4.6 Article Proceedings Paper

Hydrological issues in lateral boundary conditions for regional climate modeling: simulation of east asian summer monsoon in 1998

Journal

CLIMATE DYNAMICS
Volume 31, Issue 4, Pages 477-490

Publisher

SPRINGER
DOI: 10.1007/s00382-008-0385-7

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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.

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