This work is dealing with regional climate models. Firstly, their principle and use of them is described, including advantages and disadvantages of this approach. Further, the application of WRF numerical weather prediction model in climate mode is described and differences in use of CLWRF modification and its advantages for getting results are discussed. Possibilities of this implementation and testing runs for finding appropriate settings are presented. Finally, the results of one ten-year and four five-year simulations of model with different settings are compared with observed values. Some chapters are dedicated to possibilities of processing and graphics outputs of model results and discussion.

Equivalent temperature is an atmospheric variable that combines both dry static energy (associated with temperature) and moist static energy (associated with moisture). Changes in equivalent temperature therefore reflect changes in total surface energy content. This research is concerned with quantifying trends in equivalent temperature and its subcomponents at 8 National Weather Service (NWS) 1st Order stations in the central USA. Data quality control was conducted and time series and time-varying percentile trends of maximum and minimum equivalent temperature and its subcomponents were developed for each of the stations on the daily scale; along with a heat wave trend analysis. It was found that there is an overall positive trend in lower tropospheric heat content over the last 60 years--driven primarily by increases in low-level moisture. The largest changes in equivalent temperature occurred during spring and fall, with some of these trends as large as 5 deg. Celsius/50 years. Furthermore, it was found that there is an increase in the number of high humidity heat wave events and that these types of events are more frequent than low humidity events; which saw a slight decrease in frequency. Interestingly, one station (Nashville, TN) exhibited a slight negative trend in equivalent temperature maxima, which may be due to synoptic-scale influence such as the Great Plains low-level jet. The results demonstrate that equivalent temperature provides a different perspective than temperature for assessing regional climate change.

A commonly noted problem in the simulation of warm season convection in the North American monsoon region has been the inability of atmospheric models at the meso- scales (10 s to 100 s of kilometers) to simulate organized convection, principally mesoscale convective systems. With the use of convective parameterization, high precipitation biases in model simulations are typically observed over the peaks of mountain ranges. To address this issue, the Kain-Fritsch (KF) cumulus parameterization scheme has been modified with new diagnostic equations to compute the updraft velocity, the convective available potential energy closure assumption, and the convective trigger function. The scheme has been adapted for use in the Weather Research and Forecasting (WRF). A numerical weather prediction-type simulation is conducted for the North American Monsoon Experiment Intensive Observing Period 2 and a regional climate simulation is performed, by dynamically downscaling. In both of these applications, there are notable improvements in the WRF model-simulated precipitation due to the better representation of organized, propagating convection. The use of the modified KF scheme for atmospheric model simulations may provide a more computationally economical alternative to improve the representation of organized convection, as compared to convective-permitting simulations at the kilometer scale or a super-parameterization approach.

An ensemble of 11 dynamically downscaled CMIP3 GCMs under A2 projection scenario are first bias corrected for the historic (1971-2000) and scenario (2041-2070) period using a Scaled Distribution Mapping (SDM) technique, that preserves the relative change in the monthly mean and variance of precipitation and any model trends in temperature to generate an ensemble of streamflow projections across 3 catchments in the Colorado River basin - Upper Colorado at Lees Ferry, Salt and Verde. The hydroclimatic projections obtained from this method are compared against an existing ensemble of 15 Bias Corrected and Spatially Disaggregated (BCSD) CMIP3 models under A2 projection scenario developed by the Bureau of Reclamation (BOR). The confidence in the DD Ens. stems from its ability to represent historical flow quantiles better than BCSD Ens. Across all three basins, the mean of the dynamically downscaled ensemble (DD Ens.) projects a decrease in both monsoon and winter projected precipitation as compared to mean of the statistically downscaled ensemble (BCSD Ens.). For the Upper Colorado, both Ens. show a shift in peak hydrograph from June to May due to earlier snowmelt, but a projected decrease in precipitation (-5%) by DD Ens. as compared to a slight increase (+2%) by BCSD Ens. results in a lower April snow water equivalent (SWE) and reduced streamflows (14% by DD Ens. as compared to 5% by BCSD Ens.). The streamflow decrease over the Upper Colorado River basin, quantified by both the mean and the spread of the ensemble. is representative in high flows and flows during moist conditions. For smaller basins like Salt and Verde, DD Ens. shows a greater decrease (-11%) in precipitation than BCSD Ens. (-2%), which results in lower peak hydrograph during March and significantly reduced streamflows (-20%&-14% for Salt and Verde by DD Ens. as compared to -3% by BCSD Ens.). This decrease is more substantial in high flows, but occurs across all streamflow quantiles. The future streamflow projection, quantified by the spread of the DD Ens. presents the shifting of the streamflow range downward to be drier in the future.

Convective snow bands develop commonly over the open water surface of lakes or seas when cold airgets advected from a continent. Enhanced heat and moisture fluxes from the comparatively warm waterbody trigger shallow convection and an unstable boundary layer builds up. Relatively strong wind canorganize this convection into wind-parallel quasi-stationary cloud bands with moving individual cells.Depending on various factors like the horizontal wind, the vertical shear or the shape of the coast, thosecloud bands can form of different strength and structure. When the air mass meets the coast orographicforcing causes horizontal convergence and vertical lifting intensifies the precipitation at the coast. If thewind direction stays constant for several days a single snow band would accumulate its precipitation ina very restricted region and cause locally a significant increase in snow depth. This process leads in thecold season repeatedly to severe precipitation events at the Swedish east coast. Large amounts of snowalong with strong wind speeds can cause serious problems for traffic and infrastructure.Two different cases of convective snow bands in the Baltic Sea area were selected to simulate theassociated atmospheric conditions with a total of five different model systems. The atmosphere climatemodel RCA has been used independently at default settings as well as with increased resolution on avertical and a horizontal scale and furthermore coupled either to the ice-ocean model NEMO or the wavemodel component WAM.Comparing all models the crucial parameters like wind, temperature, heat fluxes, and precipitationvary generally in a reasonable range. However, the model systems show systematical differences amongthemselves. The strongest 10 meter wind speeds can be observed for both RCA models with increasedresolution. The RCA-WAM simulation shows its wind enhancement during the snow band event witha time shift to the other models by several hours. The mean directional wind shear above the Gulf ofBothnia, the snow band’s region of origin, is for all models small. The warmest sea surface temperaturesare reached by the RCA-NEMO simulation, which as a result also stands out for its most intense heatfluxes in both sensible and latent heat. Both high resolution RCA models as well as RCA-NEMO givethe most remarkable local precipitation rates. The original RCA and RCA-WAM simulate significantlyless snowfall. Local comparison with SMHI station measurements show that the models represent thetrend of wind, temperature and precipitation evolution well. However, all models decelerate the air masstoo rapidly when meeting the coast. Moreover, it remains a challenge to simulate the exact time andlocation of the extreme precipitation.The coupling of the atmosphere model with the ice-ocean model as well as the increased resolution ofthe atmospheric component have been observed to show great improvements in the model performanceand are suggested for future research work to be used in combination with each other for the regionalmodelling of convective snow bands in the Baltic Sea area.

Alterations to the land surface can be attributed to both human activity and natural variability. Human activities, such as urbanization and irrigation, can change the conditions of the land surface by altering albedo, soil moisture, aerodynamic roughness length, the partitioning of net radiation into sensible and latent heat, and other surface characteristics. On the other hand, natural variability, manifested through changes in atmospheric circulation, can also induce land surface changes. These regional scale land surface changes, induced either by humans or natural variability, can effectively modify atmospheric conditions through land-atmosphere interactions. However, only in recent decades have numerical models begun to include representations of the critical processes driving changes at the land surface, and their associated effects on the overlying atmosphere. In this work we explore three mechanisms by which changes to the land surface–both anthropogenic and naturally induced–impact the overlying atmosphere and affect regional hydroclimate. The first land-atmosphere interaction mechanism explored here is land-use and land-cover change (LULCC) due to urban expansion. Such changes alter the surface albedo, heat capacity, and thermal conductivity of the surface. Consequently, the energy balance in urban regions is different from that of natural surfaces. To evaluate the changes in regional hydroclimate that could arise due to projected urbanization in the Phoenix–Tucson corridor, Arizona, my first study applied the Weather Research and Forecasting (WRF) with an Urban Canopy Model (UCM; which includes a detailed urban radiation scheme) coupled to the Noah land surface model to this region. Land-cover changes were represented using land-cover data for 2005 and projections to 2050, and historical North American Regional Reanalysis (NARR) data were used to specify the lateral boundary conditions. Results suggest that temperature changes are well defined, reflecting the urban heat island (UHI) effect within areas experiencing LULCC, whereas changes in precipitation are less certain (statistically less robust). However, the study indicates the likelihood of reductions in precipitation over the mountainous regions northeast of Phoenix and decreased evening precipitation over the newly urbanized area. The second land-atmosphere interaction mechanism explored here is irrigation which, while being an important anthropogenic factor affecting the local to regional water cycle, is not typically represented in regional climate models. In this (second) study, I incorporated an irrigation scheme into the Noah land surface scheme coupled to the WRF model. Using a newly developed water vapor tracer package (developed by Miguez-Macho et al. 2013), the study tracks the path of water vapor that evapotranspires from the irrigated regions. To assess the impact of irrigation over the California Central Valley (CCV) on the regional climate of the U.S. Southwest, I ran six simulations (for three dry and three wet years), both with and without the irrigation scheme. Incorporation of the irrigation scheme resulted in simulated surface air temperature and humidity that were closer to observations, decreased the depth of the planetary boundary layer over the CCV, and increased the convective available potential energy. The results indicated an overall increase in precipitation over the Sierra Nevada Range and the Colorado River Basin during the summer, with water vapor rising from the irrigated region moving mainly northeastward and contributing to precipitation in Nevada and Idaho. The results also indicate an increase in precipitation on the windward side of the Sierra Nevada Range and over the Colorado River Basin. The former is possibly linked to a sea-breeze type circulation near the CCV, while the latter is likely associated with a wave pattern related to latent heat release over the moisture transport belt. In the third study, I investigated the role of large-scale and local-scale processes associated with heat waves using the Modern Era-Retrospective Analysis for Research and Applications (MERRA) reanalysis, and evaluate the performance of the regional climate model ensemble used in the North America Regional Climate Change Program (NARCCAP) in reproducing these processes. The Continental US is divided into different climate divisions (following the convention of the National Climate Assessment) to investigate different mechanisms associated with heat waves. At the large scale, warm air advection from terrestrial sources is a driving factor for heat waves in the Northeast and Midwest. Over the western United States, reduced maritime cool air advection results in local warming. At the local scale, an antecedent precipitation deficit leads to the continuous drying of soil moisture, more energy being partitioned into sensible heat flux and acting to warm surface air temperatures, especially over the Great Plains. My analysis indicates that the NARCCAP simulated large-scale meteorological patterns and temporal evolution of antecedent local-scale terrestrial conditions are very similar to those of MERRA. However, NARCCAP overestimates the magnitude and underestimates the frequency of Northeastern and Midwestern US heat waves, partially due to anomalous heat advection through large-scale forcing. Overall, the aforementioned studies show that utilization of new parameterizations in land surface models, such as the urban canopy scheme and the irrigation scheme, allow us to understand the detailed physical mechanisms by which anthropogenic changes in the land surface can affect regional hydroclimate, and may thus help with informed decision making and climate adaptation/mitigation. In addition to anthropogenic changes of the land surface, humans are of course affecting the overlying atmosphere. Currently, NARCCAP is the best available tool we have to help us understand the effects of changes greenhouse gas induced climate change at the regional scale. The regional climate models participating in NARCCAP are able to realistically represent the dominant processes associated with heat waves, including the atmospheric circulation changes and the land-atmosphere interactions that drive heat waves. This lends credibility, when analyzing the projections of these models with increased GHG emissions, to the assessment of changes in heat waves under a future climate.

This dissertation aims to better understand how various climate modeling approaches affect the fidelity of the North American Monsoon (NAM), as well as the sensitivity of the future state of the NAM under a global warming scenario. Here, we improved over current fully-coupled general circulation models (GCM), which struggle to fully resolve the controlling dynamics responsible for the development and maintenance of the NAM. To accomplish this, we dynamically downscaled a GCM with a regional climate model (RCM). The advantage here being a higher model resolution that improves the representation of processes on scales beyond that which GCMs can resolve. However, as all RCM applications are subject to the transference of biases inherent to the parent GCM, this study developed and evaluated a process to reduce these biases. Pertaining to both precipitation and the various controlling dynamics of the NAM, we found simulations driven by these bias-corrected forcing conditions performed moderately better across a 32-year historical climatology than simulations driven by the original GCM data. Current GCM consensus suggests future tropospheric warming associated with increased radiative forcing as greenhouse gas concentrations increase will suppress the NAM convective environment through greater atmospheric stability. This mechanism yields later onset dates and a generally drier season, but a slight increase to the intensity during July-August. After comparing downscaled simulations forced with original and corrected forcing conditions, we argue that the role of unresolved GCM surface features such as changes to the Gulf of California evaporation lead to a more convective environment. Even when downscaling the original GCM data with known biases, the inclusion of these surface features altered and in some cases reversed GCM trends throughout the southwest United States. This reversal towards a wetter NAM is further magnified in future bias-corrected simulations, which suggest (1) fewer average number of dry days by the end of the 21st century (2) onset occurring up to two to three weeks earlier than the historical average, and (3) more extreme daily precipitation values. However, consistent across each GCM and RCM model is the increase in inter-annual variability, suggesting greater susceptibility to drought conditions in the future.

The interaction between climate and land-surface hydrology is extremely important in relation to long term water resource planning. This is especially so in the presence of global warming and massive land use change, issues which seem likely to have a disproportionate impact on developing countries. This thesis develops tools aimed at the study and prediction of climate effects on land-surface hydrology (in particular streamflow), which require a minimum amount of site specific data. This minimum data requirement allows studies to be performed in areas that are data sparse, such as the developing world. ¶ A simple lumped dynamics-encapsulating conceptual rainfall-runoff model, which explicitly calculates the evaporative feedback to the atmosphere, was developed. It uses the linear streamflow routing module of the rainfall-runoff model IHACRES, with a new non-linear loss module based on the Catchment Moisture Deficit accounting scheme, and is referred to as CMD-IHACRES. In this model, evaporation can be calculated using a number of techniques depending on the data available, as a minimum, one to two years of precipitation, temperature and streamflow data are required. The model was tested on catchments covering a large range of hydroclimatologies and shown to estimate streamflow well. When tested against evaporation data the simplest technique was found to capture the medium to long term average well but had difficulty reproducing the short-term variations. ¶ A comparison of the performance of three limited area climate models (MM5/BATS, MM5/SHEELS and RegCM2) was conducted in order to quantify their ability to reproduce near surface variables. Components of the energy and water balance over the land surface display considerable variation among the models, with no model performing consistently better than the other two. However, several conclusions can be made. The MM5 longwave radiation scheme performed worse than the scheme implemented in RegCM2. Estimates of runoff displayed the largest variations and differed from observations by as much as 100%. The climate models exhibited greater variance than the observations for almost all the energy and water related fluxes investigated. ¶ An investigation into improving these streamflow predictions by utilizing CMD-IHACRES was conducted. Using CMD-IHACRES in an 'offline' mode greatly improved the streamflow estimates while the simplest evaporation technique reproduced the evaporative time series to an accuracy comparable to that obtained from the limited area models alone. The ability to conduct a climate change impact study using CMD-IHACRES and a stochastic weather generator is also demonstrated. These results warrant further investigation into incorporating the rainfall-runoff model CMD-IHACRES in a fully coupled 'online' approach.

In dieser Arbeit wird das regionale Klimamodell HIRHAM mit einer horizontalen Auflösung von 50 km und 19 vertikalen Schichten erstmals auf den asiatischen Kontinent angewendet, um die indische Monsunzirkulation unter rezenten und paläoklimatischen Bedingungen zu simulieren. Das Integrationsgebiet des Modells erstreckt sich von etwa 0ºN - 50ºN und 42ºE - 110ºE und bedeckt dabei sowohl die hohe Topographie des Himalajas und Tibet Plateaus als auch den nördlichen Indischen Ozean. Das Ziel besteht in der Beschreibung der regionalen Kopplung zwischen der Monsunzirkulation und den orographischen sowie diabatischen Antriebsmechanismen. Eine 44-jährige Modellsimulation von 1958-2001, die am seitlichen und unteren Rand von ECMWF Reanalysen (ERA40) angetrieben wird, bildet die Grundlage für die Validierung der Modellergebnisse mit Beobachtungen auf der Basis von Stations- und Gitterdatensätzen. Der Fokus liegt dabei auf der atmosphärischen Zirkulation, der Temperatur und dem Niederschlag im Sommer- und Wintermonsun, wobei die Qualität des Modells sowohl in Bezug zur langfristigen und dekadischen Klimatologie als auch zur interannuellen Variabilität evaluiert wird. Im Zusammenhang mit einer realistischen Reproduktion der Modelltopographie kann für die Muster der Zirkulation und Temperatur eine gute Übereinstimmung zwischen Modell und Daten nachgewiesen werden. Der simulierte Niederschlag zeigt eine bessere Übereinstimmung mit einem hoch aufgelösten Gitterdatensatz über der Landoberfläche Zentralindiens und in den Hochgebirgsregionen, der den Vorteil des Regionalmodells gegenüber der antreibenden Reanalyse hervorhebt. In verschiedenen Fall- und Sensitivitätsstudien werden die wesentlichen Antriebsfaktoren des indischen Monsuns (Meeresoberflächentemperaturen, Stärke des winterlichen Sibirischen Hochs und Anomalien der Bodenfeuchte) untersucht. Die Ergebnisse machen deutlich, dass die Simulation dieser Mechanismen auch mit einem Regionalmodell sehr schwierig ist, da die Komplexität des Monsunsystems hochgradig nichtlinear ist und die vor allem subgridskalig wirkenden Prozesse im Modell noch nicht ausreichend parametrisiert und verstanden sind. Ein paläoklimatisches Experiment für eine 44-jährige Zeitscheibe im mittleren Holozän (etwa 6000 Jahre vor heute), die am Rand von einer globalen ECHAM5 Simulation angetrieben wird, zeigt markante Veränderungen in der Intensität des Monsuns durch die unterschiedliche solare Einstrahlung, die wiederum Einflüsse auf die SST, die Zirkulation und damit auf die Niederschlagsmuster hat. / In this study the regional climate model HIRHAM with a horizontal resolution of 50 km and 19 vertical levels is applied over the Asian continent to simulate the Indian monsoon circulation under present-day and past conditions. The integration domain extends from 0ºN - 50ºN and 42ºE - 110ºE and covers the high topography of Himalayas and Tibetan Plateau as well as the northern Indian Ocean. The main objective is the description of the regional coupling between monsoon circulation and orographic as well as thermal driving mechanisms of monsoon. A 44-years long simulation from 1958-2001, driven at the lateral and lower boundaries by European reanalysis (ERA40), is the basis for the validation of model results with observations based on station and gridded data sets. The focus is on the the long-term and decadal summer and winter monsoon climatology and its variability concerning atmospheric circulation, temperature and precipitation. The results successfully reproduce the observations due to a realistic simulation of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40. In different case and sensitivity studies the main driving mechanisms of the Indian monsoon (Sea Surface Temperatures, strength of the Siberian High in winter and soil moisture anomalies) are investigated. The results show, that the simulation of these mechanisms with a regional climate model is also difficult related to the complex non linear monsoon system and the small-scale processes, which are not just sufficiently parameterized and understood in the model. A paleoclimatic experiment for a 44-years long time slice in mid-holocene (6000 years before present), which is driven by a global ECHAM5 simulation, shows significant changes in the monsoon intensity due to the different solar forcing, which influences the SST, the circulation and the precipitation.

This thesis evaluates regional hydrology using output from the Canadian Regional Climate Model (CRCM 4.1) and examines changes in the hydrological processes over the Churchill River Basin (CRB) by employing the Variable Infiltration Capacity (VIC) hydrology model. The CRCM evaluation has been performed by combining the atmospheric and the terrestrial water budget components of the hydrological cycle. The North American Regional Reanalysis (NARR) data are used where direct observations are not available. The outcome of the evaluation reveals the potential of the CRCM for use in long-term hydrological studies. The CRCM atmospheric moisture fluxes and storage tendencies show reasonable agreement with the NARR. The long-term moisture flux over the CRB was found to be generally divergent during summer. A systematic bias is observed in the CRCM precipitation and temperature. A quantile-based mapping of the cumulative distribution function is applied for precipitation adjustments. The temperature correction only involves shifting and scaling to adjust mean and variance. The results indicate that the techniques employed for correction are useful for hydrological studies. Bias-correction is also applied to the CRCM future climate. The CRCM bias-corrected data is then used for hydrological modeling of the CRB. The VIC-simulated streamflow exhibits acceptable agreement with observations. The VIC model's internal variables such as snow and soil moisture indicate that the model is capable of simulating internal process variables adequately. The VIC-simulated snow and soil moisture shows the potential of use as an alternative dataset for hydrological studies. Streamflow along with precipitation and temperature are analyzed for trends. No statistically significant trend is observed in the daily precipitation series. Results suggest that an increase in temperature may reduce accumulation of snow during fall and winter. The flow regime may be in transition from a snowmelt dominated regime to a rainfall dominated regime. Results from future climate simulations of the A2 emission scenario indicate a projected increase of streamflow, while the snow depth and duration exhibit a decrease. Soil moisture response to future climate warming shows an overall increase with a greater likelihood of occurrences of higher soil moisture.