COSP: a multi-instrument satellite simulator for model
evaluation
A. Bodas-Salcedo(1), M. J. Webb(1), K. D. Williams(1), S. Bony(2), H. Chepfer(2), J.-L. Dufresne(2), S. Klein(3), Y. Zhang(3), R. Marchand(4), and J. Haynes(5)
(1) Met Office Hadley Centre
(2) Laboratoire de Météorologie Dynamique/Institut Pierre Simon Laplace
(3) Lawrence Livermore National Laboratory
(4) University of Washington
(5) Monash University
Abstract
The simulation of clouds in General Circulation Models (GCMs) is a major source of spread in the climate
projections of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). This
highlights the need for developing new analysis techniques that improve our knowledge of the physical
processes that cause these differences. The Cloud Feedback Model Intercomparison Project (CFMIP)
Observational Simulator Package (COSP) has been developed to help address this issue. COSP is a flexible
software tool that enables the simulation of data from several satellite-borne sensors from model variables.
Especially, COSP will take advantage of the synergy provided by the active sensors on the A-Train, CloudSat
and CALIPSO. It facilitates the use of satellite data to evaluate models in a process-oriented and consistent
way. The flexibility of COSP makes it suitable to be used in any type of numerical model, from high-resolution
cloud-resolving models to coarse-resolution models like the GCMs used in the IPCC, and the scales in
between used in weather forecast models. This should help to evaluate clouds within a "seamless" context.
We describe the capabilities of COSP by giving examples of outputs to demonstrate its potential for model
evaluation. COSP is a flexible tool that can be easily expanded to include more sensors, and work is currently
in progress in this respect. We also describe the future plans for COSP.
2. EXAMPLES OF OUTPUTS FROM COSP
1. DESCRIPTION OF THE SOFTWARE
•The schematic below shows the modular structure of the
software
COSP
MAIN
SCOPS
SG
PRECIP
COSP SUB-GRID
CLOUDSAT
SUMMARY
STATISTICS
CALIPSO
Figure 1. Frequency of occurrence of radar reflectivitie as
function of height (similar to those in Bodas-Salcedo et al.,
2008).
Figure 3. Frequency of occurrence of cloudy pixels from MISR
simulator as function of cloud top height and optical depth.
Figure 2. Frequency of occurrence of lidar scattering ratio as
function of height.
Figure 4. Frequency of occurrence of cloudy pixels from the
ISCCP simulator as function of cloud top pressure and optical
depth.
ISCCP
(a)
MISR
(a)
(a)
RTTOV
TRMM
It contains the following instrument simulators:
•CloudSat radar (Haynes et al., 2007)
•CALIPSO lidar (Chepfer et al., 2008), with PARASOL reflectances
•ISCCP simulator (Klein and Jakob, 1999; Webb et al., 2001)
•MISR
The following simulators will be included in future
versions:
(b)
(b)
(b)
(c)
(c)
(c)
•RTTOV (Saunders et al., 1999)
•TRMM precipitation radar
COSP can be downloaded from http://www.cfmip.net/
COSP produces the following output diagnostics:
CloudSat
•Radar reflectivity in each subcolumn
•Height-reflectivity histograms
CALIPSO
•Lidar total backscatter (532 nm)
•Lidar molecular backscatter
•Height-scattering ratio histograms
•Low-level cloud fraction (CTP>680 hPa)
•Mid-levlel cloud fraction (440<CTP<680 hPa)
•High-level cloud fraction (CTP<440 hPa)
•3D Cloud fraction
•Total cloud fraction
MISR,PARASOL and combined
•PARASOL mono-directional reflectance
•MISR CTH-Tau histograms
•Total cloud fraction from CALIPSO&CloudSat
•3D cloud fraction as seen from CALIPSO but not
CloudSat
ISCCP
•Mean cloud albedo
•Cloud optical depth in each subcoumn
•Mean cloud top pressure
•Mean 10.5 micron brightness temperature
•Mean clear-sky 10.5 micron brightness
temperature
•Mean cloud optical depth
•Cloud top pressure in each subcolumn
•CTP-tau histograms
•Total cloud fraction
3. FUTURE WORK
At the 2008 WGCM meeting, it was agreed that satellite simulators will be
included in the planned activities of WGCM for the next assessment. The use of
COSP is a strong recommendation for the next IPCC assessment report (CMIP5
simulations), and some COSP outputs will be included into the "core" set of
CMIP5 outputs:
•Long timeseries : At present, only the ISCCP and CALIPSO simulators are
ready for in-line, long-term integrations. The recommendation is to use them inline in several mandatory CMIP5 experiments.
•Short timeseries : COSP (with all simulators activated together with the A-Train
orbital sampling) will be used off-line for one year (2007) in a subset of the
CMIP5 experiments:
•AMIP experiment (1979-2008). Atmosphere-only experiment forced with
observed SSTs.
•4xCO2 Hansen experiment (1979-2008). In this experiment, the AMIP
experiment is repeated with the same SSTs, but radiation sees 4CO2.
•A patterned SST-perturbed climate change experiment (1979-2008). SST
perturbation pattern based on a composite of coupled model SST responses
taken from 1% coupled model CMIP3 experiments at time of CO2
quadrupling. Although these experiments are not expected to reproduce
exactly the global mean cloud feedbacks as in a coupled experiment or slab
experiments, they are expected to explore the same range of cloud feedback
processes.
•A uniform +4K SST-perturbed climate change experiment (1979-2008).
This complements the patterned-SST above, and in combination will allow
the effects of local and remote changes in SST on cloud feedbacks to be
assessed.
REFERENCES
Bodas-Salcedo, A., M. J. Webb, M. E. Brooks, M. A. Ringer, K. D. Williams, S. F. Milton, and D. R. Wilson,
Evaluating cloud systems in the met office global forecast model using simulated cloudsat radar reflectivities, J.
Geophys. Res., 113, D00A13, 2008. doi:10.1029/2007JD009620.
Chepfer, H., S. Bony, D. Winker, M. Chiriaco, J.-L. Dufresne, and G. Seze, Use of CALIPSO lidar observations to
evaluate the cloudiness simulated by a climate model, Geophys. Res. Lett., 35, L15704, 2008.
doi:10.1029/2008GL034207.
Haynes, J. M., R. T. Marchand, Z. Luo, A. Bodas-Salcedo, and G. L. Stephens, A multi-purpose radar simulation
package: Quickbeam, Bull. Am. Meteorol. Soc., 88(11), 1723-1727, 2007. doi:10.1175/BAMS-88-11-1723.
Klein, S. A., and Jakob, C., Validation and sensitivities of frontal clouds simulated by the ECMWF model, Mon.
Weather Rev., 127(10), 2514-2531, 1999.
Figure 5. Total cloud fraction diagnosed from several simulators:
(a) CALIPSO and CloudSat, (b) CALIPSO only, and (c) ISCCP.
Met Office Hadley Centre, FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom
Tel: 01392 885680 Fax: 01392 885681
Email: alejandro.bodas@metoffice.gov.uk
Figure 6. Cloud fraction on three layers as diagnosed from
CALIPSO simulator: (a) cloud tops above 440 hPa, (b) cloud
tops between 440 and 680 hPa, and (c) cloud tops below 680
hPa.
Figure 7. Additional diagnostics from the ISCCP simulator: (a)
cloud albedo, (b) cloud top pressure, and (c) cloud optical depth.
Saunders, R., M. Matricardi, and P. Brunel, An improved fast radiative transfer model for assimilation of satellite
radiance observations, Q.J.R. Meteorol. Soc., 125, 1407-1425, 1999.
Webb, M., C. Senior, S. Bony, and J. J. Morcrette, Combining ERBE and ISCCP data to assess clouds in the
Hadley Centre, ECMWF and LMD atmospheric climate models, Clim. Dyn., 17, 905-922, 2001.
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