Rossby Center

Norrköping, Sweden

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Norrköping, Sweden
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Linders V.,Linköping University | Kupiainen M.,Rossby Center | Nordstrom J.,Linköping University
Journal of Computational Physics | Year: 2017

We present a procedure for constructing Summation-by-Parts operators with minimal dispersion error both near and far from numerical interfaces. Examples of such operators are constructed and compared with a higher order non-optimised Summation-by-Parts operator. Experiments show that the optimised operators are superior for wave propagation and turbulent flows involving large wavenumbers, long solution times and large ranges of resolution scales. © 2017 Elsevier Inc.


Pryor S.C.,Indiana University Bloomington | Pryor S.C.,Technical University of Denmark | Barthelmie R.J.,Indiana University Bloomington | Barthelmie R.J.,Technical University of Denmark | And 4 more authors.
Climate Dynamics | Year: 2012

Dynamical downscaling of ECHAM5 using HIRHAM5 and RCA3 for a northern European domain focused on Scandinavia indicates sustained extreme wind speeds with long recurrence intervals (50 years) and intense winds are not likely to evolve out of the historical envelope of variability until the end of C21st. Even then, significant changes are indicated only in the SW of the domain and across the central Baltic Sea where there is some evidence for relatively small magnitude increases in the 50 year return period wind speed (of up to 15%). There are marked differences in results based on the two Regional Climate Models. Additionally, internal (inherent) variability and initial conditions exert a strong impact on projected wind climates throughout the twenty-first century. Simulations of wind gusts by one of the RCMs (RCA3) indicate some evidence for increased magnitudes (of up to +10%) in the southwest of the domain and across the central Baltic Sea by the end of the current century. As in prior downscaling of ECHAM4, dynamical downscaling of ECHAM5 indicates a tendency towards increased energy density and thus wind power generation potential over the course of the C21st. However, caution should be used in interpreting this inference given the high degree of wind climate projection spread that derives from the specific AOGCM and RCM used in the downscaling. © 2010 Springer-Verlag.


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.


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).


Samuelsson P.,Rossby Center | Jones C.G.,Rossby Center | Willen U.,Rossby Center | Ullerstig A.,Rossby Center | And 6 more authors.
Tellus, Series A: Dynamic Meteorology and Oceanography | Year: 2011

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. ©2010 The Authors Tellus A©2010 International Meteorological Institute in Stockholm.


Pryor S.C.,Indiana University | Nikulin G.,Rossby Center | Jones C.,Rossby Center
Journal of Geophysical Research: Atmospheres | Year: 2012

Wind speeds for a nominal height of 10 m and from the lowest model level (∼70 m above ground level) from the Rossby Center regional climate model (RCM) (RCA3) run at four resolutions between approximately 50 × 50 km and 6 × 6 km are analyzed to assess the effect of model resolution on wind climates. The influence of model resolution in this topographically simple subdomain of northern Europe is more profound in the wind extremes than in the central tendency. The domain-averaged mean wind speed at 10 m increases by 5% as the resolution increases from 50 to 6.25 km, while the 50 year return period wind speed and wind gust at this height increase by over 10% and 24%, respectively. Larger changes are observed in these wind speed metrics at the lowest model level as model resolution increases (∼+10% in the mean and ∼+20% in the 50 year return period wind speed). These differences are of similar magnitude to the climate change signal in extreme wind events derived in prior research and may have implications for climate change risk and vulnerability analyses. Output from the lowest model level indicates some evidence for increased variability at synoptic and meso-α time scales with increased model resolution, but the effect is nonlinear. Furthermore, analysis of power spectra of grid cell average and tile fraction wind speeds at 10 m does not support the assertion that increased model resolution increases model skill at synoptic and meso-α time scales relative to in situ observations. Copyright 2012 by the American Geophysical Union.


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.


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

Global warming and its effects on climate are of great concern. Climate change can affect buildings in different ways. Increased structural loads from wind and water, changes in energy need and decreased moisture durability of materials are some examples of the consequences. Future climate conditions are simulated by global climate models (GCMs). Downscaling by regional climate models (RCMs) provides weather data with suitable temporal and spatial resolutions for direct use in building simulations.There are two major challenges when the future climate data are used in building simulations. The first is to handle and analyse the huge amount of data. The second challenge is to assess the uncertainties in building simulations as a consequence of uncertainties in the future climate data. In this paper two statistical methods, which have been adopted from climatology, are introduced. Applications of the methods are illustrated by looking into two uncertainty factors of the future climate; operating RCMs at different spatial resolutions and with boundary data from different GCMs. The Ferro hypothesis is introduced as a nonparametric method for comparing data at different spatial resolutions. The method is quick and subtle enough to make the comparison. The parametric method of decomposition of variabilities is described and its application in data assessment is shown by considering RCM data forced by different GCMs. The method enables to study data and its variations in different time scales. It provides a useful summary about data and its variations which makes the comparison between several data sets easier. © 2012 Elsevier Ltd.


Nikulin G.,Rossby Center | Kjellstrom E.,Rossby Center | Hansson U.,Rossby Center | Strandberg G.,Rossby Center | Ullerstig A.,Rossby Center
Tellus, Series A: Dynamic Meteorology and Oceanography | Year: 2011

Temperature, precipitation and wind extremes over Europe are examined in an ensemble of RCA3 regional climate model simulations driven by six different global climate models (ECHAM5, CCSM3, HadCM3, CNRM, BCM and IPSL) under the SRES A1B emission scenario. The extremes are expressed in terms of the 20-yr return values of annual temperature and wind extremes and seasonal precipitation extremes.The ensemble shows reduction of recurrence time of warm extremes from 20 yr in 1961-1990 (CTL) to 1-2 yr over southern Europe and to 5 yr over Scandinavia in 2071-2100 (SCN) while cold extremes, defined for CTL, almost disappear in the future. The recurrence time of intense precipitation reduces from 20 yr in CTL to 6-10 yr in SCN over northern and central Europe in summer and even more to 2-4 yr in Scandinavia in winter. The projected changes in wind extremes have a large spread among the six simulations with a disperse tendency (1-2 m s-1) of strengthening north of 45°N and weakening south of it which is sensitive to the number of simulations in the ensemble. Changes in temperature extremes are more robust compared to those in precipitation extremes while there is less confidence on changes in wind extremes. © 2010 The Authors Tellus A©2010 International Meteorological Institute in Stockholm.

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