Use of Cloud Observations and Mesoscale Meteorology Models to Evaluate and Improve Cloud Parameterizations

This research program utilizes satellite and surface-derived cloud observations together with standard meteorological measurements to evaluate and improve our ability to accurately diagnose cloud coverage. Results are to be used to compliment existing or future parameterizations of cloud effects in general circulation models, since nearly all cloud parameterizations must specify a fractional area of cloud coverage when calculating radiative or dynamic cloud effects, and current parameterizations rely on rather crude cloud cover estimates. We have compiled and reviewed a list of formulations used by various climate research groups to specify cloud cover. We find considerable variability between formulations used by various climate and meteorology models, and under some conditions, one formulation will produce a zero cloud amount, while an alternate formulation calculates 95% cloud cover under the same environmental conditions. All formulations hypothesize that cloud cover is predominantly determined by the average relative humidity, although some formulations allow local temperature lapse rates and vertical velocities to influence cloud amount

A comparison of scavenging and deposition processes in global models: results from the WCRP Cambridge Workshop of 1995

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75543/1/j.1600-0889.2000.00980.x.pd

Use of Cloud Observations and Mesoscale Meteorology Models to Evaluate and Improve Cloud Parameterizations. Technical Progress Report, 1 October 1992--30 September 1993

This research program utilizes satellite and surface-derived cloud observations together with standard meteorological measurements to evaluate and improve our ability to accurately diagnose cloud coverage. Results of this research will be used to compliment existing or future parameterizations of cloud effects in general circulation models, since nearly all cloud parameterizations must specify a fractional area of cloud coverage when calculating radiative or dynamic cloud effects, and current parameterizations rely on rather crude cloud cover estimates. During the first phase of this research program, our goal is to evaluate and improve the methods for calculating cloud cover within a mesoscale meteorology model. To accomplish this, a mesoscale meteorology model will be quantitatively evaluated using available cloud cover databases, including the US Air Force 3DNEPH and RTNEPH satellite-derived cloud fields, as well as CART data as they become available. During the second phase of this research, the cloud cover data and improved parameterizations of cloud coverage developed during the first phase will be incorporated into a mesoscale meteorology model. Model forecasts which utilize the observed cloud coverage and depth should be improved relative to forecasts which crudely specify cloud properties

Use of Cloud Observations and Mesoscale Meteorology Models to Evaluate and Improve Cloud Parameterizations. Final Technical Progress Report, December 1, 1991--September 30, 1996

The main goal of this research effort is to improve methods for calculating cloud cover within climate models. Cloud cover observations are being used with standard meteorological observations to improve the ability to diagnose cloud cover in climate models. Until now, cloud cover and heights have been diagnosed from the US Air force RTNEPH and 3DNEPH archive, although recent CART measurements are also being analyzed. Improved cloud cover formulations have been compared with existing climate model algorithms. Recently, the authors are also refining and validating an innovative Single Column Model (SCM) cumulus parameterization for calculating heating and moistening tendencies, and precipitation rates attributable to subgrid-scale convection not resolved by climate models. This SCM will be tested and evaluated using tropical convective measurements (GATE) and the author will also use incoming measurements from the Oklahoma ARM site. Further development and testing of this SCM could improve the ability to predict convective effects in climate models. The author will quantify the influence of convection on cloud cover using convective measures derived from this SCM. The output of this research will be a family of validated algorithms for assessing cloud cover under a variety of stable, unstable, continental or oceanic conditions, and an improved cumulus parameterization scheme

Use of Cloud Observations and Mesoscale Meteorology Models to Evaluate and Improve Cloud Parameterizations. Technical Progress Report, 1 October 1993--30 December 1994

The main goal of this research effort is to improve methods for calculating cloud cover within climate models. Until now, cloud cover and heights have been diagnosed from the US Air Force RTNEPH and 3DNEPH archive, and recently, CART measurements are available for analysis. Improved cloud cover formulations have been compared with existing climate model algorithms. The authors earlier conclusions were that relative humidity and convective potential were the strongest factors influencing cloud cover on regional scales. Therefore, they are refining and validating an innovative Single Column Model (SCM) cumulus parameterization for calculating heating and moistening tendencies, and precipitation rates attributable to subgrid-scale convection not resolved by climate models. This SCM will be tested and evaluated using tropical convective measurements (GATE) and they will also be applied to the incoming measurements from the Oklahoma ARM site. Further development and testing of this SCM will improve their ability to predict convective effects and cloud cover in climate models. They will quantify the influence of convection on cloud cover using convective measures derived from this SCM. The output of this research will be a family of validated algorithms for assessing cloud cover under a variety of stable, unstable, continental or oceanic conditions, and an improved cumulus parameterization scheme