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

Identifieur interne : 005727 ( Main/Exploration ); précédent : 005726; suivant : 005728

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

Auteurs : Charmaine N. Franklin [Australie] ; Christian Jakob [Australie] ; Martin Dix ; Alain Protat [France] ; Greg Roff

Source :

RBID : ISTEX:A41773217E189F0BFC786EB37132CC8F65F969A8

Descripteurs français

English descriptors

Abstract

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. Copyright © 2011 Royal Meteorological Society

Url:
DOI: 10.1002/qj.954


Affiliations:


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<term>Active monsoon phase</term>
<term>Active period</term>
<term>Active phase</term>
<term>Advective tendencies</term>
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<term>Average updraft mass</term>
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<term>Case study</term>
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<term>Cloud fraction</term>
<term>Cloud fractions</term>
<term>Cloud layers</term>
<term>Cloud properties</term>
<term>Cloud scheme</term>
<term>Cloud schemes</term>
<term>Cloudiness</term>
<term>Condensate</term>
<term>Congestus convection</term>
<term>Convection</term>
<term>Convection scheme</term>
<term>Convective</term>
<term>Convective clouds</term>
<term>Convective plumes</term>
<term>Copyright</term>
<term>Dataset</term>
<term>Deep convection</term>
<term>Deep convection scheme</term>
<term>Depositional growth</term>
<term>Detrainment</term>
<term>Diagnostic</term>
<term>Diagnostic cloud scheme</term>
<term>Diagnostic cloud scheme analysis</term>
<term>Diagnostic scheme</term>
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<term>Diagnostic scheme simulation</term>
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<term>Early morning</term>
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<term>Evaporation</term>
<term>Fall speed</term>
<term>Fall speeds</term>
<term>Fraction</term>
<term>Grid</term>
<term>Hadley centre</term>
<term>High cloud</term>
<term>Humidity</term>
<term>Humidity bias</term>
<term>Ice cloud</term>
<term>Increment</term>
<term>Iwcs</term>
<term>January</term>
<term>Julian days</term>
<term>Large particles</term>
<term>Larger concentrations</term>
<term>Larger mass</term>
<term>Many clouds</term>
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<term>Metum</term>
<term>Microphysical</term>
<term>Microphysical processes</term>
<term>Model results</term>
<term>Model simulations</term>
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<term>Moisture increments</term>
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<term>Monsoon period</term>
<term>Monsoon phase</term>
<term>Monsoon phases</term>
<term>More occurrences</term>
<term>Observations show</term>
<term>Other studies</term>
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<term>Prognostic cloud scheme</term>
<term>Prognostic scheme</term>
<term>Prognostic scheme simulation</term>
<term>Prognostic simulation</term>
<term>Radiative</term>
<term>Relative error</term>
<term>Relative humidities</term>
<term>Relative humidity</term>
<term>Relative humidity bias</term>
<term>Relative humidity errors</term>
<term>Retrieval</term>
<term>Scheme</term>
<term>Simulation</term>
<term>Single column model simulations</term>
<term>Single-column model</term>
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<term>Solid line</term>
<term>Strong relationship</term>
<term>Total cloud</term>
<term>Tropical cloud systems</term>
<term>Tropical convection</term>
<term>Unified model</term>
<term>United Kingdom</term>
<term>Updraft</term>
<term>Upper levels</term>
<term>Upper troposphere</term>
<term>Uxes</term>
<term>Validation data</term>
<term>Vapour</term>
<term>Variational</term>
<term>Variational analysis</term>
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<term>Warm pool</term>
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<term>Average mass</term>
<term>Average updraft mass</term>
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<term>Case study</term>
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<term>Cirrus cloud</term>
<term>Cloud</term>
<term>Cloud fraction</term>
<term>Cloud fractions</term>
<term>Cloud layers</term>
<term>Cloud properties</term>
<term>Cloud scheme</term>
<term>Cloud schemes</term>
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<term>Congestus convection</term>
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<term>Humidity</term>
<term>Humidity bias</term>
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<term>Julian days</term>
<term>Large particles</term>
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<term>Microphysical processes</term>
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<term>Model simulations</term>
<term>Model versions</term>
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<term>Moisture increments</term>
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<term>Monsoon phases</term>
<term>More occurrences</term>
<term>Observations show</term>
<term>Other studies</term>
<term>Parametrizations</term>
<term>Petch</term>
<term>Physical parametrizations</term>
<term>Precipitation</term>
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<term>Prognostic cloud scheme</term>
<term>Prognostic scheme</term>
<term>Prognostic scheme simulation</term>
<term>Prognostic simulation</term>
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<term>Relative humidities</term>
<term>Relative humidity</term>
<term>Relative humidity bias</term>
<term>Relative humidity errors</term>
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<term>Scheme</term>
<term>Simulation</term>
<term>Single column model simulations</term>
<term>Smith scheme</term>
<term>Solid line</term>
<term>Strong relationship</term>
<term>Total cloud</term>
<term>Tropical cloud systems</term>
<term>Tropical convection</term>
<term>Updraft</term>
<term>Upper levels</term>
<term>Upper troposphere</term>
<term>Uxes</term>
<term>Validation data</term>
<term>Vapour</term>
<term>Variational</term>
<term>Variational analysis</term>
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<term>Water content</term>
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<front>
<div type="abstract" xml:lang="en">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. Copyright © 2011 Royal Meteorological Society</div>
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