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F. Chevallier and J-J. Morcrette

Abstract

The global observation network of the atmospheric broadband radiation reached an unprecedent extent in 1998 with the simultaneous availability of longwave and shortwave measurements of the Clouds and the Earth’s Radiant Energy System instrument on board the Tropical Rainfall Measuring Mission spacecraft, and of a number of surface stations as part of the Atmospheric Radiation Measurement, Baseline Surface Radiation Network, and Surface Radiation network programs.

In this paper, these observations are used to assess the quality of the longwave and shortwave components of both the top-of-the-atmosphere and the surface radiation budget computed by the ECMWF operational forecast system.

The main features of the boundary radiation are well captured by the system. Clouds appear to be the main modulator of the uncertainty of the top-of-the-atmosphere radiation and of the shortwave surface radiation. This is explained by both model cloud deficiencies and inadequate cloud representation in the radiative transfer schemes. The longwave surface radiation uncertainty is marked by a clear sky bias, common to most of the parameterized longwave radiative transfer models.

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M. A. Giorgetta and J-J. Morcrette

Abstract

The vertical extension of a general circulation model generally requires a modification of the model's highly parameterized radiation scheme in order to include approximately the absorption by lines with a Voigt profile. For the European Centre for Medium-Range Weather Forecasts radiation scheme, a modification of the Lorentz line width provides a practical solution for this problem. Thus, the domain of this wideband radiation scheme is extended from the surface up to the mesopause.

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J-J. Morcrette, H. W. Barker, J. N. S. Cole, M. J. Iacono, and R. Pincus

Abstract

A new radiation package, “McRad,” has become operational with cycle 32R2 of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). McRad includes an improved description of the land surface albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, the Monte Carlo independent column approximation treatment of the radiative transfer in clouds, and the Rapid Radiative Transfer Model shortwave scheme. The impact of McRad on year-long simulations at T L159L91 and higher-resolution 10-day forecasts is then documented. McRad is shown to benefit the representation of most parameters over both shorter and longer time scales, relative to the previous operational version of the radiative transfer schemes. At all resolutions, McRad improves the representation of the cloud–radiation interactions, particularly in the tropical regions, with improved temperature and wind objective scores through a reduction of some systematic errors in the position of tropical convection as a result of a change in the overall distribution of diabatic heating over the vertical plane, inducing a geographical redistribution of the centers of convection. Although smaller, the improvement is also seen in the rmse of geopotential in the Northern and Southern Hemispheres and over Europe. Given the importance of cloudiness in modulating the radiative fluxes, the sensitivity of the model to cloud overlap assumption (COA) is also addressed, with emphasis on the flexibility that is inherent to this new RT approach when dealing with COA. The sensitivity of the forecasts to the space interpolation that is required to efficiently address the high computational cost of the RT parameterization is also revisited. A reduction of the radiation grid for the Ensemble Prediction System is shown to be of little impact on the scores while reducing the computational cost of the radiation computations. McRad is also shown to decrease the cold bias in ocean surface temperature in climate integrations with a coupled ocean system.

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Kwinten Van Weverberg, Cyril J. Morcrette, and Ian Boutle

Abstract

A wide range of approaches exists to account for subgrid cloud variability in regional simulations of the atmosphere. This paper addresses the following questions: 1) Is there still benefit in representing subgrid variability of cloud in convection-permitting simulations? 2) What is the sensitivity to the cloud fraction parameterization complexity? 3) Are current cloud fraction parameterizations scale-aware across convection-permitting resolutions? These questions are addressed for regional simulations of a 6-week observation campaign in the U.S. southern Great Plains. Particular attention is given to a new diagnostic cloud fraction scheme with a bimodal subgrid saturation-departure PDF, described in Part I. The model evaluation is performed using ground-based remote sensing synergies, satellite-based retrievals, and surface observations. It is shown that not using a cloud fraction parameterization results in underestimated cloud frequency and water content, even for stratocumulus. The use of a cloud fraction parameterization does not guarantee improved cloud property simulations, however. Diagnostic and prognostic cloud schemes with a symmetric subgrid saturation-departure PDF underestimate cloud fraction and cloud optical thickness, and hence overestimate surface shortwave radiation. These schemes require empirical bias-correction techniques to improve the cloud cover. The new cloud fraction parameterization, introduced in Part I, improves cloud cover, liquid water content, cloud-base height, optical thickness, and surface radiation compared to schemes reliant on a symmetric PDF. Furthermore, cloud parameterizations using turbulence-based, rather than prescribed constant subgrid variances, are shown to be more scale-aware across convection-permitting resolutions.

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Y. Fouquart, B. Bonnel, G. Brogniez, J. C. Buriez, L. Smith, J. J. Morcrette, and A. Cerf

Abstract

The results presented in this paper are a part of those obtained during the ECLATS experiment The broadband radiative characteristics of the Sahelian aerosol layer and the vertical radiative flux divergence within the dust layer were determined both from in situ measurements and Mie calculations.

In situ measurements of the aerosol layer's reflectances and transmittances of solar radiation led to aerosol single-scattering albedos close to ωA∼0.95. Measurements of the 8–14 μm radiances led to an optied depth by unit of volume of dust in a vertical column C A∼0.34 μm−1. Mie calculations assuming the aerosol refractive index published by Carlson and Benjamin for solar radiation and that measured by Volz for the atmospheric window, showed good agreement with observations. The ratio of infrared to visible optical thickness was δA(8–14 μm)/δA (0.55 μm)∼0.1, instead of 0.3 as calculated by Carlson and Benjamin. This discrepancy is attributable to differences in size distributions assumed.

The radiative budget of the Sahelian aerosol layer was determined for clear and dusty conditions. The additional aerosol shortwave heating was as much as 5 K day−1 for δA(0.55 μm) = 1.5 and with the sun overhead, whereas the additional cooling was close to 1 K day−1. As a consequence of the large temperature discontinuity at the surface, important infrared heating at the surface layer was observed.

The rather large differences between the aerosol optical properties reported here and those previously reported in the literature are due to different aerosol size distributions; therefore the present paper stresses the importance of careful determination of the size distributions.

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K. Furtado, P. R. Field, I. A. Boutle, C. J. Morcrette, and J. M. Wilkinson

Abstract

A physically based method for parameterizing the role of subgrid-scale turbulence in the production and maintenance of supercooled liquid water and mixed-phase clouds is presented. The approach used is to simplify the dynamics of supersaturation fluctuations to a stochastic differential equation that can be solved analytically, giving increments to the prognostic liquid cloud fraction and liquid water content fields in a general circulation model (GCM). Elsewhere, it has been demonstrated that the approach captures the properties of decameter-resolution large-eddy simulations of a turbulent mixed-phase environment. In this paper, it is shown that it can be implemented in a GCM, and the effects that this has on Southern Ocean biases and on Arctic stratus are investigated.

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Maike Ahlgrimm, Richard M. Forbes, Jean-Jacques Morcrette, and Roel A. J. Neggers
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Kwinten Van Weverberg, Cyril J. Morcrette, Ian Boutle, Kalli Furtado, and Paul R. Field

Abstract

Cloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional midlatitude forecasts, the Met Office uses a diagnostic cloud fraction scheme that relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. For model grid boxes located in this entrainment zone, collocated moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given gridbox mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the southern Great Plains in the United States, it is shown that the new scheme improves the relation between cloud fraction, relative humidity, and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in Part II.

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Robert D. Cess, Seth Nemesure, Ellsworth G. Dutton, John J. Deluisi, Gerald L. Potter, and Jean-Jacques Morcrette

Abstract

Two datasets have been combined to demonstrate how the availability of more comprehensive datasets could serve to elucidate the shortwave radiative impact of clouds on both the atmospheric column and the surface. These datasets consist of two measurements of net downward shortwave radiation: one of near-surface measurements made at the Boulder Atmospheric Observatory tower, and the other of collocated top-of-the-atmosphere measurements from the Earth Radiation Budget Experiment. Output from the European Centre for Medium-Range Weather Forecasts General Circulation Model also has been used as an aid in interpreting the data, while the data have in turn been employed to validate the model's shortwave radiation code as it pertains to cloud radiation properties. Combined, the datasets and model demonstrate a strategy for determining under what conditions the shortwave radiative impact of clouds leads to a heating or cooling of the atmospheric column. The datasets also show, in terms of a linear slope-offset algorithm for retrieving the net downward shortwave radiation at the surface from satellite measurements, that the clouds present during this study produced a modest negative bias in the retrieved surface flux relative to that inferred from a clear-sky algorithm.

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A. Hollingsworth, R. J. Engelen, C. Textor, A. Benedetti, O. Boucher, F. Chevallier, A. Dethof, H. Elbern, H. Eskes, J. Flemming, C. Granier, J. W. Kaiser, J.-J. Morcrette, P. Rayner, V.-H. Peuch, L. Rouil, M. G. Schultz, A. J. Simmons, and The Gems Consortium

The Global and Regional Earth System Monitoring Using Satellite and In Situ Data (GEMS) project is combining the manifold expertise in atmospheric composition research and numerical weather prediction of 32 European institutes to build a comprehensive monitoring and forecasting system for greenhouse gases, reactive gases, aerosol, and regional air quality. The project is funded by the European Commission as part of the Global Monitoring of Environment and Security (GMES) framework. GEMS has extended the data assimilation system of the European Centre for Medium-Range Weather Forecasts (ECMWF) to include various tracers for which satellite observations exist. A chemical transport model has been coupled to this system to account for the atmospheric chemistry. The GEMS system provides lateral boundary conditions for a set of 10 regional air quality forecast models and global atmospheric fields for use in surface flux inversions for the greenhouse gases. Observations from both in situ and satellite sources are used as input, and the output products will serve users such as policy makers, environmental agencies, the science community, and providers of end-user services for air quality and health. This article provides an overview of GEMS and uses some recent results to illustrate the current status of the project. It is expected that GEMS will grow into a full operational service for the atmospheric component of GMES in the next decade. Part of this transition will be the merge with the Protocol Monitoring for the GMES Service Element: Atmosphere (PROMOTE) GMES project into the Monitoring of Atmospheric Composition and Climate (MACC) project.

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