A B S T R A C T Possible future changes in Baltic Sea acidÁbase (pH) and oxygen balances were studied using a catchmentÁsea coupled model system and numerical experiments based on meteorological and hydrological forcing datasets and scenarios. By using objective statistical methods, climate runs for present climate conditions were examined and evaluated using Baltic Sea modelling. The results indicate that increased nutrient loads will not inhibit future Baltic Sea acidification; instead, the seasonal pH cycle will be amplified by increased biological production and mineralization. All examined scenarios indicate future acidification of the whole Baltic Sea that is insensitive to the chosen global climate model. The main factor controlling the direction and magnitude of future pH changes is atmospheric CO 2 concentration (i.e. emissions). Climate change and land-derived changes (e.g. nutrient loads) affect acidification mainly by altering the seasonal cycle and deep-water conditions. Apart from decreasing pH, we also project a decreased saturation state of calcium carbonate, decreased respiration index and increasing hypoxic area Á all factors that will threaten the marine ecosystem. We demonstrate that substantial reductions in fossil-fuel burning are needed to minimise the coming pH decrease and that substantial reductions in nutrient loads are needed to reduce the coming increase in hypoxic and anoxic waters.

Abstract. The midsummer drought (MSD) in Central America is characterised in order to create annual indexes representing the timing of its phases (start, minimum and end), and other features relevant for MSD forecasting such as the intensity and the magnitude. The MSD intensity is defined as the minimum rainfall detected during the MSD, meanwhile the magnitude is the total precipitation divided by the total days between the start and end of the MSD. It is shown that the MSD extends along the Pacific coast, however, a similar MSD structure was detected also in two stations in the Caribbean side of Central America, located in Nicaragua. The MSD intensity and magnitude show a negative relationship with Niño 3.4 and a positive relationship with the Caribbean low-level jet (CLLJ) index, however for the Caribbean stations the results were not statistically significant, which is indicating that other processes might be modulating the precipitation during the MSD over the Caribbean coast. On the other hand, the temporal variables (start, minimum and end) show low and no significant correlations with the same indexes.The results from canonical correlation analysis (CCA) show good performance to study the MSD intensity and magnitude, however, for the temporal indexes the performance is not satisfactory due to the low skill to predict the MSD phases. Moreover, we find that CCA shows potential predictability of the MSD intensity and magnitude using sea surface temperatures (SST) with leading times of up to 3 months. Using CCA as diagnostic tool it is found that during June, an SST dipole pattern upon the neighbouring waters to Central America is the main variability mode controlling the inter-annual variability of the MSD features. However, there is also evidence that the regional waters are playing an important role in the annual modulation of the MSD features. The waters in the PDO vicinity might be also controlling the rainfall during the MSD, however, exerting an opposite effect at the north and south regions of Central America.

The mesoscale atmospheric model WRF is used over three Svalbard glaciers. The simulations are done with a setup of the model corresponding to the state-of-the-art model for polar conditions, Polar WRF, and it was validated using surface observations. The ERA-Interim reanalysis was used for boundary forcing and the model was used with three nested smaller domains, 24 and 8 km, and 2.7 km resolution. The model was used for a two-year period as well as for a more detailed study using 3 summer and winter months. In addition sensitivity tests using finer horizontal and vertical resolution in the boundary layer and using different physics schemes were performed. Temperature and incoming short- and long-wave radiation were skillfully simulated, with lower agreement between measured and modelled wind speed. Increased vertical resolution improved the frequency distributions of the wind speed and the temperature. The choice of different physics schemes only slightly changed the model results. The polar-optimized microphysics scheme outperformed a slightly simpler microphysics scheme, but the two alternative and more sophisticated PBL schemes improved the model score. A PBL scheme developed for very stable stratifications (QNSE) proved to be better in the winter.

We present an inverse modeling approach to reconstruct annual accumulation patterns from ground-penetrating radar (GPR) data. A coupled surface energy balance-snow model simulates surface melt and the evolution of subsurface density, temperature, and water content. The inverse problem consists of iteratively calibrating accumulation, serving as input for the model, by finding a match between modeled and observed radar travel times. The inverse method is applied to a 16 km GPR transect on Nordenskiöldbreen, Svalbard, yielding annual accumulation patterns for [2007][2008][2009][2010][2011][2012]. Accumulation patterns with a mean of 0.75 meter water equivalent (mwe) a −1 contain substantial spatial variability, with a mean annual standard deviation of 0.17 mwe a −1 , and show only partial consistency from year to year. In contrast to traditional methods, accounting for melt water percolation, refreezing, and runoff facilitates accurate accumulation reconstruction in areas with substantial melt. Additionally, accounting for horizontal density variability along the transect is shown to reduce spatial variability in reconstructed accumulation, whereas incorporating irreducible water storage lowers accumulation estimates. Correlating accumulation to terrain characteristics in the dominant wind direction indicates a strong preference of snow deposition on leeward slopes, whereas weaker correlations are found with terrain curvature. Sensitivity experiments reveal a nonlinear response of the mass balance to accumulation changes. The related negative impact of small-scale accumulation variability on the mean net mass balance is quantified, yielding a negligible impact in the accumulation zone and a negative impact of −0.09 mwe a −1 in the ablation area.

Deep preferential percolation of melt water in snow and firn brings water lower along the vertical profile than a laterally homogeneous wetting front. This widely recognized process is an important source of uncertainty in simulations of subsurface temperature, density, and water content in seasonal snow and in firn packs on glaciers and ice sheets. However, observation and quantification of preferential flow is challenging and therefore it is not accounted for by most of the contemporary snow/firn models. Here we use temperature measurements in the accumulation zone of Lomonosovfonna, Svalbard, done in April 2012-2015 using multiple thermistor strings to describe the process of water percolation in snow and firn. Effects of water flow through the snow and firn profile are further explored using a coupled surface energy balance -firn model forced by the output of the regional climate model WRF. In situ air temperature, radiation, and surface height change measurements are used to constrain the surface energy and mass fluxes. To account for the effects of preferential water flow in snow and firn we test a set of depth-dependent functions allocating a certain fraction of the melt water available at the surface to each snow/firn layer. Experiments are performed for a range of characteristic percolation depths and results indicate a reduction in root mean square difference between the modeled and measured temperature by up to a factor of two compared to the results from the default water infiltration scheme. This illustrates the significance of accounting for preferential water percolation to simulate subsurface conditions. The suggested approach to parameterization of the preferential water flow requires low additional computational cost and can be implemented in layered snow/firn models applied both at local and regional scales, for distributed domains with multiple mesh points.