2.1 Pan-WCRP Monsoon Modelling Workshop Summary

Sperber, K R

Lawrence Livermore National Laboratory

关键词: Amplitudes;    Monsoons;    Recommendations;    Simulation;    58 Geosciences;   

DOI  :  10.2172/877832
RP-ID  :  UCRL-TR-213330
RP-ID  :  W-7405-ENG-48
RP-ID  :  877832

美国|英语

来源: UNT Digital Library

【 摘 要 】

Ken Sperber led a discussion of the outcome of the Pan-WCRP Monsoon Modelling Workshop that was held at the University of California at Irvine from 15-17 June 2005. At the workshop presentations from key CLIVAR and GEWEX panels were presented to highlight the outstanding problems in modelling the Earth's monsoons. Additionally, presentations from invited experts were given to highlight important aspects of monsoon phenomena and processes, such as low-level jets, air-sea interaction, predictability, observational networks/studies, and model test beds etc. Since all persons attending the CLIVAR AAMP meeting were present for all, or most, of the monsoon workshop, a detailed description of the workshop presentations was not given. Rather, the discussion was focused on the recommendations of the workshop breakout groups and their relevance to CLIVAR AAMP. CLIVAR AAMP endorsed the near-term workshop recommendation of investigating the diurnal cycle using a hierarchy of models a key way forward for promoting CLIVAR/GEWEX interactions. In GCM studies CLIVAR researchers have identified the diurnal cycle as a forced ''mode'' of variability that is poorly represented in terms of amplitude and phase, especially in the case of precipitation. Typical phase errors of 6-12 hours are noted over both land and ocean in GCMs. CLIVAR views adequate simulation of the diurnal cycle as key aspect of variability in its own right, but also because of its potential rectification on to subseasonal variability (e.g., the Madden-Julian oscillation). It is hypothesized that improvement of diurnal variability may lead to an improved representation of intraseasonal variability and improved skill of monsoon forecasts on medium-range to seasonal time scales.