The Quasi-Biennial Oscillation (QBO) is the dominant pattern of variability in the tropical stratosphere. Despite a well established theory regarding its generation in the atmosphere, the simulation in global climate models remains difficult. A set of metrics assessing the quality of model simulations is presented in this study. The QBO simulations in models submitted to the CMIP5 and CCMVal-2 intercomparison projects are characterised and compared to radiosonde observations and reanalysis datasets. Common model biases and their potential causes are addressed. As the QBO has a long intrinsic period, knowing its influences on other parts of the climate system can be used to improve long range forecasts. These teleconnections of the QBO in observations are investigated using composite analysis, multilinear regression and a novel approach called causal effect networks (CEN). Findings from these analyses confirm previous results of the QBO modulating the stratospheric polar vortex and subsequently the North Atlantic Oscillation (NAO). They also suggest that it is important to take the equatorial zonal mean zonal wind vertical profile into account when studying teleconnections, rather than the more traditional method of using just one single level. While QBO influences on the Northern Hemisphere winter polar vortex and the NAO are more clearly established, interactions within the tropics remain inconclusive. Regression analysis does not show a connection between the QBO and the MJO, whereas the CEN analysis does. Further studies are needed to understand the interaction mechanisms near the equator. Finally, following the unprecedented disruption of the QBO cycle in the winter 2015/16, the event is described and a model analogue from the MPI-ESM-MR historical simulation is presented. Future implications are unclear, although model projections indicate more frequent QBO irregularities in a warming climate.

This study investigated the impact of changing climate and growing population on water supply and demand in one of the most rapidly growing cities in the semi-arid regions of western US, Las Vegas Valley (LVV), Nevada. Future scenarios of supply and demand using climate and hydrological models of Coupled Model Intercomparison Project phase 3 (CMIP3) and a more recent CMIP5 have been evaluated and a comparison of their results has been made. A system dynamics model for LVV was developed with a period of study from 1989 to 2049. For the study area, climate and hydrological data projections for the future period (2013-2049) were obtained from the outputs of 16 Global Climate Models (GCMs) of CMIP3 model ensemble with 3 emission scenarios and that from 37 GCMs of CMIP5 model ensemble with 4 Representative concentration pathways. Population growth forecast by Center for Business and Economic Research (CBER) and prevalent conservation practices by Southern Nevada Water Authority (SNWA) were used for the model. The water availability scenario in the future for LVV in the form of Lake Mead elevation was assessed and the water demand was also predicted. This study found that mean lake elevation for the future period (2013-2049) can go as low as 21.8% lesser than that for the historical period (1989-2012). 59 of 97 projections of CMIP5 models against 27 of 48 projections of CMIP3 models indicated that the future mean lake elevation would be lower than the historical mean. Demand forecasts showed Southern Nevada Water Authority conservation goal for 2035 could be met under prevalent conservation practices. This study can be very useful for the water managers and planners to predict the future water budget, plan accordingly, and make decisions to achieve water sustainability. This study has been performed as a part of the Thriving Earth Exchange (TEX) program to assess the current vulnerability of LVV to drought, and the impact on supply and demand of water resources for the future climate scenarios.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / A dinÃmica dos processos relacionados à qualidade da Ãgua em reservatÃrios à funÃÃo da sua morfologia, da aÃÃo das variÃveis meteorolÃgicas e das afluÃncias e defluÃncias, em maior grau. Prever o comportamento hidrodinÃmico de reservatÃrios e o impacto causado por mudanÃas ou variabilidades na forÃante meteorolÃgica à essencial ao gerenciamento da qualidade da Ãgua e foi o objetivo principal desta tese. Para tanto foram utilizados modelos climÃticos, hidrolÃgicos, hidrodinÃmicos e de balanÃo de energia, em cascata. O comportamento da hidrodinÃmica resultante da modelagem mostrou resultados consonantes com reservatÃrios de regiÃes tropicais, representando os padrÃes diÃrios de circulaÃÃo e a formaÃÃo de estratificaÃÃes tÃrmicas no reservatÃrio modelado. As principais variaÃÃes hidrodinÃmicas sazonais puderam ser modeladas, ainda que com um alto Ãndice de incerteza. Foi realizado um monitoramento no reservatÃrio Pereira de Miranda que forneceu meios para dar inÃcio ao ciclo de modelagem e monitoramento integrado. Foi apresentada a tÃcnica de downscaling dinÃmico para a obtenÃÃo das variÃveis meteorolÃgicas de previsÃo regionalizadas, demostrando algumas possibilidades de aplicaÃÃo dos resultados dos modelos climÃticos na modelagem hidrodinÃmica de reservatÃrios, indispensÃvel na modelagem da qualidade da Ãgua. Os resultados mostraram a possibilidade de calibraÃÃo e validaÃÃo do modelo hidrodinÃmico CE-QUAL-W2 com o uso de dados de reanÃlise atmosfÃrica, aplicaÃÃo de tÃcnicas de previsÃo climÃtica na avaliaÃÃo e previsÃo dos padrÃes hidrodinÃmicos de reservatÃrios e a necessidade de um sistema de monitoramento como subsidiÃrio de informaÃÃes relevantes à modelagem, no sentido de melhorar os sistemas existentes e aumentar o nÃvel de conhecimento sobre a dinÃmica de reservatÃrios localizados no semiÃrido. / The dynamics of water quality related processes in reservoirs is a function of its morphology, the action of meteorological variables and defluÃncias inflows and, to a greater extent. Predict the hydrodynamic behavior of reservoirs and the impact of changes or variability in weather forcing is essential to the management of water quality and was the main objective of this thesis. Therefore, we used climate models, hydrological, hydrodynamic and energy balance in cascade. The behavior of the resulting hydrodynamic modeling showed results in line with tropical reservoirs, representing the daily patterns of movement and the formation of thermal stratification in modeled reservoir. The main hydrodynamic seasonal variations could be modeled, albeit with a high level of uncertainty. Monitoring on a Miranda Pereira reservoir that provided a means to begin the modeling and integrated monitoring cycle was performed. The dynamic downscaling technique to obtain the meteorological variables of regionalized forecast was presented, showing some application possibilities of the results of climate models in hydrodynamic modeling of reservoirs, essential in modeling of water quality. The results showed the possibility of calibration and validation of the hydrodynamic model CE-QUAL-W2 using atmospheric reanalysis data, application of climate prediction techniques in assessing and predicting the hydrodynamic patterns of tanks and the need for a monitoring system as Subsidiary information relevant to modeling, to improve existing systems and increase the level of knowledge about the dynamics of reservoirs located in the semiarid.

Predictive anisotropy is a phenomenon referring to unequal predictability of surface wind components in different directions. This study addresses the question of whether predictive anisotropy resulting from statistical prediction is influenced by physical factors or by types of regression methods (linear vs nonlinear) used to construct the statistical prediction. A systematic study of statistical predictability of surface wind components at 2109 land stations across the globe is carried out. The results show that predictive anisotropy is a common characteristic for both linear and nonlinear statistical prediction, which suggests that the type of regression method is not a major influential factor. Both strong predictive anisotropy and poor predictability are more likely to be associated with wind components characterized by relatively weak and non-Gaussian variability and in areas characterized by surface heterogeneity. An idealized mathematical model is developed separating predictive signal and noise between large-scale (predictable) and local (unpredictable) contributions to the variability of surface wind, such that small signal-to-noise ratio (SNR) corresponds to low and anisotropic predictability associated with non-Gaussian local variability. The comparison of observed and simulated statistical predictability by Regional Climate models (RCM) and reanalysis in the Northern Hemisphere indicates that small-scale processes that cannot be captured well by RCMs contribute to poor predictability and strong predictive anisotropy in observations. A second idealized mathematical model shows that spatial variability in specifically the minimum directional predictability, resulting from local processes, is the major contributor to predictive anisotropy. / Graduate

An analysis of the air temperature and precipitation for historical and future experiments of regional climate models from Euro-CORDEX activity is presented. A validation of models was performed for the time period 1989 - 2005 using the comparison of model results with E-OBS dataset which represents real values. For this period results show good agreement for temperature, much worse agreement appears for precipitation where their overestimation is more typical. The future evaluation based on the scenarios of greenhouse gases RCP4.5 and RCP8.5 was investigated for periods 2021 - 2050 and 2071 - 2100 in comparison with the period 1971 - 2000 as reference. For the simulations of the future climate we can notice an approximately linear increase of temperatures which is most significant in the northeast Europe. For precipitation models predict their increase in the north Europe and decrease in the south Europe.

L'Oscillation de Madden-Julian (MJO) est le principal mode de variabilité intrasaisonnière (20-90 jours) dans les tropiques. La MJO se caractérise par une perturbation de la dynamique de grande échelle et des précipitations se propageant principalement vers l'Est à une vitesse 5 m/s à l'équateur, et aussi vers le Nord en été boréal. Malgré son importance, cette perturbation est mal reproduite dans les modèles de circulation générale (MCG). Ce défaut des MCGs a été attribué en partie à un déclenchement trop fréquent du schéma de convection profonde du modèle qui préserverait trop la stabilité statique dans les tropiques et empêcherait la formation de fortes perturbations organisées de la convection et le développement de la réponse dynamique de grande échelle qui en résulte. Cette thèse a donc pour objectif d'étudier l'impact de l'inhibition de la convection sur l'état moyen et la variabilité tropicale dans le MCG LMDZ. Pour cela, deux paramètres - la fermeture et l'entraînement - d'un même schéma convectif, qui étaient initialement basés sur le profil vertical de la convergence d'humidité, ont été modifiés. Le taux entraînement du schéma modifié est proportionnel à l'humidité relative de l'environnement. Des études de sensibilité dans un modèle unidimensionnel montrent que, par rapport au schéma initial, cette modification a pour effet d'inhiber la convection dans une atmosphère sèche et de la favoriser en atmosphère humide, les précipitations deviennent donc plus rares et plus intenses. Avec ce nouvel entraînement, les simulations globales du modèle atmosphérique LMDZ présentent effectivement une plus forte variabilité tropicale de la dynamique et des précipitations à toutes les échelles de temps. Le cycle saisonnier des précipitations est aussi mieux reproduit ainsi que la propagation vers l'Est et vers le Nord des perturbations intrasaisonnières. L'ajout d'une fermeture en CAPE modifie peu ce comportement, mais accélère légèrement la propagation vers le Nord et vers l'Est de la MJO, et donne un état moyen et une variabilité un peu plus réaliste dans les tropiques. / The Madden-Julian oscillation (MJO) is the dominant mode of the Tropical intraseasonal variability. The MJO is characterized by a wide region of rain perturbation propagating eastward along the equator at a speed of about 5 m/s, from the Indian Ocean to the Central Pacific with a period of 20-90 days. Its boreal summer counterpart, referred as the Boreal Summer Intraseasonal Oscillation (BSISO), propagates both eastward and northward. The LMDZ atmospheric global circulation model (GCM), like most climate models, still has difficulties to represent correctly these two modes of tropical intraseasonal variability. One of the causes of this deficiency has been attributed to the lack of intense rain events organized at large scale. If the convection is triggered too easily in a GCM, the convective instability cannot accumulate in a column and trigger an organized convection at a basin scale. This thesis consisted in testing the role of several ways of inhibiting the convection in the simulation of the MJO in the LMDZ GCM. For this purpose, we have first evaluated the impact of entrainment and closure assumptions of the convective scheme on the structure of the atmospheric column using a 1D model and on the tropical variability using the LMDZ GCM. An entrainment that is dependant on the relative humidity of the environment has been implemented in the Tiedtke (1989) convective scheme. The new entrainment inhibits the convection in a dry environment and promotes the convection in a humid environment. This favours strong ascents and subsidence and consequently increases the variance of precipitation at all time scales. The new closure, based on the convective instability (CAPE) instead of the moisture convergence, decreases the occurrence of strong rain events and gives a more realistic mean state. The east-west ratio is increased at intraseasonal scale but it is not sufficient to organise correctly the eastward propagation related to the MJO. The seasonal cycle of the tropical precipitation over India is however improved. The LMDZ is able to reproduce correctly the signature of the northward propagation of the BSISO with a period of 40 days in Boreal Summer. We have shown, with A Local Mode Analysis (LMA), that the new entrainment produces intraseasonal perturbations related to the northward propagation of the BSISO which are more reproducible and more organized on the northern Indo-Pacific region.

As a result of increase in global average surface temperature, abnormalities in different hydroclimatic components such as evapotranspiration, stream flow and precipitation have been experienced. So investigation has to be carried out to assess the hidden abnormality subsisting in the hydroclimatological time series in the form of trend. This thesis broadly consists of following four parts. The first part comprises of a detailed review of various trend detection approaches. Approaches incorporating the effect of serial correlation for trend detection and interesting developments concerning various non parametric approaches are focused explicitly. Recent trends in annual, monthly, and seasonl (winter, pre-monsoon, monsoon and post-monsoon) Tmax and Tmin have been analyzed considering three time slots viz. 1901-2003, 1948-2003 and 1970-2003. For this purpose, time series of Tmax and Tmin of India as a whole and for seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) were originally considered. During the last three decades significant upward trend in Tmin is found to be present in all regions considered either at annual or seasonal level. Sequential Mann Kendall test revealed that most of the significant upward trends both in Tmax and Tmin began after 1970. The second part discusses about numerous climate models from both Coupled Model Inter comparison Project-5 and 3 (i.e. CMIP5, CMIP3) and their skills in simulating Indian climate and assessing their performance using various evaluation measures. Performances of climate models were evaluated for whole of India and over all the individual grid points covering India. The newly defined metric symbolized as Skill_All is an intersection of the three metrics i.e. Skill_r, Skill_s and Skill_rmse, is used for overall model evaluation analysis. A notable enhancement of Skill_All for CMIP5 over CMIP3 was found. After overall model evaluation study, Compromise Programming, a distance based decision making technique, was employed to rank the GCMs gridwise. Entropy method was employed to obtain weights of the chosen indicators. Group decision making methodology was used to arrive at a consensus based on the ranking pattern obtained by individual grid points. In the third part, a detailed detection and attribution (D&A) analysis is performed to determine the causes of changes in seasonal Tmax and Tmin during the period 1950-2005. This formal D&A exercise helps in providing better insight (than trend detection analysis) into the nature of the observed seasonal temperature changes. It was noticed that the emergence of observed trend was more pronounced in Tmin compared to Tmax. Although observed changes were not solely associated with one specific causative factor, most of the changes in Tmin are above the bounds of natural internal climate variability. Finally in the fourth part, to understand the climate change impact on the hydrological cycle, a spatiotemporal change detection study of potential evapotranspiration (PET) along with Tmax and Tmin over India has been performed. Climatology patterns for PET confirmed a greater PET rate during the month of March, April, May and June. A significant increasing trend in both Tmax and Tmin (Tmin being more) was observed in more number of grid points compared to PET. Significant positive trends in Tmax, Tmin and PET were observed over most of the grid points in the IP region. Heterogeneities existed in the spatiotemporal variability of PET over all India. This spatio-temporal change detection study would be helpful for present and future water resources management.

Northern regions of Canada are of special interest for renewable energy investment due to the high cost of traditional energy generation in remote communities (Das & Canizares 2016b). However, climate variability and change have a substantial impact on renewable energy yield and system vulnerability (e.g., Ravestein et al. 2018; van der Wiel et al. 2019), and the North will experience more dramatic impacts due to climate change compared with other parts of Canada (Serreze 2015). Using the Canadian Regional Climate Model Version 4 (CanRCM4) large ensemble driven by Representative Concentration Pathway 8.5, current and future wind and solar energy potential, variability and covariability in northern Canada were assessed. Eight focal communities were additionally selected for in-depth analysis based on the work of Das & Canizares (2016b). Robust increases in annual average wind power potential (WPP) are projected across the northernmost part of the study area by 2070-2099 (up to 30%), with changes most pronounced in cold seasons. Decreases in WPP are projected for southern areas. Solar power potential (SPP) is projected to decrease across the study area, with robust changes emerging by as early as 2010-2039. For the focal communities, WPP stability (as measured through inter- and intra-annual variability) is projected to increase, while SPP stability is projected to decrease. The changes in WPP variability are associated with a dampening of the seasonal cycle of WPP in the north. Monthly mean WPP and SPP are negatively correlated, with approximately oppositely-phased seasonal cycles. Combined wind/solar installations therefore show reduced sub-annual variability, stabilizing power supplies relative to installations of solely wind or solar power. Drivers of change in WPP and SPP are complex, but changes in sea ice across the 21st century will play an important role for both WPP and SPP. Over the northern ocean regions, the influence of sea ice loss on roughness length is found to be more important than impacts on surface layer stability. Changes in storm winds also play a role, but impacts due to synoptic storm activity are difficult to distinguish from shifts in the wind speed distribution. Decreases in SPP can be attributed to projected reductions in downwelling shortwave radiation, which in turn are closely associated with changes in cloud characteristics (e.g., optical depth), as measured through CanRCM4 column liquid/ice water content. Clear-sky changes in shortwave radiation were not directly assessed, but are potentially impacted by robust increases in column water vapour. Overall, northern regions of Canada and the focal communities show high potential for renewable energy generation across the 21st century. Projected increases in wind power resources and wind power stability in the focal communities could enhance the cost-savings and emissions reductions predicted based on current climate assessments (e.g., Das & Canizares 2016b). With ever improving technologies and declining costs, the viability of renewable power in the north is likely to become even more certain in years to come. / Graduate

Title: Assessment of regional climate models performance in simulating present-day climate over the area of the Czech Republic Author: Lenka Crhová Department: Department of Meteorology and Environment Protection Supervisor:doc. RNDr. Jaroslava Kalvová, CSc. Supervisor's e-mail address: Jaroslava.Kalvova@mff.cuni.cz Abstract: Today a great attention is turned to climate changes and their impacts. Since eighties the Regional Climate Models (RCMs) are developed for assessment of future climate at regional scales. But their outputs suffer from many uncertain- ties. Therefore, it is necessary to assess models ability to simulate observed climate characteristics and uncertainties in their outputs before they are applied in consecu- tive studies. In the first chapters of this thesis the sources of uncertainties in climate model outputs and selected methods of climate models performance evaluation are reviewed. Several methods of model performance assessment are then applied to si- mulations of the Czech regional climate model ALADIN-Climate/CZ and selected RCMs from the ENSEMBLES project for the reference period 1961-1990 in the area of the Czech Republic. The attention is paid especially to comparison of simulated and observed spatial and temporal variability of several climatic elements. Within this thesis the...

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