We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byLily McKinney
Modified over 3 years ago
© Crown copyright Met Office Cloudier Evaluating a new GCM prognostic cloud scheme using CRM data Cyril Morcrette, Reading University, 19 February 2008
© Crown copyright Met Office The need for a cloud scheme Clouds exists well before grid-box reaches 100% relative humidity. But clouds exists on scales much smaller than GCM grid boxes. Cant represent them explicitly. Need to parameterize them.
© Crown copyright Met Office Summary of moisture variables in our Cloud Scheme VariableCurrent schemePC2 q cl (Liquid Water Content) DiagnosticPrognostic q cf (Ice Water Content) Prognostic q t (Total water content) Prognosticq t =q cl +q cf C l (Liquid cloud fraction) DiagnosticPrognostic C f (Ice cloud fraction) DiagnosticPrognostic
© Crown copyright Met Office Fields from LEM simulation of TOGA-COARE (Tropical convection) Mean qcl in envMean qcf in env Liquid cloud fraction Ice cloud fraction Height (km) Time (hours) Height (km) 20 144 0.1 g/kg
© Crown copyright Met Office Tendencies from the LEM fields d (qcl) / dt d (qcf) / dt d (Cl) / dt d (Cf) / dt 0.36 / hr 0.036 g/kg/hr
© Crown copyright Met Office Increments from Convection Detrainment dx/dt=D(x plume -x env ) Detrainment Also consider: vertical transport by compensating subsidence evaporation following warming due to compensating subsidence. (These are small effects)
© Crown copyright Met Office Increments from Convection d (qcl) / dt d (Cl) / dt d (qcf) / dt d (Cf) / dt
© Crown copyright Met Office Microphysical effects on d(qcf)/dt Deposition Sublimation Autoconversion of ice crystals to snow Fall of ice 0.036 g/kg/hr
© Crown copyright Met Office Effects on d(qcf)/dt All microphysics Advection by compensating subsidence
© Crown copyright Met Office Effects on d(Cf)/dt Fall of ice Sublimation Advection by compensating subsidence
© Crown copyright Met Office Effects on d(qcl)/dt Adiabatic warming by compensating subsidence Advection by compensating subsidence Large-scale forcing Boundary-layer processes
© Crown copyright Met Office Effects on d(Cl)/dt Adiabatic warming by compensating subsidence Boundary-layer processes Large-scale forcing Advection by compensating subsidence
© Crown copyright Met Office Parameterized tendencies d (qcl) / dt d (qcf) / dt d (Cl) / dt d (Cf) / dt
© Crown copyright Met Office Comparing Tendencies d (qcl) / dt d (qcf) / dt d (Cl) / dt d (Cf) / dt Truth from LEM Parametrization
© Crown copyright Met Office Conclusions (work in progress) General methodology seems promising. Source from convective detrainment appears to be too high. (This may be due to way detrainment is calculated from LEM data) Future work Consider using a diagnostic cloud fraction for shallow convection which doesnt have large anvils.
© Crown copyright Met Office Questions and answers
© Crown copyright Met Office Extra figures Massflux
© Crown copyright Met Office Overview of Cloud Scheme Developments at the Met Office Cyril Morcrette November 2009, Reading University.
ECMWF Training Course Peter Bechtold and Christian Jakob
Page 1© Crown copyright 2006 Precipitating Shallow Cumulus Case Intercomparison For the 9th GCSS Boundary Layer Cloud Workshop, September 2006, GISS.
Page 1© Crown copyright 2005 Damian Wilson, 12 th October 2005 Assessment of model performance and potential improvements using CloudNet data.
© Crown copyright Met Office Systematic Biases in Microphysics: observations and parametrization Ian Boutle, Steven Abel, Peter Hill, Cyril Morcrette QJ.
© Crown copyright 2006Page 1 CFMIP II sensitivity experiments Mark Webb (Met Office Hadley Centre) Johannes Quaas (MPI) Tomoo Ogura (NIES) With thanks.
APR CRM simulations of the development of convection – some sensitivities Jon Petch Richard Forbes Met Office Andy Brown ECMWF October 29 th 2003.
Cloud Resolving Model Studies of Tropical Deep Convection Observed During HIBISCUS By Daniel Grosvenor, Thomas W. Choularton, & Hugh Coe - The University.
1 Numerical Weather Prediction Parameterization of diabatic processes Convection III The ECMWF convection scheme Christian Jakob and Peter Bechtold.
© Crown copyright Met Office Developments in UM Microphysics Jonathan Wilkinson Reading and Met Office Collaboration, 17 November 2009.
GFDL Geophysical Fluid Dynamics GFDL Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey AM2 cloud sensitivity to details of convection and cloud.
GFS Deep and Shallow Cumulus Convection Schemes
Met Office GPCI simulations Adrian Lock. © Crown copyright UK Met Office simulations in GPCI HadGAM1 climate – for IPCC AR4 38 levels (~300m at 1km),
R. Forbes, 17 Nov 09 ECMWF Clouds and Radiation University of Reading ECMWF Cloud and Radiation Parametrization: Recent Activities Richard Forbes, Maike.
Georg A. Grell (NOAA / ESRL/GSD) and Saulo R. Freitas (INPE/CPTEC) A scale and aerosol aware stochastic convective parameterization for weather and air.
The Problem of Parameterization in Numerical Models METEO 6030 Xuanli Li University of Utah Department of Meteorology Spring 2005.
Convection plans Alison Stirling.
Page 1© Crown copyright 2005 DEVELOPMENT OF 1- 4KM RESOLUTION DATA ASSIMILATION FOR NOWCASTING AT THE MET OFFICE Sue Ballard, September 2005 Z. Li, M.
Ewan OConnor, Robin Hogan, Anthony Illingworth Drizzle comparisons.
© 2017 SlidePlayer.com Inc. All rights reserved.