The Impact of Different Physical Parameterizations and Their Interactions on Cold Season QPF in the American River Basin

Abstract

The most significant precipitation events in California occur during the winter and are often related to synoptic-scale storms from the Pacific Ocean. Because of the terrain characteristics and the fact that the urban and infrastructural expansion is concentrated in lower elevation areas of the California Central Valley, a high risk of flooding is usually associated with these events. In the present study, the area of interest was the American River basin (ARB). The main focus of the present study was to investigate methods for Quantitative Precipitation Forecast (QPF) improvement by estimating the impact that various microphysical schemes, planetary boundary layer (PBL) schemes, and initialization methods have on cold season precipitation, primarily orographically induced. For this purpose, 3-km grid spacing Weather Research and Forecasting (WRF) model simulations of four Hydrometeorological Test bed (HMT) events were used. For each event, four different microphysical schemes and two different PBL schemes were used. All runs were initialized with both a diabatic Local Analysis and Prediction System (LAPS) "hot" start and 40-km eta analyses.To quantify the impact of physical schemes, their interactions, and initial conditions upon simulated rain volume, the factor separation methodology was used. The results showed that simulated rain volume was particularly affected by changes in microphysical schemes for both initializations. When the initialization was changed from the LAPS to the eta analysis, the change in the PBL scheme and corresponding synergistic terms (which corresponded to the interactions between different microphysical and PBL schemes) resulted in a statistically significant impact on rain volume. In addition, by combining model runs based on the knowledge about their impact on simulated rain volume obtained through the factor separation methodology, the bias in simulated rain volume was reduced.

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

“…In published literature, one can find an extensive list of different parameterization schemes depicting the same physical process, and several studies were conducted aiming to investigate the model performance on the simulation of meteorological variables under different physical parameterization schemes (Awan et al, 2011;Chigullapalli and Mölders, 2008;Gallus and Bresch, 2006;Gilliam and Pleim, 2010;Gilliam et al, 2007;Hutchinson et al, 2005;Jankov et al, 2005Jankov et al, , 2007Krieger et al, 2009). Challa et al (2009) performed a simulation study of mesoscale coastal circulations in Mississippi Gulf coast with the WRF model, concluding that the YSU scheme shows improvement over MYJ scheme in the simulation of internal boundary layer characteristics and the overall performance of predicted mean variables.…”

Evaluating the Effect of Physics Schemes in WRF Simulations of Summer Rainfall in North West Iran

“…The greatest variability in forecasts was found to come from changes in the choice of convective scheme, while notable impacts also occurred by changes in the microphysics and PBL schemes. On the other hand [21], 3 km resolution WRF model was simulated with four different microphysics schemes and two different PBL schemes. The results showed that simulated rain volume was particularly affected by changes in microphysics schemes for both initializations.…”

NOAA's Rapid Response to the Howard A. Hanson Dam Flood Risk Management Crisis

“…The selectable physics packages used in the HMT model include the Thompson microphysics scheme (Thompson et al 2004) and the nonlocal mixing Yonsei University (YSU) planetary boundary layer scheme (Noh et al 2003). These schemes were chosen based on 5 yr of experience gained in running the ARW-WRF over the western United States for HMT (Jankov et al 2007(Jankov et al , 2009(Jankov et al , 2011Yuan et al 2008Yuan et al , 2009). This experience allowed for rapid extension of the HMT model to cover the Pacific Northwest and for the water vapor flux tool to be tested in a new environment.…”