Multiple global climate models suggest that the Canadian Prairies will experience temperature increases due to climate warming. This could influence pasture and grazing production. Three climate scenarios CGCM2 A21, CSIROMk2 B11 and HadCM3 A21 were used to predict daily weather data to 2099 and incorporated into the GrassGro decision support tool to project pastoral production during 30-year increments, 2010 to 2099. Simulations were compared with the World Meterological Organization baseline years, 1961-1990 at two sites (Saskatoon and Melfort) and two soil textures (loam topsoil / loam subsoil and sandy-loam / sandy-clay-loam). Two tame grasses [crested wheatgrass (CWG; <i>Agropyron cristatum</i>) and hybrid bromegrass (HBG; <i>Bromus inermis x Bromus riparius</i>) and a mixed native pasture (<i>Festuca hallii; Elymus lanceolatus; Pascopyrum smithii; Nassella viridula</i>) were studied at each location.<p> Soil moisture was greater for loam/loam than sandy-loam/sandy-clay-loam resulting in more plant available moisture in all climate scenarios at both locations. However, plant available moisture alone was unable to explain changes in pasture dry matter (DM) production. The results projected from CGCM2 A21 were more favorable to plant and livestock production than those of CSIROMk2 B11 and HadCM3 A21. CGCM2 A21 simulated increases in mean DM production of HBG at both locations during spring each 30-yr period (P<0.05) but an overall decline (P<0.05) in mean average daily gain (ADG) of steers at Melfort, whereas at Saskatoon there was an increase in ADG (P<0.05). CWG decreased in DM production at Melfort during summer and increased at Saskatoon with CGCM2 A21 but there was an overall decrease in ADG of steers during each 30-yr period relative to baseline. It was concluded that HBG was better able to stabilize production under various future climatic conditions than CWG. There was a shift in species dominance from <i>Festuca hallii</i> to <i>Elymus lanceolatus</i> in the mixed native pasture at both locations associated with the increase in summer temperatures. This suggests that various grass species may respond differently to climate change.These results indicate that climate change will cause significant changes in soil moisture, productivity and quality of tame pastures, liveweight of grazing cattle and species composition of native pasture.

Multiple global climate models suggest that the Canadian Prairies will experience temperature increases due to climate warming. This could influence pasture and grazing production. Three climate scenarios CGCM2 A21, CSIROMk2 B11 and HadCM3 A21 were used to predict daily weather data to 2099 and incorporated into the GrassGro decision support tool to project pastoral production during 30-year increments, 2010 to 2099. Simulations were compared with the World Meterological Organization baseline years, 1961-1990 at two sites (Saskatoon and Melfort) and two soil textures (loam topsoil / loam subsoil and sandy-loam / sandy-clay-loam). Two tame grasses [crested wheatgrass (CWG; <i>Agropyron cristatum</i>) and hybrid bromegrass (HBG; <i>Bromus inermis x Bromus riparius</i>) and a mixed native pasture (<i>Festuca hallii; Elymus lanceolatus; Pascopyrum smithii; Nassella viridula</i>) were studied at each location.<p> Soil moisture was greater for loam/loam than sandy-loam/sandy-clay-loam resulting in more plant available moisture in all climate scenarios at both locations. However, plant available moisture alone was unable to explain changes in pasture dry matter (DM) production. The results projected from CGCM2 A21 were more favorable to plant and livestock production than those of CSIROMk2 B11 and HadCM3 A21. CGCM2 A21 simulated increases in mean DM production of HBG at both locations during spring each 30-yr period (P<0.05) but an overall decline (P<0.05) in mean average daily gain (ADG) of steers at Melfort, whereas at Saskatoon there was an increase in ADG (P<0.05). CWG decreased in DM production at Melfort during summer and increased at Saskatoon with CGCM2 A21 but there was an overall decrease in ADG of steers during each 30-yr period relative to baseline. It was concluded that HBG was better able to stabilize production under various future climatic conditions than CWG. There was a shift in species dominance from <i>Festuca hallii</i> to <i>Elymus lanceolatus</i> in the mixed native pasture at both locations associated with the increase in summer temperatures. This suggests that various grass species may respond differently to climate change.These results indicate that climate change will cause significant changes in soil moisture, productivity and quality of tame pastures, liveweight of grazing cattle and species composition of native pasture.

Diplomová práce se věnuje analýze chaotického chování v řadách (pseudo)pozorovaných a simulovaných klimatických veličin. Nejprve objasňuji ně- které základní teoretické pojmy související s dynamickými systémy. Potom se zabývám zp·soby rekonstrukce fázového prostoru a uvedu metody odhadu kore- lační dimenze a největšího Ljapunovova exponentu. V praktické části se zabývám pr·měrnou denní teplotou z reanalýz ERA-40 a reanalýzami NCEP/NCAR v tlakových hladinách 850 a 500 hPa z let 1960-2000. Nejprve zkoumám podrobně jednu vybranou řadu. Používám např. metodu falešných soused· a určuji míru vzájemné informace. Zjiš'uji, že korelační dimenze nenabývá konkrétní hodnotu. Pro analýzu celých tlakových hladin vyvíjím program, který počítá divergenci blízkých trajektorií, což je postup používaný při výpočtu největšího Ljapunovo- va exponentu. Tento program postupně aplikuji na oblasti velikosti 20◦ × 30◦ kterými je pokryta celá zeměkoule. Postupně ukazuji a srovnávám výsledky pro reanalýzy v obou tlakových hladinách s ročním chodem a odečteným ročním cho- dem. Tuto metodu aplikuji na výstupy globálních klimatických model· HadCM3 a MPI-ESM-MR v hladině 500 hPa. Podobnou analýzu ještě uskutečňuji u jed- nodimenzionálních řad teploty u reanalýz a u model·. Výsledky opět vizuálně srovnávám. 1

Over the years, global climate modelling has advanced, aiming for realistic and precise models by increasing their complexity. An integral component of climate models, the physics parameterizations, are a major limitation, but are required due to limited computational power. Grid adaptivity is an avenue that is being explored to mitigate these challenges, but comes with its own difficulties. For example, the question of whether the physics should be ``scale-aware’’, by adjusting according to the resolution and the fact that parameterizations are optimized for specific grid ranges. To research these challenges, test cases that work in both the adaptive and non-adaptive cases are required. This thesis concentrates on physics parameterizations of Atmospheric Global Climate Models (AGCMs) presenting the current hierarchy of idealized physics parameterizations found in the literature. It focuses on and provides a comprehensive explanation of a simplified dry physics model for AGCMs, exploring where it is situated in the current hierarchy and its steady states in the uncoupled case. A coupling of the physics model to the adaptive dynamical core wavetrisk is explained and explored. This includes characterizing the results in the non-adaptive case for time convergence, grid convergence, and the effects of the soil, while also benchmarking the climatology of the coupling. The simplified dry physics model introduces another level of complexity in the current dry physics hierarchy and is stable in the coupled and uncoupled cases. A decreasing temperature trend with height is observed, however warmer surface temperatures and cooler upper atmosphere temperatures, than that of Earth, are produced in the steady states. Additionally a linear rate of convergence in space is noted and an improvement in parallel efficiency with resolution is required. Overall these results can be used as a benchmark for future coupling in the adaptive case. / Thesis / Master of Science (MSc)

A mesoscale evaluation is performed to determine the impacts of climate change on terrestrial hydrological components and the Net Irrigation Water Requirement (NIWR) throughout the Chesapeake Bay watershed in the mid-Atlantic region of the United States. The Noah-MP land surface model is calibrated and evaluated against the observed datasets of United States Geological Survey (USGS) streamflow gages, actual evapotranspiration from USGS Simplified Surface Energy Balance (SSEBop) Model and soil moisture from Soil Analysis Climate Network (SCAN). Six best performing Global Climate Models (GCM) based on Multivariate Adaptive Constructed Analogs (MACA) scheme are included for two future scenarios (RCP 4.5 and RCP 8.5), to assess the change in water balance components, change in NIWR for two dominant crops (corn and soybeans) and uncertainty in GCM projections. Using these long-term simulations, the flood inundation maps are developed for future scenarios along the Susquehanna River including the City of Harrisburg in Pennsylvania. The HEC-RAS 2D model is calibrated and evaluated against the high-water marks from major historical flood events and the stage-discharge relationship of the available USGS streamgages. Finally, the impacts of climate change are assessed on flood inundation depth and extent by comparing a 30-yr and 100-yr flood event based on the historical and future (scenario-based) peak discharge estimates at the USGS streamgages. Interestingly, flood inundation extent and severity predicted by the model along the Susquehanna River near Harrisburg is expected to rise in the future climate scenarios due to the greater frequency of extreme events increasing total precipitation. / Master of Science / Climate change is inevitable due to increased greenhouse gas emissions, with impacts varying in space and time significantly throughout the globe. The impacts are strongly driven by the change in precipitation and temperature which affect the control of the movement of water on the surface of the Earth. These changes in the water cycle require an understanding of hydrological components like streamflow, soil moisture, and evapotranspiration. Development of long-term climate models and computational hydrological models (based on mathematical equations and governed by laws of physics) has helped us in understanding this climate variability in space and time. This study performs a long-term simulation using the datasets from six different climate models to analyze the change in terrestrial hydrological components for the entire Chesapeake Bay watershed in the mid-Atlantic region of the United States. The simulations provide an understanding of the interplay between various land surface processes due to climate change and can help determine future water availability and consumption. To illustrate the usefulness of such long-term simulations, the crop water requirement is quantified for the dominant crops in Chesapeake Bay watershed to project water availability and support the development of mitigation strategies. Flood inundation maps are also developed for a section of Susquehanna River near the City of Harrisburg in south-central Pennsylvania using the streamflow from long-term simulations. The flood inundation depth and extent for major flood events such as Tropical Storm Agnes (1972) and Tropical Storm Lee (2011) are compared along the Susquehanna River, which can aid in managing flood operations, reduce the future flood damages and prioritize the mitigation efforts for endangered communities near the City of Harrisburg.

Climate change is impacting the intensity, duration, and frequency of climatic events. With climate change comes a multitude of adverse conditions, including extreme heat events, changes in disease patterns, and increased likelihood and frequency of natural disasters, including in places previously not exposed to such conditions. Human health has foundations in the environment; therefore, these adverse climatic conditions are directly linked to human health. Rural communities in Appalachia are likely to experience negative consequences of climate change more severely due to unique geomorphology and sociopolitical realities of the region. Non-governmental organizations (NGOs) throughout the Appalachian region are currently working to build resilience and prepare for potential adverse effects from climate change. To aid in this process, projections of future climate scenarios are needed to understand possible situations and adequately prepare. In partnership with Ohio University and West Virginia University, this study aims to characterize potential future climatic scenarios from publicly-available global climate models (GCMs) and prepare information to share with Appalachian communities. Climate model information for this analysis was obtained from NASA's Coupled Model Intercomparison Project (CMIP6). All code for data processing and analysis was prepared using the open-source R programming language to support reproducibility. To confirm that models can accurately simulate Appalachian climatic conditions, CMIP6 hindcast simulations for precipitation and maximum temperature were compared to observed weather records from NOAA. Climate models over and underestimated average precipitation values depending on location, while models consistently underestimated extreme precipitation values, simulated by total five-day precipitation. For temperature, climate models consistently underestimated average and extreme high temperature indicators. For Appalachian region projections, three towns of interest (one for each state involved in the study: Virginia, West Virginia, and Ohio) were selected based on current community resilience efforts. In these locations, mid-century (2040 – 2064) and end-of-century (2075 – 2099) projections for precipitation and temperature were summarized under a low emissions scenario and a high emissions scenario. Increases in precipitation and temperature were observed under average and extreme scenarios; these increases were noticeably more extreme under higher emissions scenarios. These trends are consistent with other studies and climate science consensus. When compared to hindcast values, observed average precipitation values were overestimated and underestimated, while observed extreme precipitation indices, average temperatures, and heat wave indices were underestimated by GCMs. Context with observed data is important to understanding model accuracy for the Appalachian region. GCMs are a useful tool to project potential future climate scenarios at specific locations in the Appalachian region, though model data is best used to communicate general trends rather than as inputs for other physical models. / Master of Science / Climate change is driving previously unseen changes in many aspects of the environment. Among these aspects, and of particular concern, are increased precipitation and increased high temperatures, which have direct negative outcomes on human health. Climate change can impact human health in a variety of ways, such as increasing instances of heat-related illnesses like heatstroke, changing insect-carried diseases patterns (i.e. Lyme disease, malaria), worsening preexisting conditions like asthma, and increasing the likelihood of natural disasters like flooding. Climate change also impacts mental health, especially increasing instances of anxiety and post-traumatic stress disorder from disasters. Rural communities like Appalachia are more likely to experience severe negative outcomes due to lack of resources, remote location, and economies historically based on resource extraction. Appalachia specifically also faces unique challenges with flooding, as many towns are situated in valleys with streams or rivers running through the center of town. To address and prepare for possible climate change outcomes, community-based planning is required to build resiliency. Throughout many areas, but specifically in Appalachia, many community-based organizations are already working to strengthen their communities by providing stable housing, addressing flooding, and preparing emergency response teams. To aid in these efforts, information about potential future climate is beneficial to these organizations to understand and prepare for potential conditions. This study aims to use publicly-available climate models to generate information about possible future climate conditions to be shared with community organizations. Additionally, this project's datasets and procedures are publicly available, so this analysis can be performed by communities anywhere in the world given they have adequate computing power. To check that models are a good indicator of previous climate conditions, and therefore would be useful for future projections, historic projected climate model outputs were compared to observed weather data. After confirming that the models used were fairly consistent with observed data, projected values for midcentury (2040 – 2064) and end-of-century (2075 – 2099) were gathered for Appalachian towns with interested community organizations. Projected values show increases in high temperatures and precipitation throughout the Appalachian region, including in short-term event scenarios, which is consistent with other climate science. Higher emissions scenarios result in greater increases in average and extreme temperature and precipitation values. Climate models can be a useful tool in understanding potential general climatic trends for a specific location and can support climate science communication.

Radiative feedbacks associated with changes in water vapor, temperature, surface albedo and clouds remain a major source of uncertainty in our understanding of climate's response to anthropogenic forcing. In this dissertation climate model data is used to investigate variations in feedbacks that result from changing CO��� forcing and the time scales on which feedbacks operate, focusing on the applicability of one method in particular, the radiative kernel technique, to these problems. This computationally efficient technique uses a uniform, incremental change in feedback variables to infer top-of-atmosphere (TOA) radiative flux changes. The first chapters explore the suitability of the linear radiative kernel technique for large forcing scenarios. We show that kernels based on the present-day climate misestimate TOA flux changes for large perturbations, translating into biased feedback estimates. We address this issue by calculating additional kernels based on a large forcing climate state with eight times present day CO��� concentrations. Differences between these and the present-day kernels result from added absorption of radiation by CO��� and water vapor, and increased longwave emission due to higher temperatures. Combining present-day and 8xCO��� kernels leads to significant improvement in the approximation of TOA flux changes and accuracy of feedback estimates. While climate sensitivity remains constant with increasing CO��� forcing when the inaccurate present-day kernels are used, sensitivity increases significantly when new kernels are used. Comparison of feedbacks in climate models with observations is one way towards understanding the disagreement among models. However, climate change feedbacks operate on time scales that are too long to be evaluated from the observational record. Rather, short-term proxies for greenhouse-gas-driven warming are often used to compute feedbacks from observations. The third chapter of this dissertation examines links between the seasonal cycle and global warming using pattern correlations of spatial distribution of feedback variables and radiative flux changes. We find strong correlations between time scales for changes in surface temperature and climate variables, but not for TOA flux anomalies, reaffirming conclusions drawn in previous work. Finally, we investigate the fitness of the radiative kernel technique for evaluation of short-term feedbacks in a comparison with the more accurate, but more computationally expensive, partial radiative perturbations. / Graduation date: 2013

The application of atmospheric circulation classifications in the interpretation of climate model outputs Mgr. Jan Stryhal Automated (computer-assisted) classifications of atmospheric circulation patterns (circulation classifications, for short) constitute a tool widely used in synoptic and dynamic climatology to study atmospheric circulation and its link to various atmospheric, environmental, and societal phenomena. The application of circulation classifications to output of dynamical models of the atmosphere has developed considerably since the pioneering studies about three decades ago, reflecting rapid development in statistics, computing technology, and-naturally-climatological research, increasingly more and more dependent on simulations of the atmosphere, facing the paradigm of anthropogenic climate change. An uncoordinated use of various statistical approaches to analyzing output of global climate models (GCM) or their various ensembles, and an arbitrary selection of circulation variables, spatial and temporal domains, and reference datasets, have contributed to a need for a comparative study, which would shed some light on the sensitivity of studies dealing with an intercomparison of circulation classifications in two datasets to subjective choices. The present thesis responds to this need...

Title: Analysis of Climate Model Outputs Author: RNDr. Zuzana Chládová E-mail: zuzana.chladova@gmail.com Department: Department of Meteorology and Environment Protection, Faculty of Mathematics and Physics, Charles University in Prague Supervisor: RNDr. Aleš Raidl, Ph.D. Supervisor's e-mail address: ales.raidl@mff.cuni.cz Consultant: doc. RNDr. Jaroslava Kalvová, CSc. Regional climate models are currently the most important tools regularly used for downscaling outputs of global climate models. This analysis compares control and future runs of the global climate models HadCM3, ECHAM5/OPYC3 and ARPÉGE/OPA and the regional climate models RCAO, RCA3, HIRHAM4, HIRHAM5 and ALADIN- CLIMATE/CZ with observed data and CRU data for the Czech Republic. In the period 1961-1990, the global climate models underestimated the air temperature in comparison with corresponding virtual time series representing real data; mean annual courses and variance of the temperature, on the other hand, were simulated satisfactorily. The results of the regional climate models showed overestimation of the model temperature in winter season, while in other seasons the model temperatures corresponded better with real values and the results of simulation were generally more accurate in comparison with global climate models. Concerning...

En Europe, l'augmentation des températures moyennes de surface de l'air projetée au cours du 21ème siècle s'accompagne d'une augmentation des extrêmes chauds et d'une diminution des extrêmes froids. Dans les dernières décennies, des indices témoignent déjà de ces changements, comme l'établissement récurrent de nouveaux records de chaleur ou l'augmentation des canicules. Nous étudions l'évolution des extrêmes journaliers de température au cours du 20ème et du 21ème siècle en France et en Europe, et ce en termes d'occurrence et d'intensité. Un intérêt particulier est aussi porté aux mécanismes responsables de ces futurs extrêmes climatiques, ainsi qu'aux futures températures maximales. Nous nous intéressons tout d'abord à l'évolution des records journaliers de température à partir d'observations et de modèles de climat. Entre 1950 et 1980, l'évolution théorique des records dans le cadre d'un climat stationnaire représente correctement l'évolution observée des records chauds et froids. Depuis les années 1980, un écart à ce climat stationnaire est observé, avec respectivement une augmentation et une diminution de l'occurrence des records chauds et froids. Les modèles climatiques suggèrent une accentuation de ces changements au cours du siècle. L'occurrence moyenne des records chauds à la fin du siècle présente une forte augmentation par rapport aux premières décennies de la période observée. L'augmentation la plus importante des records chauds est projetée en été, en particulier dans la région méditerranéenne. Quant aux records froids, les modèles indiquent une diminution très importante de leur occurrence, avec une occurrence quasi-nulle dans les dernières décennies. Les variations observées d'occurrence de records sont, au début du 21ème siècle, toujours dans l'éventail des fluctuations de la variabilité interne du climat. Au cours du siècle, l'émergence de l'influence anthropique de ces fluctuations est détectable dans l'évolution des records chauds et froids en été, et ce respectivement autour des décennies 2030 et 2020. À l'horizon de la fin du siècle, les changements moyens d'occurrence de records ne peuvent pas être uniquement expliqués par des fluctuations naturelles. Nous nous sommes ensuite intéressés aux futures températures estivales extrêmes, ainsi qu'aux canicules intenses qui peuvent être à l'origine de ces extrêmes. Pour cela, l'utilisation de modèles climatiques globaux est associée à la modélisation climatique régionale et à des stations d'observations en France. Tout d'abord, l'augmentation maximale des valeurs maximales des records journaliers de température en été en France est estimée à partir d'une simulation régionale à haute résolution spatiale. À l'horizon 2100, les projections indiquent une augmentation maximale de ces valeurs extrêmes en été comprise entre de 6.6°C et 9.9°C selon les régions de la France. La comparaison de ces projections avec un ensemble de modèles climatiques indique que ces augmentations maximales pourraient être plus importantes. La médiane de la distribution des modèles indique en effet une augmentation maximale de ces valeurs maximales des records journaliers de température de 11.8°C en été et en France. Puis, des expériences de modélisation de canicules intenses du climat européen de la fin du 21ème siècle ont été réalisées à partir d'événements particuliers d'un modèle de climat. Ces expériences ont mis en évidence le rôle des interactions entre le sol et l'atmosphère dans l'amplification des températures extrêmes lors de futurs évènements caniculaire intenses. L'occurrence de telles canicules est d'abord dépendante de la circulation atmosphérique, mais l'intensité des températures peut ensuite être fortement amplifiée en fonction du contenu en humidité des sols avant la canicule, et donc des conditions climatiques des semaines et des mois précédents. / Over the 21st century, the mean increase in surface air temperatures is projected to be associated with an increase in warm temperature extremes and a decrease in the cold ones. Over the last decades, evidence already suggests these changes, as for example recurrent warm record-breaking temperatures or the increase in heatwave occurrence. We investigate the evolution of daily temperature extremes over the 20th and the 21st centuries in France and in Europe, their possible changes in frequency and intensity. We also focus on the mechanisms responsible for these projected climate extremes, as well as the maximum values of temperature extremes at the end of the century. First, we investigate the evolution of daily record-breaking temperatures in Europe based on the observations and an ensemble of climate models. From the 1950s to the 1980s, the theoretical evolution of the records in a stationary climate correctly reproduce the observed one, for both cold and warm records. From 1980, a shift from that theoretical evolution is observed, with an increase in the occurrence of warm records and a decrease in the occurrence of the cold ones. Climate models suggest an amplification of these changes over the century. At the end of the 21st century, the mean number of warm records shows a strong increase compared to the first decades of the observed period. The strongest increase in warm record-breaking temperatures is found in summer, and particularly over the Mediterranean edge. On the contrary, the occurrence of cold record-breaking temperatures is projected to strongly decrease, with almost no new records in the last decades of the century, for all seasons and over the entire European domain. Observed variations of daily record-breaking temperatures are still, at the beginning of the 21st century, consistent with internal climate variability only. Over the century, the anthropogenic influence emerge from these fluctuations in the summer record evolutions, around the 2030 and the 2020 for the warm and cold records respectively. By 2100, the mean changes in record occurrences cannot be explained by the internal climate variability solely, for all seasons and over the entire European domain. Then, we investigate future extreme temperatures at the end of the 21st century, as well as severe heatwaves leading to these extremes. Climate models analyses are associated with regional climate modeling and a French station-based dataset of observations. The summer 21st century evolution of the maximum values of daily warm record-breaking temperatures is first examined in the observations and the high resolution simulation of the regional model. By 2100, an increase of these values is projected, with maximum changes between +6.6°C and +9.9°C in summer among the French regions. These projections assessed from a regional model may underestimate the changes. The multi-model mean estimate of the maximum increase of these values is indeed around +11.8°C in summer over France. Finally, regional modeling experiments of severe heatwaves in the climate of the end of the 21st century in Europe are performed. These severe heatwaves are selected cases from a global climate model trajectory. The experiments results show the role of the soil-atmosphere interactions in the amplification of the extreme temperatures during such future severe warm events. The occurrence of the heatwave is first caused by the atmospheric circulation, but the temperature anomaly can then be amplified according to the soil moisture content before the event, and thus the climatic conditions of the preceding weeks and months.