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Performance of the Rossby Centre regional atmospheric model in Southern Sweden: comparison of simulated and observed precipitation
Authors:C Achberger  M-L Linderson  D Chen
Institution:(1) Earth Sciences Centre, Göteborg University, Sweden, SE;(2) Department of Physical Geography and Ecosystems Analysis, Lund University, Sweden, SE;(3) National Climate Center, China Meteorological Administration, China, CN
Abstract:Summary Two climate model simulations made with the Rossby Centre regional Atmospheric model version 1 (RCA1) are evaluated for the precipitation climate in Scania, southernmost Sweden. These simulations are driven by the HadCM2 and the ECHAM4/OPYC3 global circulation models (GCMs) for 10 years. Output from the global and the regional simulations are compared with an observational data set, constructed from a dense precipitation gauge network in Scania. Area-averaged time series corresponding to the size and location of the RCA1 grid points in Scania have been created (the Scanian Data Set). This data set was compared to a commonly used gridded surface climatology provided by the Climatic Research Unit (CRU). Relatively large differences were found, mainly due to the fact that the CRU-climatology uses fewer stations and lacks a correction for rain-gauge under-catch. This underlines the importance of the data set chosen for model evaluations. The validation is carried out at a large scale including the whole area of Scania and at the finest resolution of RCA1 (the grid point level). When integrated over the whole area of Scania, RCA1 improves the shape of the annual precipitation cycle and the inter-annual variability compared to output from the GCMs. The RCA1 control climate is generally too wet compared to the observations. At the grid point level, RCA1 improves the simulation of the variability compared to the GCMs. There is a strong positive correlation between precipitation and altitude in all seasons in the observations. This relationship is, however, much weaker and even reversed in the RCA1 simulations. Analysis of the dense rain gauge network reveals features of spatial variability at around 20–35thinspkm in the area and indicates that a finer resolution is needed if the spatial variability in the area is to be better captured by RCA1.
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