Evaluation of a WRF dynamical downscaling simulation over California

Abstract

This paper presents results from a 40 year Weather Research and Forecasting (WRF) based dynamical downscaling experiment performed at 12 km horizontal grid spacing, centered on the state of California, and forced by a 1 • × 1.25 • finite-volume current-climate Community Climate System Model ver. 3 (CCSM3) simulation. In-depth comparisons between modeled and observed regional-average precipitation, 2 m temperature, and snowpack are performed. The regional model reproduces the spatial distribution of precipitation quite well, but substantially overestimates rainfall along windward slopes. This is due to strong overprediction of precipitation intensity; precipitation frequency is actually underpredicted by the model. Moisture fluxes impinging on the coast seem to be well-represented over California, implying that precipitation bias is caused by processes internal to WRF. Positive-definite moisture advection and use of the Grell cumulus parameterization result in some decrease in precipitation bias, but other sources are needed to explain the full bias magnitude. Surface temperature is well simulated in all seasons except summer, when overly-dry soil moisture results in a several degree warm bias in both CCSM3 and WRF. Additionally, coastal temperatures appear to be too warm due to a coastal sea surface temperature bias inherited from CCSM3. Modeled snowfall/snowmelt agrees quite well with observations, but snow water equivalent is found to be much too low due to monthly reinitialization of all regional model fields from CCSM3 values.

Identifying extreme hottest days from large scale upper air data: a pilot scheme to find California Central Valley summertime maximum surface temperatures

“…She compared the daytime maximum WRF SATs against California Irrigation Management Information System (CIMIS) station data and found typical errors of 3-4 K. Valade (2009) also showed that the nighttime minimum SATs are much better simulated than the maximum SATs by WRF, consistent with data in KK2007a and KK2007b where the daily mean values are more accurate than the maximum temperature values. Caldwell et al (2009) downscale NCAR CCSM finite volume (1 9 1.25°) simulations and remark that maximum temperature bias is smaller than minimum temperature while stating that daily average summer SATs are 'several degrees' K higher than observed. Soong et al (2006) compare WRF and MM5 (the Pennsylvania State University/NCAR mesoscale model version 5; Grell et al 1994) simulations during an ozone pollution event: 31 July to 2 August, 2000.…”

WRF simulation of downslope wind events in coastal Santa Barbara County

“…Caldwell et al, 2009;Chin et al, 2010;Smith et al, 2010;Dulière et al, 2011). Since the focus of this study is on dry conditions, we tested two additional configurations.…”

Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models

“…This lack of convergence is problematic because climate change impact studies often require climatic information at the small scales characteristic of, for example, a single watershed (Kanamitsu and Kanamaru, 2007;Caldwell et al, 2009). High-resolution climate model simulations are a seemingly obvious way to provide climatic information at these scales, but non-convergent behavior (e.g., extreme precipitation that systematically increases with increasing resolution) complicates interpretation of climate change studies (Li et al, 2011a,b).…”