Evaluation of water vapor distribution in general circulation models using satellite observations

This paper presents a comparison of the water vapor distribution obtained from two general circulation models, the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the National Center for Atmospheric Reseach (NCAR) Community Climate Model (CCM), with satellite observations of total precipitable water (TPW) from SSM/I and upper tropospheric relative humidity (UTH) from GOES. Overall, both models are successful in capturing the primary features of the observed water vapor distribution and its seasonal variation. For the ECMWF model, however, a systematic moist bias in TPW is noted over well-known stratocumulus regions in the eastern subtropical oceans. Comparison with radiosonde profiles suggests that this problem is attributable to difficulties in modeling the shallowness of the boundary layer and large vertical water vapor gradients which characterize these regions. In comparison, the CCM is more successful in capturing the low values of TPW in the stratocumulus regions, although it tends to exhibit a dry bias over the eastern half of the subtropical oceans and a corresponding moist bias in the western half. The CCM also significantly overestimates the daily variability of the moisture fields in convective regions, suggesting a problem in simulating the temporal nature of moisture transport by deep convection. Comparison of the monthly mean UTH distribution indicates generally larger discrepancies than were noted for TPW owing to the greater influence of large-scale dynamical processes in determining the distribution of UTH. In particular, the ECMWF model exhibits a distinct dry bias along the ITCZ and a moist bias over the subtropical descending branches of the Hadley cell, suggesting an underprediction in the strength of the Hadley circulation. The CCM, on the other hand, demonstrates greater discrepancies in UTH than are observed for the ECMWF model, but none that are as clearly correlated with well-known features of the large-scale circulation.

[1]  Arthur P. Mizzi,et al.  Diabatic initialization for improvement in the tropical analysis of divergence and moisture using satellite radiometric imagery data , 1994 .

[2]  Albert A. M. Holtslag,et al.  Local Versus Nonlocal Boundary-Layer Diffusion in a Global Climate Model , 1993 .

[3]  F. Bretherton,et al.  Upper tropospheric relative humidity from the GOES 6.7 μm channel: method and climatology for July 1987 , 1993 .

[4]  Siri Jodha Singh Khalsa,et al.  A climatology of the water vapor band brightness temperatures from NOAA operational satellites , 1993 .

[5]  P. Rasch,et al.  Description of the NCAR community climate model (CCM2), June 1993. Technical note , 1993 .

[6]  B. Soden.  Validation of cloud forcing simulated by the National Center for Atmospheric Research Community Climate Model using observations from the Earth Radiation Budget Experiment , 1992 .

[7]  J. Kiehl,et al.  Comparison of the observed and calculated clear sky greenhouse effect: Implications for climate studies , 1992 .

[8]  A comparison of observations and model simulations of tropospheric water vapor , 1992 .

[9]  W. Timothy Liu,et al.  Precipitable water and surface humidity over global oceans from special sensor microwave imager and European Center for Medium Range Weather Forecasts , 1992 .

[10]  Moustafa T. Chahine,et al.  GEWEX: The Global Energy and Water Cycle Experiment , 1992 .

[11]  W. Elliott,et al.  On the Utility of Radiosonde Humidity Archives for climate studies , 1991 .

[12]  J. Kiehl,et al.  Dependence of cloud amount on horizontal resolution in the National Center for Atmospheric Research community climate model , 1991 .

[13]  J. Lerner,et al.  Positive water vapour feedback in climate models confirmed by satellite data , 1991, Nature.

[14]  T. Haar,et al.  Clouds-radiation interactions in a general circulation model - Impact upon the planetary radiation balance , 1991 .

[15]  John F. B. Mitchell,et al.  Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models , 1990 .

[16]  S. A. Snyder,et al.  Determination of oceanic total precipitable water from the SSM/I , 1990 .

[17]  P. Rasch,et al.  Computational aspects of moisture transport in global models of the atmosphere , 1990 .

[18]  Graeme L. Stephens,et al.  On the relationship between water vapor over the oceans and sea surface temperature , 1990 .

[19]  R. Lindzen.  Some Coolness Concerning Global Warming , 1990 .

[20]  V. Ramanathan,et al.  Observational determination of the greenhouse effect , 1989, Nature.

[21]  L. Illari.  The quality of satellite precipitable water content data and their impact on analyzed moisture fields , 1989 .

[22]  Kevin E. Trenberth,et al.  An Evaluation and Intercomparison of Global Analyses from the National Meteorological Center and the European Centre for Medium Range Weather Forecasts , 1988 .

[23]  J. Schmetz,et al.  Estimation of the Upper Tropospheric Relative Humidity Field from METFOSAT Water Vapor Image Data , 1988 .

[24]  C. Prabhakara,et al.  Remote sensing of precipitable water over the oceans from Nimbus 7 microwave measurements , 1982 .

[25]  A. Gruber,et al.  Atmospheric Water Content over the Tropical Pacific Derived from the Nimbus-6 Scanning Microwave Spectrometer , 1980 .

[26]  C. Prabhakara,et al.  Remote Sensing of Seasonal Distribution of Precipitable Water Vapor over the Oceans and the Inference of Boundary-Layer Structure , 1979 .

[27]  David H. Staelin,et al.  Remote Sensing of Atmospheric Water Vapor and Liquid Water with the Nimbus 5 Microwave Spectrometer , 1976 .

[28]  F. Möller.  Atmospheric water vapor measurements at 6–7 microns from a satellite , 1961 .