Exploring Radiation Biases Over the Tropical and Subtropical Oceans Based on Treatments of Frozen‐Hydrometeor Radiative Properties in CMIP6 Models

Abstract

To explore the impacts of hydrometeor radiative effects over subtropical and tropical Pacific and Atlantic Oceans, we quantify the mean radiation biases in historical climate simulations based on how frozen‐hydrometeors radiative properties are calculated in CMIP6 models. CMIP6 models are divided with cloud ice only (NOS), with combined (SON1), and with separate treatments (SON2) of cloud ice and falling ice (snow) radiative properties. Over the deep convective regions, NOS models overestimate outgoing longwave radiation (RLUT) and surface shortwave irradiance (RSDS), while underestimate top‐of‐atmosphere reflected shortwave radiation (RSUT). SON2 models reduce these biases by 4–14 W m−2. However, this improvement is not seen in SON1 against NOS. Spatially averaged absolute biases in radiative fluxes for SON1 models are larger than those of NOS, suggesting that the SON1 approach of falling ice radiative effects may not produce the expected hydrometeor–radiation interactions. Over the south Pacific trade‐wind regions, both SON2 and SON1 show similar improvements in RLUT, RSUT, and RSDS with positive absolute bias differences up to 20 W m−2 against NOS, leading to improvement of CMIP6 over CMIP5 ensembles. The seasonal cycles are consistent with the annual means over these two regions except with larger differences between subsets of models during January–May than during June–December. In general, improvement from CMIP5 to CMIP6 due to more participating SON2 models is limited because of offset by SON1. These results suggest that a separate treatment of frozen‐hydrometeor radiative properties may be critical for reducing the spread of CMIP models.

Comparisons of simulated radiation, surface wind stress and SST fields over tropical pacific by the GISS CMIP6 versions of global climate models with observations

“…Improvements in radiation components from GISS-E2.1 to GISS-E3 are expected to have an effect on enhancing surface wind stress (Li et al 2015(Li et al , 2022b in GISS-E3, where weaker surface winds with biases of westerly and meridional low-level divergences anomalies of TAU in GISS-E2.1 are reduced in GISS-E3 (figure 5).…”

“…For example, it has been reported that current coupled GCMs (e.g., CMIP5/CMIP6) show biases of underestimated TOA reflected shortwave radiation, excessive downward shortwave radiation at the surface and overestimated outgoing longwave radiation over precipitation active regions such as the ITCZ/SPCZ and TWP (e.g., Li et al 2013Li et al , 2014aLi et al , 2014bLi et al , 2020a. The above-mentioned biases then produce biases in patterns of weaker surface wind stress, leading to warm SST (Li et al 2022b), excessive precipitation and water vapor over trade-wind regions against observations over the Tropical Pacific Ocean (Li et al 2014a(Li et al , 2014b(Li et al , 2016(Li et al , 2020b.…”

Comparing surface wind stress and sea surface temperature biases over the tropical and subtropical oceans in subsets of CMIP6 models categorized by frozen hydrometeors-radiation interactions

“…Extensive efforts have been made to mitigate SST and TAU biases (Luo et al 2005, Chikira 2010, Zhang and Song 2010, Li et al 2015, 2016. Recently, impacts of falling ice radiative effects (FIREs) on tropical radiative fluxes and circulation are found evidently important in the CMIP5 (Li et al 2012(Li et al , 2015(Li et al , 2016 and 6th phase of CMIP (CMIP6) models (Gettelman and Morrison 2015, Kodama et al 2015, Chen et al 2018, Michibata et al 2019, Li et al 2020b, 2022. Most GCMs in CMIP5 and CMIP6 do not include FIREs but only cloud ice radiative effects (Jiang et al 2012, while in reality radiation interacts with all frozen hydrometeors (Waliser et al 2009, 2011.…”

“…The puzzling results also appear in radiation fields and surface precipitation when comparing CMIP6 SON with NOS groups (Li et al 2020a). Li et al (2020bLi et al ( , 2022 further categorized the SON group of models into two subgroups based upon treatments of frozen hydrometeors-radiation interactions; one with combined frozen hydrometeors radiative properties (SON1) and the other with separated cloud ice and falling frozen hydrometeors radiative properties (SON2). They found that SON2 significantly improves tropical precipitation biases including double intertropical convergence zone (ITCZ) (Li et al 2020a) and radiation (Li et al 2022) biases against SON1 and NOS in CMIP6 models.…”

“…Li et al (2020bLi et al ( , 2022 further categorized the SON group of models into two subgroups based upon treatments of frozen hydrometeors-radiation interactions; one with combined frozen hydrometeors radiative properties (SON1) and the other with separated cloud ice and falling frozen hydrometeors radiative properties (SON2). They found that SON2 significantly improves tropical precipitation biases including double intertropical convergence zone (ITCZ) (Li et al 2020a) and radiation (Li et al 2022) biases against SON1 and NOS in CMIP6 models. Their findings motivate us to further evaluate simulated surface wind stress and SST between NOS, SON1 and SON2 subgroups against observations in the context of tropical atmosphere-ocean interactions induced by hydrometeors-radiation interactions.…”