO2-rich air might be used by workers for the construction of ventilation turrets on top of the nest mound, which is expected to promote the wind-induced ventilation and the removal of carbon dioxide from the underground. The climatic conditions inside the nest tunnels also influence the structural features of the turrets constructed by workers on top the nest. While airflow and humidity have no effect on turret structure, outflow of CO2-rich air from the nest causes workers to construct turrets with additional openings and increased aperture, potentially enhancing the airflow-driven gas exchanges within the nest. Finally, the effect of airflow and ventilation turrets on the gas exchanges in Atta vollenweideri nests is tested experimentally on a physical model of a small nest consisting of a single chamber and two nest tunnels. The carbon dioxide clearance rate from the underground was measured depending on both the presence of airflow in the nest and the structural features of the built turrets. Carbon dioxide is removed faster from the physical nest model when air moves through the nest, confirming the contribution of wind-induced flow inside the nest tunnels to the ventilation of Atta vollenweideri nests. In addition, turrets placed on top of one of the tunnel openings of the nest further enhance the CO2 clearance rate and the effect is positively correlated with turret aperture. Taken together, climatic variables like airflow, carbon dioxide and humidity levels strongly affect the building responses of Atta vollenweideri leaf-cutting ants. Workers use these environmental stimuli as orientation cue in the nest during tasks related to excavation, soil transport and turret construction. Although the effects of these building responses on the microclimatic conditions inside the nest remain elusive so far, the described behaviors are expected to allow ant colonies to restore and maintain a proper nest climate in the underground.}, subject = {Verhalten}, language = {en} } @phdthesis{Vogt2014, author = {Vogt, Gernot}, title = {Future changes and signal analyses of climate means and extremes in the Mediterranean Area deduced from a CMIP3 multi-model ensemble}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-117369}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2014}, abstract = {Considering its social, economic and natural conditions the Mediterranean Area is a highly vulnerable region by designated affections of climate change. Furthermore, its climatic characteristics are subordinated to high natural variability and are steered by various elements, leading to strong seasonal alterations. Additionally, General Circulation Models project compelling trends in specific climate variables within this region. These circumstances recommend this region for the scientific analyses conducted within this study. Based on the data of the CMIP3 database, the fundamental aim of this study is a detailed investigation of the total variability and the accompanied uncertainty, which superpose these trends, in the projections of temperature, precipitation and sea-level pressure by GCMs and their specific realizations. Special focus in the whole study is dedicated to the German model ECHAM5/MPI-OM. Following this ambition detailed trends and mean values are calculated and displayed for meaningful time periods and compared to reanalysis data of ERA40 and NCEP. To provide quantitative comparison the mentioned data are interpolated to a common 3x3° grid. The total amount of variability is separated in its contributors by the application of an Analysis of Variance (ANOVA). For individual GCMs and their ensemble-members this is done with the application of a 1-way ANOVA, separating a treatment common to all ensemble-members and variability perturbating the signal given by different initial conditions. With the 2-way ANOVA the projections of numerous models and their realizations are analysed and the total amount of variability is separated into a common treatment effect, a linear bias between the models, an interaction coefficient and the residuals. By doing this, the study is fulfilled in a very detailed approach, by considering yearly and seasonal variations in various reasonable time periods of 1961-2000 to match up with the reanalysis data, from 1961-2050 to provide a transient time period, 2001-2098 with exclusive regard on future simulations and 1901-2098 to comprise a time period of maximum length. The statistical analyses are conducted for regional-averages on the one hand and with respect to individual grid-cells on the other hand. For each of these applications the SRES scenarios of A1B, A2 and B1 are utilized. Furthermore, the spatial approach of the ANOVA is substituted by a temporal approach detecting the temporal development of individual variables. Additionally, an attempt is made to enlarge the signal by applying selected statistical methods. In the detailed investigation it becomes evident, that the different parameters (i.e. length of temporal period, geographic location, climate variable, season, scenarios, models, etc…) have compelling impact on the results, either in enforcing or weakening them by different combinations. This holds on the one hand for the means and trends but also on the other hand for the contributions of the variabilities affecting the uncertainty and the signal. While temperature is a climate variable showing strong signals across these parameters, for precipitation mainly the noise comes to the fore, while for sea-level pressure a more differentiated result manifests. In turn, this recommends the distinguished consideration of the individual parameters in climate impact studies and processes in model generation, as the affecting parameters also provide information about the linkage within the system. Finally, an investigation of extreme precipitation is conducted, implementing the variables of the total amount of heavy precipitation, the frequency of heavy-precipitation events, the percentage of this heavy precipitation to overall precipitation and the mean daily intensity from events of heavy precipitation. Each time heavy precipitation is defined to exceed the 95th percentile of overall precipitation. Consecutively mean values of these variables are displayed for ECHAM5/MPI-OM and the multi-model mean and climate sensitivities, by means of their difference between their average of the past period of 1981-2000 and the average of one of the future periods of 2046-2065 or 2081-2100. Following this investigation again an ANOVA is conducted providing a quantitative measurement of the severity of change of trends in heavy precipitation across several GCMs. Besides it is a difficult task to account for extreme precipitation by GCMs, it is noteworthy that the investigated models differ highly in their projections, resulting partially in a more smoothed and meaningful multi-model mean. Seasonal alterations of the strength of this behaviour are quantitatively supported by the ANOVA.}, subject = {Klimaschwankung}, language = {en} } @phdthesis{Paxian2012, author = {Paxian, Andreas}, title = {Future changes in climate means and extremes in the Mediterranean region deduced from a regional climate model}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-72155}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2012}, abstract = {The Mediterranean area reveals a strong vulnerability to future climate change due to a high exposure to projected impacts and a low capacity for adaptation highlighting the need for robust regional or local climate change projections, especially for extreme events strongly affecting the Mediterranean environment. The prevailing study investigates two major topics of the Mediterranean climate variability: the analysis of dynamical downscaling of present-day and future temperature and precipitation means and extremes from global to regional scale and the comprehensive investigation of temperature and rainfall extremes including the estimation of uncertainties and the comparison of different statistical methods for precipitation extremes. For these investigations, several observational datasets of CRU, E-OBS and original stations are used as well as ensemble simulations of the regional climate model REMO driven by the coupled global general circulation model ECHAM5/MPI-OM and applying future greenhouse gas (GHG) emission and land degradation scenarios.}, subject = {Mittelmeerraum}, language = {en} } @phdthesis{Duenkeloh2011, author = {D{\"u}nkeloh, Armin}, title = {Water Balance Dynamics of Cyprus - Actual State and Impacts of Climate Change}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75165}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2011}, abstract = {A completely revised and enhanced version of the water balance model MODBIL of the regional water balance dynamics of Cyprus was developed for this study. The model is based on a physical, process-oriented, spatially distributed concept and is applied for the calculation of all important water balance components of the island for the time period of 1961-2004. The calibrated results are statistically analysed and visualised for the whole island area, and evaluated with respect to the renewability of natural water resources. Climate variability and changes of the past decades are analysed with regard to their influence on water balances. A further part of the study focusses on the simulation of impacts of potential climate change. The water balances are simulated under changing climatic conditions on the base of theoretical precipitation, temperature and relative humidity changes and the revealed impacts on the water balances and renewable resources are discussed. Furthermore, a first principal water balance scenario is developed for the assessment of the regional hydrological changes expected for Cyprus by the end of the 21st century. The scenarios are based on recently calculated climate change assessments for this part of the Mediterranean, under an assumed further increase of greenhouse gasses in the atmosphere.}, subject = {Wasserhaushalt}, language = {en} } @phdthesis{Baumann2009, author = {Baumann, Sabine Christine}, title = {Mapping, analysis, and interpretation of the glacier inventory data from Jotunheimen, South Norway, since the maximum of the 'Little Ice Age'}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-46320}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2009}, abstract = {Glacier outlines during the 'Little Ice Age' maximum in Jotunheimen were mapped by using remote sensing techniques (vertical aerial photos and satellite imagery), glacier outlines from the 1980s and 2003, a digital terrain model (DTM), geomorphological maps of individual glaciers, and field-GPS measurements. The related inventory data (surface area, minimum and maximum altitude) and several other variables (e.g. slope, range) were calculated automatically by using a geographical information system. The length of the glacier flowline was mapped manually based on the glacier outlines at the maximum of the 'Little Ice Age' and the DTM. The glacier data during the maximum of the 'Little Ice Age' were compared with the Norwegian glacier inventory of 2003. Based on the glacier inventories during the maximum of the 'Little Ice Age', the 1980s and 2003, a simple parameterization after HAEBERLI \& HOELZLE (1995) was performed to estimate unmeasured glacier variables, as e.g. surface velocity or mean net mass balance. Input data were composed of surface glacier area, minimum and maximum elevation, and glacier length. The results of the parameterization were compared with the results of previous parameterizations in the European Alps and the Southern Alps of New Zealand (HAEBERLI \& HOELZLE 1995; HOELZLE et al. 2007). A relationship between these results of the inventories and of the parameterization and climate and climate changes was made.}, subject = {Gletscher}, language = {en} }