Objectives: Respiratory diseases are ranked second in Europe in terms of mortality, prevalence and costs. Studies have shown that extreme heat has a large impact on mortality and morbidity, with a large relative increase for respiratory diseases. Expected increases in mean temperature and the number of extreme heat events over the coming decades due to climate change raise questions about the possible health impacts. We assess the number of heat-related respiratory hospital admissions in a future with a different climate. Design: A Europe-wide health impact assessment. Setting: An assessment for each of the EU27 countries. Methods: Heat-related hospital admissions under a changing climate are projected using multicity epidemiological exposure-response relationships applied to gridded population data and country-specific baseline respiratory hospital admission rates. Times-series of temperatures are simulated with a regional climate model based on four global climate models, under two greenhouse gas emission scenarios. Results: Between a reference period (1981-2010) and a future period (2021-2050), the total number of respiratory hospital admissions attributed to heat is projected to be larger in southern Europe, with three times more heat attributed respiratory hospital admissions in the future period. The smallest change was estimated in Eastern Europe with about a twofold increase. For all of Europe, the number of heat-related respiratory hospital admissions is projected to be 26 000 annually in the future period compared with 11 000 in the reference period. Conclusions: The results suggest that the projected effects of climate change on temperature and the number of extreme heat events could substantially influence respiratory morbidity across Europe.

Since 1990, the academic literature on historical responsibility (HR) for climate change has grown considerably. Over these years, the approaches to defining this responsibility have varied considerably. This article demonstrates how this variation can be explained by combining various defining aspects of historical contribution and responsibility. Scientific knowledge that takes for granted choices among defining aspects will likely become a basis for distrust within science, among negotiators under the United Nations Framework Convention on Climate Change (UNFCCC), and elsewhere. On the other hand, for various reasons, not all choices can be explicated at all times. In this article, we examine the full breadth of complexities involved in scientifically defining HR and discuss how these complexities have consequences for the science-policy interface concerning HR. To this end, we review and classify the academic literature on historical contributions to and responsibility for climate change into categories of defining aspects. One immediately policy-relevant conclusion emerges from this exercise: Coupled with negotiators' highly divergent understandings of historical responsibility, the sheer number of defining aspects makes it virtually impossible to offer scientific advice without creating distrust in certain parts of the policy circle. This conclusion suggests that scientific attempts to narrow the options for policymakers will have little chance of succeeding unless policymakers first negotiate a clearer framework for historical responsibility. For further resources related to this article, please visit the . Conflict of interest: The authors have declared no conflicts of interest for this article.

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.

Anthropogenic land-cover change (ALCC) is one of the few climate forcings for which the net direction of the climate response over the last two centuries is still not known. The uncertainty is due to the often counteracting temperature responses to the many biogeophysical effects and to the biogeochemical versus biogeophysical effects. Palaeoecological studies show that the major transformation of the landscape by anthropogenic activities in the southern zone of the Baltic Sea basin occurred between 6000 and 3000/2500 cal year BP. The only modelling study of the biogeophysical effects of past ALCCs on regional climate in north-western Europe suggests that deforestation between 6000 and 200 cal year BP may have caused significant change in winter and summer temperature. There is no indication that deforestation in the Baltic Sea area since AD 1850 would have been a major cause of the recent climate warming in the region through a positive biogeochemical feedback. Several model studies suggest that boreal reforestation might not be an effective climate warming mitigation tool as it might lead to increased warming through biogeophysical processes.

The need for long time series of gridded meteorological data with a fine spatial and temporal resolution has increased in recent years. The requirements for this type of gridded meteorological data fields arise from many different areas of the society, in connection to atmospheric environment studies of air quality and deposition and trends in these parameters, regional climate change, wind energy, hydrological studies etc. The aim of the present project is to investigate the possibility of producing historical, high quality and time consistent, meso-scale re analyses for the whole of Europe regarding precipitation, 2 m temperature and wind for at least 25 years back in time.The MESAN analysis system (Häggmark et al., 2000) at SMHI was chosen as a basis for the reanalysis and the system was adjusted to cover the whole of Europe. In order to find the most appropriate first guess fields to be used in the MESAN system, a pilot study was performed. ERA- 40 data from ECMWF was selected as best possible first guess fields for the re analysis. The performed re-analysis, which is denoted ERAMESAN, includes gridded data covering all Europe with a time resolution of 6 h and a spatial resolution of 0.1º (11 km) in a rotated latitude longitude coordinate system for the time-period 1980-2004. All analyses are archived in GRIB-format and stored on disc at SMHI. The dataset is also available within the EUMETNET optional programme Showcase EUROGRID.A partial validation for the years 1998-2000, using a cross validation procedure with independent observations (5.5% of the total amount of stations), shows an improvement in ERAMESAN compared to the ERA-40 data for all studied parameters with regard to root mean square deviation, mean absolute deviation and mean bias deviation for all seasons. The deviations are roughly of the order of 15% smaller compared to what is obtained from ERA-40. The frequency distribution of large precipitation amounts per day and high wind speeds are substantially better described in ERAMESAN compared to ERA-40. However, the tendency to underestimate the frequency of very large precipitation amounts or high wind speeds, compared to observations, can be seen also for ERAMESAN. It is important to be aware of this limitation when using ERAMESAN data for practical applications concerning evaluation of risks for extreme wind speeds or very large precipitation amounts or in e.g. wind energy studies.

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.

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.

The demand is growing for practical information on climate projections and the impacts expected in different geographical regions and different sectors. It is a challenge to transform the vast amount of data produced in climate models into relevant information for climate change impact studies. Climate indices based on climate model data can be used as means to communicate climate change impact relations. In this report a vast amount of results is presented from a multitude of indices based on different regional climate scenarios.The regional climate scenarios described in this report show many similarities with previous scenarios in terms of general evolution and amplitude of future European climate change. The broad features are manifested in increases in warm and decreases in cold indices. Likewise are presented increases in wet indices in the north and dry indices in the south.Despite the extensive nature of the material presented, it does not cover the full range of possible climate change. We foresee a continued interactive process with stakeholders as well as continued efforts and updates of the results presented in the report.

SMHI fick i sitt regleringsbrev för år 2014 uppdraget att, i samråd med berörda myndigheter och andra aktörer, ta fram en vägledning för användandet av klimatscenarier. Enligt önskemål framtogs vägledningen som en webb-produkt på smhi.se, i anslutning till klimatscenarier. Materialet finns även samlat i denna rapport, såsom det lanserades hösten 2014. Eftersom materialet är uppbyggt för webb-presentation, där läsaren ska kunna gå in i kapitel utan att ha läst de tidigare, förekommer en del upprepningar. Klimatscenarier är beskrivningar av hur klimatet kan utvecklas i framtiden. Vägledningen ger stöd för att tolka och använda klimatscenarier, med dess möjligheter och begränsningar. Klimateffektstudier beskrivs översiktligt och med fokus på hydrologiska effektstudier. Några enkla steg för att komma igång med klimatanpassning presenteras också. I ordlistan förklaras de begrepp som används.

Under hösten 2006 utförde Rossby Centre ett omfattande arbete för att till olika sektorer i samhället ta fram underlagsmaterial om klimatets utveckling. Beställare var framförallt Klimat- och sårbarhetsutredningens olika arbetsgrupper men också energibranschen. Föreliggande rapport beskriver en delleverans till Elforsk-projektet ”Tänkbara konsekvenser för den svenska energisektorn av klimatförändringar – effekter, sårbarhet och anpassning”. Material togs fram som belyser en möjlig temperaturutveckling i ett relativt kort framtidsperspektiv representerat av perioden 2011-2040. Det fanns önskemål om att särskilt titta på utvecklingen för tre platser med olika klimat i ett nord-sydligt perspektiv och med närhet till större befolkningsgrupper.Analyserna inom projektet har finansierats av Elforsk. Modellsimuleringarna har gjorts på den dedikerade klimatdatorresursen ”Tornado” vid Nationellt Superdatorcentrum, Linköpings universitet. Tornado finansieras av Knut och Alice Wallenbergs Stiftelse.I denna rapport presenteras materialet avseende de tre platserna kompletterat med ett litet urval kartor som visar några temperaturindex. Ett mycket omfattande kartmaterial finns att tillgå på Rossby Centrets hemsida som nås via www.smhi.se.

Variability and long-term climate change in Fennoscandia is investi-gated in a 1000-year long climate model simulation. We use the Rossby Centre Regional Climate model (RCA3) with boundaryconditions from a General Circulation Model (GCM). Solar variability, changes in orbital parameters and changes in greenhouse gases over the last millennium are used to force the climate models. It is shown that RCA3 generates a warm period corresponding to the Medieval Climate Anomaly (MCA) being the warmest period within the millennium apart from the 20th century. Moreover, an analogy forthe Little Ice Age (LIA) was shown to be the coldest period. The simulated periods are 1100-1299 A.D. for the MCA and 1600-1799 A.D. for the LIA, respectively. This is in agreement with recon-structions and mostly related to changes in the solar irradiance. We found that multi decadal variability has an important impact on the appearance of the MCA and LIA. Moreover, multi decadal variability mayhelp to explain sometimes contradicting reconstructions if these are representative for relatively short non-overlapping periods. In addition to time series, we investigate spatial patterns of temperature, sealevel pressure, precipitation, cloud cover, wind speed and gustiness for annual and seasonal means. Most parameters show the clearest response for the winter season. For instance, winter during the MCAare 1-2.5 K warmer than during the LIA for multi decadal averages.

Variability and long-term climate change in the Baltic Sea region is investigated for the pre-industrial period of the last millennium. For the first time dynamical down-scaling covering the complete millennium is conducted with a regional climate model in this area. As a result of changing external forcing conditions, the model simulation shows warm conditions in the first centuries followed by a gradual cooling until ca. 1700 before temperature increases in the last centuries. This long-term evolution, with a Medieval Climate Anomaly (MCA) and a Little Ice Age (LIA), is in broad agreement with proxy-based reconstructions. However, the timing of warm and cold events is not captured at all times. We show that the regional response to the global climate anomalies is to a strong degree modified by the large-scale circulation in the model. In particular, we find that a positive phase of the North Atlantic Oscillation (NAO) simulated during MCA contributes to enhancing winter temperatures and precipitation in the region while a negative NAO index in the LIA reduces them. In a second step, the regional ocean model (RCO-SCOBI) is used to investigate the impact of atmospheric changes onto the Baltic Sea for two 100 yr time slices representing the MCA and the LIA. Besides the warming of the Baltic Sea, the water becomes fresher at all levels during the MCA. This is induced by increased runoff and stronger westerly winds. Moreover, the oxygen concentrations in the deep layers are slightly reduced during the MCA. Additional sensitivity studies are conducted to investigate the impact of even higher temperatures and increased nutrient loads. The presented experiments suggest that changing nutrient loads may be more important determining oxygen depletion than changes in temperature or dynamic feedbacks.

This report documents Coordinated Regional Downscaling Experiment (CORDEX) climate model simulations at 50 km horizontal resolution over Europe with the Rossby Centre regional atmospheric model (RCA4) for i) a ERA-Interim-driven (ERAINT) simulation used to evaluate model performance in the recent past climate, ii) historical simulations of the recent decades with forcing from nine different global climate models (GCMs) and iii) future scenarios RCP 4.5 and RCP 8.5 forced by the same nine different GCMs. Those simulations represent a subset of all CORDEX simulations produced at the Rossby Centre and a general conclusion drawn at the Rossby Centre is that such large ensembles could not have been produced without the establishment of an efficient production chain as outlined here. The first part of this report documents RCA4 and its performance in a perfect boundary simulation where ERAINT was downscaled. RCA4 is to a large extent replicating the large-scale circulation in ERAINT, but some local biases in mean sea level pressure appear. In general the seasonal cycles of temperature and precipitation are simulated in relatively close agreement to observations. Some biases occur, such as too much precipitation in northern Europe and too little in the south. In winter, there is also too much precipitation in eastern Europe. Temperatures are generally biased low in northern Europe and in the Mediterranean region in winter while overestimated temperatures are seen in southeastern Europe in winter and in the Mediterranean area in summer. RCA4 performs generally well when simulating the recent past climate taking boundary conditions from the GCMs. A large part of the RCA4 simulated climate is attributed to the driving GCMs, but RCA4 creates its own climate inside the model domain and adds details due to higher resolution. All nine downscaled GCMs share problems in their representation of the large-scale circulation in winter. This feature is inherited in RCA4. The biases in large-scale circulation induce some biases in temperature and precipitation in RCA4. The climate change signal in the RCP 4.5 and RCP 8.5 ensembles simulated by RCA4 is very similar to what has been presented previously. Both scenarios RCP 4.5 and RCP 8.5 project Europe to be warmer in the future. In winter the warming is largest in northern Europe and in summer in southern Europe. The summer maximum daily temperature increases in a way similar to summer temperature, but somewhat more in southern Europe. The winter minimum daily temperature in northern Europe is the temperature that changes the most. Precipitation is projected to increase in all seasons in northern Europe and decrease in southern Europe. The largest amount of rainfall per day (and per seven day period) is projected to increase in almost all of Europe and in all seasons. At the same time the longest period without precipitation is projected to be longer in southern Europe. Small changes in mean wind speed are generally projected. There are, however, regions with significant changes in wind. The ensemble approach is a way to describe the uncertainties in the scenarios, but there are other possible ensembles using other models which would give other results. Still, the ensemble used here is found to be similar enough to these other possible ensembles to be representative of the whole set of GCMs. Dynamical downscaling using RCA4 changes the climate change signal, and the ensemble spread is sometimes reduced, but the ensemble of nine RCA4 simulations, using different GCMs, is considered to be representative of the full ensemble. All scenarios agree on a climate change pattern; the amplitude of the change is determined by the choice of scenario. The relative importance of the chosen scenario increases with time.

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, similar to 6 and similar to 0.2 k BP in Europe. We apply We apply the Rossby Centre regional climate model RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land use (deforestation) from the HYDE3.1 (History Database of the Global Environment) scenario (V + H3.1), and (iii) potential vegetation with anthropogenic land use from the KK10 scenario (V + KK10). The climate model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At similar to 6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5-1 degrees C. At similar to 0.2 k BP, extensive deforestation, particularly according to the KK10 model, leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe because evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates in southern Europe also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from -1 degrees C in south-western Europe to +1 degrees C in eastern Europe. The choice of anthropogenic land-cover scenario has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a definitive discrimination among climate model results.