Influence of Initial Conditions on the WRF–ARW Model QPF Response to Physical Parameterization Changes

Abstract

To assist in optimizing a mixed-physics ensemble for warm season mesoscale convective system rainfall forecasting, the impact of various physical schemes as well as their interactions on rainfall when different initializations were used has been investigated. For this purpose, high-resolution Weather Research and Forecasting (WRF) model simulations of eight International H2O Project events were performed. For each case, three different treatments of convection, three different microphysical schemes, and two different planetary boundary layer (PBL) schemes were used. All cases were initialized with both Local Analyses and Prediction System (LAPS) "hot" start analyses and 40-km Eta Model analyses. To evaluate the impacts of the variation of two different physical schemes and their interaction on the simulated rainfall under the two different initial conditions, the factor separation method was used. The sensitivity to the use of various physical schemes and their interactions was found to be dependent on the initialization dataset. Runs initialized with Eta analyses appeared to be influenced by the use of the Betts-Miller-JanjiÄ ‡ scheme in that model's assimilation system, which tended to reduce the WRF's sensitivity to changes in the microphysical scheme compared with that present when LAPS analyses were used for initialization. In addition, differences in initialized thermodynamics resulted in changes in sensitivity to PBL and convective schemes. With both initialization datasets, the greatest sensitivity to the simulated rain rate was due to changes in the convective scheme. However, for rain volume, substantial sensitivity was present due to changes in both the physical parameterizations and the initial datasets. KeywordsAgronomy, local analyses and prediction system, planetary boundary layer, weather research and forecasting model simulations, atmospheric thermodynamics, boundary layers, computer simulation, mathematical models, parameterization, rain, convective system, data set, ensemble forecasting, mesoscale meteorology, parameterization, rainfall, sensitivity analysis, simulation ABSTRACTTo assist in optimizing a mixed-physics ensemble for warm season mesoscale convective system rainfall forecasting, the impact of various physical schemes as well as their interactions on rainfall when different initializations were used has been investigated. For this purpose, high-resolution Weather Research and Forecasting (WRF) model simulations of eight International H 2 O Project events were performed. For each case, three different treatments of convection, three different microphysical schemes, and two different planetary boundary layer (PBL) schemes were used. All cases were initialized with both Local Analyses and Prediction System (LAPS) "hot" start analyses and 40-km Eta Model analyses. To evaluate the impacts of the variation of two different physical schemes and their interaction on the simulated rainfall under the two different initial conditions, the factor separation method was used. The sensiti...

Comparison of the Diurnal Precipitation Cycle in Convection-Resolving and Non-Convection-Resolving Mesoscale Models

“…One such hot start method is the Local Analysis and Prediction System (LAPS; Jian et al 2003). Jankov et al (2007) showed that a 12-km gridspacing version of the WRF model initialized with LAPS was able to spin up the grid-resolved component of precipitation much faster than the same version using the same 40-km initialization data used in the present study. Further investigation is needed to examine whether the use of hot start initialization would result in an improvement in the location and magnitude of the propagating rainfall axis for a large number of cases during the first diurnal cycle.…”

Prediction of Convective Morphology in Near-Cloud-Permitting WRF Model Simulations

“…Because forecasts are also sensitive to initial and lateral boundary conditions (Jankov et al 2007;Weisman et al 2008), an additional test was performed for each case study where in the control run, GFS data were used for initial and lateral boundary conditions instead of NAM.…”

“…Because forecasts are sensitive to initial and lateral boundary conditions (Jankov et al 2007;Weisman et al 2008), one test was performed using GFS data instead of NAM for initialization and lateral boundary conditions. The Thompson et al (2008) microphysics scheme was used for direct comparison to the original simulation with NAM initial conditions.…”

“…Most past efforts toward improving forecasting of convection have focused on quantitative precipitation forecasting (QPF) (Olson et al 1995;Gallus 1999;Alhamed et al 2002;Gallus and Bresch 2006), finding that in models with grid spacings coarse enough to require use of a convective scheme, QPF is profoundly sensitive to the convective scheme used Jankov et al 2007). noted that convectionallowing models (e.g.…”

Quantification of Cloud Microphysical Parameterization Uncertainty Using Radar Reflectivity

“…Many studies have investigated the effect of microphysical parameterization choices on cloud-resolving model (CRM) behavior, however, most are limited to the consideration of relatively few variations in parameterization. One such approach has been to compare the behavior of disparate schemes within idealized frameworks (Stensrud et al 2000;Thompson et al 2004;Morrison and Grabowski 2007;Morrison et al 2009;Li et al 2009) or real cases (McCumber et al 1991;Jankov et al 2007;Clark et al 2008;Gallus and Pfeifer 2008). Another approach has been to perform sensitivity tests of a single parameter within a single microphysics scheme (Thompson et al 2004;Milbrandt and Yau 2005).…”