Regional climate models add value to global model data, A Review and Selected Examples

By F. Feser, B. Rockel, Hans von Storch, Joerg Winterfeldt, M. Zahn. 2011

498 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/5dd48f9e3f06607bf7b0f0cd8266a3517ad140db

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. C. Castro
2. Y. Tramblay
3. P. Lucas‐Picher
4. Peter Berg
5. D. Lüthi
6. C. Caillaud
7. J. Schmidli
8. Peter Troch

In Global and Planetary Change

1. C. Castro
2. Y. Tramblay
3. P. Lucas‐Picher
4. Peter Berg
5. D. Lüthi
6. C. Caillaud
7. J. Schmidli
8. Peter Troch

Citations in the corpus

• Dynamical downscaling of CMIP5 global circulation models over CORDEX-Africa with COSMO-CLM: evaluation over the present climate and analysis of the added value (2015, background): “According to Feser et al. (2011) the added variability occurs mainly on spatial scales that are best resolved by the regional model.”
• A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges (2015, methodology): “So far, spectral nudging has mainly been used for LSM hindcast simulations [Feser et al., 2011], where added value was found for many meteorological variables such as near-surface temperature or precipitation [e.g., Feser, 2006; Meinke et al., 2006] and for phenomena such as tropical cyclones…”
• Convection‐permitting modeling with regional climate models: Latest developments and next steps (2021, background): “Thus, related regional meteorological phenomena are simulated more realistically (Feser et al., 2011; Lucas-Picher et al., 2017; Rummukainen, 2016).”
• Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes (2016, background): “Even though RCMs can provide added value (Fowler et al., 2007; Feser et al., 2011; Di Luca et al., 2013; Kotlarski, 2014), systematic errors in the model output still exist (Mearns et al., 2012; Sillmann et al., 2013).”
• Robust bias-correction of precipitation extremes using a novel hybrid empirical quantile-mapping method (2021, background): “In dynamical downscaling, a regional climate model (RCM) is forced with a GCM, resulting in finer-scale output in which regional climate processes, topography, and orography are incorporated (Feser et al. 2011).”