Microphysics of Clouds with the Relaxed Arakawa–Schubert Scheme (McRAS). Part I: Design and Evaluation with GATE Phase III Data

Y. C. Sud Climate and Radiation Branch, Laboratory for Atmospheres, NASA/Goddard Space Flight Center, Greenbelt, Maryland

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G. K. Walker Climate and Radiation Branch, Laboratory for Atmospheres, NASA/Goddard Space Flight Center, Greenbelt, Maryland

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Abstract

A prognostic cloud scheme named McRAS (Microphysics of Clouds with Relaxed Arakawa–Schubert Scheme) has been designed and developed with the aim of improving moist processes, microphysics of clouds, and cloud–radiation interactions in GCMs. McRAS distinguishes three types of clouds: convective, stratiform, and boundary layer. The convective clouds transform and merge into stratiform clouds on an hourly timescale, while the boundary layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the autoconversion equations of Sundqvist that contain a parametric adaptation for the Bergeron–Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud microphysics throughout the life cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry.

An evaluation of McRAS in a single-column model (SCM) with the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) Phase III data has shown that, together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. The time history and time mean in-cloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvils and towers, and the convective updraft and downdraft velocities and mass fluxes all simulate a realistic behavior. Some of these diagnostics are not verifiable with data on hand. These SCM sensitivity tests show that (i) without clouds the simulated GATE-SCM atmosphere is cooler than observed; (ii) the model’s convective scheme, RAS, is an important subparameterization of McRAS; and (iii) advection of cloud water substance is helpful in simulating better cloud distribution and cloud–radiation interaction. An evaluation of the performance of McRAS in the Goddard Earth Observing System II GCM is given in a companion paper (Part II).

* Current affiliation: General Sciences Corporation, Laurel, Maryland.

Corresponding author address: Dr. Yogesh C. Sud, Climate and Radiation Branch, Laboratory for Atmospheres, NASA/Goddard Space Flight Center, Greenbelt, MD 20771.

Abstract

A prognostic cloud scheme named McRAS (Microphysics of Clouds with Relaxed Arakawa–Schubert Scheme) has been designed and developed with the aim of improving moist processes, microphysics of clouds, and cloud–radiation interactions in GCMs. McRAS distinguishes three types of clouds: convective, stratiform, and boundary layer. The convective clouds transform and merge into stratiform clouds on an hourly timescale, while the boundary layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the autoconversion equations of Sundqvist that contain a parametric adaptation for the Bergeron–Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud microphysics throughout the life cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry.

An evaluation of McRAS in a single-column model (SCM) with the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) Phase III data has shown that, together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. The time history and time mean in-cloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvils and towers, and the convective updraft and downdraft velocities and mass fluxes all simulate a realistic behavior. Some of these diagnostics are not verifiable with data on hand. These SCM sensitivity tests show that (i) without clouds the simulated GATE-SCM atmosphere is cooler than observed; (ii) the model’s convective scheme, RAS, is an important subparameterization of McRAS; and (iii) advection of cloud water substance is helpful in simulating better cloud distribution and cloud–radiation interaction. An evaluation of the performance of McRAS in the Goddard Earth Observing System II GCM is given in a companion paper (Part II).

* Current affiliation: General Sciences Corporation, Laurel, Maryland.

Corresponding author address: Dr. Yogesh C. Sud, Climate and Radiation Branch, Laboratory for Atmospheres, NASA/Goddard Space Flight Center, Greenbelt, MD 20771.

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