Abstract
Abstract. The current operational version of National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) shows significant low cloud bias. These biases also appear in the Coupled Forecast System (CFS), which is developed from the GFS. These low cloud biases degrade seasonal and longer climate forecasts, particularly of short-wave cloud radiative forcing, and affect predicted sea surface temperature. Reducing this bias in the GFS will aid the development of future CFS versions and contributes to NCEP's goal of unified weather and climate modelling. Changes are made to the shallow convection and planetary boundary layer parameterisations to make them more consistent with current knowledge of these processes and to reduce the low cloud bias. These changes are tested in a single-column version of GFS and in global simulations with GFS coupled to a dynamical ocean model. In the single-column model, we focus on changing parameters that set the following: the strength of shallow cumulus lateral entrainment, the conversion of updraught liquid water to precipitation and grid-scale condensate, shallow cumulus cloud top, and the effect of shallow convection in stratocumulus environments. Results show that these changes improve the single-column simulations when compared to large eddy simulations, in particular through decreasing the precipitation efficiency of boundary layer clouds. These changes, combined with a few other model improvements, also reduce boundary layer cloud and albedo biases in global coupled simulations.
Highlights
The National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS, http://www.emc.ncep.noaa. gov/Global Forecasting System (GFS)/doc.php) is an important model for operational weather forecasting
It is necessary to change all of these parameters together in order to address these compensating errors, so we only show results from simulations in which multiple parameters were changed
To improve the GFS simulation of subtropical boundary layer cloud, we used single-column simulations to identify and attribute underlying problems in the shallow convection scheme, and we tested improvements suggested by this approach in short global coupled simulations
Summary
The National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS, http://www.emc.ncep.noaa. gov/GFS/doc.php) is an important model for operational weather forecasting. The National Centers for Environmental Prediction (NCEP) Global Forecast System A frozen version of the GFS is coupled to the Modular Ocean Model v4 (http://www.gfdl.noaa.gov/ mom-ocean-model) and called the Coupled Forecast System (CFS); this is used for seasonal to inter-decadal climate predictions and reanalyses (Saha et al, 2006, 2010). An outstanding problem for both the GFS and CFS, described in more detail below, is the representation of boundary layer clouds. The purpose of the CPT was to improve the representation of subtropical boundary layer cloud processes in the GFS and CFS, as well as in the Community Earth System Model (CESM, http://www.cesm.ucar.edu/), using the relative strengths and weaknesses of these two rather different modelling systems to help inform further parameterisation advances in both models. The CPT has involved researchers from the Jet Propulsion Laboratory, University of California Los Angeles, the National Center for Atmospheric Research (NCAR), and Lawrence Livermore National Laboratories
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