Duane Waliser (PI)
Jet Propulsion Laboratory/California Institute of Technology
duane.waliser@jpl.nasa.gov

Exploiting Satellite Observations and Cloud-Resolving Models to Improve GCM Representations of Cloud-Radiation-Dynamical Interactions

The proper simulation of clouds and their associated interactions with radiation and dynamics represents the remaining greatest challenge to producing more realistic and accurate weather and climate forecasts.  Much of this problem stems from the need to parameterize the sub-grid scale properties of convection and clouds.  Solving the parameterization issue involves addressing a number of complex issues.  These include the representation of microphysical processes, the influence of the macro-scale on these processes, interfacing the cloud and radiation representations to properly simulate their interaction, accounting for boundary-layer influences on cloud processes, and the general consideration of making trade-offs between complexity (and thus more realistic but yet computationally demanding) versus simplicity (and thus less accurate but yet computationally efficient).  The above problems are highly exacerbated by the fact that there has been so little observational data to help guide, constrain and validate model development and parameterization.  Addressing the above challenge is an absolute necessity in order to answer at least three of the five fundamental questions driving NASA Earth Science Enterprise (ESE) research.   The above cloud-related parameterization problems are expected to be solved via two lines of research and development.  First, additional observational resources need to be developed and applied to the problem.  Great headway in this direction has been initiated through the EOS-era of satellites and their associated suite of sensors.  These global observational resources provide a wealth of new and important information on atmospheric composition and thermodynamics, including cloud and radiation characteristics, that can be brought to bear on the problem.  Second, it will ultimately be necessary to utilize cloud-resolving models (CRMs) to the greatest extent possible in order: 1) to best exploit these new high-resolution satellite observations for model development and validation, and 2) to ultimately shed many of the nagging uncertainties associated with the cloud parameterization issue.  This proposal aims to combine both these lines of development in order to improve the representation of cloud-radiation-dynamical interactions in global atmospheric models and thus ultimately reduce uncertainties associated with weather forecasts and global climate projections.   Specifically, we plan to combine the following elements in our proposed work: 1) global satellite observations of clouds, radiation and physical properties (e.g., AIRS, TRMM, CloudSat – launch 2005), 2) climate simulations from GMAO and GISS atmospheric and coupled general circulation models (GCMs), and 3) a global CRM that utilizes a new and novel technique referred to as Diabatic Acceleration and REscaling (DARE) to reduce the scale separation between the convective scale and the large-scale motions associated with synoptic systems and the general circulation.  Using these three elements, we will be able to compare cloud-radiation interactions between the observations, traditional GCM formulations, and a global CRM.   Our study will include analysis of high-resolution spectral characteristics from sensors such as AIRS and physical retrievals of clouds and profile information from sensors such as AIRS, TRMM, CERES/VIRS/MODIS and CloudSat, as well as address fundamental questions concerning cloud and water vapor feedback, and tropical circulation features such as the ITCZ/Hadley/Walker circulation, ENSO, equatorial waves and the Madden-Julian Oscillation (MJO).  This work primarily focuses on the B.3 Cloud Modeling and Analysis Initiative (CMAI), particularly item 3) which involves the scale-dependence of the coupling of dynamics with radiation and precipitation.  Moreover, the proposed work will provide the means to augment GEWEX Cloud System Study Data Integration for Model Evaluation (GCSS-DIME) through at least 2-3 of the suggested 4 mechanisms outlined in the NRA.  In addition, the analysis and outcomes will directly involve and impact the B.1 Global Modeling and Assimilation Office (GMAO) and B.2. Goddard Institute for Space Studies (GISS) areas.  More broadly, this work cuts across NASA-ESE research foci on Climate Variability and Change, the Global Water and Energy cycle, and weather.

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