Parameterization of Convective Precipitation in Mesoscale Numerical Models: A Critical Review

Molinari, John; Dudek, Michael P.

doi:10.1175/1520-0493(1992)120<0326:pocpim>2.0.co;2

Cited by 271 publications

(178 citation statements)

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“…It is well known (e.g., Zhang et al 1994) that the CPS scheme chosen will be at least as important as the microphysics scheme selected. There are several reports published on the sensitivity of WRF to the choice of CPS (Molinari and Dudek 1992;Wang and Seaman 1997;Mercader et al 2010). Rather than repeating their work, we have decided to build on these results by adopting the more successful Kain-Fritsch convective scheme in this study.…”

Section: B Parameterization Schemes-configurationsmentioning

confidence: 99%

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Parameterization Schemes for Regional Climates of Europe over the Period 1990–95

2013

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The Weather Research and Forecasting model (WRF) is used to downscale interim ECMWF Re-Analysis (ERA-Interim) data for the climate over Europe for the period 1990-95 with grid spacing of 0.448 for 12 combinations of physical parameterizations. Two longwave radiation schemes, two land surface models (LSMs), two microphysics schemes, and two planetary boundary layer (PBL) schemes have been investigated while the remaining physics schemes were unchanged. WRF simulations are compared with Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) observations gridded dataset (E-OBS) for surface air temperatures (T2), precipitation, and mean sea level pressure (MSLP) in eight subregions within the model domain to assess the performance of the different parameterizations on widely varying regional climates. This work shows that T2 is modeled well by WRF with high correlation coefficients (0.8 , R , 0.95) and biases less than 48C. T2 shows greatest sensitivity to land surface models, some sensitivity to longwave radiation schemes, and less sensitivity to microphysics and PBL schemes. Precipitation is not well modeled by WRF with low correlation coefficients (0.1 , R , 0.3) and high root-mean-square differences (RMSDs; 8-9 mm day 21 ). Precipitation shows sensitivity to LSMs in summer. No significant bias has been observed in the MSLP modeled by WRF. Correlation coefficients are typically in the range 0.7 , R , 0.8 while RMSDs are in the range 6-10 hPa. MSLP output is sensitive to longwave radiation scheme in summer but is relatively insensitive to either microphysics or the choice of LSM. The optimum combination of parameterizations for all three state variables examined is strongly dependent on subregion and demonstrates the need to carefully select parameterization combinations when attempting to use WRF as a regional climate model.

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Section: B Parameterization Schemes-configurationsmentioning

confidence: 99%

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Parameterization Schemes for Regional Climates of Europe over the Period 1990–95

2013

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“…Explicitly resolving these clouds in decades-long climate simulations is not yet computationally feasible; thus, it is beneficial to parameterize deep convection (e.g., Molinari and Dudek, 1992;Weisman et al, 1997;Warner and Hsu, 2000;Sato et al, 2009;Noda et al, 2010). Deep convective clouds are difficult to parameterize, however, partly because they produce copious ice and precipitation, which interact strongly with storm dynamics.…”

Section: Introductionmentioning

confidence: 99%

Parameterizing deep convection using the assumed probability density function method

et al. 2015

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Abstract. Due to their coarse horizontal resolution, presentday climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

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“…West et al (2007) noted that the NARR precipitation analyses can be associated with spurious grid scale precipitation, which occurs when convection is aliased to the smallest resolved scale of the model due to failures in the convective parametrization scheme to remove instability (Molinari and Dudek, 1992). As both events occur after 2002, the NARR analyses were generated in near-real time, with the use of radar-dominated precipitation analyses (US National Centers for Environmental Prediction stage-IV analysis) to disaggregate the daily gauge-based precipitation analyses into hourly bins (West et al, 2007).…”

Section: Mesoscale Model and Datamentioning

confidence: 99%

The use of potential vorticity inversion to evaluate the effect of precipitation on downstream mesoscale processes

Baxter

Schumacher

Boustead³

2011

Quart J Royal Meteoro Soc

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Parameterization of Convective Precipitation in Mesoscale Numerical Models: A Critical Review

Cited by 271 publications

References 0 publications

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Parameterization Schemes for Regional Climates of Europe over the Period 1990–95

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Parameterization Schemes for Regional Climates of Europe over the Period 1990–95

Parameterizing deep convection using the assumed probability density function method

The use of potential vorticity inversion to evaluate the effect of precipitation on downstream mesoscale processes

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