Upper-tropospheric (200 hPa) velocity potential is useful in identifying areas of rising or sinking atmospheric motions on varying temporal scales (e.g., weekly, seasonal, interannual) especially in the global tropics. These areas are associated with enhancement (rising motion) or suppression (sinking motion) of tropical convection and subsequent weather phenomena dependent on these processes (e.g., tropical cyclones). This study employed three commonly used global weather reanalysis datasets (NCEP/NCAR Reanalysis 1, JMA JRA-55, ECMWF ERA5) to calculate and compare upper-tropospheric velocity potential fields on varying temporal scales and quantify any differences that existed between them from 1958 to 2020 over four key regions of variability (Equatorial Africa, Amazon Basin, Equatorial Central Pacific, and Equatorial Indonesia). To supplement this analysis, the highly correlated variables to velocity potential of outgoing longwave radiation (OLR) and daily precipitation rate were used and directly compared with independent OLR and precipitation datasets to determine the reanalysis' level of agreement with the independent data. The ECMWF ERA5 held the highest agreement to these data over all regions examined and was reasoned to have the highest confidence in capturing the variability of upper-tropospheric velocity potential fields for the study period. Confidence was decreased in the usefulness of the NCEP/NCAR Reanalysis 1 as it consistently performed poorly over much of the study domain. The results of this study also emphasized the usefulness in ensemble-based approaches to assessing climate variability and understanding potential biases and uncertainties that are inherent in the data sources. / Master of Science / Historical weather data across the globe is analyzed using global weather reanalysis datasets which provide the most complete picture of how the atmosphere has evolved over the course of the last several decades. This data is a vital component in today's research investigating climate change and variability over time. This study examined how the history of upper-tropospheric velocity potential was captured in three commonly used global weather reanalysis datasets (NCEP/NCAR Reanalysis 1, JMA JRA-55, ECMWF ERA5) from 1958 to 2020 over four key regions of variability (Equatorial Africa, Amazon Basin, Equatorial Central Pacific, and Equatorial Indonesia). The variable of velocity potential is useful in identifying areas of rising or sinking atmospheric motions on varying time scales (e.g., weekly, seasonal, interannual) especially in the global tropics. These areas are associated with enhancement (rising motion) or suppression (sinking motion) of tropical convection (i.e., thunderstorms) and subsequent weather phenomena dependent on these processes (e.g., tropical cyclones). The analysis conducted found that the newest of the reanalysis datasets, the ECMWF ERA5, held the highest agreement to independent weather observations over all regions examined was reasoned to have the highest confidence in capturing the variability of upper-tropospheric velocity potential fields for the study period. Confidence was decreased in the usefulness of the NCEP/NCAR Reanalysis 1, the oldest of the reanalysis datasets, as it consistently performed poorly over much of the study domain. The results of this study also emphasized the usefulness in ensemble-based approaches to assessing climate variability and understanding potential biases and uncertainties that can be found in the data sources.

abstract: ABSTRACT Famine is the result of a complex set of environmental and social factors. Climate conditions are established as environmental factors contributing to famine occurrence, often through teleconnective patterns. This dissertation is designed to investigate the combined influence on world famine patterns of teleconnections, specifically the North Atlantic Oscillation (NAO), Southern Oscillation (SO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), or regional climate variations such as the South Asian Summer Monsoon (SASM). The investigation is three regional case studies of famine patterns specifically, Egypt, the British Isles, and India. The first study (published in Holocene) employs the results of a Principal Component Analysis (PCA) yielding a SO-NAO eigenvector to predict major Egyptian famines between AD 1049-1921. The SO-NAO eigenvector (1) successfully discriminates between the 5-10 years preceding a famine and the other years, (2) predicts eight of ten major famines, and (3) correctly identifies fifty out of eighty events (63%) of food availability decline leading up to major famines. The second study investigates the impact of the NAO, PDO, SO, and AMO on 63 British Isle famines between AD 1049 and 1914 attributed to climate causes in historical texts. Stepwise Regression Analysis demonstrates that the 5-year lagged NAO is the primary teleconnective influence on famine patterns; it successfully discriminates 73.8% of weather-related famines in the British Isles from 1049 to 1914. The final study identifies the aggregated influence of the NAO, SO, PDO, and SASM on 70 Indian famines from AD 1049 to 1955. PCA results in a NAO-SOI vector and SASM vector that predicts famine conditions with a positive NAO and negative SO, distinct from the secondary SASM influence. The NAO-famine relationship is consistently the strongest; 181 of 220 (82%) of all famines occurred during positive NAO years. Ultimately, the causes of famine are complex and involve many factors including societal and climatic. This dissertation demonstrates that climate teleconnections impact famine patterns and often the aggregates of multiple climate variables hold the most significant climatic impact. These results will increase the understanding of famine patterns and will help to better allocate resources to alleviate future famines. / Dissertation/Thesis / Doctoral Dissertation Geography 2017

In the recent scenario of climate change, the natural variability and uncertainty associated with the hydrologic variables is of great concern to the community. This thesis opens up a new area of multi-disciplinary research. It is a promising field of research in hydrology and water resources that uses the information from the field of atmospheric science. A new way to identify and capture the variability and uncertainty associated with the hydrologic variables is established through this thesis. Assessment of hydroclimatic teleconnection for Indian subcontinent and its use in basin-scale hydrologic time series analysis and forecasting is the broad aim of this PhD thesis. The initial part of the thesis is devoted to investigate and establish the dependence of Indian summer monsoon rainfall (ISMR) on large-scale Oceanic-atmospheric circulation phenomena from tropical Pacific Ocean and Indian Ocean regions. El Niño-Southern Oscillation (ENSO) is the well established coupled Ocean-atmosphere mode of tropical Pacific Ocean whereas Indian Ocean Dipole (IOD) mode is the recently identified coupled Ocean-atmosphere mode of tropical Indian Ocean. Equatorial Indian Ocean Oscillation (EQUINOO) is known as the atmospheric component of IOD mode. The potential of ENSO and EQUINOO for predicting ISMR is investigated by Bayesian dynamic linear model (BDLM). A major advantage of this method is that, it is able to capture the dynamic nature of the cause-effect relationship between large-scale circulation information and hydrologic variables, which is quite expected in the climate change scenario. Another new method, proposed to capture the dependence between the teleconnected hydroclimatic variables is based on the theory of copula, which itself is quite new to the field of hydrology. The dependence of ISMR on ENSO and EQUINOO is captured and investigated for its potential use to predict the monthly variation of ISMR using the proposed method. The association of monthly variation of ISMR with the combined information of ENSO and EQUINOO, denoted by monthly composite index (MCI), is also investigated and established. The spatial variability of such association is also investigated. It is observed that MCI is significantly associated with monthly rainfall variation all over India, except over North-East (NE) India, where it is poor. Having established the hydroclimatic teleconnection at a comparatively larger scale, the hydroclimatic teleconnection for basin-scale hydrologic variables is then investigated and established. The association of large-scale atmospheric circulation with inflow during monsoon season into Hirakud reservoir, located in the state of Orissa in India, has been investigated. The strong predictive potential of the composite index of ENSO and EQUINOO is established for extreme inflow conditions. So the methodology of inflow prediction using the information of hydroclimatic teleconnection would be very suitable even for ungauged or poorly gauged watersheds as this approach does not use any information about the rainfall in the catchment. Recognizing the basin-scale hydroclimatic association with both ENSO and EQUINOO at seasonal scale, the information of hydroclimatic teleconnection is used for streamflow forecasting for the Mahanadi River basin in the state of Orissa, India, both at seasonal and monthly scale. It is established that the basin-scale streamflow is influenced by the large-scale atmospheric circulation phenomena. Information of streamflow from previous month(s) alone, as used in most of the traditional modeling approaches, is shown to be inadequate. It is successfully established that incorporation of large-scale atmospheric circulation information significantly improves the performance of prediction at monthly scale. Again, the prevailing conditions/characteristics of watershed are also important. Thus, consideration of both the information of previous streamflow and large-scale atmospheric circulations are important for basin-scale streamflow prediction at monthly time-scale. Adopting the developed approach of using the information of hydroclimatic teleconnection, hydrologic variables can be predicted with better accuracy which will be a very useful input for better management of water resources.