Evaluation of the sensitivity of the weather research and forecasting model to parameterization schemes for regional climates of europe over the period 1990-95
Correlation coefficient
; Ecmwf re-analysis
; Era interims
; Europe
; Grid-spacings
; Land surface models
; Long-wave radiation
; Low correlation
; Mean sea level pressures
; Microphysics
; Model domains
; Model evaluation/performance
; Optimum combination
; Parameterization schemes
; Planetary boundary layers
; Regional climate
; Regional climate models
; Regional model
; Root mean squares
; State variables
; Surface air temperatures
; Surface temperatures
; Weather research and forecasting models
; Atmospheric temperature
; Climate change
; Climate models
; Computer simulation
; Lasers
; Parameterization
; Physics
; Sea level
; Surface measurement
; Weather forecasting
; air temperature
; boundary layer
; climate change
; climate modeling
; climate prediction
; downscaling
; ensemble forecasting
; longwave radiation
; model validation
; parameterization
; precipitation (climatology)
; regional climate
; surface temperature
; weather forecasting
; Europe
英文摘要:
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 byWRF with high correlation coefficients (0.8 < R < 0.95) and biases less than 4°C. 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 day21). Precipitation shows sensitivity to LSMs in summer. No significant bias has been observed in theMSLP modeled byWRF. Correlation coefficients are typically in the range 0.7
Department of Physics, University of Oxford, Oxford, United Kingdom; ICARUS, Department of Geography, National University of Ireland Maynooth, Kildare, Ireland; Department of Experimental Physics, National University of Ireland Maynooth, Kildare, Ireland; Department of Geography, National University of Ireland Maynooth, Kildare, Ireland
Recommended Citation:
Mooney P.A.,Mulligan. F.J.,Fealy R.. Evaluation of the sensitivity of the weather research and forecasting model to parameterization schemes for regional climates of europe over the period 1990-95[J]. Journal of Climate,2013-01-01,26(3)