Climate change concerns the energy sector to a high degree because the sector is sensitive both to changing conditions for power and heat production, and to changing demand for electricity, heating and cooling. In this study potential consequences of climate change on different parts of the Swedish energy sector were assessed in a series of workshops, where climate and energy scientists, energy systems experts and analysts met with representatives of the energy sector to assess the vulnerability of the sector and consider what climate indicators could be used to assess impacts of relevance.

The impact of climate change depends on the energy type. Hydropower, for which production is naturally linked to weather and climate, is significantly impacted by climate change. For other forms of production, such as nuclear power, other factors such as e.g. policy and technology development are more important. The series of workshops held in this study, where different aspects of climate change and consequences were discussed, proved very successful and has increased our understanding of climate impacts on the energy system.

Climate change and global warming are already affecting food production, and the impact is predicted to intensify in the future. Previous studies have been based on global data and have provided general information about climate change effects on food production. Regional high-resolution data are, however, needed to evaluate the effect of future scenarios of climate change to support strategic and tactical planning to safeguard food production. Here, we provide results on the future potential distribution range of fungal plant pathogens in the Nordic and Baltic countries. This is done using regional climate model data at 12.5 km horizontal resolution. The temperature dependent infection risk and species richness are calculated using data for 80 plant pathogens. Within the region the studied pathogens will in most cases thrive more and be more abundant in a warmer climate; leading to a longer infection risk season and the introduction of new pathogens. This applies to all emissions scenarios, even though the effects are stronger with high emissions. Our results indicate that plant diseases will increase, and this will negatively affect crop production and food security.

This paper studies the impact of land use and land cover change (LULCC) on the climate around 2500 years ago (2.5 ka), a period of rapid transitions across the European landscape. One global climate model was used to force two regional climate models (RCMs). The RCMs used two land cover descriptions. The first was from a dynamical vegetation model representing potential land cover, and the second was from a land cover description reconstructed from pollen data by statistical interpolation. The two different land covers enable us to study the impact of land cover on climate conditions. Since the difference in landscape openness between potential and reconstructed land cover is mostly due to LULCC, this can be taken as a measure of early anthropogenic effects on climate. Since the sensitivity to LULCC is dependent on the choice of climate model, we also use two RCMs. The results show that the simulated 2.5 ka climate was warmer than the simulated pre-industrial (PI, 1850 CE) climate. The largest differences are seen in northern Europe, where the 2.5 ka climate is 2-4 degrees C warmer than the PI period. In summer, the difference between the simulated 2.5 ka and PI climates is smaller (0-3 degrees C), with the smallest differences in southern Europe. Differences in seasonal precipitation are mostly within +/- 10 %. In parts of northern Europe, the 2.5 ka climate is up to 30% wetter in winter than that of the PI climate. In summer there is a tendency for the 2.5 ka climate to be drier than the PI climate in the Mediterranean region. The results also suggest that LULCC at 2.5 ka impacted the climate in parts of Europe. Simulations including reconstructed LULCC (i.e. those using pollen-derived land cover descriptions) give up to 1 degrees C higher temperature in parts of northern Europe in winter and up to 1.5 degrees C warmer in southern Europe in summer than simulations with potential land cover. Although the results are model dependent, the relatively strong response implies that anthropogenic land cover changes that had occurred during the Neolithic and Bronze Age could have affected the European climate by 2.5 ka.

Land-cover changes have a clear impact on local climates via biophysical effects. European land cover has been affected by human activities for at least 6000 years, but possibly longer. It is thus highly probable that humans altered climate before the industrial revolution (AD1750–1850). In this study, climate and vegetation 6000 years (6 ka) ago is investigated using one global climate model, two regional climate models, one dynamical vegetation model, pollen-based reconstruction of past vegetation cover using a model of the pollen-vegetation relationship and a statistical model for spatial interpolation of the reconstructed land cover. This approach enables us to study 6 ka climate with potential natural and reconstructed land cover, and to determine how differences in land cover impact upon simulated climate. The use of two regional climate models enables us to discuss the robustness of the results. This is the first experiment with two regional climate models of simulated palaeo-climate based on regional climate models.

Different estimates of 6 ka vegetation are constructed: simulated potential vegetation and reconstructed vegetation. Potential vegetation is the natural climate-induced vegetation as simulated by a dynamical vegetation model driven by climate conditions from a climate model. Bayesian spatial model interpolated point estimates of pollen-based plant abundances combined with estimates of climate-induced potential un-vegetated land cover were used for reconstructed vegetation. The simulated potential vegetation is heavily dominated by forests: evergreen coniferous forests dominate in northern and eastern Europe, while deciduous broadleaved forests dominate central and western Europe. In contrast, the reconstructed vegetation cover has a large component of open land in most of Europe.

The simulated 6 ka climate using reconstructed vegetation was 0–5 °C warmer than the pre-industrial (PI) climate, depending on season and region. The largest differences are seen in north-eastern Europe in winter with about 4–6 °C, and the smallest differences (close to zero) in southwestern Europe in winter. The simulated 6 ka climate had 10–20% more precipitation than PI climate in northern Europe and 10–20% less precipitation in southern Europe in summer. The results are in reasonable agreement with proxy-based climate reconstructions and previous similar climate modelling studies. As expected, the global model and regional models indicate relatively similar climates albeit with regional differences indicating that, models response to land-cover changes differently.

The results indicate that the anthropogenic land-cover changes, as given by the reconstructed vegetation, in this study are large enough to have a significant impact on climate. It is likely that anthropogenic impact on European climate via land-use change was already taking place at 6 ka. Our results suggest that anthropogenic land-cover changes at 6 ka lead to around 0.5 °C warmer in southern Europe in summer due to biogeophysical forcing.

Large historical and future ensemble simulations from the Max-Planck Institute and the Canadian Earth System Models and from CMIP5 have been analysed to investigate the uncertainty due to internal variability in multi-decadal temperature and precipitation trends over Europe. Internal variability dominates the uncertainties in temperature and precipitation trends in all seasons at 30-year time scales. Locally, seasonal 30-year temperature trends deviate up to +/- 3 degrees C from the ensemble mean trend. Thus, in the entire of Europe, local seasonal temperature changes until year 2050 from below -1 degrees C up to more than 4 degrees C are possible according to the model results. Up to 30% of all ensemble members show negative temperature trends until year 2050 in winter, up to 10% of the members in summer. Uncertainties of 30-year precipitation trends due to internal variability exceed the trends almost everywhere in Europe. Only in few European regions more than 75% of the members agree on the sign of the change until year 2050. In southern Sweden, minimum and maximum winter (summer) temperature trends in the next 30years differ with up to 7 degrees C (5 degrees C) between individual members of the large model ensembles. Large positive temperature trends are linked to positive (negative) precipitation trends in winter (summer) in southern Sweden. This variability is attributed to the variability in large scale atmospheric circulation trends, mainly due to internal atmospheric variability. We find only weak linkages between the variability of temperature trends and the dominant decadal to multi-decadal climate modes. This indicates that there is limited potential to predict the multi-decadal variability in climate trends. The main findings from our study are robust across the large ensembles from the different models used in this study but at the local scale, the results depend also on the choice of the model.

Studies in paleoclimate are important because they give us knowledge about how the climate system works and puts the current climate change in necessary perspective. By studying (pre)historic periods we increase our knowledge not just about these periods, but also about the processes that are important for climatic variations and changes. This thesis deals mainly with the interaction between climate and vegetation. Vegetation changes can affect climate in many different ways. These effects can be divided into two main categories: biogeochemical and biogeophysical processes. This thesis studies the biogeophysical effects of vegetation changes on climate in climate models. Climate models are a necessary tool for investigating how climate responds to changes in the climate system, as well as for making predictions of future climate. The biogeophysical processes are strongly related to characteristics of the land surface. Vegetation changes alter the land surface’s albedo (ability to reflect incoming solar radiation), roughness and evapotranspiration (the sum of evaporation and tran-spiration), which in turn affects the energy fluxes between the land surface and the atmosphere and thereby the climate. It is not, however, evident in what way; denser vegetation (e.g. forest instead of grassland) gives decreased albedo, which results in higher temperature, but also increased evapotranspiration, which contrastingly results in lower temperature. Vegetation changes are in this thesis studied in four different (pre)historic periods: two very cold periods with no human influence (c. 44,000 and 21,000 years ago), one warm period with minor human influence (c. 6,000 years ago) and a cold period with substantial human influence (c. 200 years ago). In addition to that the present climate is studied. The combination of these periods gives an estimate of the effect of both natural and anthropogenic vegetation on climate in different climatic contexts. The results show that vegetation changes can change temperature with 1–3 °C depending on season and region. The response is not the same everywhere, but depends on local properties of the land surface. During the winter half of the year, the albedo effect is usually most important as the difference in albedo between forest and open land is very large. During the summer half of the year the evapotranspiration effect is usually most important as differences in albedo between different vegetation types are smaller. A prerequisite for differences in evapotranspiration is that there is sufficient amount of water available. In dry regions, evapotranspiration does not change much with changes in vegetation, which means that the albedo effect will dominate also in summer. The conclusion of these studies is that vegetation changes can have a considerable effect on climate, comparable to the effect of increasing amounts of greenhouse gases in scenarios of future climate. Thus, it is important to have an appropriate description of the vegetation in studies of past, present and future climate. This means that vegetation has the potential to work as a feedback mechanism to natural climatic variations, but also that man can alter climate by altering the vegetation. It also means that mankind may have influenced climate before we started to use fossil fuel. Consequently, vegetation changes can be used as a means to mitigate climate change locally.

Studiet av paleoklimat är viktigt för att det ger kunskap om hur klimatsystemet fungerar samt för att det sätter nuvarande klimatförändring i ett nödvändigt perspektiv. Genom att studera (för)historiska perioder ökar vi vår kunskap om dessa perioder, men också om vilka processer som har betydelse för klimatets variationer. Denna avhandling behandlar framförallt interaktionen mellan klimat och växtlighet. Förändringar i växtligheten kan påverka klimatet på flera olika sätt. Dessa kan delas in i två huvudgrupper: biogeokemiska och biogeofysikaliska processer. Denna avhandling studerar de biogeofysikaliska effekterna på klimatet i klimatmodeller. Klimatmodeller är ett nödvändigt verktyg för att studera hur klimatet svarar på förändringar i klimatsystemet, samt för att göra förutsägelser om framtidens klimat. De biogeofysikaliska processerna är förknippade med markytans egenskaper. Förändrad växtlighet förändrar markytans albedo (förmågan att reflektera inkommande soltrålning), skrovlighet och förmågan att transportera vatten från marken till atmosfären genom evapotranspiration (summan av avdunstning och transpiration), vilket i sin tur påverkar energiflödena mellan markytan och atmosfären. Dessa förändringar påverkar sedermera klimatet. Det är emellertid inte självklart på vilket sätt; tätare växtlighet (t.ex. skog i stället för äng) ger minskat albedo vilket ger högre temperatur, men också ökad evapotranspiration vilket däremot ger lägre temperatur. Växtlighetsförändringars påverkan på klimatet studeras i denna avhandling i fyra olika (för)historiska perioder: två väldigt kalla perioder utan mänsklig påverkan (ca 44 000 och 21 000 år sedan), en varm period med liten mänsklig påverkan (ca 6 000 år sedan) och en kall period med avsevärd mänsklig påverkan (ca 200 år sedan). I tillägg till det studeras också dagens klimat. Resultaten visar att förändringar i växtlighet lokalt kan ha en signifikant effekt på klimatet. Kombinationen av dessa perioder ger en uppskattning av effekten av både naturlig och antropogen växtlighet i olika klimatsammanhang. Förändrad växtlighet kan ändra temperaturen med 1-3 °C beroende på årstid och område. Responsen är inte densamma överallt utan beror på lokala egenskaper hos markytan. Under vinterhalvåret är oftast albedoeffekten viktigast eftersom skillnaden i albedo mellan skog och öppet landskap då är mycket stor. Under sommarhalvåret är evapotranspirationen oftast viktigast eftersom skillnaden i albedo mellan olika växtlighetstyper då oftast är små. En förutsättning för det är att det finns tillräckligt med vatten tillgängligt för evapotranspiration. I torra områden förändras evapotranspirationen inte särskilt mycket när växtligheten förändras, vilket gör att albedoeffekten dominerar även på sommaren.  Slutsatsen av dessa studier blir att förändrad växtlighet kan ha en betydande effekt på klimatet, jämförbar med den effekt som ökade halter av växthusgaser har i scenarier för framtida klimat. Alltså är det viktigt att ha en korrekt beskrivning av växtligheten i studier av (för)historiskt, nutida och framtida klimat. Det betyder att växtligheten har potentialen att fungera som en återkopplingsmekanism till naturliga klimatvariationer, men också att människan kan påverka klimatet genom att förändra växtligheten. Det betyder också att mänskligheten kan ha påverkat klimatet innan vi började använda fossilt bränsle. Följaktligen kan växtlighetsförändringar användas som ett sätt att lokalt begränsa klimatförändringar.

The study of past climate is important because it increases our understanding of how the climate system works. Past climate is often reconstructed by using proxies (that is observations of things that tell something about past climate, for example tree rings, pollen in lake sediments and fossils). Model simulations of past climate further increases the knowledge since it has the possibility to gap the space and time between the sparse and scattered proxy observations, since a model simulation gives relatively continuous information about the whole simulated area. Model simulations can also give internally coherent information about parameters that is not easily reconstructed from proxies (for example heat fluxes).  In this thesis two periods in the past are simulated by climate models: the Marine Isotope Stage 3 (MIS 3), 44 000 years ago, and the Last Glacial Maximum (LGM), 21 000 years ago. Both periods are characterised by low temperature, low sea level and low level of carbon dioxide. The topography in northern Europe is dominated by ice sheets covering Iceland, Norway and parts of Sweden at MIS3; and more extensive ice sheets covering Iceland, Scandinavia, the British Isles and Northern Germany at LGM. These periods are firstly simulated by a global climate model. Those simulations are subsequently used in a regional climate model to increase the level of detail over Europe. To make the regional climate model simulation more realistic vegetation simulated by a dynamical vegetation model is used in the regional climate model.   The climate models simulate European climates much colder than today, especially at LGM. The temperature differences ranges from 5 to 45 °C colder than today; the largest differences being at the ice sheets where the perennial ice cover and the high altitude keep temperatures low. Precipitation is reduced with as much as almost 100 % in northern Europe due to reduced evaporation. Precipitation is increased with as much as 100 % in parts of southern Europe due to changes in atmospheric circulation. The simulations are in broad agreement with proxies, although there are differences.  The vegetation model simulates tundra like vegetation (herbs and shrubs) in the ice-free parts of central and southern Europe. The eastern parts of Europe are dominated by needle-leaved trees. The short and cool summers limit vegetation. The simulated vegetation is in broad agreement with reconstructions. Sensitivity studies of vegetation show that changed vegetation can change the monthly mean temperature with 1-3 °C in some seasons and regions. The response depends on regional surface characteristics. Sensitivity studies of ice sheets show that the simulated climate is consistent with the assumptions about the ice sheet extent made in the simulation. The simulated climate is cold enough in northern Europe to support the ice sheet, and warm enough in southern Europe to prevent the ice sheet from expanding in this direction. A removal of the ice sheet would only have an effect on the local scale in the vicinity of the ice sheet, but this experiment did not include changes in the large-scale global atmospheric circulation.  Although the regional climate model simulations are to a large degree depending on the global climate model simulations they provide new information. When comparing proxies with model data or studying local/regional climatic features (such as the interplay between climate and vegetation) high horizontal resolution, as in the regional climate model, is important.  

Studiet av klimat i det förgångna är viktigt eftersom det ökar vår förståelse för hur klimatsystemet fungerar. Förgånget klimat rekonstrueras ofta med hjälp av proxies (det vill säga observationer av saker som säger något om klimatet förr i tiden, till exempel trädringar, pollen i sjösediment och fossiler). Modellsimuleringar av förgånget klimat ökar kunskapen ytterligare eftersom det ger en möjlighet att fylla i luckorna, i tid och rum, mellan de glesa och spridda proxy-observationerna, eftersom en modellsimulering ger information om hela det simulerade området. Modellsimuleringar kan också ge information om parametrar som inte så lätt rekonstrueras från proxies (till exempel värmeflöden).   I denna avhandling simuleras med klimatmodeller två perioder i det förgångna: MIS 3 (Marine Isotope Stage 3), för 44 000 år sedan och LGM (Last Glacial Maximum), för 21 000 år sedan. Båda perioderna kännetecknas av låg temperatur, låg havsnivå och låg halt av koldioxid. Topografin i norra Europa domineras av istäcken som täcker Island, Norge och Sverige vid MIS 3; och istäcken över Island, Skandinavien, Brittiska öarna och norra Tyskland vid LGM. Dessa perioder simuleras först av en global klimatmodell. Simuleringarna används senare i en regional klimatmodell för att öka detaljgraden över Europa. För att göra den regionala klimatmodell-simuleringen mer realistisk så används i den regionala klimatmodellen vegetation som är simulerad av en dynamisk vegetationsmodell. Klimatmodellerna simulerar europeiska klimat som är mycket kallare än dagens, särskilt vid LGM. Temperaturdifferensen spänner från 5 till 45 °C kallare än idag; de största skillnaderna är vid istäckena där det ständiga istäcket och den höga altituden håller temperaturen nere. Nederbörden minskar med så mycket som nästan 100 % i norra Europa på grund av minskad avdunstning. Nederbörden ökar med så mycket som 100 % i delar av södra Europa på grund av förändringar i atmosfärens cirkulation. Simuleringarna stämmer i stora drag överens med proxies, även om det finns skillnader.  Vegetationsmodellen simulerar tundralik vegetation (örter och snår) i de isfria delarna av centrala och södra Europa. De östra delarna av Europa domineras av barrträd. De korta och kalla somrarna begränsar vegetationen. Den simulerade vegetationen stämmer i stora drag överens med rekonstruktionerna. Känslighetsstudier av vegetationen visar att förändrad vegetation kan förändra månadsmedeltemperaturen med 1-3 °C i vissa regioner och under vissa säsonger. Responsen beror på regionala egenskaper vid markytan. Känslighetsstudier av istäckena visar att det simulerade klimatet är förenligt med de antaganden av istäckenas utbredning som görs i simuleringen. Det simulerade klimatet är tillräckligt kallt i norra Europa för att göra ett istäcke möjligt, och tillräckligt varmt i södra Europa för att hindra istäcket från att växa i den riktningen. Om istäcket skulle tas bort skulle det bara ha en effekt på lokal skala i närheten av istäcket, men detta experiment innefattade inte förändringar i atmosfärens cirkulation. Även om de regionala klimatmodell-simuleringarna till stor del beror på de globala klimatmodell-simuleringarna så ger de ny information. Vid jämförelser av proxies och modelldata eller studier av lokala/regionala egenskaper hos klimatet (som växelverkan mellan klimat och vegetation) så är hög horisontell upplösning, som i en regional klimatmodell, viktigt.

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.

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.

A fully coupled atmosphere–ocean general circulation model is used to simulate climate conditions during the last glacial maximum (LGM). Forcing conditions include astronomical parameters, greenhouse gases, ice sheets and vegetation. A 50-yr period of the global simulation is dynamically downscaled to 50 km horizontal resolution over Europe with a regional climate model (RCM). A dynamic vegetation model is used to produce vegetation that is consistent with the climate simulated by the RCM. This vegetation is used in a final simulation with the RCM. The resulting climate is 5–10 °C colder than the recent past climate (representative of year 1990) over ice-free parts of Europe as an annual average; over the ice-sheet up to 40 °C colder in winter. The average model-proxy error is about the same for summer and winter, for pollen-based proxies. The RCM results are within (outside) the uncertainty limits for winter (summer). Sensitivity studies performed with the RCM indicate that the simulated climate is sensitive to changes in vegetation, whereas the location of the ice sheet only affects the climate around the ice sheet. The RCM-simulated interannual variability in near surface temperature is significantly larger at LGM than in the recent past climate.