Evaluation of a WRF dynamical downscaling simulation over California
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- Caldwell, P., Chin, HN.S., Bader, D.C. et al. Climatic Change (2009) 95: 499. doi:10.1007/s10584-009-9583-5
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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.