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Norrköping, Sweden

Berg P.,Institute for Meteorology and Climate Research IMK TRO | Berg P.,Rossby Center | Wagner S.,Institute for Meteorology and Climate Research IMK IFU | Kunstmann H.,Institute for Meteorology and Climate Research IMK IFU | Schadler G.,Institute for Meteorology and Climate Research IMK TRO
Climate Dynamics | Year: 2013

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i. e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution. © 2012 Springer-Verlag.

Wagner S.,Institute for Meteorology and Climate Research IMK IFU | Berg P.,Institute for Meteorology and Climate Research IMK TRO | Berg P.,Rossby Center | Schadler G.,Institute for Meteorology and Climate Research IMK TRO | Kunstmann H.,Institute for Meteorology and Climate Research IMK IFU
Climate Dynamics | Year: 2013

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0. 8 and 1. 3 K with an average of 1. 1 K. For mean annual precipitation the climate change signal varies in the range of -2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. © 2012 The Author(s).

Krueger O.,University of Edinburgh | Krueger O.,Helmholtz Center Geesthacht | Feser F.,Helmholtz Center Geesthacht | Barring L.,Rossby Center | And 4 more authors.
Climate Dynamics | Year: 2014

The main subject of this article is to comment on the issue of storminess trends derived from the twentieth century reanalysis (20CR) and from observations in the North Atlantic region written about in Wang et al. (Clim Dyn 40(11-12):2775-2800, 2012). The statement that the 20CR estimates would be consistent with storminess derived from pressure-based proxies does not hold for the time prior to 1950. © 2013 Springer-Verlag Berlin Heidelberg.

Kendon E.J.,UK Met Office | Jones R.G.,University of Reading | Kjellstrom E.,Rossby Center | Murphy J.M.,UK Met Office
Journal of Climate | Year: 2010

Multimodel ensembles, whereby different global climate models (GCMs) and regional climate models (RCMs) are combined, have been widely used to explore uncertainties in regional climate projections. In this study, the extent to which information can be enhanced from sparsely filled GCM-RCM ensemble matrices and the way in which simulations should be prioritized to sample uncertainties most effectively are examined. A simple scaling technique, whereby the local climate response in an RCM is predicted from the large-scale change in the GCM, is found to often show skill in estimating local changes for missing GCM-RCM combinations. In particular, scaling shows skill for precipitation indices (including mean, variance, and extremes) across Europe in winter and mean and extreme temperature in summer and winter, except for hot extremes over central/northern Europe in summer. However, internal variability significantly impacts the ability to determine scaling skill for precipitation indices, with a three-member ensemble found to be insufficient for identifying robust local scaling relationships in many cases. This study suggests that, given limited computer resources, ensembles should be designed to prioritize the sampling of GCM uncertainty, using a reduced set of RCMs. Exceptions are found over the Alps and northeasternEuropeinwinter and central Europeinsummer, where sampling multiple RCMs maybe equally or more important for capturing uncertainty in local temperature or precipitation change. This reflects the significant role of local processes in these regions. Also, to determine the ensemble strategy in some cases, notably precipitation extremes in summer, better sampling of internal variability is needed. © 2010 American Meteorological Society.

Nik V.M.,Chalmers University of Technology | Sasic Kalagasidis A.,Chalmers University of Technology | Kjellstrom E.,Rossby Center
Building and Environment | Year: 2012

Most of the last 20 years in Sweden have been mild and wet compared to the 1961-1990 climate reference period. After a few relatively cold years in the mid-1980s, practically all years have been warmer than the preceding 30 years average. During the indicated period, an increase of moisture-related problems (mould growth) was observed in ventilated attics, a moisture sensitive building part.This work investigates hygrothermal performance of ventilated attics in respect to possible climate change. Hygrothermal simulations of attics were performed numerically in Matlab. Four attic constructions are investigated - a conventional attic and three alternative constructions suggested by practitioners. Simulations were done for the period of 1961-2100 using the weather data of RCA3 climate model. Effects of three different emissions scenarios are considered. Hygrothermal conditions in the attic are assessed using a mould growth model. Based on the results the highest risk of mould growth was found on the north roof of the attic in Gothenburg, Sweden. Results point to increment of the moisture problems in attics in future. Different emissions scenarios do not influence the risk of mould growth inside the attic due to compensating changes in different variables. Assessing the future performance of the four attics shows that the safe solution is to ventilate the attic mechanically, though this solution inevitably requires extra use of electrical energy for running the fan. Insulating roofs of the attic can decrease the condensation on roofs, but it cannot decrease the risk of mould growth considerably, on the wooden roof underlay. © 2012 Elsevier Ltd.

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