ABOUT GMAO
GMAO Brochure (PDF)
GMAO Annual Research Reports
GMAO LINKS
Personnel Directory
Job Opportunities
Upcoming Events
Ancillary Data
Software
Contact Us
Intranet (Internal)
Extranet (login required)
NASA LINKS
MAP (Modeling,Analysis,Prediction)
NASA
GSFC
Goddard Intranet (Internal)
GES DISC
JCSDA
Sciences and Exploration Directorate
GSFC Earth Sciences Division
SMD Earth Sciences
CISTO
GPM
|
SEMINAR ABSTRACT
Begin Main Content
Presenter: Bin Wang
Seminar Title: How accurately do coupled climate models predict the leading modes of Asian-Australian Monsoon interannual variability?
We show that in one-month lead hindcast for the period of 1981-2001 the multi-model ensemble (MME) derived from 10 state-of-the-art coupled atmosphere-ocean-land climate models capture the two observed major modes of A-AM rainfall variability, which account for 43% of the total interannual variances, better than those captured by the ERA-40 and NCEP-2 reanalysis datasets in terms of seasonally evolving spatial patterns and year-to-year temporal variations. The first mode is associated with the turnabout of warming to cooling in the El Niño-Southern Oscillation (ENSO), whereas the second mode leads the warming/cooling by about one year, signaling precursory conditions for ENSO. However, the MME underestimates the total variances of the two modes and the biennial tendency of the first mode. The models have difficulties in capturing precipitation over the maritime continent and the Walker-type teleconnection in the decaying phase of ENSO, which may contribute in part to a monsoon "spring prediction barrier". As the lead time increases, the fractional variance of the first mode increases, suggesting that the long-lead predictability of A-AM rainfall comes primarily from ENSO predictability. The correlation skill for the first principal component remains about 0.9 up to six months before it drops rapidly, but for the spatial pattern it exhibits a drop across the boreal spring.
return to Seminars
|
|