Author: Pradnya Satish Khimsara

Publisher:

Published: 2011

Total Pages:

ISBN-13: 9781267239006

The climate of a region contributes to every element of ecology, economy and well being of that region. Thus, climate data is a vital input in formulating various models such as simulating atmospheric-land hydrologic processes for flood management purposes, climate change impact studies and so on. Over the years, General Circulation models have been developed to simulate the Earth's climate. Various such models have been run for futuristic simulations at a global scale to study the change in climate over the coming century. These models have a coarse grid resolution for the atmospheric variables. However, for smaller regions, the simulated atmospheric data has to be downscaled to a more perceivable grid resolution for interpretation of shifts in trends. This thesis uses the fifth generation PSU/NCAR mesoscale model for downscaling to a finer resolution such future atmospheric data, focusing on three stations along the Sacramento River. These datasets are obtained from the GCM's and are based on three realizations of the A2 family from the Special Reports on emissions scenarios (SRES). The downscaled data is then analyzed for the three stations - Butte, Redding and Sacramento in the Central valley. Climate change trends of precipitation and temperature for these stations have been scrutinized in this study. The data has also been examined for intra-annual changes over three time frames along the century. The results exhibit consistent change at all three stations with the temperature gradients slowly rising by about a degree towards the mid of the century and then steepening to a rise of a cumulative four degrees by the end of the century. There is also a notable rise in the precipitation towards the end of the century. Though the intra-annual changes for temperatures are consistent, there is a shift in the precipitation patterns. Towards the end of the century there is an increase in the number of wet months occurring in the annual rainfall cycle.