In:
Environmental Research Communications, IOP Publishing, Vol. 4, No. 5 ( 2022-05-01), p. 055009-
Abstract:
We evaluate the simulations of surface wind stress (TAU) and sea surface temperature (SST) over subtropical and tropical Pacific and Atlantic oceans in subsets of CMIP6 models that are categorized by frozen hydrometeors-radiation interactions. The CMIP6 models are divided into two subsets with combined (SON1) and separated (SON2) radiative properties of cloud ice and falling ice (snow) and compared to the set with cloud ice radiative effects only (NOS). There is evidence that these hydrometeors-radiation interaction treatments induce different atmospheric dynamic responses that influence the surface properties. Excessive westerly TAU and meridional TAU divergence away from convective zones are reduced significantly in SON1 and SON2 relative to NOS against QuikSCAT observations; while the differences between SON2 and SON1 are small. SON2 reduces cold SST biases over north oceans and equatorial zones drastically (1 to 2 K), and warm biases (up to 1 K) off the coasts of America and zonal TAU biases are reduced relative to NOS. Unlike SON2, SON1 improves SSTs mainly over south of Pacific Ocean and limited areas over the tropical belts relative to NOS although TAU is reduced drastically as in SON2, implying that other factors play a role in degrading the SST simulations in SON1 relative to SON2. SON2 outperforms NOS and SON1 in the seasonal cycles of SST mean biases and mean absolute biases averaged over the equatorial area, north ocean, and South Pacific against ERSST observations. Despite the significant improvements in TAU and SST simulations, SON2 models still exhibit non-trivial biases over south and north flanks of equatorial zones. These results suggest that there are direct linkages of TAU with SST changes resulting from the hydrometeors-radiation interactions in SON2, but not in SON1, relative to NOS, implying that a separated treatment of cloud ice and falling ice radiative properties in climate models is preferred.
Type of Medium:
Online Resource
ISSN:
2515-7620
DOI:
10.1088/2515-7620/ac70ac
Language:
Unknown
Publisher:
IOP Publishing
Publication Date:
2022
detail.hit.zdb_id:
2968222-8
