Research Projects

ATMOSPHERIC DYNAMICS, CLOUDS, AND RADIATION

Projects...

PI: Veron

Co-PI: None

Agency: DOE (subcontract through NOAA)

Title: Investigation of the Aerosol Indirect Effect at the Southern Great Plains Using Ground Based Remote Sensors and Modeling

Abstract: The ARM Southern Great Plains (SGP) site is equipped with a broad suite of instruments pertaining to the study of clouds and climate. This instrumentation also offers a rare and unprecedented opportunity to investigate the effect of aerosols on clouds -- the aerosol ``indirect effect", which is perhaps the single largest unknown in climate forcing. Here we propose to use ground-based remote sensors, supplemented by in situ measurements when available, to explore the indirect effect in non-precipitating, ice-free clouds. The study will use archived ARM data on sub-cloud aerosol extinction, cloud liquid water path, cloud optical depth, drop effective radius, and boundary layer dynamics to investigate the relationship between aerosol extinction and drop effective radius. The fact that so many parameters can be measured simultaneously will allow us to categorize the data into various subsets and determine the most important parameters. Two approaches will be taken: the first will be an empirical approach which will explore relationships between various measured parameters and their statistical significance; the second will use a variety of numerical models, ranging from parcel models to large eddy simulations, to explore the underlying physical processes at similar temporal and spatial scales to those observed.  By approaching the problem from both of these perspectives we will produce valuable data for evaluation of the indirect effect that will benefit the satellite and GCM communities and therefore our climate forecasting capabilities.

PI: Veron

Co-PI: None

Agency: DOE

Title: Evaluation and Development of Stochastic Radiative Transfer as an Atmospheric General Circulation Model Parameterization

Abstract: Stochastic radiative transfer modeling has recently been shown to be a promising approach to modeling the domain-average shortwave radiation fields that occur in scattered cloud conditions. However, current stochastic models are too computationally expensive to use in an atmospheric general circulation model (AGCM). This is a proposal to parameterize the influence of the stochastic method on shortwave radiation fields and heating rates in broken clouds. It follows on from recent work by the PI that showed this approach to be a more physical representation of the radiation field occurring when low-level, scattered clouds are present.

The primary aims of this research are to:

• Determine under what conditions a stochastic cloud and radiation parameterization would be useful in an AGCM.

• Develop the parameterization from the results of the current stand-alone model using a single-column model.

• Evaluate the parameterization in an atmospheric general circulation model.

The parameterization development will be conducted using data already available from the Atmospheric Radiation Measurement (ARM) Program’s Data Archive. The resulting parameterization will yield more realistic radiation fields in the AGCM grid cells where scattered clouds are likely to occur. Additionally, this will lead to better understanding of the statistical feature of cloud fields and may aid in decreasing the uncertainty of climate predictions by incorporating the influence of cloud shape and distribution on the radiation fields.

PI: Weaver
Co-PI: Joel R. Norris, Stephen A. Klein

Agency: DOE

Title: Parameterization of Mesoscale Circulations and Frontal Cloudiness in GCMs Based on ARM Observations

Abstract: Cloudiness associated with extratropical cyclones is currently poorly represented in GCMs due to incorrect and insufficient representation of subgrid-scale processes, leading to erroneous cloud-climate feedbacks. This project will develop an understanding of the relationship between mesoscale variability and large-scale synoptic forcing so that mesoscale variability and its impacts on clouds and water vapor may be parameterized in a GCM. Observations from the ARM SGP/CART site will be used to characterize mesoscale distributions of cloud cover, temperature, and moisture as a function of large-scale forcing. Observations from the SGP March 2000 IOP will be combined with output from the Regional Atmospheric Modeling System (RAMS) forced by observed boundary conditions to provide a detailed set of cloud and dynamical information. An ensemble of runs will be carried out to investigate what processes are responsible for producing mesoscale circulations and cloud structures and how much the large-scale synoptic forcing determines specific mesoscale features. Output from a high-resolution run with enhanced microphysics will be made available to the ARM community for March 2000 IOP cases. The results of the observational analyses and RAMS simulations will be combined with theory for frontal rainbands to develop a parameterization representing the mesoscale distribution of synoptically generated cloudiness. The resulting parameterization will be tested and implemented in the GFDL Flexible Modeling System and the NCAR Community Atmosphere Model.

PI: Weaver

Co-PI: Dana E. Veron

Agency: NSF

Title: Stochastic Radiative Transfer Through an Inhomogeneous Cloud Field Produced by a 3-D, High-Resolution Numerical Atmospheric Model

Abstract: Development of improved cloud parameterizations for Global Climate Models (GCMs) is one of the top priorities of the climate research community. Improving such parameterizations is widely recognized as a prerequisite for fundamental advances in climate change research. The difficulty in creating cloud parameterizations that give accurate results across a wide range of regions, times, and climate regimes is that the underlying dynamical processes are unresolved at current GCM grid scales. In addition, many important physical processes, of which radiative transfer is among the most important, are nonlinear with respect to the unresolved cloud spatial distribution. One promising current strategy for addressing these issues is to explicitly predict these subgrid distributions inside each GCM grid cell. However, developing, testing, and refining such “statistical cloud schemes” are in their earliest stages. In particular, the impact of spatially variable cloud fields on model radiative transfer has not been well quantified. The radiative consequences of using the more realistic representations of cloud water spatial variability that would be produced by a statistical cloud scheme and the potential gains and tradeoffs of such a strategy are major unanswered questions. More generally, much additional work is needed on the problem of radiative transfer through an inhomogeneous cloud field, a problem that has important implications for understanding atmospheric and climate system processes.

 Here we describe a proposal for a Small Grant for Exploratory Research (SGER) to begin addressing these issues. Part of the motivation for this proposal comes from the opportunity to combine two powerful tools for investigating cloud variability and radiative transfer and to apply the combination to the scientific issues discussed above. These tools are: (i) a state-of-the-art, high-resolution, 3-D numerical atmospheric model; (ii) a state-of-the-art stochastic radiative transfer model that can accurately represent shortwave fluxes through a highly variable cloud field.

 This project has three major objectives:

 1.      To quantify, for a number of case studies, the impact of the atmospheric model’s realistic, high-resolution cloud distributions, compared to more idealized or more homogeneous (“GCM-like”) distributions, on the shortwave fluxes predicted by the stochastic radiative transfer model;

2.      To link differences in this impact to differences in synoptic regime, atmospheric dynamical processes, and cloud type;

3.      To begin developing and testing a valuable tool that we expect to have important applications for cloud parameterization development and fundamental research into the problem of radiative transfer through a cloudy atmosphere: namely, our proposed methodology of coupling output from a high-resolution, 3-D atmospheric numerical model with an advanced radiative transfer model capable of accurately capture the effects of cloud spatial heterogeneity.

 Taken together, we expect this analysis will have broader impacts on the climate research and modeling communities by yielding useful insights into the impact of smaller-scale cloud variability on GCM-scale radiative fluxes, when and where the representation of such variability might be needed or desirable, and the dependence of this impact on the underlying resolution of the cloud field and the cloud-producing dynamics and thermodynamics. As such, the proposed work speaks directly to the goals of the NSF Climate Dynamics program in the Atmospheric Sciences Division to investigate the processes that govern climate and climate change and to develop and use climate models to diagnose and simulate climate. Furthermore, we believe that linking a high-resolution, 3-D atmospheric numerical model to a sophisticated radiative transfer scheme with the capability to take advantage of the additional information on cloud spatial variability provided will prove to be a highly effective methodology for investigating fundamental questions of radiative transfer through a cloudy atmosphere and aiding parameterization development. Therefore, the development and demonstration of this methodology is an appropriate subject for an SGER proposal.