Hydrological issues in lateral boundary conditions for regional climate modeling: simulation of east asian summer monsoon in 1998 |
| |
| Authors: | Bin Wang Hongwei Yang |
| |
| Institution: | (1) International Pacific Research Center and Department of Meteorology, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822, USA;(2) LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;(3) College of Physical Oceanography and Environment, Ocean University of China, 266100 Qingdao, China |
| |
| Abstract: | The atmospheric branch of the hydrological cycle associated with the East Asian summer monsoon is intricate due to its distinct
land-sea configurations: the highest mountains are to its west, the oceans are to its south and east, and mid-latitude influences
come from its north. Here we use the weather research and forecast (WRF) model to demonstrate that using two different large-scale
driving fields, derived from the NCEP/DOE R2 and ERA40 reanalysis data and the same model configuration yielded remarkable
differences. We found that the differences are primarily caused by uncertainties in the water vapor influx across the lateral
boundaries in the reanalyses. The summer-mean water vapor convergence into the model domain computed from the ERA40 reanalysis
is 47% higher than that from the R2 reanalysis. The largest uncertainties in moisture transport are found in the regions of
the Philippine Sea and the Bay of Bengal, where the moisture transport has the most significant impacts on the East Asian
summer monsoon rainfall distribution. The sensitivity test results suggest that the biases in the seasonal mean, seasonal
march of the rain band, and individual rainfall events may be reduced by using an “ensemble” average of R2 and ERA40 as lateral
boundary forcing. While the large-scale forcing field does not conserve water vapor, the WRF simulation conserves water vapor
in the inner model domain. The regional model simulation has corrected the biases in the total amount and the month-to-month
distribution of precipitation in the large-scale driving field. However, RCM’s daily precipitation is poorer than that in
the reanalysis filed. Since the RCM solutions may sensitively depend on the reanalysis forcing, intercomparison of models’
performance based on a single set of the reanalysis may not be reliable. This calls for attention to reshape our strategy
for validation of RCMs. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
