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

Abstract

This study compares the overall performance between versions 2.1 and 3 of National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) global climate models (referred to as GISS-E2.1 and GISS-E3, respectively), in simulating the present-day Pacific climate using the CMIP6 protocol. Model physical representations and configurations are extensively changed from GISS-E2.1 to GISS-E3, which result in greatly reduced discrepancies, including ice water path (IWP), ice water content (IWC), radiative fluxes, surface wind stress (TAU), sea surface temperature (SST), precipitation (PR) and column water vapor (PRW), relative to satellite-based observational products over south Pacific oceans. Cloud only IWP (CIWP) shows the largest change, decreasing biases from ~400 g kg-1 in GISS-E2.1 to 10—20 g kg-1 in GISS-E3. The combination of improved CIWP and the inclusion of snow in GISS-E3 may play roles on reducing overestimated outgoing longwave radiation, overestimated reflected shortwave at the top of atmosphere, and underestimated surface downward shortwave in GISS-E2.1. Both models’ intertropical convergence zones (ITCZs) are, however, located far too north of the equator, as found in radiative fluxes, PR and PRW but not in SST relative to observations. This introduces biases in TAU, PR and PRW over north flank of the equator and north Pacific. Over south Pacific, especially the trade wind regions, the improvements of radiation fluxes, SST, PR and PRW appear to be due to improved TAU associated with inclusion of snow-radiative effects. In particular, GISS-E3 reduces a longstanding too warm SST bias over trade-wind regions, from 4 K in GISS-E2.1 to within 0.5 K, and too cold SST bias over north Pacific Ocean. Although GISS-E3 shows improved geographic patterns of the simulated fields in particular over south Pacific oceans compared to GISS-E2.1, our results suggest that the location of ITCZ needs to be further improved.

Radiatively Active Hydrometeors Frequencies from CloudSat-CALIPSO Data for Evaluating Cloud Fraction in Global Climate Models

“…The filtered frequency of non-precipitating and non-convective hydrometeors (NPCHF, also called cloud-only HF) and total HF (THF), which is the sum of NPCHF, convective liquid/ice and precipitating ice (snow) HFs, can be utilized for a sensible "apple to apple" comparison within the limitation of measurement accuracy for models that produce either cloud-only cloud fraction (CMIP5 models) or cloud fraction with snow considered for computing the associated radiative effects in GCMs (such as in CESM2-CAM6 in CMIP6), respectively. Note that the precipitating liquid (rain) is not radiatively active in all current GCMs except in new version of GISS-E3 (Li et al, 2022). However, there is no snow fraction output available in CESM2-CAM6 for model-data comparison.…”

“…Our previous studies have been focusing on characterizing and diagnosing systematic biases in the CMIP3/CMIP5/CMIP6 models associated with the precipitating ice radiative effects as well as the biases in weather models such as the European Centre for Medium-range Weather Forecast (ECMWF) . For example, these biases produce underestimated land surface temperature (Li et al, 2016b), overestimated sea ice concentration (Li et al, 2022) and have impacts on the modeled sea surface temperatures (Li et al, , 2016a(Li et al, , b, 2021.…”

Evaluation of Radiatively Active Frozen Hydrometeors Mass in CMIP6 Global Climate Models Using CloudSat‐CALIPSO Observations

“…In order to further explore the role of FIREs, Li et al. (2020, Li et al., 2023a, 2022c) analyzed precipitation, radiation and wind stress/SST biases among NOS, SON1, and SON2 subgroups, respectively. Li et al.…”

“…The satellite simulator includes the signals from all hydrometeor species such as floating cloud ice, convective core ice, falling ice (snow, graupels, and hails), while in CMIP6 models, some models only have cloud‐only hydrometeors or with snow as a part of frozen hydrometeors. In addition, models do not produce the area fractions of different falling hydrometeors (Li et al., 2023b), which are critical inputs to a satellite simulator.…”

“…The objective of this study is to evaluate three types of frozen hydrometeors mass in subsets of CMIP6 models partially in the context of radiation‐circulation‐precipitating coupling in the tropics and assess the performance of SON2 models in producing snow water path/content against observational estimates. Evaluation of TIWP and TIWC globally will be emphasized, rather than just over the tropical and subtropical Pacific and Atlantic in this series of CMIP6 studies (Li et al., 2020a; Li et al., 2023a, 2020c, 2022a, 2022c). It should be pointed out that there are uncertainties in 2C‐ICE (Deng et al., 2010, 2013) estimates of IWP and IWC such as those due to attenuation of signals and these estimates include masses of other types of frozen hydrometeors such as hails and graupel, which will be further discussed in Section 2.…”