Impacts of Boundary Conditions on the Simulation of Atmospheric Fields Using RegCM4 over CORDEX East Asia

M. Suh,Seok-Geun Oh

Published 2015 in Algorithmic Approaches for Transportation Modeling, Optimization, and Systems

ABSTRACT

The impacts of boundary conditions (BCs) on simulations of RegCM4 for mid-to-upper atmospheric fields over the CORDEX (COordinated Regional Downscaling EXperiment) East Asia domain were investigated using two datasets from integrations over 20 years (1989–2008) with two BCs (ERA and R2). The two datasets showed large differences for the atmospheric variables regardless of the geographic locations, heights, and seasons. The ERA dataset at 850 hPa displayed stronger northerly winds in the western Pacific Ocean, colder temperatures around northern India, and higher relative humidity compared with the R2 dataset during summer. The large differences in the BCs resulted in the significantly different simulations of RegCM4 in both surface and atmospheric variables. The temperatures and wind simulated at 850 hPa with the ERA dataset were warmer and stronger, respectively, than those simulated with the R2 dataset during summer. In addition, RegCM4 with the ERA dataset as a BC generally simulated a stronger southerly wind at 850 hPa over eastern China and more unstable environments than with the R2 dataset, and accordingly generated more precipitation over the eastern part of the domain. Contrary to the forcing data, the trends of simulated relative humidity and the mixing ratios from the two different BCs showed similar patterns irrespective of height and season. The significant impacts of the BCs on the simulation results indicate the importance of BCs in regional climate simulations.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    Algorithmic Approaches for Transportation Modeling, Optimization, and Systems

  • Publication date

    2015-06-05

  • Fields of study

    Environmental Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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