An important new development within the European ENSEMBLES project has been to explore performance-based weighting of regional climate models (RCMs). Until now, although no weighting has been applied in multi-RCM analyses, one could claim that an assumption of 'equal weight' was implicitly adopted. At the same time, different RCMs generate different results, e. g. for various types of extremes, and these results need to be combined when using the full RCM ensemble. The process of constructing, assigning and combining metrics of model performance is not straightforward. Rather, there is a considerable degree of subjectivity both in the choice of metrics and on how these may be combined into weights. We explore the applicability of combining a set of 6 specifically designed RCM performance metrics to produce one aggregated model weight with the purpose of combining climate change information from the range of RCMs used within ENSEMBLES. These metrics capture aspects of model performance in reproducing large-scale circulation patterns, meso-scale signals, daily temperature and precipitation distributions and extremes, trends and the annual cycle. We examine different aggregation procedures that generate different inter-model spreads of weights. The use of model weights is sensitive to the aggregation procedure and shows different sensitivities to the selected metrics. Generally, however, we do not find compelling evidence of an improved description of mean climate states using performance-based weights in comparison to the use of equal weights. We suggest that model weighting adds another level of uncertainty to the generation of ensemble-based climate projections, which should be suitably explored, although our results indicate that this uncertainty remains relatively small for the weighting procedures examined.
This chapter builds on the comprehensive summary of climate change scenarios in the first BACC assessment published in 2008. This chapter first addresses the dynamical downscaling of general circulation model (GCM) results to the regional scale, focussing on results from 13 regional climate model (RCM) simulations in the ENSEMBLES project as this European-scale ensemble simulation is also relevant for the Baltic Sea region and many studies on temperature, precipitation, wind speed and snow amounts have been performed. This chapter then reviews statistical downscaling studies that use large-scale atmospheric variables (predictors) to estimate possible future change in several smaller scale fields (predictands), with the greatest emphasis given to hydrological variables (such as precipitation and run-off). For the Baltic Sea basin, the findings of the statistical downscaling studies are generally in line with studies employing dynamical downscaling.
Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071-2100 and the 1961-1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs-in particular in terms of precipitation-is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.
Ten regional climate models (RCM) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre boundary conditions. The response over Europe, calculated as the difference between the 2071 2100and the 1961-1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance in eight sub-European boxes. Four sources of uncertainty can be evaluated with the material provided by the PRUDENCE project. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30). Model uncertainty is due to the fact that the models use different techniques to discretize the equations and to represent sub-grid effects. Radiative uncertainty is due to the fact that IPCC-SRES A2 is merely one hypothesis. Some RCMs have been run with another scenario of greenhouse gas concentration (IPCC-SRES B2). Boundary uncertainty is due to the fact that the regional models have been run under the constraint of the same global model. Some RCMs have been run with other boundary forcings. The contribution of the different sources varies according to the field, the region and the season, but the role of boundary forcing is generally greater than the role of the RCM, in particular for temperature. Maps of minimum expected 2m temperature and precipitation responses for the IPCC-A2 scenario show that, despite the above mentioned uncertainties, the signal from the PRUDENCE ensemble is significant.
A 10-year climatology of long-range atmospheric transport to Ny-(A) over circle lesund, Svalbard (78.9degreesN, 11.9degreesE) is developed using three-dimensional 5-day back-trajectories. We calculate trajectories arriving twice daily at 950, 850 and 750 hPa during 1992-2001, using European Centre for Medium-Range Weather Forecasts (ECMWF) analyzed wind, fields. Cluster analysis is used to classify the trajectories into distinct transport patterns. The clustering procedure is performed on the whole 10-year set of trajectories, to study both year-to-year and mouth-to-mouth variability in the synoptic-scale atmospheric circulation. We identify eight major transport patterns to Ny-(A) over circle lesund, which we find to be consistent with mean-pressure charts of the Arctic region. The distribution of trajectories between these flows is similar for all years during the 10-year period. However, there are seasonal differences in when different clusters are most prevalent. The calculated clusters provide an indication of source regions and transport pathways influencing Svalbard at different times of the year. Such information is valuable for interpreting measured time-series of trace gases and aerosols and could serve as guidance for formulating sampling strategies. We compare the trajectory clusters to CO2 measurements to study to what degree different atmospheric flow patterns influence the variability of the atmospheric CO2. Overall we see a linkage between CO2 concentration and the large-scale circulation. For instance, in connection with transport over Europe and Siberia during winter, high CO2 mixing ratios are observed, whereas trajectories originating from the Atlantic are associated with low CO2 concentrations. However, during some periods and for some individual trajectories we see no conclusive linkage between variability in atmospheric CO2 and transport. This can be due to a combination of the complex structure Of CO2 sources and sinks and its relatively long atmospheric turn-over time. CO2 and Rn-222 mixing ratios are calculated using the three-dimensional transport model MATCH to further illustrate these characteristics of CO2. (C) 2003 Elsevier Ltd. All rights reserved.
The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover - CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs 'grassland' and 'agricultural land' at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.
The aim of this study was to reconstruct river flow to the Baltic Sea using data from different periods during the past thousand years. A hydrological model coupled to simulations from climate models was used to estimate river flow. A "millennium" simulation of past climate from the ECHO-G coupled atmosphere-ocean global climate model provided climatological inputs. Results from this global model were downscaled with the RCA3 regional climate model over northern Europe. Temperature and precipitation from the downscaled simulation results were then used in the HBV hydrological model to simulate river flows to the Baltic Sea for the periods 1000-1199 and 1551-1929. These were compared with observations for the period 1921-2002. A general conclusion from this work is that although climate has varied during the past millennium, variability in annual river flow to the Baltic Sea does not appear more pronounced in recent years than during the previous millennium, or vice versa.
Climate observations, research, and models are used extensively to help understand key processes underlying changes to the climate on a range of time scales from months to decades, and to investigate and describe possible longer-term future climates. The knowledge generated serves as a scientific basis for climate services that are provided with the aim of tailoring information for decision-makers and policy-makers. Climate models and climate services are crucial elements for supporting policy and other societal actions to mitigate and adapt to climate change, and for making society better prepared and more resilient to climate-related risks. We present recommendations for future research topics for climate modeling and for climate services. These recommendations were produced by a group of experts in climate modeling and climate services, selected based on their individual leadership roles or participation in international activities. The recommendations were reached through extensive analysis, consideration and discussion of current and desired research capabilities, and wider engagement and refinement of the recommendations was achieved through a targeted workshop of initial recommendations and an open meeting at the European Geosciences Union General Assembly. The findings emphasize how research and innovation activities in the fields of climate modeling and climate services can contribute to improving climate knowledge and information with saliency for users in order to enhance capacity to transition to a sustainable and resilient society. The findings are relevant worldwide but are deliberately intended to influence the European Commission's next major multi-annual framework program of research and innovation over the period 2021-27.
The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.
The European CORDEX (EURO-CORDEX) initiative is a large voluntary effort that seeks to advance regional climate and Earth system science in Europe. As part of the World Climate Research Programme (WCRP) - Coordinated Regional Downscaling Experiment (CORDEX), it shares the broader goals of providing a model evaluation and climate projection framework and improving communication with both the General Circulation Model (GCM) and climate data user communities. EURO-CORDEX oversees the design and coordination of ongoing ensembles of regional climate projections of unprecedented size and resolution (0.11 degrees EUR-11 and 0.44 degrees EUR-44 domains). Additionally, the inclusion of empirical-statistical downscaling allows investigation of much larger multi-model ensembles. These complementary approaches provide a foundation for scientific studies within the climate research community and others. The value of the EURO-CORDEX ensemble is shown via numerous peer-reviewed studies and its use in the development of climate services. Evaluations of the EUR-44 and EUR-11 ensembles also show the benefits of higher resolution. However, significant challenges remain. To further advance scientific understanding, two flagship pilot studies (FPS) were initiated. The first investigates local-regional phenomena at convection-permitting scales over central Europe and the Mediterranean in collaboration with the Med-CORDEX community. The second investigates the impacts of land cover changes on European climate across spatial and temporal scales. Over the coming years, the EURO-CORDEX community looks forward to closer collaboration with other communities, new advances, supporting international initiatives such as the IPCC reports, and continuing to provide the basis for research on regional climate impacts and adaptation in Europe.
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 northeastern Europe in winter and central Europe in summer, where sampling multiple RCMs may be 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.
A set of six regional climate model experiments is investigated for future changes in daily temperature and precipitation in Europe. Changes in the probability distributions for these variables are studied. It is found that the asymmetry of these distributions change differently depending on location and season. Large summertime changes in extremely high temperatures in central, eastern and southern Europe are followed by higher than average temperature increases on warm days in general. Likewise, temperatures on cold days increase much more than the average temperature increase during winter in eastern and northern Europe. A comparison with historical data on wintertime temperature shows that the model simulated and observed daily variability are similar. In particular, the much stronger increase in temperatures on cold days, compared to the average temperature increase as observed in warm compared to cold historical periods, is simulated also by the model. The contribution from heavy precipitation events is simulated to increase over most parts of Europe in all seasons.
Det klimatvetenskapliga kunskapsläget har förstärkts ytterligare under senare år. IPCC:s utvärderingsrapporter utgör de mest omfattande synteserna som finns på området. Huvudbudskapen i den senaste utvärderingsrapporten (AR5) är i allt väsentligt i linje med föregående rapport, även om ny kunskap har tillkommit och tidigare kunskap fördjupats.Uppvärmningen av klimatsystemet har fortsatt och människans påverkan är tydligSäkerheten i slutsatsen att människan påverkar klimatet har successivt stärkts i varje ny utvärderingsrapport från IPCC. Till de observerade förändringarna i klimatet hör att den lägre atmosfären och haven blivit varmare, nederbördsmönster ändrats, snötäckets utbredning på norra halvklotet liksom utbredningen av Arktis havsis har minskat. Som följd av uppvärmningen minskar också istäcket på Grönland och Antarktis samtidigt som många glaciärer smälter vilket bidrar till den stigande havsnivån. De ökade halterna av växthusgaser i atmosfären, främst koldioxid till följd av människans utsläpp, påverkar jordens strålningsbalans och är den främsta orsaken till den snabba uppvärmningen.Vi står inför fortsatt kraftig klimatförändring med allvarliga konsekvenserHur stor den framtida klimatförändringen blir beror på graden av ändrad strålningsbalans samt på klimatsystemets respons. Av de klimatscenarier som presenteras i AR5 är det bara i scenariot med minst klimatpåverkan som ökningen av den globala medel-temperaturen sannolikt inte kommer att överstiga 2°C jämfört med förindustriella nivåer. I ett scenario med nuvarande politik kan temperaturöverskridandet bli över 4°C och havsytans medelnivå höjas med uppemot en meter, eller möjligen mer, till år 2100. Generellt förväntas nederbörden öka där det redan regnar mycket och minska där det är torrt. Förekomsten av extrema väderhändelser förväntas också öka. Följdeffekterna inkluderar mer översvämningar och torka, och därigenom större risk för spridning av sjukdomar, brist på rent vatten och skördebortfall.Klimatförändringar drabbar redan utsatta värst, men Sverige påverkas också negativtFramtida klimatförändringar väntas innebära en rad negativa effekter för människor, samhällen och ekosystem. Dessa effekter blir mer kännbara vid högre grad av klimatpåverkan. IPCC slår fast att ytterligare uppvärmning ger en ökad sannolikhet för allvarliga, genomträngande och bestående effekter. Detta rör t.ex. hotade ekosystem i stora delar av världen där många arter kan komma att utrotas, kustnära samhällen som hotas av havsnivåhöjning och negativ påverkan på livsmedelsförsörjning. Även sekundära effekter som försvårande av fattigdomsbekämpning och ökad risk för skärpta konflikter i redan utsatta delar av världen pekas på som risker för samhället.Sveriges klimat har blivit varmare och mer nederbördsrikt. Fortsatta förändringar är att vänta och även om den globala medeltemperaturökningen begränsas till under 2 °C väntas kraftiga förändringar som kan komma att påverka samhället och naturmiljön. Skyfall och kraftiga regn förväntas öka i intensitet vilket kan ge ökade problem med översvämningar. Översvämningar kan också komma att drabba låglänta kusttrakter i södra Sverige p.g.a. stigande havsnivåer. Uppvärmningen väntas få konsekvenser för jord- och skogsbruk och även för naturliga ekosystem, inte minst i fjällkedjan där trädgränsen förväntas flytta högre upp i terrängen.Om vi agerar kraftfullt kan den globala temperaturökningen fortfarande begränsas till under 2 °CVärldens utsläpp fortsätter öka snabbt. Utsläppen av koldioxid mellan 1970 och 2010 överskred den sammanlagda mängden som släpptes ut före 1970. Den kraftiga ökningen av utsläppen mellan 2000 och 2010 har främst skett i tillväxtekonomier. Utsläppen bedöms fortsätta öka även i framtiden med dagens beslutade politik och styrmedel.För att "sannolikt" (med mer än 66 procents sannolikhet) begränsa temperaturökningen till under 2 °C år 2100 behöver de globala utsläppen nå sin kulmen inom en snar framtid, minska med 40 till 70 procent till år 2050 och till nära noll eller bli negativa år 2100. En så stor utsläppsreduktion kräver omfattande omställningar världen över i såväl industrialiserade som i snabbt växande ekonomier. Internationellt samarbete och verktyg för att främja utsläppsminskning är därför nödvändiga. För att begränsa effekterna och sårbarheten för de klimatförändringar som uppstår måste åtgärderna för utsläpps-minskningar kompletteras med klimatanpassningsåtgärder.Åtgärder för utsläppsminskning måste sättas in snart och kommer att krävas under mycket lång tidPå kort sikt behöver inlåsningar i koldioxidintensiv och energikrävande teknik och samhällsbyggnad undvikas genom att bygga hållbart från början. En sådan inriktning gör det också enklare att utveckla mer hållbara beteendemönster. Inriktningen är särskilt viktigt i de delar av världen där en stor mängd städer och energianläggningar nu håller på att byggas och expandera men också när tidigt industrialiserade länder nu genomför åter-investeringar i den befintliga bebyggelsen och infrastrukturen.Eftersom energieffektivisering minskar behovet av att tillföra ytterligare energi i systemet visar IPCC:s scenariomodelleringar att omfattande investeringar behöver göras i energi-effektiviserande åtgärder i perioden innan 2030.På lång sikt behöver energi- och resursanvändningen bli mycket mer effektiv än i dag, energitillförseln behöver nå nollutsläpp eller till och med negativa utsläpp och upptaget av koldioxid i skog och mark behöver öka. Ökad tillgång på bioenergi som producerats på ett hållbart sätt är viktigt för att få ner kostnaderna för omställningen. Försenas utsläpps-minskningarna ökar risken för allvarliga klimatförändringar och kostnaderna för klimat-politiken betydligt. IPCC-rapporten visar att ju längre världens länder väntar, desto mer behöver världen förlita sig på en omfattande användning av osäkra tekniker såsom bio-baserade energianläggningar med koldioxidfångning och lagring (bio-CCS) för att kunna åstadkomma negativa utsläpp (upptag av koldioxid från atmosfären) till år 2100.Klimatåtgärder som en del av hållbar utvecklingKlimatåtgärderna kan i många fall leda till positiva synergier med andra samhällsmål t.ex. när åtgärderna även innebär att vi hushåller med energi och vatten, att utsläppen av luft-föroreningar minskar, att det utvecklas ett hållbart jord- och skogsbruk, att energi-fattigdom minskar samt genom att ekosystemtjänster upprätthålls. Samtidigt kan klimat-åtgärder även medföra risker för negativa sidoeffekter, t.ex. om användningen av bioenergi utvecklas i konflikt med livsmedelsproduktion och biodiversitet. IPCC-rapporten betonar därför vikten av att främja de åtgärder som skapar synergier med andra samhällsmål, inklusive anpassning till klimatförändringarna.
The scientific basis related to climate change grows stronger, for example as reported by the latest report by the first working group of the IPCC in 2021. Primarily as a result of human emissions of carbon dioxide to the atmosphere, the global mean temperature has increased by more than 1.1 degrees since the second half of the 19th century. Continued emissions will lead to even larger increases in the future. Exactly how strong is unknown as the size of future emissions is not known and as there is an uncertainty related to the climate sensitivity. Despite this, it is clear that, in addition to higher temperatures in all areas, also precipitation will change as will different types of extreme conditions. The extent of snow and ice will decline and global sea level continue to rise. Such changes are expected to lead to various consequences both for society and the environment.The report presents what types of climate information that are available for work on climate change adaptation, how the information can be used, what limitations it has and what can be improved. Continued development of methods and models is one key component to be able to produce and improve climate information supporting climate change adaptation. Another relates to ensuring the existence of long time series reflecting variability and change. Large ensembles of high-resolution climate scenarios are needed to analyse, understand and describe future climate change under different scenarios. This is especially important for calculating probabilities of extreme weather events, which is a key component of the risk analysis. The report points to the importance of a longterm approach in the work with producing climate change information, and that it is important to involve the whole chain from observations and models to users of the information.
We evaluated daily and monthly statistics of maximum and minimum temperatures and precipitation in an ensemble of 16 regional climate models (RCMs) forced by boundary conditions from reanalysis data for 1961-1990. A high-resolution gridded observational data set for land areas in Europe was used. Skill scores were calculated based on the match of simulated and observed empirical probability density functions. The evaluation for different variables, seasons and regions showed that some models were better/worse than others in an overall sense. It also showed that no model that was best/worst in all variables, seasons or regions. Biases in daily precipitation were most pronounced in the wettest part of the probability distribution where the RCMs tended to overestimate precipitation compared to observations. We also applied the skill scores as weights used to calculate weighted ensemble means of the variables. We found that weighted ensemble means were slightly better in comparison to observations than corresponding unweighted ensemble means for most seasons, regions and variables. A number of sensitivity tests showed that the weights were highly sensitive to the choice of skill score metric and data sets involved in the comparison.
State-of-the-art climate models were used to simulate climate conditions in Europe during Greenland Stadial (GS) 12 at 44 ka BP. The models employed for these simulations were: (i) a fully coupled atmosphere-ocean global climate model (AOGCM), and (ii) a regional atmospheric climate model (RCM) to dynamically downscale results from the global model for a more detailed investigation of European climate conditions. The vegetation was simulated off-line by a dynamic vegetation model forced by the climate from the RCM. The resulting vegetation was then compared with the a priori vegetation used in the first simulation. In a subsequent step, the RCM was rerun to yield a new climate more consistent with the simulated vegetation. Forcing conditions included orbital forcing, land-sea distribution, ice-sheet configuration, and atmospheric greenhouse gas concentrations representative for 44 ka BP. The results show a cold climate on the global scale, with global annual mean surface temperatures 5 degrees C colder than the modern climate. This is still significantly warmer than temperatures derived from the same model system for the Last Glacial Maximum (LGM). Regional, northern European climate is much colder than today, but still significantly warmer than during the LGM. Comparisons between the simulated climate and proxy-based sea-surface temperature reconstructions show that the results are in broad agreement, albeit with a possible cold bias in parts of the North Atlantic in summer. Given a prescribed restricted Marine Isotope Stage 3 ice-sheet configuration, with large ice-free regions in Sweden and Finland, the AOGCM and RCM model simulations produce a cold and dry climate in line with the restricted ice-sheet configuration during GS 12. The simulated temperature climate, with prescribed ice-free conditions in south-central Fennoscandia, is favourable for the development of permafrost, but does not allow local ice-sheet formation as all snow melts during summer.
This report presents the latest version of the Rossby Centre regional atmospheric model, RCA3, with focus on model improvements since the earlier version, RCA2. The main changes in RCA3 relate to the treatment of land surface processes. Apart from the changes in land surface parameterizations several changes in the calculation of radiation, clouds, condensate and precipitation have been made. The new parameterizations hold a more realistic description of the climate system.Simulated present day climate is evaluated compared to observations. The new model version show equally good, or better, correspondence to observational climatologies as RCA2, when forced by perfect boundary conditions. Seasonal mean temperature errors are generally within ±1oC except during winter in north-western Russia where a larger positive bias is identified. Both the diurnal temperature range and the annual temperature range are found to be underestimated in the model. Precipitation biases are generally smaller than in the corresponding reanalysis data used as boundary conditions, showing the benefit of a higher horizontal resolution.The model is used for the regionalization of two transient global climate change projections for the time period 1961- 2100. The radiative forcing of the climate system is based on observed concentrations of greenhouse gases until 1990 and on the IPCC SRES B2 and A2 emissions scenarios for the remaining time period. Long-term averages as well as measures of the variability around these averages are presented for a number of variables including precipitation and near-surface temperature. It is shown that the changes in variability sometimes differ from the changes in averages. For instance, in north-eastern Europe, the mean increase in wintertime temperatures is followed by an even stronger reduction in the number of very cold days in winter. This kind of performance of the climate system implies that methods of inferring data from climate change projections to other periods than those actually simulated have to be used with care, at least when it comes to variables that are expected to change in a non-linear way. Further, these new regional climate change projections address the whole 21st century.
Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (+/- 5 degrees C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries.
A climate change experiment with a fully coupled high resolution regional atmosphere-ocean model for the Baltic Sea is compared to an experiment with a stand-alone regional atmospheric model. Both experiments simulate 30-yr periods with boundary data from the same global climate model system. This particular global model system simulates very high sea surface temperatures during summer for the Baltic Sea at the end of this century under the investigated emission scenario. We show that the sea surface temperatures are less warm in the coupled regional model compared to the global model system and that this difference is dependent on the atmospheric circulation. In summers with a high NAO index and thereby relatively strong westerly flow over the North Atlantic the differences between the two models are small, while in summers with a weaker, more northerly flow over the Baltic Sea the differences are very large. The higher sea surface temperatures in the uncoupled experiment lead to an intensified hydrological cycle over the Baltic Sea, with more than 30% additional precipitation in summer taken as an average over the full 30-yr period and over the entire Baltic Sea. The differences are mostly local, over the sea, but there are differences in surrounding land areas.