There is a strong interest in the climate community to improve the ability to accurately predict future trends of climate variables. Recently, machine learning methods have proven their ability to contribute to more accurate predictions of historical data on a variety of climate variables. There is also a strong interest in using statistical downscaling to predict local station data from the output of multi-model ensembles. This project looks at using the machine learning algorithm XGBoost and evaluating its ability to accurately predict historical monthly precipitation, with a focus of applying this method to simulate future precipitation trends. / Thesis / Master of Science (MSc)

The current cycle of climate change along with increases in hurricane activity, changing precipitation patterns, glacial melt, and other extremes of weather has led to interest and research into the global correlation or teleconnection between these events. Examination of historical climate records, proxies and observations is leading to formulation of hypotheses of climate dynamics with modeling and simulation being used to test these hypotheses as well as making projections. Ocean currents are believed to be an important factor in climate change with thermohaline circulation (THC) fluctuations being implicated in past cycles of abrupt change. Freshwater water discharge into high-latitude oceans attributed to changing precipitation patterns and glacial melt, particularly the North Atlantic, has also been associated with historical abrupt climate changes and is believed to have inhibited or shut down the THC overturning mechanism by diluting saline surface waters transported from the tropics. Here we analyze outputs of general circulation model (GCM) simulations parameterized by different levels of freshwater flux (no flux (control), 0.1 Sverdrup (Sv) and 1.0 Sv) with respect to tropical cyclone-like vortices (TCLVs) to determine any trend in simulated tropical storm frequency, duration, and location relative to flux level, as well as considering the applicability of using GCMs for tropical weather research. Increasing flux levels produced fewer storms and storm days, increased storm duration, a southerly and westerly shift (more pronounced for the 0.1 Sv level) in geographic distribution and increased activity near the African coast (more pronounced for the 1.0 Sv level). Storm intensities and tracks were not realistic compared to observational (real-life) values and is attributed to the GCM resolution not being fine enough to realistically simulate storm (microscale) dynamics.

Global Climate Models (GCMs) are indispensable tools for modeling climate change projections. Due to approximations, errors are introduced in the GCM computations of atmospheric radiation. The existing methodologies for the comparison of the GCM-computed shortwave fluxes (SWF) exiting the top of the atmosphere (TOA) against satellite observations do not separate the model errors in terms of the atmospheric and surface components. A new methodology has been developed for estimating the GCM systematic errors in the SWF at the TOA under clear-sky (CS) conditions. The new methodology is based on physical principles and utilizes in-situ measurements of SWF at the surface. This error adjustment methodology (EAM) has been validated by comparing GCM results against satellite measurements from the Clouds and the Earth’s Radiant Energy System (CERES) mission. The EAM was implemented in an error estimation model for solar radiation (EEMSR), and then applied to examine the hypothesis that the Community Climate System Model (CCSM), one of the most widely used GCMs, was deficient in representing the annual phenology of vegetation in many areas, and that satellite measurements of vegetation characteristics offered the means to rectify the problem. The CCSM computed monthly climatologies of TOA-CS-SWF were compared to the CERES climatology. The incorporation of satellite-derived land surface parameters improved the TOA SWF in many regions. However, for more meaningful interpretations of the comparisons, it was necessary to account for the uncertainties arising from the radiation calculations of CCSM. In-situ measurements from two sites were used by EMBC to relate the observations and model estimates via a predictive equation to derive the errors in TOA CS-SWF for monthly climatologies. The model climatologies were adjusted using the computed error and then compared to CERES climatology at the two sites. The new results showed that at one of the sites, CCSM consistently overestimated the atmospheric transmissivity whereas at the other site the CCSM overestimated during the spring, summer and early fall and underestimated during late fall and winter. The bias adjustment using the EMBC helped determine more clearly that at the two sites the utilization of satellite-derived land surface parameters improved the TOA CS-SWF.

Anthropogenic climate change will impact Virginia's hydrologic processes in unforeseen ways in the coming decades. This research describes variability in meteorology (temperature and precipitation) and associated hydrologic processes (evapotranspiration) throughout an ensemble of 31 general circulation models (GCMs) used by the Chesapeake Bay Program (CBP). Trends are compared with surface runoff generation patterns for a variety of land uses to investigate climate's effect on runoff generation. Scenarios representing pairings of the tenth, fiftieth, and ninetieth percentiles of precipitation and temperature in the CBP 31-model ensemble were run through VADEQ's VA Hydro hydrologic model to investigate streamflow's response to climate. Temperature changes across the study area were minimized in the tenth percentile scenario (+1.02 to +1.24◦C) and maximized in the ninetieth (+2.20 to +3.02◦C), with evapotranspiration change following this trend (tenth: +2.84 to +3.81%; ninetieth: +6.53 to +10.2%). Precipitation change ranged from -10.9 to -7.30% in the tenth to +22.1 to +28.0% in the ninetieth. Runoff per unit area was largely dependent on land use, with the most extreme changes in runoff often seen in forested and natural land uses (-24% in tenth; +53% in ninetieth) and the least extreme seen in impervious and feeding space land(tenth: -11%; ninetieth: +30%). Both overall runoff per unit area and streamflow changed drastically from the base in the tenth (-20.4% to -25.9% change in median runoff; -19.8% to -27.1% change in median streamflow) and ninetieth (+30.4% to +53.7% change in median runoff; +33.0% to +77.8% change in median streamflow) percentile scenarios. / Master of Science / Human-caused climate change will impact Virginia's hydrologic processes in unforeseen ways in the coming decades. This research describes variability in meteorology (temperature and precipitation) and associated hydrologic processes (evapotranspiration) throughout an ensemble of 31 general circulation models (GCMs) used by the Chesapeake Bay Program (CBP). Trends are compared with surface runoff generation patterns for a variety of land uses to investigate climate's effect on runoff generation. Scenarios representing pairings of the tenth, fiftieth, and ninetieth percentiles of precipitation and temperature in the CBP 31-model ensemble were run through VADEQ's VA Hydro hydrologic model to investigate streamflow's response to climate. Temperature changes across the study area were minimized in the tenth percentile scenario (+1.02 to +1.24◦C) and maximized in the ninetieth (+2.20 to +3.02◦C), with evapotranspiration change following this trend (tenth: +2.84 to +3.81%; ninetieth: +6.53 to +10.2%). Precipitation change ranged from -10.9 to -7.30% in the tenth to +22.1 to +28.0% in the ninetieth. Runoff per unit area was largely dependent on land use, with the most extreme changes in runoff often seen in forested and natural land uses (-24% in tenth; +53% in ninetieth) and the least extreme seen in impervious and feeding space land(tenth: -11%; ninetieth: +30%). Both overall runoff per unit area and streamflow changed drastically from the base in the tenth (-20.4% to -25.9% change in median runoff; -19.8% to -27.1% change in median streamflow) and ninetieth (+30.4% to +53.7% change in median runoff; +33.0% to +77.8% change in median streamflow) percentile scenarios.

During the "Green Sahara" period (11,000 to 5000 years before the present), the Sahara desert received high amounts of rainfall, supporting diverse vegetation, permanent lakes, and human populations. Our knowledge of rainfall rates and the spatiotemporal extent of wet conditions has suffered from a lack of continuous sedimentary records. We present a quantitative reconstruction of western Saharan precipitation derived from leaf wax isotopes in marine sediments. Our data indicate that the Green Sahara extended to 31 degrees N and likely ended abruptly. We find evidence for a prolonged "pause" in Green Sahara conditions 8000 years ago, coincident with a temporary abandonment of occupational sites by Neolithic humans. The rainfall rates inferred from our data are best explained by strong vegetation and dust feedbacks; without these mechanisms, climate models systematically fail to reproduce the Green Sahara. This study suggests that accurate simulations of future climate change in the Sahara and Sahel will require improvements in our ability to simulate vegetation and dust feedbacks.

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.

Submitted by Erika Demachki (erikademachki@gmail.com) on 2014-10-15T19:25:11Z No. of bitstreams: 2 Dissertação - Diogo Silva Pena - 2013.pdf: 3166468 bytes, checksum: 0b15748ebfd5186f66f8e329d0d57146 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2014-10-16T18:11:42Z (GMT) No. of bitstreams: 2 Dissertação - Diogo Silva Pena - 2013.pdf: 3166468 bytes, checksum: 0b15748ebfd5186f66f8e329d0d57146 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-10-16T18:11:42Z (GMT). No. of bitstreams: 2 Dissertação - Diogo Silva Pena - 2013.pdf: 3166468 bytes, checksum: 0b15748ebfd5186f66f8e329d0d57146 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-12-20 / Among the plants recommended for the production of biodiesel there is the Jatropha (Jatropha curcas L.), however there is a lack of studies for this crop in particular regarding its management. Climate variables can sometimes restrain the growth and development of certain kinds of plant specious, especially by extremes ranges of temperature and rainfall. This study`s purpose was to define areas suitable in Goiás state for the cultivation of Jatropha by conducting a study based on an agroclimatic zoning using a Geographic Information System. Some other products were also created, as the climate characterization of the state, by generating temperature, precipitation and evapotranspiration maps, as well as defining the water balance of the state. The zoning does not show evidences of any area that is considered unsuitable for cultivation of Jatropha in the state, which much of the state appears to be fully suitable, with some marginal regions, either by water deficiency, or by thermal deficiency. A total of 64,6% of Goiás is suitable for cultivation of Jatropha, while 35,4% have a condition of marginality for the development of the plant. Among all the areas defined as marginal for the cultivation of Jatropha, 28,8% is considered to be marginal by water deficiency, and 6,6% is considered to be marginal by thermal deficiency. / A cultura do pinhão manso destaca-se no cenário do agronegócio brasileiro como uma das mais promissoras para a produção de biodiesel, muito embora sejam poucos os estudos voltados para a implantação, manejo e técnicas de cultivo dessa cultura. As variáveis climáticas podem em algumas regiões restringir o plantio e a condução da cultura, em especial a temperatura e a pluviosidade. Por meio da caracterização do clima do estado através da geração de mapas de temperatura, precipitação e evapotranspiração, bem como a definição do balanço hídrico do estado, objetivou-se neste trabalho, definir áreas aptas no estado de Goiás para o cultivo do pinhão manso por meio de realização de um zoneamento agroclimático. Para isso foram utilizados dados climáticos de precipitação pluviométrica de 114 estações com média de 20 anos de registro, e dados climáticos de temperatura do ar referentes à 34 estações, também com média de 20 anos de registro, que foram usadas para estimar os valores médios de temperatura do ar para as demais localidades do estado, via modelo de regressão linear múltipla. O zoneamento não evidenciou nenhuma área que seja considerada inapta ao cultivo do pinhão no estado, estando grande parte do território sujeito à aptidão plena da cultura, com algumas regiões marginais, ora por deficiência hídrica, ora por deficiência térmica. Do total do estado de Goiás, 64,6% do território goiano é apto ao cultivo do pinhão manso, enquanto que 35,4% apresenta alguma condição de marginalidade para o desenvolvimento da cultura. Deste total de áreas definidas como marginais ao cultivo do pinhão, 28,8% é tida como marginal por deficiência hídrica, e 6,6% é tida como marginal por deficiência térmica.

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.

This thesis focuses on the glaciation of the Late Saalian period (160 -140 ka) over Eurasia. The Quaternary Environment of the Eurasian North (QUEEN) project determined that during this period, the Eurasian ice sheet was substantially larger than during the entire Weichselian cycle and especially that of the Last Glacial Maximum (21 ka, LGM). The Late Saalian astronomical forcing was different than during the LGM while greenhouse gas concentrations were similar. To understand how this ice sheet could have grown so large over Eurasia during the Late Saalian, we use an Atmospherical General Circulation Model (AGCM) coupled to an oceanic mixed layer and a vegetation model to explore the influence of regional parameters, sea surface temperatures (SST) and orbital parameters on the surface mass balance (SMB) of the Late Saalian Eurasian ice sheet. At140 ka, proglacial lakes, vegetation and simulated Late Saalian SST cool the Eurasian climate, which reduce the ablation along the southern ice sheet margins. Dust deposition on snow has the opposite effect. The presence of a Canada Basin ice-shelf during MIS6 in the Arctic Ocean, does not affect the mass balance of the ice sheet. According to geological evidence, the Late Saalian Eurasian ice sheet reached its maximum extent before 160 ka. Northern Hemisphere high latitude summer insolation shows a large insolation peak near 150 ka. The simulated climate prior to 140 ka is milder and ablation is larger along the southern margins of the Eurasian ice sheet although the mean annual SMB is positive. The Late Saalian Eurasian ice sheet may have been large enough to generate its own cooling, thus maintaining itself over Eurasia. / Joint PhD Degree between Stockholm University and Université Joseph FourierAt the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Submitted. Paper 4: Submitted. Paper 5: Manuscript.

The isotopic composition of water in the atmosphere is influenced by how the water evaporated, how it was transported, and how it formed in the cloud before falling. Because these processes are temperature dependent, the isotopic ratios stored in glacial ice and other proxy sources have been used as an indicator of pre-instrumental climate. There is uncertainty, however, as to whether isotopic ratios should be interpreted as a proxy of local temperature, or as a broader indicator of changes in how the vapor was transported. To better understand these processes, the NASA GISS general circulation model (GCM) was used to examine two different types of controls on the isotopic composition of moisture. The first control was the large-scale circulation of the atmosphere. Over Europe, it was found that δ18O is strongly controlled by a Northern Annular Mode-like pattern, detected in both the GCM and for Europe’s high-quality precipitation δ18O data. Over the southwest Yukon, it was found that higher δ18O was associated with moisture transport from the south, which led to a re-interpretation of the large mid-19th century δ18O shift seen in the ice cores from Mt. Logan. The second type of control was microphysical, relating to the way precipitation interacts with vapor after it has formed. Using a GCM sensitivity experiment, the effects of ‘post-condensation exchange’ were found to depend primarily on the proportion between the amount of upstream precipitation that fell as rain and the amount that fell as snow, and at low latitudes, on the strength of atmospheric moisture recycling. This led to a partitioning of the well-observed correlation between temperature and precipitation δ18O into its initial and post-condensation components, and a GCM-based interpretation of satellite measurements of the isotopic composition of water vapor in the troposphere.