A gridded dataset (SMHI Gridded Climatology - SMHIGridClim) has been produced forthe years 1961 - 2018 over an area covering the Nordic countries on a grid with 2.5 kmhorizontal resolution. The variables considered are the two meter temperature and twometer relative humidity on 1, 3 or 6 hour resolution, varying over the time periodcovered, the daily minimum and maximum temperatures, the daily precipitation and thedaily snow depth. The gridding was done using optimal interpolation with the gridppopen source software from the Norwegian Meteorological Institute.Observations for the analysis are provided by the Swedish, Finish and Norwegianmeteorological institutes, and the ECMWF. The ECA&D observation data set (e.g. usedfor the gridded E-OBS dataset) was considered for inclusion but was left out because ofcomplications with time stamps and accumulation periods varying between countries andperiods. Quality check of the observations was performed using the open source softwareTITAN, also developed at the Norwegian Meteorological Institute.The first guess to the optimal interpolation was given by statistically downscaledforecasts from the UERRA-HARMONIE reanalysis at 11 km horizontal resolution. Thedownscaling was done to fit the output from the operational MEPS NWP system at 2.5km with a daily and yearly variation in the downscaling parameters.The quality of the SMHIGridClim dataset, in terms of annual mean RMSE, was shown tobe similar to that of gridded datasets covering the other Nordic countries; “seNorge”from Norway and the dataset “FMI_ClimGrid” from Finland.

Twenty-one land-surface schemes (LSSs) participated in the Project for Intercomparison of Land-surface Parameterizations (PILPS) Phase 2(e) experiment, which used data from the Tome-Kalix Rivers in northern Scandinavia. Atmospheric forcing data (precipitation, air temperature, specific humidity, wind speed, downward shortwave and longwave radiation) for a 20-year period (1979-1998) were provided to the 21 participating modeling groups for 218 1/4degrees grid cells that represented the study domain. The first decade (1979-1988) of the period was used for model spin-up. The quality of meteorologic forcing variables is of particular concern in high-latitude experiments and the quality of the gridded dataset was assessed to the extent possible. The lack of sub-daily precipitation, underestimation of true precipitation and the necessity to estimate incoming solar radiation were the primary data concerns for this study. The results from two of the three types of runs are analyzed in this, the first of a three-part paper: (1) calibration-validation runs-calibration of model parameters using observed streamflow was allowed for two small catchments (570 and 1300 km(2)), and parameters were then transferred to two other catchments of roughly similar size (2600 and 1500 km(2)) to assess the ability of models to represent ungauged areas elsewhere; and 2) reruns-using revised forcing data (to resolve problems with apparent underestimation of solar radiation of approximately 36%, and certain other problems with surface wind in the original forcing data). Model results for the period 1989-1998 are used to evaluate the performance of the participating land-surface schemes in a context that allows exploration of their ability to capture key processes spatially. In general, the experiment demonstrated that many of the LSSs are able to capture the limitations imposed on annual latent heat by the small net radiation available in this high-latitude environment. Simulated annual average net radiation varied between 16 and 40 W/m(2) for the 21 models, and latent heat varied between 18 and 36 W/m(2). Among-model differences in winter latent heat due to the treatment of aerodynamic resistance appear to be at least as important as those attributable to the treatment of canopy interception. In many models, the small annual net radiation forced negative sensible heat on average, which varied among the models between - 11 and 9 W/m(2). Even though the largest evaporation rates occur in the summer (June, July and August), model-predicted snow sublimation in winter has proportionately more influence on differences in annual runoff volume among the models. A calibration experiment for four small sub-catchments of the Torne-Kalix basin showed that model parameters that are typically adjusted during calibration, those that control storage of moisture in the soil column or on the land surface via ponding, influence the seasonal distribution of runoff, but have relatively little impact on annual runoff ratios. Similarly, there was no relationship between annual runoff ratios and the proportion of surface and subsurface discharge for the basin as a whole. (C) 2003 Elsevier Science B.V. All rights reserved.

The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991-2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons.

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.

A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. The first set of simulations with a horizontal resolution of 12.5 km was completed for the new emission scenarios RCP4.5 and RCP8.5 with more simulations expected to follow. The aim of this paper is to present this data set to the different communities active in regional climate modelling, impact assessment and adaptation. The EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The large-scale patterns of changes in mean temperature and precipitation are similar in all three scenarios, but they differ in regional details, which can partly be related to the higher resolution in EURO-CORDEX. The results strengthen those obtained in ENSEMBLES, but need further investigations. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities.

Dynamic modelling was used to quantify the impact of projected climate change, and potential changes in population and land use, on phosphorus (P) export from a sub-catchment in SW Ireland using the Generalised watershed Loading Functions (GWLF) model. Overall the results indicated that the increase in annual total phosphorus loads attributable to climate change was greater than that from either population or land use change, and therefore that future climate variability will pose an increasingly significant threat to the successful long-term implementation of catchment management initiatives. The seasonal pattern in projected P export mirrored changes in streamflow, with higher rates between January and April and lower rates in summer. The potential reduction in export in summer was, however, negated when increases in population were included in simulations. A change in the slurry spreading period from that stipulated in national regulations to the months between April and September could potentially mitigate against future increases in dissolved P export in spring. The results indicate that projected changes in climate should be included when undertaking modelling exercises in support of decision making for catchment management plans. (C) 2009 Elsevier Ltd. All rights reserved.

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.

The meteorological characteristics of the drought of 2005 in Amazonia, one of the most severe in the last 100 years were assessed using a suite of seven regional models obtained from the CLARIS LPB project. The models were forced with the ERA-Interim reanalyses as boundary conditions. We used a combination of rainfall and temperature observations and the low-level circulation and evaporation fields from the reanalyses to determine the climatic and meteorological characteristics of this particular drought. The models reproduce in some degree the observed annual cycle of precipitation and the geographical distribution of negative rainfall anomalies during the summer months of 2005. With respect to the evolution of rainfall during 2004-2006, some of the models were able to simulate the negative rainfall departures during early summer of 2005 (December 2004 to February 2005). The interannual variability of rainfall anomalies for both austral summer and fall over northern and southern Amazonia show a large spread among models, with some of them capable of reproducing the 2005 observed negative rainfall departures (four out of seven models in southern Amazonia during DJF). In comparison, all models simulated the observed southern Amazonia negative rainfall and positive air temperature anomalies during the El Nino-related drought in 1998. The spatial structure of the simulated rainfall and temperature anomalies in DJF and MAM 2005 shows biases that are different among models. While some models simulated the observed negative rainfall anomalies over parts of western and southern Amazonia during DJF, others simulated positive rainfall departures over central Amazonia. The simulated circulation patterns indicate a weaker northeasterly flow from the tropical North Atlantic into Amazonia, and reduced flows from southern Amazonia into the La Plata basin in DJF, which is consistent with observations. In general, we can say that in some degree the regional models are able to capture the response to the forcing from the tropical Atlantic during the drought of 2005 in Amazonia. Moreover, extreme climatic conditions in response to anomalous low-level circulation features are also well captured, since the boundary conditions come from reanalysis and the models are largely constrained by the information provided at the boundaries. The analysis of the 2005 drought suggests that when the forcing leading to extreme anomalous conditions is associated with both local and non-local mechanisms (soil moisture feedbacks and remote SST anomalies, respectively) the models are not fully capable of representing these feedbacks and hence, the associated anomalies. The reason may be a deficient reproduction of the land-atmosphere interactions.

The assessment report of the 4th International Panel on Climate Change confirms that global warming is strongly affecting biological systems and that 20-30% of species risk extinction from projected future increases in temperature. It is essential that any measures taken to conserve individual species and their constituent populations against climate-mediated declines are appropriate. The release of captive bred animals to augment wild populations is a widespread management strategy for many species but has proven controversial. Using a regression model based on a 37-year study of wild and sea ranched Atlantic salmon (Salmo salar) spawning together in the wild, we show that the escape of captive bred animals into the wild can substantially depress recruitment and more specifically disrupt the capacity of natural populations to adapt to higher winter water temperatures associated with climate variability. We speculate the mechanisms underlying this seasonal response and suggest that an explanation based on bio-energetic processes with physiological responses synchronized by photoperiod is plausible. Furthermore, we predict, by running the model forward using projected future climate scenarios, that these cultured fish substantially increase the risk of extinction for the studied population within 20 generations. In contrast, we show that positive outcomes to climate change are possible if captive bred animals are prevented from breeding in the wild. Rather than imposing an additional genetic load on wild populations by releasing maladapted captive bred animals, we propose that conservation efforts should focus on optimizing conditions for adaptation to occur by reducing exploitation and protecting critical habitats. Our findings are likely to hold true for most poikilothermic species where captive breeding programmes are used in population management.

We investigate the performance of one stretched-grid atmospheric global model, five different regional climate models and a statistical downscaling technique in simulating 3 months (January 1971, November 1986, July 1996) characterized by anomalous climate conditions in the southern La Plata Basin. Models were driven by reanalysis (ERA-40). The analysis has emphasized on the simulation of the precipitation over land and has provided a quantification of the biases of and scatter between the different regional simulations. Most but not all dynamical models underpredict precipitation amounts in south eastern South America during the three periods. Results suggest that models have regime dependence, performing better for some conditions than others. The models' ensemble and the statistical technique succeed in reproducing the overall observed frequency of daily precipitation for all periods. But most models tend to underestimate the frequency of dry days and overestimate the amount of light rainfall days. The number of events with strong or heavy precipitation tends to be under simulated by the models.

A simple, rapid, and flexible modelling approach was applied to explore the impacts of climate change on hydrologic inputs and consequent implications for nutrient loading to Lake Malaren, Sweden using a loading function model (GWLF). The first step in the process was to adapt the model for use in a large and complex Swedish catchment. We focused on the Galten basin with four rivers draining into the western region of Malaren. The catchment model was calibrated and tested using long-term historical data for river discharge and dissolved nutrients (N, P). Then multiple regional climate model simulation results were downscaled to the local catchment level, and used to simulate possible hydrological and nutrient loading responses to warmer world scenarios. Climate change projections for the rivers of Galten basin show profound changes in the timing of discharge and nutrient delivery due to increased winter precipitation and earlier snow melt. Impacts on total annual discharge and load are minimal, but the alteration in river flow regime and the timing of nutrient delivery for future climate scenarios is strikingly different from historical conditions.

An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of similar to 50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989-2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precipitation climate compared to that from their boundary condition dataset, that is, ERA-Interim. A common problem in the majority of the RCMs is that precipitation is triggered too early during the diurnal cycle, although a small subset of models does have a reasonable representation of the phase of the diurnal cycle. The systematic bias in the diurnal cycle is not improved when the ensemble mean is considered. Based on this performance analysis, it is assessed that the present set of RCMs can be used to provide useful information on climate projections over Africa.

The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990-2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical SA.

Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above-freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal "best'' model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.

A basic analysis is presented for a series of regional climate change simulations that were conducted by the Swedish Rossby Centre and contribute to the PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects) project. For each of the two driving global models HadAM3H and ECHAM4/OPYC3, a 30-year control run and two 30-year scenario runs (based on the SRES A2 and B2 emission scenarios) were made with the regional model. In this way, four realizations of climate change from 1961-1990 to 2071-2100 were obtained. The simulated changes are larger for the A2 than the B2 scenario (although with few qualitative differences) and in most cases in the ECHAM4/OPYC3-driven (RE) than in the HadAM3H-driven (RH) regional simulations. In all the scenario runs, the warming in northern Europe is largest in winter or late autumn. In central and southern Europe, the warming peaks in summer when it locally reaches 10 degreesC in the RE-A2 simulation and 6-7 degreesC in the RH-A2 and RE-B2 simulations. The four simulations agree on a general increase in precipitation in northern Europe especially in winter and on a general decrease in precipitation in southern and central Europe in summer, but the magnitude and the geographical patterns of the change differ markedly between RH and RE. This reflects very different changes in the atmospheric circulation during the winter half-year, which also lead to quite different simulated changes in windiness. All four simulations show a large increase in the lowest minimum temperatures in northern, central and eastern Europe, most likely due to reduced snow cover. Extreme daily precipitation increases even in most of those areas where the mean annual precipitation decreases.

A series of six general circulation model (GCM) driven regional climate simulations made at the Rossby Centre, SMHI, during the year 2002 are documented. For both the two driving GCMs HadAM3H andECHAM4/OPYC3, a 30-year (1961-1990) control run and two 30-year (2071-2100) scenario runs have been made. The scenario runs are based on the IPCC SRES A2 and B2 forcing scenarios. These simulations were made at 49 km atmospheric resolution and they are part of the European PRUDENCE project.Many aspects of the simulated control climates compare favourably with observations, but some problems are also evident. For example, the simulated cloudiness and precipitation appear generally too abundant in northern Europe (although biases in precipitation measurements complicate the interpretation), whereas too clear and dry conditions prevail in southern Europe. There is a lot of similarity between the HadAM3Hdriven (RCAO-H) and ECHAM4/OPYC3-driven (RCAO-E) control simulations, although the problems associated with the hydrological cycle and cloudiness are somewhat larger in the latter.The simulated climate changes (2071-2100 minus 1961-1990) depend on both the forcing scenario (the changes are generally larger for A2 than B2) and the driving global model (the largest changes tend to occur in RCAO-E). In all the scenario simulations, the warming in northern Europe is largest in winter or autumn. In central and southern Europe, the warming peaks in summer and reaches in the RCAO-E A2 simulation locally 10°C. The four simulations agree on a general increase in precipitation in northern Europe especiallyin winter and on a general decrease in precipitation in southern and central Europe in summer, but the magnitude and the geographical patterns of the change differ a lot between RCAO-H and RCAO-E. Thisreflects very different changes in the atmospheric circulation during the winter half-year, which also have a large impact on the simulated changes in windiness. A very large increase in the lowest minimumtemperatures occurs in a large part of Europe, most probably due to reduced snow cover. Extreme daily precipitation increases even in most of those areas where the mean annual precipitation decreases.

This paper describes the impact of changes in aerodynamic roughness length for snow-covered surfaces in a land-surface scheme (LSS) on simulated runoff and evapotranspiration. The study was undertaken as the LSS in question produced widely divergent results in runoff, depending on whether it was used in uncoupled one-dimensional simulations forced by observations from the PILPS2e project, or in three-dimensional simulations coupled to an atmospheric model. The LSS was applied in two versions (LSS1 and LSS2) for both uncoupled and coupled simulations, where the only difference between the two versions was in the roughness length of latent heat used over snow-covered surfaces. The results show that feedback mechanisms in temperature and humidity in the coupled simulations were able to compensate for deficiencies in parameterizations and therefore, LSS1 and LSS2 yielded similar runoff results in this case. Since such feedback mechanisms are absent in uncoupled simulations, the two LSS versions produced very different runoff results in the uncoupled case. However, the magnitude of these feedback mechanisms is small compared to normal variability in temperature and humidity and cannot, by themselves, reveal any deficiencies in a parameterization. The conclusion we obtained is that the magnitude of the aerodynamic resistance is important to correctly simulate fluxes and runoff, but feedback mechanisms in a coupled model can partly compensate for errors. (C) 2003 Elsevier Science B.V. All rights reserved.

This report describes the physical processes as part of the surface scheme in the Rossby Centre Regional Atmospheric Climate Model (RCA4). Or more strictly for the version used for the CORDEX downscalings with RCA4. The most important aspects of the surface scheme that are changed with respect to RCA3 are that (i) a new physiography data base is used, (ii) the number of soil layers with respect to soil moisture are increased from two to three and there is also separate soil columns with respect to soil water under forest and open land, respectively, (iii) an exponential root distribution is used, (iv) the density of organic carbon is used to modify soil properties, (v) the prognostic snow albedo is modified to perform better in cold-climate conditions, (vi) Flake is introduced as lake model and lake depth is defined from a global lake-depth data base, (vii) the dynamic vegetation model LPJ-GUESS is introduced for vegetation-climate feedback studies.

This report describes the physical processes as part of the Land-Surface Scheme (LSS) in the Rossby Centre Regional Atmospheric Climate Model (RCA3). The LSS is a tiled scheme with the three main tiles with respect to temperature: forest, open land, and snow. The open land tile is divided into a vegetated and a bare soil part for latent heat flux calculations. The individual fluxes of heat and momentum from these tiles are weighted in order to obtain grid-averaged values at the lowest atmospheric model level according to the fractional areas of the tiles. The forest tile is internally divided into three sub-tiles: forest canopy, forest floor soil, and snow on forest floor. All together this gives three to five different surface energy balances depending on if snow is present or not.The soil is divided into five layers with respect to temperature, with a no-flux boundary condition at three meters depth, and into two layers with respect to soil moisture, with a maximum depth of just above 2.2 meters. Runoff generated at the bottom of the deep soil layer may be used as input to a routing scheme.In addition to the soil moisture storages there are six more water storages in the LSS: interception of water on open land vegetation and on forest canopy, snow water equivalent of open land and forest snow, and liquid water content in both snow storages.Diagnostic variables of temperature and humidity at 2m and wind at 10m are calculated individually for each tile.

The impact of lakes on the European climate is considered by analysing two 30-year regional climate model (RCM) simulations. The RCM applied is the Rossby Centre regional climate model RCA3.5. A simulation where all lakes in the model domain are replaced by land surface is compared with a simulation where the effect of lakes is accounted for through the use of the lake model FLake coupled to RCA. The difference in 2m open-land air temperature between the two simulations shows that lakes induce a warming on the European climate for all seasons. The greatest impact is seen during autumn and winter over southern Finland and western Russia where the warming exceeds 1 C. Locally, e.g. over southern Finland and over Lake Ladoga, the convective precipitation is enhanced by 20%-40% during late summer and early autumn while it is reduced by more than 70% over Lake Ladoga during early summer.

The results of an ensemble of regional climate model (RCM) simulations over South America are presented. This is the first coordinated exercise of regional climate modelling studies over the continent, as part of the CLARIS-LPB EU FP7 project. The results of different future periods, with the main focus on (2071-2100) is shown, when forced by several global climate models, all using the A1B greenhouse gases emissions scenario. The analysis is focused on the mean climate conditions for both temperature and precipitation. The common climate change signals show an overall increase of temperature for all the seasons and regions, generally larger for the austral winter season. Future climate shows a precipitation decrease over the tropical region, and an increase over the subtropical areas. These climate change signals arise independently of the driving global model and the RCM. The internal variability of the driving global models introduces a very small level of uncertainty, compared with that due to the choice of the driving model and the RCM. Moreover, the level of uncertainty is larger for longer horizon projections for both temperature and precipitation. The uncertainty in the temperature changes is larger for the subtropical than for the tropical ones. The current analysis allows identification of the common climate change signals and their associated uncertainties for several subregions within the South American continent.

Responses of precipitation seasonal means and extremes over South America in a downscaling of a Climate change scenario are assessed with the Rossby Centre Regional Atmospheric Model (RCA). The anthropogenic warming under A1B scenario influences more on the likelihood of occurrence of severe extreme events like heavy precipitation and dry spells than on the mean seasonal precipitation. The risk of extreme precipitation increases in the La Plata Basin with a factor of 1.5-2.5 during all seasons and in the northwestern part of the continent with a factor 1.5-3 in summer, while it decreases in central and northeastern Brazil during winter and spring. The maximum amount of 5-days precipitation increases by up to 50% in La Plata Basin, indicating risks of flooding. Over central Brazil and the Bolivian lowland, where present 5-days precipitation is higher, the increases are similar in magnitude and could cause less impacts. In southern Amazonia, northeastern Brazil and the Amazon basin, the maximum number of consecutive dry days increases and mean winter and spring precipitation decreases, indicating a longer dry season. In the La Plata Basin, there is no clear pattern of change for the dry spell duration.

We summarize the recent progress in regional climate modeling in South America with the Rossby Centre regional atmospheric climate model (RCA3-E), with emphasis on soil moisture processes. A series of climatological integrations using a continental scale domain nested in reanalysis data were carried out for the initial and mature stages of the South American Monsoon System (SAMS) of 1993-92 and were analyzed on seasonal and monthly timescales. The role of including a spatially varying soil depth, which extends to 8 m in tropical forest, was evaluated against the standard constant soil depth of the model of about 2 m, through two five member ensemble simulations. The influence of the soil depth was relatively weak, with both beneficial and detrimental effects on the simulation of the seasonal mean rainfall. Secondly, two ensembles that differ in their initial state of soil moisture were prepared to study the influence of anomalously in subtropical South America as well. Finally, we calculated the soil moisture-precipitation coupling strength through comparing a ten member ensemble forced by the same space-time series of soil moisture fields with an ensemble with interactive soil moisture. Coupling strength is defined as the degree to which the prescribed boundary conditions affect some atmospheric quantity in a climate model, in this context a quantification of the fraction of atmospheric variability that can be ascribed to soil moisture anomalies. La Plata Basin appears as a region where the precipitation is partly controlled by soil moisture, especially in November and January. The continental convective monsoon regions and subtropical South America appears as a region with relatively high coupling strength during the mature phase of monsoon development dry and wet soil moisture initial conditions on the intraseasonal development of the SAMS. In these simulations the austral winter soil moisture initial condition has a strong influence on wet season rainfall over feed back upon the monsoon, not only over the Amazon region but in subtropical South America as well. Finally, we calculated the soil moisture-precipitation coupling strength through comparing a ten member ensemble forced by the same space-time series of soil moisture fields with an ensemble with interactive soil moisture. Coupling strength is defined as the degree to which the prescribed boundary conditions affect some atmospheric quantity in a climate model, in this context a quantification of the fraction of atmospheric variability that can be ascribed to soil moisture anomalies. La Plata Basin appears as a region where the precipitation is partly controlled by soil moisture, especially in November and January. The continental convective monsoon regions and subtropical South America appears as a region with relatively high coupling strength during the mature phase of monsoon development.

The capability of a set of 7 coordinated regional climate model simulations performed in the framework of the CLARIS-LPB Project in reproducing the mean climate conditions over the South American continent has been evaluated. The model simulations were forced by the ERA-Interim reanalysis dataset for the period 1990-2008 on a grid resolution of 50 km, following the CORDEX protocol. The analysis was focused on evaluating the reliability of simulating mean precipitation and surface air temperature, which are the variables most commonly used for impact studies. Both the common features and the differences among individual models have been evaluated and compared against several observational datasets. In this study the ensemble bias and the degree of agreement among individual models have been quantified. The evaluation was focused on the seasonal means, the area-averaged annual cycles and the frequency distributions of monthly means over target sub-regions. Results show that the Regional Climate Model ensemble reproduces adequately well these features, with biases mostly within +/- 2 A degrees C and +/- 20 % for temperature and precipitation, respectively. However, the multi-model ensemble depicts larger biases and larger uncertainty (as defined by the standard deviation of the models) over tropical regions compared with subtropical regions. Though some systematic biases were detected particularly over the La Plata Basin region, such as underestimation of rainfall during winter months and overestimation of temperature during summer months, every model shares a similar behavior and, consequently, the uncertainty in simulating current climate conditions is low. Every model is able to capture the variety in the shape of the frequency distribution for both temperature and precipitation along the South American continent. Differences among individual models and observations revealed the nature of individual model biases, showing either a shift in the distribution or an overestimation or underestimation of the range of variability.

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.

A new regional coupled model system for the North Sea and the Baltic Sea is developed, which is composed of the regional setup of ocean model NEMO, the Rossby Centre regional climate model RCA4, the sea ice model LIM3 and the river routing model CaMa-Flood. The performance of this coupled model system is assessed using a simulation forced with ERA-Interim reanalysis data at the lateral boundaries during the period 1979-2010. Compared to observations, this coupled model system can realistically simulate the present climate. Since the active coupling area covers the North Sea and Baltic Sea only, the impact of the ocean on the atmosphere over Europe is small. However, we found some local, statistically significant impacts on surface parameters like 2m air temperature and sea surface temperature (SST). A precipitation-SST correlation analysis indicates that both coupled and uncoupled models can reproduce the air-sea relationship reasonably well. However, the coupled simulation gives slightly better correlations even when all seasons are taken into account. The seasonal correlation analysis shows that the air-sea interaction has a strong seasonal dependence. Strongest discrepancies between the coupled and the uncoupled simulations occur during summer. Due to lack of air-sea interaction, in the Baltic Sea in the uncoupled atmosphere-standalone run the correlation between precipitation and SST is too small compared to observations, whereas the coupled run is more realistic. Further, the correlation analysis between heat flux components and SST tendency suggests that the coupled model has a stronger correlation. Our analyses show that this coupled model system is stable and suitable for different climate change studies.

We performed simulations of future biophysical vegetation-climate feedbacks with a regional Earth System Model, RCA-GUESS, interactively coupling a regional climate model and a process-based model of vegetation dynamics and biogeochemistry. Simulated variations in leaf area index and in the relative coverage of evergreen forest, deciduous forest, and open land vegetation in response to simulated climate influence atmospheric state via variations in albedo, surface roughness, and the partitioning of the land-atmosphere heat flux into latent and sensible components. The model was applied on a similar to 50 x 50 km grid over Europe under a future climate scenario. Three potential "hot spots" of vegetation-climate feedbacks could be identified. In the Scandinavian Mountains, reduced albedo resulting from the snow-masking effect of forest expansion enhanced the winter warming trend. In central Europe, the stimulation of photosynthesis and plant growth by "CO2 fertilization" mitigated warming, through a negative evapotranspiration feedback associated with increased vegetation cover and leaf area index. In southern Europe, increased summer dryness restricted plant growth and survival, causing a positive warming feedback through reduced evapotranspiration. Our results suggest that vegetation-climate feedbacks over the European study area will be rather modest compared to the radiative forcing of increased global CO2 concentrations but may modify warming projections locally, regionally, and seasonally, compared with results from traditional "off-line" regional climate models lacking a representation of the relevant feedback mechanisms.

Recent accelerated warming over the Arctic coincides with sea ice reduction and shifting patterns of land cover. We use a state-of-the-art regional Earth system model, RCAO-GUESS, which comprises a dynamic vegetation model (LPJ-GUESS), a regional atmosphere model (RCA), and an ocean sea ice model (RCO), to explore the dynamic coupling between vegetation and sea ice during 1989-2011. Our results show that RCAO-GUESS captures recent trends in observed sea ice concentration and extent, with the inclusion of vegetation dynamics resulting in larger, more realistic variations in summer and autumn than the model that does not account for vegetation dynamics. Vegetation feedbacks induce concomitant changes in downwelling longwave radiation, near-surface temperature, mean sea level pressure, and sea ice reductions, suggesting a feedback chain linking vegetation change to sea ice dynamics. This study highlights the importance of including interactive vegetation dynamics in modeling the Arctic climate system, particularly when predicting sea ice dynamics. Plain Language Summary Recent accelerated warming over the Arctic is associated with dramatic changes in the physical environment, among which unprecedented sea ice decline has received particular attention. In this study, we use a regional Earth system model accounting for interactive coupling between the atmosphere, land vegetation, and sea ice dynamics to explore their potential links. Our model simulates observed spatiotemporal patterns of sea ice thickness and extent reasonably well. Furthermore, the results show that feedbacks of warming-driven vegetation changes on the near-surface radiation balance can cause greater variations in sea ice between seasons, which can contribute to an accelerated trend of sea ice reduction. The changes in mean sea level pressure caused by vegetation changes can alter the transport of energy and warm the land, sea, and sea ice surfaces. Downwelling longwave radiation is the dominant factor contributing to the near-surface warming and increased sea ice melting. Our study highlights the importance of adopting fully coupled Earth system models that account for interactive effects of vegetation dynamics on the physical climate system, in particular when analyzing the reduction of sea ice in the Arctic.

Continued warming of the Arctic will likely accelerate terrestrial carbon (C) cycling by increasing both uptake and release of C. Yet, there are still large uncertainties in modelling Arctic terrestrial ecosystems as a source or sink of C. Most modelling studies assessing or projecting the future fate of C exchange with the atmosphere are based on either stand-alone process-based models or coupled climate-C cycle general circulation models, and often disregard biogeophysical feedbacks of land-surface changes to the atmosphere. To understand how biogeophysical feedbacks might impact on both climate and the C budget in Arctic terrestrial ecosystems, we apply the regional Earth system model RCA-GUESS over the CORDEX-Arctic domain. The model is forced with lateral boundary conditions from an EC-Earth CMIP5 climate projection under the representative concentration pathway (RCP) 8.5 scenario. We perform two simulations, with or without interactive vegetation dynamics respectively, to assess the impacts of biogeophysical feedbacks. Both simulations indicate that Arctic terrestrial ecosystems will continue to sequester C with an increased uptake rate until the 2060-2070s, after which the C budget will return to a weak C sink as increased soil respiration and biomass burning outpaces increased net primary productivity. The additional C sinks arising from biogeophysical feedbacks are approximately 8.5 Gt C, accounting for 22% of the total C sinks, of which 83.5% are located in areas of extant Arctic tundra. Two opposing feedback mechanisms, mediated by albedo and evapotranspiration changes respectively, contribute to this response. The albedo feedback dominates in the winter and spring seasons, amplifying the near-surface warming by up to 1.35 degrees C in spring, while the evapotranspiration feedback dominates in the summer months, and leads to a cooling of up to 0.81 degrees C. Such feedbacks stimulate vegetation growth due to an earlier onset of the growing season, leading to compositional changes in woody plants and vegetation redistribution.