On the Importance of a Consistent Treatment of Prognostic Moisture Variables between Convective and Microphysical Parameterizations
Analysis of WRF Model output from experiments using two double-moment microphysics schemes is carried out to demonstrate that there can be an inconsistency between the predicted mass and number concentrations when a single-moment convective parameterization is used together with a double-moment micr...
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Veröffentlicht in: | Monthly weather review 2018-05, Vol.146 (5), p.1527-1548 |
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description | Analysis of WRF Model output from experiments using two double-moment microphysics schemes is carried out to demonstrate that there can be an inconsistency between the predicted mass and number concentrations when a single-moment convective parameterization is used together with a double-moment microphysics scheme. This inconsistency may arise because the grid-scale and subgrid-scale cloud schemes generally apply different levels of complexity to the parameterized microphysical processes. In particular, when a multimoment formulation is used in the microphysics scheme and other physical parameterizations modify only the mass-related moment while the values of the second (or higher) moment for individual hydrometeors remain unchanged, an unintended modification of the particle size distribution occurs. Simulated radar reflectivity is shown to be a valuable tool in diagnosing this inconsistency. In addition, potential ways to minimize the problem are explored by including number concentration calculations in the cumulus parameterization that are consistent with the assumptions of hydrometeor sizes in the microphysics parameterization. The results of this study indicate that it is physically preferable to unify microphysical assumptions between the grid-resolved and subgrid cloud parameterization schemes in weather and climate simulation models. |
doi_str_mv | 10.1175/MWR-D-17-0305.1 |
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This inconsistency may arise because the grid-scale and subgrid-scale cloud schemes generally apply different levels of complexity to the parameterized microphysical processes. In particular, when a multimoment formulation is used in the microphysics scheme and other physical parameterizations modify only the mass-related moment while the values of the second (or higher) moment for individual hydrometeors remain unchanged, an unintended modification of the particle size distribution occurs. Simulated radar reflectivity is shown to be a valuable tool in diagnosing this inconsistency. In addition, potential ways to minimize the problem are explored by including number concentration calculations in the cumulus parameterization that are consistent with the assumptions of hydrometeor sizes in the microphysics parameterization. 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This inconsistency may arise because the grid-scale and subgrid-scale cloud schemes generally apply different levels of complexity to the parameterized microphysical processes. In particular, when a multimoment formulation is used in the microphysics scheme and other physical parameterizations modify only the mass-related moment while the values of the second (or higher) moment for individual hydrometeors remain unchanged, an unintended modification of the particle size distribution occurs. Simulated radar reflectivity is shown to be a valuable tool in diagnosing this inconsistency. In addition, potential ways to minimize the problem are explored by including number concentration calculations in the cumulus parameterization that are consistent with the assumptions of hydrometeor sizes in the microphysics parameterization. The results of this study indicate that it is physically preferable to unify microphysical assumptions between the grid-resolved and subgrid cloud parameterization schemes in weather and climate simulation models.</description><subject>Climate change</subject><subject>Climate models</subject><subject>Cloud parameterization</subject><subject>Clouds</subject><subject>Computer simulation</subject><subject>Environmental science</subject><subject>Hydrometeors</subject><subject>Ice</subject><subject>Laboratories</subject><subject>Microphysics</subject><subject>Parameterization</subject><subject>Particle size</subject><subject>Particle size distribution</subject><subject>Precipitation</subject><subject>Radar</subject><subject>Radar reflectivity</subject><subject>Reflectance</subject><subject>Sedimentation & deposition</subject><subject>Size distribution</subject><subject>Weather</subject><subject>Weather 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This inconsistency may arise because the grid-scale and subgrid-scale cloud schemes generally apply different levels of complexity to the parameterized microphysical processes. In particular, when a multimoment formulation is used in the microphysics scheme and other physical parameterizations modify only the mass-related moment while the values of the second (or higher) moment for individual hydrometeors remain unchanged, an unintended modification of the particle size distribution occurs. Simulated radar reflectivity is shown to be a valuable tool in diagnosing this inconsistency. In addition, potential ways to minimize the problem are explored by including number concentration calculations in the cumulus parameterization that are consistent with the assumptions of hydrometeor sizes in the microphysics parameterization. The results of this study indicate that it is physically preferable to unify microphysical assumptions between the grid-resolved and subgrid cloud parameterization schemes in weather and climate simulation models.</abstract><cop>Washington</cop><pub>American Meteorological Society</pub><doi>10.1175/MWR-D-17-0305.1</doi><tpages>22</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Climate change Climate models Cloud parameterization Clouds Computer simulation Environmental science Hydrometeors Ice Laboratories Microphysics Parameterization Particle size Particle size distribution Precipitation Radar Radar reflectivity Reflectance Sedimentation & deposition Size distribution Weather Weather forecasting |
title | On the Importance of a Consistent Treatment of Prognostic Moisture Variables between Convective and Microphysical Parameterizations |
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