Evaluating CMIP5 models using AIRS tropospheric air temperature and specific humidity climatology

Tian, Baijun; Fetzer, Eric J.; Kahn, Brian H.; Teixeira, J.; Manning, Evan; Hearty, Thomas

doi:10.1029/2012jd018607

Cited by 111 publications

(139 citation statements)

References 79 publications

Supporting

Mentioning

119

Contrasting

Unclassified

Order By: Relevance

“…Near the polar tropopause (about 250 hPa) there is a relatively large cold bias up to 8 K over the Arctic during JJA, and up to 10 K over the Antarctica during DecemberFebruary (DJF). This tropospheric cold bias is one common problem in many CMIP5 models (Charlton-Perez et al, 2013;Tian et al, 2013). In the lower polar troposphere…”

Section: General Model Performancementioning

confidence: 99%

“…One notable difference is that we use ERA-Interim (Dee et al, 2011) and JRA-55 (Ebita et al, 2011) reanalysis data instead of ERA40 and NCEP to reflect recent advances in reanalysis systems. We use estimates of specific humidity from National Aeronautics and Space Administration (NASA) Modern Era Retrospective analysis for Research and Applications (MERRA, Rienecker et al, 2011) instead of the Atmospheric Infrared Sounder (AIRS) experiment, as Tian et al (2013) indicated MERRA specific humidity probably has a smaller uncertainty than the AIRS data set. The International Satellite Cloud Climatology Project (ISCCP, Rossow and Schiffer, 1999;Dueñas, 2004) D2 andCLOUDSAT (L'Ecuyer et al, 2008) data sets are used to examine the total cloud cover.…”

Section: General Model Performancementioning

confidence: 99%

“…In terms of relative difference, the model's dry bias in the tropical lower troposphere approaches 15 %, and the wet bias in the tropical upper troposphere approaches 50 %. This humidity bias pattern is also presented in many CMIP5 models (Tian et al, 2013).…”

mentioning

confidence: 99%

See 2 more Smart Citations

Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1

et al. 2014

View full text Add to dashboard Cite

Abstract. An earth system model has been developed at Beijing Normal University (Beijing Normal University Earth System Model, BNU-ESM); the model is based on several widely evaluated climate model components and is used to study mechanisms of ocean-atmosphere interactions, natural climate variability and carbon-climate feedbacks at interannual to interdecadal time scales. In this paper, the model structure and individual components are described briefly. Further, results for the CMIP5 (Coupled Model Intercomparison Project phase 5) pre-industrial control and historical simulations are presented to demonstrate the model's performance in terms of the mean model state and the internal variability. It is illustrated that BNU-ESM can simulate many observed features of the earth climate system, such as the climatological annual cycle of surface-air temperature and precipitation, annual cycle of tropical Pacific sea surface temperature (SST), the overall patterns and positions of cells in global ocean meridional overturning circulation. For example, the El Niño-Southern Oscillation (ENSO) simulated in BNU-ESM exhibits an irregular oscillation between 2 and 5 years with the seasonal phase locking feature of ENSO. Important biases with regard to observations are presented and discussed, including warm SST discrepancies in the major upwelling regions, an equatorward drift of midlatitude westerly wind bands, and tropical precipitation bias over the ocean that is related to the double Intertropical Convergence Zone (ITCZ).

show abstract

Section: General Model Performancementioning

confidence: 99%

Section: General Model Performancementioning

confidence: 99%

See 1 more Smart Citation

Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1

et al. 2014

View full text Add to dashboard Cite

show abstract

“…It was found that models exhibit regional moist and dry biases relative to the observations [9][10][11][12][13] and the biases can sometimes reach 100%. Evaluations of humidity in the climate models participating in Coupled Model Inter-comparison Project phase-5 (CMIP5) by Tian et al [14] and Jiang et al [15] show that the model error in simulating humidity is largest in the upper troposphere. There are many studies that validate the simulation of the diurnal cycle of UTH in models using infrared satellite observations [16][17][18], and these are mostly data from geostationary platforms having full diurnal coverage.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Diurnal Cycle of Upper Tropospheric Humidity in Two Different Climate Models Using Satellite Observations

Kottayil

John

Buehler³

et al. 2016

Remote Sensing

View full text Add to dashboard Cite

Abstract:The diurnal cycle of upper tropospheric humidity (UTH) is known to be influenced by such processes as convection and the formation of clouds which are parameterized in current global climate models. In this study, we evaluate the performance of two climate models, the Community Atmospheric Model version 5 (CAM-5) and the Global Atmosphere 3.0 (GA-3) model in simulating the diurnal cycle of UTH (represented by a combination of sinusoids of 12 and 24 h periods) by comparing with microwave and infrared (IR) measurements (where available). These comparisons were made over two convective land regions in South America and Africa, and over oceanic regions in the Atlantic, Indian and West Pacific for the month of January 2007. We analyzed how the diurnal cycles from IR and microwave instruments differ, and the reason for the differences. Our study suggests that the differences in the diurnal cycles of IR and microwave UTH result from sampling differences due to the presence of clouds. As noted by earlier studies, the models exhibit considerable discrepancies in diurnal amplitude and phase relative to observations, and these discrepancies have different magnitudes over land and ocean.

show abstract

“…Compared to groundbased observations, satellite-observed SST data play a crucial role in climate study and model development by providing uniform resolution data encompassing the entire globe. The retrievals of AIRS data over the last decade have a significant contribution to various climate studies and model evaluations (Aumann et al, 2003;Tian et al, 2013;Yoo et al, 2013). AIRS retrievals have produced atmospheric temperature, moisture, and ozone profiles on a global scale by the AIRS method itself or together with other instruments .…”

Section: Introductionmentioning

confidence: 99%

Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

et al. 2015

View full text Add to dashboard Cite

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16-24 April and 15-23 September) 2003-2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992-0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968-0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ∼ 2.8 ± 1.9 K decade −1 ) in the northern high regions (70-80 • N) as expected from the icealbedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.

show abstract

Evaluating CMIP5 models using AIRS tropospheric air temperature and specific humidity climatology

Cited by 111 publications

References 79 publications

Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1

Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1

Evaluating the Diurnal Cycle of Upper Tropospheric Humidity in Two Different Climate Models Using Satellite Observations

Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

Contact Info

Product

Resources

About