Representation of soil hydrology in permafrost regions may explain large part of inter-model spread in simulated Arctic and subarctic climate

The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the MPI Earth System model to investigate how different plausible assumptions for the representation of the permafrost hydrology modulate the land-atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively "wet" or "dry" conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21st-century trend in the simulated soil water content and result in substantial differences in the land-atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.publishedVersio

Surface wind over Europe: Data and variability

This work improves the characterization and knowledge of the surface wind climatology over Europe with the development of an observational database with unprecedented quality control (QC), the European Surface Wind Observational database (EuSWiO). EuSWiO includes more than 3,829 stations with sub-daily resolution for wind speed and direction, with a number of sites spanning the period of 1880–2017, a few hundred time series starting in the 1930s and relatively good spatial coverage since the 1970s. The creation of EuSWiO entails the merging of eight different data sets and its submission to a common QC. About 5% of the total observations were flagged, correcting a great part of the extreme and unrealistic values, which have a discernible impact on the statistics of the database. The daily wind variability was characterized by means of a classification technique, identifying 11 independent subregions with distinct temporal wind variability over the 2000–2015 period. Significant decreases in the wind speed during this period are found in five regions, whereas two regions show increases. Most regions allow for extending the analysis to earlier decades. Caution in interpreting long-term trends is needed as wind speed data have not been homogenized. Nevertheless, decreases in the wind speed since the 1980s can be noticed in most of the regions. This work contributes to a deeper understanding of the temporal and spatial surface wind variability in Europe. It will allow from meteorological to climate and climate change studies, including potential applications to the analyses of extreme events, wind power assessments or the evaluation of reanalysis or model-data comparison exercises at continental scales

Report on WRF model sensitivity studies and specifications for the mesoscale wind atlas production runs:Deliverable D4.3

This report describes the sensitivity studies performed with the mesoscale model WRF in preparation of the mesoscale wind atlas production runs. The objective of this work was to find a model setup that is not just a best practice setup but well-founded and based on scientific evaluation. We started with performing some initial sensitivity experiments changing the PBL scheme and the initialisation of the model. The work was distributed among several partners, each conducting the same set of experiments but on a different domain. The objective of this first phase was to ensure that everybody speaks the same language in terms of applying WRF in the context of NEWA. The results were analysed and compared in terms of the mean wind climate. To draw conclusions regarding the quality of the experiments, the results of one domain were compared to tall mast observations. Overall the model showed a good performance with slightly better results for one of the two tested PBL schemes (MYNN) and weekly initialisation of simulations (compared to daily). In the next phase, further sensitivity tests were conducted for one of the previously defined domains, varying a multitude of parameters as e.g. model version, vertical resolution, forcing data and land surface parameterisation. These studies showed that virtually each parameter change is affecting the results in some way, while significant effects on the wind climate are mostly obtained by changes in physical parameterisation e.g. PBL scheme, representation of the land surface and surface roughness. However, also non-physical parameters as the simulation length and the domain size affects the results considerably. The results suggest to use rather small domains and not too long simulations (in the order of 1–2 weeks). One of the objectives of NEWA is to create a probabilistic wind atlas, i.e. to provide uncertainty information to the mesoscale wind atlas (see Deliverables D3.1 and D4.4). This will be achieved by generating an ensemble of WRF simulations with different model configurations. While the final ensemble to be run over the complete NEWA domain will only include a few members, a much larger ensemble was run for a smaller sub-domain to find the ensemble members that generate the largest spread and will be used in the final NEWA ensemble. A second objective of this initial large ensemble was to find an optimal setup for the mesoscale production run. Based on the experience gained in the previous sensitivity experiments, a 47-member ensemble was assembled and run. The individual members were compared against each other, as well as against tall mast observations. Different metrics were explored to assess the performance of the members, i.e. not only the usual statistical measures as RMSE, BIAS and correlation but also metrics that compare the wind speed distributions. In the final part of this report we present the ultimate WRF setup for the NEWA production run that was run between August 2018 and March 2019 on the MareNostrum supercomputer in Barcelona

European warm-season temperature and hydroclimate since 850 CE

The long-term relationship between temperature and rainfall variables (hydroclimate) remains uncertain due to the short length of instrumental measurements and inconsistent results from climate model simulations. This lack of understanding is critical with regard to projecting future drought and flood risks. Here we assess northern Hemisphere summertime co-variability patterns between temperature and rainfall, over Europe back to 850 CE using instrumental measurements, tree-ring reconstructions, and climate model simulations. We find the temperature–hydroclimate relationship, in both the instrumental and proxt data to be more positive at lower frequencies, but less so in model simulations. In comp[arison to instrumental climate data, climate model simulations reveal a more negative co-variability between temperature and hydroclimate, across all timescales both lower and higher frequency. The reconstructions exhibit more positive co-variability. Despite observed differences in the temperature–hydroclimate co-variability patterns in instrumental, reconstructed and model simulated data, all data types share similar phase-relationships between temperature and hydroclimate, all of which indicate the common influence of external forcing of the climate system. The co-variability between temperature and soil moisture in the model simulations is overestimated, implying a possible overestimation of temperature-driven future drought risks

Assessing the spatial signature of European climate reconstructions

Much progress has recently been made in reconstructing European temperature variability over centuries to millennia. In contrast, there are only a few attempts at long-term precipitation and/or drought reconstruction, which are spatially less significant. Here we discuss the possibility of using climate reconstructions from tree-ring density and width to make spatially explicit estimates of European temperature and drought variability, respectively. Four experiments were performed to assess spatial field correlations of (1) parameter-specific mean reconstructions, (2) individual site reconstructions, (3) instrumental stations, and (4) model analogues. The simple mean of 4 temperature reconstructions from northern Scandinavia and high-elevation sites in the Tatra, Alps, and Pyrenees revealed a significant positive correlation (r &gt; 0.4) with the gridded Central European summer temperature south of 55 degrees N and west of 25 degrees E. In contrast, the mean of 11 hydro-climatic reconstructions located between Sweden and Turkey had a significant positive correlation with only a handful of small patches scattered along an east-west corridor from the British Isles over Germany to the Baltic. The significant positive correlation increased to 71% of the European landmass between 35-70 degrees N and 10 degrees W-40 degrees E when using the individual 4 temperature reconstructions instead. The 11 individual hydro-climatic reconstructions had a significant positve correlation with summer drought over only 16% of the area. The proxy-based correlation fields are greatly supported by the spatial significance of instrumental station measurements and model analogues corresponding to the initial tree-ring site locations.</p

Assessing the spatial signature of European climate reconstructions

Much progress has recently been made in reconstructing European temperature variability over centuries to millennia. In contrast, there are only a few attempts at long-term precipitation and/or drought reconstruction, which are spatially less significant. Here we discuss the possibility of using climate reconstructions from tree-ring density and width to make spatially explicit estimates of European temperature and drought variability, respectively. Four experiments were performed to assess spatial field correlations of (1) parameter-specific mean reconstructions, (2) individual site reconstructions, (3) instrumental stations, and (4) model analogues. The simple mean of 4 temperature reconstructions from northern Scandinavia and high-elevation sites in the Tatra, Alps, and Pyrenees revealed a significant positive correlation (r &gt; 0.4) with the gridded Central European summer temperature south of 55 degrees N and west of 25 degrees E. In contrast, the mean of 11 hydro-climatic reconstructions located between Sweden and Turkey had a significant positive correlation with only a handful of small patches scattered along an east-west corridor from the British Isles over Germany to the Baltic. The significant positive correlation increased to 71% of the European landmass between 35-70 degrees N and 10 degrees W-40 degrees E when using the individual 4 temperature reconstructions instead. The 11 individual hydro-climatic reconstructions had a significant positve correlation with summer drought over only 16% of the area. The proxy-based correlation fields are greatly supported by the spatial significance of instrumental station measurements and model analogues corresponding to the initial tree-ring site locations.</p