Effects of climatological model biases on the projection of tropical climate change

Citation:
Zhou, ZQ, Xie SP.  2015.  Effects of climatological model biases on the projection of tropical climate change. Journal of Climate. 28:9909-9917.

Date Published:

2015/12

Keywords:

Atmosphere-ocean interaction, circulation, climate models, climate prediction, CMIP5, coupled ocean, cycle, dynamics, el-nino, entity, forecasting, general-circulation models, Geographic location, indo-pacific, Models and modeling, multimodel ensemble, precipitation change, Rainbands, rainfall, seasonal, surface warming patterns, teleconnections, tropics, Walker circulation

Abstract:

Climate models suffer from long-standing biases, including the double intertropical convergence zone (ITCZ) problem and the excessive westward extension of the equatorial Pacific cold tongue. An atmospheric general circulation model is used to investigate how model biases in the mean state affect the projection of tropical climate change. The model is forced with a pattern of sea surface temperature (SST) increase derived from a coupled simulation of global warming but uses an SST climatology derived from either observations or a coupled historical simulation. The comparison of the experiments reveals that the climatological biases have important impacts on projected changes in the tropics. Specifically, during February-April when the climatological ITCZ displaces spuriously into the Southern Hemisphere, the model overestimates (underestimates) the projected rainfall increase in the warmer climate south (north) of the equator over the eastern Pacific. Furthermore, the global warming-induced Walker circulation slowdown is biased weak in the projection using coupled model climatology, suggesting that the projection of the reduced equatorial Pacific trade winds may also be underestimated. This is related to the bias that the climatological Walker circulation is too weak in the model, which is in turn due to a too-weak mean SST gradient in the zonal direction. The results highlight the importance of improving the climatological simulation for more reliable projections of regional climate change.

Notes:

n/a

Website

DOI:

10.1175/jcli-d-15-0243.1