11:15 AM - 11:30 AM
[AAS01-03] Potential impact of Doppler CPR observation by EarthCARE on climate modeling
Keywords:Cloud Profiling Radar, Vertical Doppler velocity, Satellite simulator
Until now, the fall velocity of cloud and precipitation droplets has been regarded as a tuning parameter of Global Climate Models due to the lack of global satellite observations. Too much focus on improving the performance of GCMs may lead to distancing the cloud microphysics settings in GCMs from reality.
EarthCARE is a new satellite scheduled for launch this year, which will produce newer vertical Doppler velocity observation. This pioneering product will shed light on the vertical motion and microphysics of cloud droplets. Here, we develop a new simulator for this Doppler CPR of EarthCARE on CFMIP Observation Simulator Package v2 (COSP2). This simulator allows the GCM outputs to be translated into equivalent variables to the observations. In this presentation, based on the comparisons of Doppler velocity simulator mounted on GCM MIROC6 with ground-based radar observation at Tokyo, we aim to improve cloud microphysics scheme and investigate its impact on climate state.
The Doppler velocity simulator calculated qualitatively reasonable CFAD statistics, which show a gradual increase in fall velocity as cloud ice and snow particles grow from high to middle altitudes, and a further increase in fall velocity with melting of snow particles. However, quantitatively, MIROC6 underestimates droplet fall speed, especially rain, and also underestimates variance of Doppler velocity statistics.
Sensitivity test of fall speed tuning on MIROC6 can modify radiative energy balance through changes in cloud distributions. Adjusting to increase the fall speed of ice particles in MIROC6 to match ground-based radar observations shortens the lifetime of clouds in the upper troposphere and increases outgoing longwave radiation. This perturbation implies that error compensations in or beyond cloud microphysics might support the “good” performance to date. There is room for improvement in the ice particle growth processes or aerosol interaction, for instance. EarthCARE will provide newer observation of Doppler velocity and expand this comparative study to a global scale for GCM evaluation and improvement in a process-oriented way.
EarthCARE is a new satellite scheduled for launch this year, which will produce newer vertical Doppler velocity observation. This pioneering product will shed light on the vertical motion and microphysics of cloud droplets. Here, we develop a new simulator for this Doppler CPR of EarthCARE on CFMIP Observation Simulator Package v2 (COSP2). This simulator allows the GCM outputs to be translated into equivalent variables to the observations. In this presentation, based on the comparisons of Doppler velocity simulator mounted on GCM MIROC6 with ground-based radar observation at Tokyo, we aim to improve cloud microphysics scheme and investigate its impact on climate state.
The Doppler velocity simulator calculated qualitatively reasonable CFAD statistics, which show a gradual increase in fall velocity as cloud ice and snow particles grow from high to middle altitudes, and a further increase in fall velocity with melting of snow particles. However, quantitatively, MIROC6 underestimates droplet fall speed, especially rain, and also underestimates variance of Doppler velocity statistics.
Sensitivity test of fall speed tuning on MIROC6 can modify radiative energy balance through changes in cloud distributions. Adjusting to increase the fall speed of ice particles in MIROC6 to match ground-based radar observations shortens the lifetime of clouds in the upper troposphere and increases outgoing longwave radiation. This perturbation implies that error compensations in or beyond cloud microphysics might support the “good” performance to date. There is room for improvement in the ice particle growth processes or aerosol interaction, for instance. EarthCARE will provide newer observation of Doppler velocity and expand this comparative study to a global scale for GCM evaluation and improvement in a process-oriented way.