The Rossby Centre Regional Climate model RCA3: model description and performance

Abstract

This paper describes the third full release of the Rossby Centre Regional Climate model (RCA3), with an emphasis on changes compared to earlier versions, in particular the introduction of a new tiled land-surface scheme. The model performance over Europe when driven at the boundaries by ERA40 reanalysis is discussed and systematic biases identified. This discussion is performed for key near-surface variables, such as temperature, precipitation, wind speed and snow amounts at both seasonal and daily timescales. An analysis of simulated clouds and surface turbulent and radiation fluxes is also made, to understand the causes of the identified biases. RCA3 shows equally good, or better, correspondence to observations than previous model versions at both analysed timescales. The primary model bias relates to an underestimate of the diurnal surface temperature range over Northern Europe, which maximizes in summer. This error is mainly linked to an overestimate of soil heat flux. It is shown that the introduction of an organic soil component reduces the error significantly. During the summer season, precipitation and surface evaporation are both overestimated over Northern Europe, whereas for most other regions and seasons precipitation and surface turbulent fluxes are well simulated.

Spatial variability in the trends in extreme storm surges and weekly-scale high water levels in the eastern Baltic Sea

“…1a). The model run for May 1961-May 2005, the data from which are used in our analysis, was forced with a meteorological data set with a horizontal resolution of 22 km derived from the ERA-40 reanalysis (Samuelsson et al, 2011) and was coupled to a sea ice model. The output of the model replicates both time series and statistics of water levels generally well.…”

Making energy simulation easier for future climate – Synthesizing typical and extreme weather data sets out of regional climate models (RCMs)

“…The weather data sets which are used in this work were generated by two versions of the Rossby Centre regional climate model: RCA3 [11] and RCA4 [80]. Weather data for Stockholm were dynamically downscaled by RCA3 with the spatial resolution of 50 km and for Geneva by RCA4 with 12.5 km resolution.…”

“…the considered season), regions and considered phenomena [8,9]. Dynamic downscaling of GCMs by means of regional climate models (RCMs) has the advantage of generating physically consistent data sets across different variables [10,11]. RCMs provide weather data with suitable temporal (down to 15 min) and spatial resolutions (down to 2.5 km 2 ) for direct use in building and energy simulations (e.g.…”

Separation of the Baltic Sea water level into daily and multi-weekly components

“…Its horizontal and vertical resolutions are 2 Â 2 nautical miles (about 3.7 km) and 3-12 m, respectively. The model run for May 1961-May 2005 is coupled to a sea ice model and uses boundary information in the northern Kattegat and a meteorological data set with a horizontal resolution of 22 km produced from the ERA-40 re-analysis (Samuelsson et al, 2011). Generally the model represents well both the time series and statistics of water levels but shows a certain mismatch for storm surges in the western Baltic Sea (Meier et al, 2004).…”