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Cecile Hannay


Evaluation of Southeast Pacific Stratocumulus in climate models

    We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 to 5 days to determine the differences with the EPIC field observations.

    Observations during the EPIC cruise show a well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the models is that the planetary boundary layer (PBL) height is too low when compared to EPIC observations. However, we suggest that better PBL heights are achieved with more physically realistic PBL schemes: at one end, CAM uses a dry and surface driven PBL scheme and produces a very shallow PBL while the ECWMF model uses eddy-diffusivity/mass-flux approach and produces a deeper and better-mixed PBL. All the models produce a strong diurnal cycle in the liquid water path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface and the surface energy budget. This is particularly relevant for coupled simulations as this can lead to a large SST bias.

    • Cécile Hannay, David L Williamson, James J Hack, Jeffrey T Kiehl, Jerry G Olson, Stephen A Klein, Christopher S Bretherton, and Martin Koehler (2009), Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models. J. Climate, 22, 2871-2889. [Manuscript]

GCSS Pacific Cross-section Intercomparison (GPCI)

    Climate models are commonly validated against various statistics based on observations. However, climate models can achieve a reasonable mean state as the result of compensating errors, which are impossible to untangle after long integrations. An innovative way to evaluate parameterizations in climate models is to use the weather forecasting approach. The state of the atmosphere is initialized with realistic conditions and the model is run for short-term forecasts (e.g., 3-10 days). This approach can be very valuable because it allows direct comparison of the parameterized variables (e.g. clouds, precipitation) with available observations early in the forecast while the forecast state is still near that of the atmosphere. It is possible to gain insight into the parameterization deficiencies and to diagnose the processes behind the drift away from reality.

    Here we use short-term forecasts along the GCSS Pacific cross-section to evaluate parameterizations in the Community Atmospheric Model (CAM). The forecasts are initialized from ECMWF analyses and the CAM is run for 5 days to determine the differences with satellite data. The comparison is made for the JJA 2003 period using a set of satellite observations from AIRS, ISCCP, TRMM, SSMI, MISR, and GPCP. We also use GPS PBL height and Cloudsat data for different periods to indicate other shortcomings of the parameterizations.

    We use this testbed to examine the forecast errors in CAM3 and to assess new parameterizations for the next generation model, CAM4. This includes new parameterizations of deep convection, shallow convection, PBL and microphysics. The cross-section is particularly relevant for such a comparison because it includes several important cloud regimes. Near the coast of California, the downwelling branch of the Hadley circulation over cold SSTs creates a persistent stratocumulus deck; further to the southwest, in the trade wind regions, the stratocumulus deck breaks up into shallow cumulus and near the equator, the ITCZ region is characterized by deep convection.

    The mean forecast biases grow very quickly in CAM3, and after 5 days, the error pattern is very similar to the mean climate error along the cross-section. Around the ITCZ, most of the temperature and moisture errors have developed after a single day. The error is due to an excessive drying of the lower troposphere and the rainout of the moisture by the deep convection scheme. Over the stratocumulus region, the error grows more slowly and it takes 5 days before the mean forecast error reaches the amplitude of the mean climate error. In this region, CAM3 shows a systematic collapse of the PBL compared to the initial state.

    Initial results suggest that the errors in temperature and moisture are reduced in CAM4. We also observe a dramatic improvement of the precipitation in the ITCZ region and more realistic low-levelclouds.

    Weather and climate prediction models are analyzed along a cross-section in the Pacific Ocean, from California to the Equator. The cross-section over the Pacific Ocean encompasses several fundamental cloud regimes such as stratocumulus, shallow cumulus and deep cumulus, as well as the transitions between them. The model outputs are collected every 3 hours (JJA 1998 and 2003), which allows for a better understanding of issues associated with the diurnal cycle of clouds and cloud related processes in the tropics and subtropics. Presently, GPCI has collected output from 6 models from GFDL, NCAR, UKMO, MeteoFrance, JMA and KNMI.

Last modified: Jan 8 2010   by