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F. Chevallier
,
P. Bauer
,
G. Kelly
,
C. Jakob
, and
T. McNally

Abstract

Radiation observations are a key element in the evaluation of the 40-yr reanalysis at the European Centre for Medium-Range Weather Forecasts. This paper uses the High-Resolution Infrared Radiation Sounder/2 (HIRS/2) and Microwave Sounding Unit (MSU) observations on board the National Oceanic and Atmospheric Administration satellites, to assess the characteristics of the cloud fields produced by the forecasting system over midlatitude and tropical oceans. Infrared and microwave radiation have different sensitivities to clouds and are therefore complementary. Observed and model-generated radiances, as well as HIRS/2-derived cloud parameters, are compared.

The model clouds are shown to be well distributed, with realistic seasonal cycles. However, deficiencies are identified and discussed: the cloud radiative impact may be too low in the midlatitudes, the frequency of occurrence of high clouds is overestimated in the intertropical convergence zone, and the stratocumulus off the west coast of the continents is underestimated. The methods described here provide a framework for assessing the impact of forthcoming improvements to the cloud scheme.

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K. D. Williams
,
A. Bodas-Salcedo
,
M. Déqué
,
S. Fermepin
,
B. Medeiros
,
M. Watanabe
,
C. Jakob
,
S. A. Klein
,
C. A. Senior
, and
D. L. Williamson

Abstract

The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses.

The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.

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J. Teixeira
,
S. Cardoso
,
M. Bonazzola
,
J. Cole
,
A. DelGenio
,
C. DeMott
,
C. Franklin
,
C. Hannay
,
C. Jakob
,
Y. Jiao
,
J. Karlsson
,
H. Kitagawa
,
M. Köhler
,
A. Kuwano-Yoshida
,
C. LeDrian
,
J. Li
,
A. Lock
,
M. J. Miller
,
P. Marquet
,
J. Martins
,
C. R. Mechoso
,
E. v. Meijgaard
,
I. Meinke
,
P. M. A. Miranda
,
D. Mironov
,
R. Neggers
,
H. L. Pan
,
D. A. Randall
,
P. J. Rasch
,
B. Rockel
,
W. B. Rossow
,
B. Ritter
,
A. P. Siebesma
,
P. M. M. Soares
,
F. J. Turk
,
P. A. Vaillancourt
,
A. Von Engeln
, and
M. Zhao

Abstract

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

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