Lisi Pei 1,2, Nathan Moore 1, Sharon Zhong 1, Zhiqiu
Gao 2, Lifeng Luo 1, Xindi Bian 3, Warren E. Heilman 3, 1. Michigan State University,
East Lansing, Michigan 2. Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China 3. North Central Research Station, USDA Forest
Service, East Lansing, Michigan
The suitability of WRF
v3.3.1 as a regional climate downscaling tool has been evaluated through
half-year simulations over the Southern High Plains. The growing season
(Apr.-Sept.) of three pairs of dry and wet years are selected to verify the
performance of the WRF model initialized with different GCM data (CFSR&NARR).
Sensitivity tests are done with different domain settings and multiple physical
schemes. Results show that without any spectral nudging under a growing season
of dynamical downscaling, WRF reproduced the daily spatial averaged mean
precipitation and temperature values over the Southern High Plains reasonably
well. Patterns of monthly accumulated precipitation in wet years agree better
with observation than those of the dry years. Wet years also have lower biases
for the daily spatially averaged mean (and max/min) temperature compared to dry
years. The model performance is found to be sensitive to a set of factors
including driving GCM data, domain settings and physical schemes.