Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model

By U. Heikkilä, A. Sandvik, A. Sorteberg. 2011

206 citations recorded by the source corpus.

Results from a first-time employment of the WRF regional climate model to climatological simulations in Europe are presented. The ERA-40 reanalysis (resolution 1°) has been downscaled to a horizontal resolution of 30 and 10 km for the period of 1961–1990. This model setup includes the whole North Atlantic in the 30 km domain and spectral nudging is used to keep the large scales consistent with the driving ERA-40 reanalysis. The model results are compared against an extensive observational network of surface variables in complex terrain in Norway. The comparison shows that the WRF model is able to add significant detail to the representation of precipitation and 2-m temperature of the ERA-40 reanalysis. Especially the geographical distribution, wet day frequency and extreme values of precipitation are highly improved due to the better representation of the orography. Refining the resolution from 30 to 10 km further increases the skill of the model, especially in case of precipitation. Our results indicate that the use of 10-km resolution is advantageous for producing regional future climate projections. Use of a large domain and spectral nudging seems to be useful in reproducing the extreme precipitation events due to the better resolved synoptic scale features over the North Atlantic, and also helps to reduce the large regional temperature biases over Norway. This study presents a high-resolution, high-quality climatological data set useful for reference climate impact studies.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/6d80f4437ed82b7c5c5331db79a23f8120149017

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Citations in the corpus

An Improved Dynamical Downscaling Method with GCM Bias Corrections and Its Validation with 30 Years of Climate Simulations (2012, methodology): “(4) only adjusted the climatological mean states of CAM simulations, which is the same as the bias correction method used by Holland et al. (2010).”
Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques (2014, result): “Figure 4 illustrates the ability of both statistical (Ghosh, 2010) and dynamical (Heikkilä et al., 2010) downscaling to provide precise insights compared to the original global model results.”
Green and cool roofs to mitigate urban heat island effects in the Chicago metropolitan area: evaluation with a regional climate model (2016, methodology): “…employed a non-hydrostatic, compressible WRF regional climate model (version 3.4.1; Skamarock et al 2005)which is used to simulate climate at multiple spatial resolutions (mesoscale at ∼50 km to local scales at∼50m) (Heikkilä et al2011, SharmaandHuang2012, Talbot et al 2012, Conry et al 2015).”
A review of statistical methods to analyze extreme precipitation and temperature events in the Mediterranean region (2019, background): “Moreover, Coelho et al. (2007) and Heikkila et al. (2011) claim that 95% threshold represents an acceptable balance between a high-enough cutoff value to define extreme events and a sufficient quantity of exceedances to represent those events.”