PaiMazumder, Debasish, and James Done, National
Center for Atmospheric Research
Extremes in
precipitation and temperature bring enormous environmental, social, and
political impacts. It is therefore essential to investigate the climate
variability and extremes at the regional and fine temporal scales to enable
improved adaptation strategies. Coupled Atmosphere–Ocean Global Climate
Models (AOGCM) used in the Fourth Assessment Report from the IPCC cannot be
applied directly at the regional scale without further downscaling of the
information due to their too coarse resolution to realistically represent
climate variability and extremes. Regional Climate Models (RCMs) is a useful
tool to develop high-resolution climate scenarios at higher temporal and
spatial scales by allowing for greater topographic complexity and finer-scale
atmospheric dynamics, and thereby representing a more adequate tool for
generating climate change information required for many impact and adaptation
studies.
The aim of this study is
to assess the dynamical downscaling ability of the NRCM when driven by GCM data
and bias corrected GCM data, to reproduce the observed extreme and high- and
low-frequency climate variability. To achieve this goal, a sensitivity study is
performed using Community Climate System Model (CCSM) simulation, NRCM
simulations driven by CCSM at 36-km and 12-km grid spacing in one-way nesting
configuration.