For regional weather forecasts and climate predictions, it is important to determine the optimal domain size, location, and top height. A wide model domain can be chosen to avoid noises from lateral boundaries but this can include the Tibetan Plateau and areas of northern Manchuria to the Kamchatka Peninsula in Northeast Asia. This study shows that topographic regions around the Tibetan Plateau and warm pool areas over the Manchuria in an extended model domain may have harmful effects on the accuracy of short- to medium-range regional predictions on the downwind side in spring. The inaccuracy is related to model errors due to steep terrain regions in the Tibetan Plateau and cold bias in the lower stratosphere north of Manchuria. Well-designed spectral nudging over the eastern flank of the Tibetan Plateau and the use of a higher model top are found to improve regional predictions for Northeast Asia in spring by effectively eliminating errors associated with steep topography and temperature biases in the upper troposphere and lower stratosphere, respectively. Our findings suggest possible ways to mitigate biases due to steep mountains and upper-level processes in regional modeling. We discuss the role of our method in terms of uncertainties in regional weather forecasts and climate predictions.
Bibliographical noteFunding Information:
We are greatly appreciated the reviewer for spending his valuable time to read through the manuscript and to give us useful comments and suggestions on our manuscript. ECMWF Interim reanalyses are available through https:// rda.ucar.edu/datasets/ds627.0/, and NCEP GFS forecasts can be obtained from ftp://ftp.ncep.noaa.gov/pub/data/nccf/ com/gfs/prod/. The modeling results presented in this study are available at doi:10.22647/EAPL-MD_2013040300 and http://eapl.yonsei.ac.kr. This work was funded by the Korean Meteorological Industry Promotion Agency under Grant KMIPA-2015-2063 and the Korea Polar Research Institute (PN17081). I.-S.S. was supported by research fund PE17020 from Korea Polar Research Institute.
All Science Journal Classification (ASJC) codes
- Atmospheric Science