ALBERT

Description: The surface of the world’s oceans has been warming since the beginning of industrialization. In addition to this, multidecadal sea surface temperature (SST) variations of internal origin exist. Evidence suggests that the North Atlantic Ocean exhibits the strongest multidecadal SST variations and that these variations are connected to the overturning circulation. This work investigates the extent to which these internal multidecadal variations have contributed to enhancing or diminishing the trend induced by the external radiative forcing, globally and in the North Atlantic. A model study is carried out wherein the analyses of a long control simulation with constant radiative forcing at preindustrial level and of an ensemble of simulations with historical forcing from 1850 until 2005 are combined. First, it is noted that global SST trends calculated from the different historical simulations are similar, while there is a large disagreement between the North Atlantic SST trends. Then the control simulation is analyzed, where a relationship between SST anomalies and anomalies in the Atlantic meridional overturning circulation (AMOC) for multidecadal and longer time scales is identified. This relationship enables the extraction of the AMOC-related SST variability from each individual member of the ensemble of historical simulations and then the calculation of the SST trends with the AMOC-related variability excluded. For the global SST trends this causes only a little difference while SST trends with AMOC-related variability excluded for the North Atlantic show closer agreement than with the AMOC-related variability included. From this it is concluded that AMOC variability has contributed significantly to North Atlantic SST trends since the mid nineteenth century.

Description: The aim of this article is to describe the reference configuration of the convection-permitting numerical weather prediction (NWP) model HARMONIE-AROME, which is used for operational short-range weather forecasts in Denmark, Estonia, Finland, Iceland, Ireland, Lithuania, the Netherlands, Norway, Spain, and Sweden. It is developed, maintained, and validated as part of the shared ALADIN–HIRLAM system by a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale NWP. HARMONIE–AROME is based on the model AROME developed within the ALADIN consortium. Along with the joint modeling framework, AROME was implemented and utilized in both northern and southern European conditions by the above listed countries, and this activity has led to extensive updates to the model’s physical parameterizations. In this paper the authors present the differences in model dynamics and physical parameterizations compared with AROME, as well as important configuration choices of the reference, such as lateral boundary conditions, model levels, horizontal resolution, model time step, as well as topography, physiography, and aerosol databases used. Separate documentation will be provided for the atmospheric and surface data-assimilation algorithms and observation types used, as well as a separate description of the ensemble prediction system based on HARMONIE–AROME, which is called HarmonEPS.

Description: Met Éireann, the Irish Meteorological Service, has generated a very high resolution (2.5-km horizontal grid) regional climate reanalysis for Ireland called the Met Éireann Reanalysis (MÉRA). MÉRA spans the period from 1981 to 2015 and was produced using the shared ALADIN–HIRLAM numerical weather prediction system. This article includes comparisons with the ERA-Interim and Uncertainties in Ensembles of Regional Reanalyses (UERRA) datasets, analysis of data assimilation outputs, precipitation comparisons, and a focus on extremes of wind and rainfall. The comparisons with the reanalysis datasets show that MÉRA provides a high-quality reconstruction of recent Irish climate and benefits from the use of a very high resolution grid, in particular in relation to wind and precipitation extremes.

Description: Large scale atmospheric oscillations are known to have an influence on waves in the North Atlantic. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale oscillations using indices such as the North Atlantic Oscillation (NAO: fluctuations in the difference between the Icelandic low pressure system and the Azore high pressure system). In this study a statistical analysis of the station-based NAO index was carried out using an ensemble of EC-Earth global climate simulations, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. The NAO index was compared to observations and to projected changes in the index by the end of the century under the RCP4.5 and RCP8.5 forcing scenarios. In addition, an ensemble of EC-Earth driven WAVEWATCH III wave model projections over the North Atlantic was analysed to determine the correlations between the NAO and significant wave height (Hs) and the NAO and extreme ocean states. For the most part, no statistically significant differences were found between the distributions of observed and modelled station-based NAO or in projected distributions of the NAO. Means and extremes of Hs are projected to decrease on average by the end of this century. The 95th percentile of Hs is strongly positively correlated to the NAO. Projections of Hs extremes are location dependent and in fact, under the influence of positive NAO the 20-year return levels of Hs were found to be amplified in some regions. However, it is important to note that the projected decreases in the 95th percentile of Hs off the west coast of Ireland are not statistically significant in one of the RCP4.5 and one of the RCP8.5 simulations (me41, me83) which indicates that there is still uncertainty in the projections of higher percentiles.

Description: The Irish Meteorological Service, Met Éireann, has carried out a 35-year very high resolution (2.5 km horizontal grid) regional climate reanalysis for Ireland using the ALADIN-HIRLAM numerical weather prediction system. This article provides an overview of the reanalysis, called MÉRA, as well as a preliminary analysis of surface parameters including screen level temperature, 10 m wind speeds, mean sea-level pressure (MSLP), soil temperatures, soil moisture and 24 h rainfall accumulations. The quality of the 3-D variational data assimilation used in the reanalysis is also assessed. Preliminary analysis shows that it takes almost 12 months to spin up the deep soil in terms of moisture, justifying the choice of running year-long spin up periods. Overall, the model performed consistently over the time period. Small biases were found in screen-level temperatures (less than −0.5 °C), MSLP (within 0.5 hPa) and 10 m wind speed (up to 0.5 m s−1) Soil temperatures are well represented by the model. 24 h accumulations of precipitation generally exhibit a small positive bias of  ∼ 1 mm per day and negative biases over mountains due to a mismatch between the model orography and the geography of the region. MÉRA outperforms the ERA-Interim reanalysis, particularly in terms of standard deviations in screen-level temperatures and surface winds. This dataset is the first of its kind for Ireland that will be made publically available during spring 2017.

Description: This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the model, without compromising on computational efficiency. In mesoscale models fast interactions between clouds and radiation and the surface and radiation can be of greater importance than accounting for the spectral details of clear-sky radiation; thus calling the routines more frequently can be of greater benefit than the deterioration due to loss of spectral details. Fast but physically based radiation parametrizations are expected to be valuable for high-resolution ensemble forecasting, because as well as the speed of their execution, they may provide realistic physical perturbations. Results from single-column diagnostic experiments based on CIRC benchmark cases and an evaluation of 10 years of radiation output from the FMI operational archive of HIRLAM forecasts indicate that HLRADIA performs sufficiently well with respect to the clear-sky downwelling SW and longwave LW fluxes at the surface. In general, HLRADIA tends to overestimate surface fluxes, with the exception of LW fluxes under cold and dry conditions. The most obvious overestimation of the surface SW flux was seen in the cloudy cases in the 10-year comparison; this bias may be related to using a cloud inhomogeneity correction, which was too large. According to the CIRC comparisons, the outgoing LW and SW fluxes at the top of atmosphere are mostly overestimated by HLRADIA and the net LW flux is underestimated above clouds. The absorption of SW radiation by the atmosphere seems to be underestimated and LW absorption seems to be overestimated. Despite these issues, the overall results are satisfying and work on the improvement of HLRADIA for the use in HARMONIE-AROME NWP system is ongoing. In a HARMONIE-AROME 3-D forecast experiment we have shown that the frequency of the call for the radiation parametrization and choice of the parametrization scheme makes a difference to the surface radiation fluxes and changes the spatial distribution of the vertically integrated cloud cover and precipitation.

Description: The Northeast Atlantic possesses an energetic and variable wind and wave climate which has a large potential for renewable energy extraction; for example along the western seaboards off Ireland. The role of surface winds in the generation of ocean waves means that global atmospheric circulation patterns and wave climate characteristics are inherently connected. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale atmospheric oscillations using indices such as the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA) and the Scandinavian pattern (SCAND). In this study a statistical analysis of these teleconnections was carried out using an ensemble of EC-Earth global climate simulations run under the RCP4.5 and RCP8.5 forcing scenarios, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. In addition, EC-Earth model fields were used to drive the WAVEWATCH III wave model over the North Atlantic basin to create the highest resolution wave projection dataset currently available for Ireland. Using this dataset we analysed the correlations between teleconnections and significant wave heights (Hs) with a particular focus on extreme ocean states using a range of statistical methods. The strongest, statistically significant correlations exist between the 95th percentile of significant wave height and the NAO. Correlations between extreme Hs and the EA and SCAND are weaker and not statistically significant over parts of the North Atlantic. When the NAO is in its positive phase (NAO+) and the EA and SCAND are in a negative phase (EA−, SCAND−) the strongest effects are seen on 20-year return levels of extreme ocean waves. Under RCP8.5 there are large areas around Ireland where the 20-year return level of Hs increases by the end of the century, despite an overall decreasing trend in mean wind speeds and hence mean Hs.

Description: HARMONIE-AROME is a convection-permitting non-hydrostatic model that includes the multi-purpose SURFEX surface model. It is developed for high resolution (1–3 km) weather forecasting and applied in a number of regions in Europe and the Mediterranean. A version of HARMONIE-AROME is also under development for regional climate modelling. Here we run HARMONIE-AROME for a domain over Greenland that includes a significant portion of the Greenland ice sheet. The model output reproduces temperature, wind speed and direction and relative humidity over the ice sheet well when compared with the observations from PROMICE automatic weather stations (AWS) operated within the model domain on the ice sheet (mean temperature bias 1.31 ± 3.6 K) but we identified a much lower bias (−0.16 ± 2.3 K) at PROMICE sites on days where melt does not occur at the ice sheet surface and is thus an artefact of the simplified surface scheme over glaciers in the existing HARMONIE-AROME operational set-up. The bias in summer time temperature also affects wind speed and direction as the dominant katabatic winds are caused by the cold ice surface and slope gradient. By setting an upper threshold to the surface temperature of the ice surface within SURFEX we show that the weather forecast error over the Greenland ice sheet can be reduced in summer when glacier ice is exposed. This improvement will facilitate accurate ice melt and run-off computations, important both for ice surface mass budget estimation and for commercial applications such as hydro-power forecasting. Furthermore, the HCLIM regional climate model derived from HARMONIE-AROME will need to accurately account for glacier surface processes in these regions in order to be used to accurately compute the surface mass budget of ice sheets and glaciers, a key goal of regional climate modelling studies in Greenland.