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  • 1.
    Alexandersson, Hans
    et al.
    SMHI.
    Tuomenvirta, H
    Schmith, T
    Iden, K
    Trends of storms in NW Europe derived from an updated pressure data set2000Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 14, nr 1, s. 71-73Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Within the WASA project (von Storch et al. 1998; Bull Am Meterol Soc 79(5):741-760) an extensive data set containing station pressure values was used to calculate geostrophic winds (Alexandersson et al. 1998; Global Atmos Ocean Syst 6:97-120). Geostrophic winds were analysed in terms of percentiles to give a measure of long-term variations in synoptic-scale storminess. In this paper an update to 1998 is presented. In the Scandinavia, Finland and Baltic Sea area the most recent years, especially the cold and calm year 1996, seem to have brought an end to the stormy period centred on 1990. In the more westerly British Isles, North Sea and Norwegian Sea area, storminess is still at high levels compared with the less intense period between 1930 and 1980. The long-term increasing trend in NW Europe storminess that started in the 1960s seems to have been broken.

  • 2.
    Bergström, Sten
    et al.
    SMHI, Forskningsavdelningen, Hydrologi.
    Carlsson, Bengt
    SMHI, Forskningsavdelningen, Hydrologi.
    Gardelin, Marie
    SMHI, Affärsverksamhet.
    Lindström, Göran
    SMHI, Forskningsavdelningen, Hydrologi.
    Pettersson, Anna
    SMHI, Forskningsavdelningen, Hydrologi.
    Rummukainen, Markku
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Climate change impacts on runoff in Sweden - assessments by global climate models, dynamical downscaling and hydrological modelling2001Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 16, nr 2, s. 101-112Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Swedish regional climate modelling programme, SWECLIM, started in 1997 with the main goal being to produce regional climate change scenarios over the Nordic area on a time scale of 50 to 100 yr. An additional goal is to produce water resources scenarios with a focus on hydropower production, dam safety, water supply and environmental aspects of water resources. The scenarios are produced by a combination of global climate models (GCMs), regional climate models and hydrological runoff models. The GCM simulations used thus far are 10 yr time slices from 2 different GCMs, UKMO HadCM2 from the Hadley Centre and the ECHAM4/OPYC3 of the Max Planck Institute for Meteorology. The regional climate model is a modified version of the international HIRLAM forecast model and the hydrological model is the HBV model developed at the Swedish Meteorological and Hydrological Institute. Scenarios of river runoff have been simulated for 6 selected basins covering the major climate regions in Sweden. Changes in runoff totals, runoff regimes and extreme values have been analysed with a focus on the uncertainties introduced by the choice of GCM and routines for estimation of evapotranspiration in the hydrological model. It is further shown how these choices affect the statistical return periods of future extremes in a design situation.

  • 3.
    Bärring, Lars
    et al.
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Holt, Tom
    Linderson, Maj-Lena
    Radziejewski, Madej
    Moriondo, Marco
    Palutikof, Jean P.
    Defining dry/wet spells for point observations, observed area averages, and regional climate model gridboxes in Europe2006Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 31, nr 1, s. 35-49Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A new method for optimising threshold values of dry/wet spells is evaluated. A set of indices is used to find the best threshold giving good correspondence between the frequency of dry/wet spells in Hadley Centre regional model (HadRM3) output, reference observations with predetermined thresholds, and area-averaged observations. The analyses focus on selected model gridboxes in 3 different European climate regimes (Sweden, UK, Italy), where station data are available from several locations. In addition, a pan-European analysis using the European Climate Assessment (ECA) dataset is carried out. Generally, there is good agreement between point observations and the corresponding area average using the common thresholds of 0.1 or 1.0 mm with observational data. Applying the optimal thresholds on the model output is important, as it typically results in substantially better agreement between the simulated and observed series of dry/wet days. The fitted optimal pan-European dry/wet threshold is (1) 0.47 or 0.15 mm, depending on model version, for the observed point data threshold of 0.1 mm, and (2) 1.2 or 0.56 mm, depending on model version, for the threshold of 1.0 mm.

  • 4. Christensen, Jens Hesselbjerg
    et al.
    Kjellström, Erik
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Giorgi, Filippo
    Lenderink, Geert
    Rummukainen, Markku
    SMHI, Samhälle och säkerhet.
    Weight assignment in regional climate models2010Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 44, nr 2-3, s. 179-194Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    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.

  • 5. Good, P.
    et al.
    Bärring, Lars
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Giannakopoulos, C.
    Holt, T.
    Palutikof, J.
    Non-linear regional relationships between climate extremes and annual mean temperatures in model projections for 1961-2099 over Europe2006Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 31, nr 1, s. 19-34Artikkel i tidsskrift (Fagfellevurdert)
  • 6. Hellstrom, C
    et al.
    Chen, D L
    Achberger, C
    Räisänen, Jouni
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Comparison of climate change scenarios for Sweden based on statistical and dynamical downscaling of monthly precipitation2001Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 19, nr 1, s. 45-55Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Two dynamically and statistically downscaled precipitation scenarios for Sweden are compared with respect to changes in the mean, The dynamically downscaled scenarios are generated by a 44 km version of the Rossby Centre regional climate model (RCM). The RCM is driven by data from 2 global greenhouse gas simulations sharing a 2.6degreesC global warming, one made by the HadCM2 and the other by the ECHAM4 general circulation model (GCM). The statistical downscaling model driven by the same GCMs is regression-based and incorporates large-scale circulation indices of the 2 geostrophic wind components (u and v), total vorticity (xi) and large-scale humidity at 850 hPa (q850) as predictors. The precipitation climates of the GCMs, RCMs and statistical models from the control runs are compared with respect to their ability to reproduce the observed seasonal cycle. Great improvements in the simulation of the seasonal cycle by all the downscaling models compared to the GCMs significantly increase the credibility of the downscaling models, The precipitation changes produced by the statistical models result from changes in all predictors, but the change in 4 is the greatest contributor in southern Sweden followed by q850 and u, while changes in q850 have greater effects in the northern parts of the country. The temporal and spatial variability of precipitation changes are higher in the statistically downscaled scenarios than in the dynamically downscaled ones. Comparisons of the 4 scenarios show that the spread of the scenarios created by the statistical model is on average larger than that between the RCM scenarios. The relatively large average spread is mainly due to the large differences found in summer. The seasonally averaged difference of the dynamical and statistical scenarios for the ECHAM4-based downscaled scenarios is 12%, and for the HadCM2 downscaled scenarios 21%. The differences in annual precipitation change are smaller, on average 4.5% among the HadCM2-based downscaled scenarios, and 6.9% among the ECHAM4-based downscaling scenarios.

  • 7.
    Johansson, Barbro
    et al.
    SMHI, Affärsverksamhet.
    Chen, D L
    Estimation of areal precipitation for runoff modelling using wind data: a case study in Sweden2005Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 29, nr 1, s. 53-61Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In mountainous regions, rainfall distribution is influenced by topography in combination with wind speed and direction. This has implications for estimates of catchment precipitation as input to hydrological models. The objective of this work was to investigate if wind information can be used to improve the accuracy of precipitation estimates, particularly for operational applications. A geostrophic wind, computed from pressure observations, was assumed to represent the airflow at an altitude relevant for precipitation distribution. Interpolated values of precipitation (optimal interpolation) were verified directly against point observations. In some mountainous catchments with low annual evapotranspiration, estimates of long-term mean areal precipitation could be verified through the water balance equation. The effects of the interpolations with and without wind information on the performance of a rainfall-runoff model were also investigated. There were 2 main factors in favour of using wind information in the interpolation: (1) a better description of the seasonal distribution; and (2) a lower sensitivity to reductions in the number of meteorological stations.

  • 8.
    Kjellström, Erik
    et al.
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Boberg, Fredrik
    Castro, Manuel
    Christensen, Jens Hesselbjerg
    Nikulin, Grigory
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Sanchez, Enrique
    Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models2010Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 44, nr 2-3, s. 135-150Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    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.

  • 9.
    Kjellström, Erik
    et al.
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Giorgi, Filippo
    Regional Climate Model evaluation and weighting Introduction2010Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 44, nr 2-3, s. 117-119Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    An ensemble of regional climate models downscaling reanalysis data has been evaluated against observations for the time period 1961-2000. Various aspects of model performance including both their representation of large-scale features and their ability to add value on smaller spatial scales have been considered. A set of metrics has been derived and combined into a performance-based weigthing system that is used in the production of probabilistic climate change projections. Strengths and weaknesses of weighting techniques for RCM ensembles are discussed.

  • 10.
    Kjellström, Erik
    et al.
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Thejll, Peter
    Rummukainen, Markku
    SMHI, Samhälle och säkerhet.
    Christensen, Jens H.
    Boberg, Fredrik
    Christensen, Ole B.
    Maule, Cathrine Fox
    Emerging regional climate change signals for Europe under varying large-scale circulation conditions2013Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 56, nr 2, s. 103-119Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A large ensemble of regional climate model projections was investigated regarding if and when they show an emergence of significant climate change signals in seasonal temperature and precipitation within Europe. The influence of the North Atlantic Oscillation (NAO), as simulated in the projections, was investigated. In most parts of Europe, the projections indicate robust emergence of temperature change in the first 2 decades of the 21st century, typically earlier for summer than for winter. For precipitation changes, signals generally emerge much later than for temperature. For Europe as a whole, the precipitation signals tend to emerge some 40 to 60 yr later than the temperature signals. In some sub-regions, robust signals for precipitation are not found within the studied period, i.e. until 2100. Some sub-regions, notably the Mediterranean area and Scandinavia, show different behaviour in some aspects compared to the ensemble-based results as a whole. NAO has some influence on the temperature change signals, which emerge earlier in winter for some models and regions if NAO is accounted for. For summer temperatures, the influence of NAO is less evident. Similarly, for precipitation, accounting for NAO leads to an earlier emergence in some regions and models. Here, we find an impact for both summer and winter.

  • 11.
    Meier, Markus
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Broman, Barry
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Kjellström, Erik
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Simulated sea level in past and future climates of the Baltic Sea2004Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 27, nr 1, s. 59-75Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Sea levels of the Baltic Sea in past and future climates were investigated based upon 6-hourly regional model results. For the future climate, the Rossby Centre Atmosphere Ocean model was used to perform a set of 30 yr time slice experiments. For each of the 2 driving global models HadAM3H and ECHAM4/OPYC3, one control run (1961 to 1990) and 2 scenario runs (2071 to 2100) based upon the scenarios A2 and B2 of the Special Report on Emission Scenarios (SRES) were conducted. To estimate uncertainties in the global and regional models, 3 sea level scenarios for the Baltic Sea were compiled assuming global average sea level rises between 0.09 and 0.88 m and considering land uplift and the impact of regional changes in wind direction and velocity from the time slice experiments. In the scenarios forced with ECHAM4/OPYC3 the mean sea level between October and April increases significantly compared to the control climate, and storm surges increase even more than monthly mean sea level. In the scenarios forced with HadAM3H the changes are mostly not significant. Depending on the sea level rise, the risk of flooding at the coasts may either decrease in the entire Baltic, or it may increase, especially at the eastern ends of the Gulf of Finland and Gulf of Riga and in Gdansk Bay. Here, maximum changes of about 1 m are found in the winter mean 99% quantiles of the sea level. For the past climate the regional ocean model was forced with reconstructed surface wind fields for 1903 to 1998. The results are close to observations, but storm surges in the western Baltic are underestimated.

  • 12.
    Meier, Markus
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Eilola, Kari
    SMHI, Forskningsavdelningen, Oceanografi.
    Almroth-Rosell, Elin
    SMHI, Forskningsavdelningen, Oceanografi.
    Climate-related changes in marine ecosystems simulated with a three-dimensional coupled physical -biogeochemical model of the Baltic Sea2011Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 48, s. 31-55Artikkel i tidsskrift (Fagfellevurdert)
  • 13.
    Meier, Markus
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Kauker, F
    Sensitivity of the Baltic Sea salinity to the freshwater supply2003Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 24, nr 3, s. 231-242Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The sensitivity of the Baltic Sea salinity to the freshwater supply is investigated using a 3-dimensional (3D) coupled sea-ice-ocean model. Today's climate is characterized by an average salinity of about 7.4 parts per thousand. and a freshwater supply, including river runoff and net precipitation, of about 16 000 m(3) s(-1). As recent results of some regional climate models have suggested a significant increase in precipitation in the Baltic catchment area due to anthropogenic climate change, in this study the response of salinity in the Baltic Sea to changing freshwater inflow is investigated. Of special interest is the possibility of the Baltic Sea becoming a freshwater sea with 0 parts per thousand salinity in the future. Therefore, model simulations with modified river runoff and precipitation for 1902-1998 were performed. The model is forced with daily sea-level observations in the Kattegat, monthly basin-wide discharge data, and reconstructed atmospheric surface data. The reconstruction utilizes a statistical model to calculate daily sea-level pressure, and monthly surface-air temperature, dew-point temperature, precipitation, and cloud-cover fields. It is assumed that the Kattegat deepwater salinity of about 33 parts per thousand. will not change regardless of the changed freshwater supply. In most of the experiments the final stratification is almost in a steady state after 100 yr. We found that even for a freshwater supply increased by 100% compared to 1902-1998 the Baltic Sea cannot be classified as a freshwater sea. A pronounced halocline still separates the upper and lower layers in the Baltic Proper, limiting the impact of direct wind mixing to the surface layer. A calculated phase diagram suggests that the relationship between freshwater supply and average salinity of the final steady state is non-linear. The results of the 3D model are in agreement with an analytical steady-state model assumed to work for freshwater changes smaller than 30 %. The latter model was applied in scenarios for the average salinity of the Baltic Sea.

  • 14.
    Omstedt, Anders
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Gustafsson, B
    Rodhe, J
    Walin, G
    Use of Baltic Sea modelling to investigate the water cycle and the heat balance in GCM and regional climate models2000Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 15, nr 2, s. 95-108Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Results from the first simulations with the Rossby Centre regional climate atmosphere (RCA) model were used to force 2 versions of process-oriented models of the Baltic Sea-one time-dependent, the other considering the mean state. The purpose was primarily to obtain a first scenario of the future state of the Baltic Sea. In addition, we looked at this exercise as a method to evaluate the consistency of the water cycle and the heat balance produced by atmospheric climate models. The RCA model is a high-resolution atmospheric regional model which is forced with lateral conditions from a global model. A large-scale Baltic drainage basin hydrological model, forced by the RCA model, was used to simulate river runoff. Using RCA model data from the control run we found that that the temperature and ice conditions in the Baltic Sea were reasonably realistic while the salinity field was poorly reproduced. We conclude that the modelling of the water cycle needs considerable improvement. We also conclude that the time for the Baltic Sea to respond to the water cycle is much longer than the integration period so far used with the RCA model. Forcing the ocean models with RCA model data from a future scenario with an enhanced greenhouse effect gives an increased sea-surface temperature and a much reduced extent of ice in the Baltic Sea due to climate warming. Also the salinity is reduced, which implies possible serious effects on the future marine life in the Baltic Sea. The results demonstrate that accurate atmospheric modelling of not only the heat balance but also the water cycle is crucial for Baltic Sea climate simulations.

  • 15.
    Rutgersson, Anna
    et al.
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Omstedt, Anders
    SMHI, Forskningsavdelningen, Oceanografi.
    Räisänen, Jouni
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Net precipitation over the Baltic Sea during present and future climate conditions2002Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 22, nr 1, s. 27-39Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    By using a process-oriented ocean model forced with data from a gridded synoptic database, net precipitation values (precipitation minus evaporation) over the Baltic Sea are obtained. For a range of realistic meteorological forcing the average annual value obtained from an 18 yr (1981-1998) simulation ranges between 1100 and 2500 m(3) s(-1). The monthly variations are significant with the highest values occurring in early summer and even negative values in late autumn. Ice is an important factor, and the net precipitation is close to zero in the southern basins with no ice. Calculated net precipitation for a 98 yr period (1901-1998) using river runoff and maximum ice extent indicates that the investigated 18 yr period was wetter than the almost 100 yr climate mean. A realistic climate estimate of net precipitation during the 20th century is estimated to be 1500 +/-1000 m(3) s(-1). The evaluation of 2 present day regional climate simulations indicated high precipitation, low evaporation, and thus excessive net precipitation compared to the climate estimate from this investigation. When simulating the effect of increased greenhouse gases, the change in net precipitation was positive but small due to the compensating effects of increased precipitation and increased evaporation associated with increased temperature and reduced ice.

  • 16. Skalak, Petr
    et al.
    Deque, Michel
    Belda, Michal
    Farda, Ales
    Halenka, Tomas
    Csima, Gabriella
    Bartholy, Judit
    Caian, Mihaela
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Spiridonov, Valery
    CECILIA regional climate simulations for the present climate: validation and inter-comparison2014Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 60, nr 1, s. 1-12Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We investigated high-resolution simulations of regional climate models (RCMs) driven by ERA-40 reanalyses over areas of selected European countries (Austria, Czech Republic, Hungary, Slovakia and Romania) for the period 1961-1990. RCMs were run at a spatial resolution of 10 km in the framework of the CECILIA project, and their outputs were compared with the EOBS dataset of gridded observations and RCM simulations at coarser 25 km resolution from the ENSEMBLES project to identify a possible gain from the CECILIA experiments over ENSEMBLES. Cold biases of air temperature and wet biases of precipitation dominate in the CECILIA simulations. Spatial variability and distribution of the air temperature field are well captured. The precipitation field, relative to observations, often shows inadequately small spatial variability and lowered correlations but is nevertheless comparable to the ENSEMBLES model. Inter-annual variability (IAV) of air temperature is captured differently among seasons but mostly improved in CECILIA compared with ENSEMBLES. Precipitation IAV shows a similar or worse score. The detected weaknesses found within the validation of the CECILIA RCMs are attributed to the resolution dependence of the set of physical parameterizations in the models and the choice of integration domain. The gain obtained by using a high resolution over a small domain (as in CECILIA) relative to a lower resolution (25 km) over a larger domain (as in ENSEMBLES) is clear for air temperature but limited for precipitation.

  • 17. Winsor, P
    et al.
    Rodhe, J
    Omstedt, Anders
    SMHI, Forskningsavdelningen, Oceanografi.
    Baltic Sea ocean climate: an analysis of 100 yr of hydrographic data with focus on the freshwater budget2001Inngår i: Climate Research (CR), ISSN 0936-577X, E-ISSN 1616-1572, Vol. 18, nr 1-2, s. 5-15Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Baltic Sea climate is analysed based upon long-term oceanographic measurements. The objective of the work is to study the natural variability of present day climate with focus on the freshwater budget. The results are designed to be used for validation of climate models and for discrimination of the significance of modelled climate change scenarios. Almost 100 yr of observations are used in the study, including data for river runoff, water exchange through the Danish Straits (as calculated from river runoff and from sea level data from the Kattegat), salinity data from the Baltic Sea and the Kattegat, and oxygen content in the deep Baltic Sea. The analyses illustrate that freshwater supply to the Baltic shows large variations on time scales up to several decades. The long-term variations in freshwater storage are closely correlated to accumulated changes in river runoff. This indicates strong positive feedback between the amount of outflowing surface water from the Baltic Sea and the salinity of the inflowing Kattegat water. One implication of the study is that climate control simulations must cover several decades, probably up to 100 yr in order to capture the natural variability of present day climate. Also, models designed to study climate change for the Baltic Sea probably need to start integrating from the present day.

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