The development and verification of a cloud prediction scheme for the ECMWF model

SLINGO, JM

doi:10.1256/smsqj.47708

Cited by 211 publications

(117 citation statements)

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“…Interesting insight on these scheme interactions can be obtained by comparing the resulting cloud fields for the TWP-ICE case, which exhibits quite varied convection characteristics. Early cloud parametrizations were frequently based on an explicit relationship between grid-average relative humidity and cloud fraction (e.g., Slingo, 1987). None of the two schemes employed here uses such an explicit relationship and it is therefore of interest to compare the simulated relative humidity-cloud fraction relationships with those from the TWP-ICE dataset.…”

Section: Comparison Of Cloud Variability Between the Prognostic And Dmentioning

confidence: 99%

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Franklin

Jakob

Protat

et al. 2011

Quart J Royal Meteoro Soc

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Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.

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Section: Comparison Of Cloud Variability Between the Prognostic And Dmentioning

confidence: 99%

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Franklin

Jakob

Protat

et al. 2011

Quart J Royal Meteoro Soc

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“…The cloud water paths that were originally specified as functions of height and latitude are calculated according to the cloud water determined by the SUN scheme. The original Slingo [1987] parameterization for fractional cloud coverage is replaced by the SUN parameterization. The "nonlocal" boundary layer parameterization [Holstag and Boville, 1993] diagnoses the boundary layer depth and determines diffusivity profiles and turbulent transport within the boundary layer.…”

Section: Ncar Ccm2mentioning

confidence: 99%

Sensitivity of a cloud parameterization package in the National Center for Atmospheric Research Community Climate Model

Kao¹,

Smith²

1999

J. Geophys. Res.

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Abstract. A physically based cloud parameterization package, which includes the Arakawa-Schubert (AS) scheme for subgrid-scale convective clouds and the Sundqvist (SUN) scheme for nonconvective grid-scale layered clouds (hereafter referred to as the SUNAS cloud package), is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, Version 2 (CCM2). The AS scheme is used for a more reasonable heating distribution due to convective clouds and their associated precipitation. The SUN scheme allows for the prognostic computation of cloud water so that the cloud optical properties are more physically determined for shortwave and longwave radiation calculations. In addition, the formation of anvil-like clouds from deep convective systems is able to be simulated with the SUNAS package. A 10-year simulation spanning the period from 1980 to 1989 is conducted, and the effect of the cloud package on the January climate is assessed by comparing it with various available data sets and the National Center for Environmental Protection/NCAR reanalysis.

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“…Longwave radiation (Harshvardhan et al 1987) including the iterative cloud radiation scheme of Slingo (1987) is calculated every 3 h of simulation and the shortwave radiation (Lacis and Hansen 1974) is calculated every 1 h of simulation. The model also contains (i) the simple biosphere model of Sellers et al (1986) as formulated by Xue et al (1991) over the land and the bulk aerodynamic scheme of Miyakoda and Sirutis (1986) over the oceans, (ii) the planetary boundary layer scheme of Mellor and Yamada (1982), and (iii) the gravity wave drag scheme of Kirtman et al (1993).…”

Section: Description Of Nwp Model and Its Performancementioning

confidence: 99%

Performance Evaluation Statistics Applied to Derived Fields of NWP Model Forecasts

Satyamurty¹,

Bittencourt²

1999

Wea. Forecasting

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NWP model skill as obtained from the standard statistics applied to derived atmospheric fields such as thermal advection and moisture convergence is different from that obtained by the same statistics applied to basic model output fields such as temperature or wind components. An analysis with a combination of two simple wave functions shows that the errors in the forecast of the phase of the shortwave component are overwhelmingly more important. For an error of 2Њ longitude in the phase forecast of the shortwave component (wavenumber ϳ20) the correlation coefficient for the derived fields is only 0.7 whereas it is nearly 0.9 for the basic variable fields. The prediction range of useful forecasts in terms of the derived variables decreases drastically in comparison to that obtained with the simple variables. These aspects are demonstrated with the Centro de Previsão de Tempo e Estudos Climáticos-Center for Ocean-Land-Atmosphere studies operational NWP model in two real synoptic cases that are representative of active weather situations in austral winter over the southern half of South America.

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The development and verification of a cloud prediction scheme for the ECMWF model

Cited by 211 publications

References 0 publications

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Sensitivity of a cloud parameterization package in the National Center for Atmospheric Research Community Climate Model

Performance Evaluation Statistics Applied to Derived Fields of NWP Model Forecasts

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