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Abstract. We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation.Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations.We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understanding of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.

Abstract. We statistically analyse the relationship between the structure of migrating dunes in the southern Baltic and the driving wind conditions over the past 26 years, with the long-term aim of using migrating dunes as a proxy for past wind conditions at an interannual resolution.The present analysis is based on the dune record derived from geo-radar measurements by Ludwig et al. (2017). The dune system is located at the Baltic Sea coast of Poland and is migrating from west to east along the coast. The dunes present layers with different thicknesses that can be assigned to absolute dates at interannual timescales and put in relation to seasonal wind conditions. To statistically analyse this record and calibrate it as a wind proxy, we used a gridded regional meteorological reanalysis data set (coastDat2) covering recent decades. The identified link between the dune annual layers and wind conditions was additionally supported by the co-variability between dune layers and observed sea level variations in the southern Baltic Sea.We include precipitation and temperature into our analysis, in addition to wind, to learn more about the dependency between these three atmospheric factors and their common influence on the dune system. We set up a statistical linear model based on the correlation between the frequency of days with specific wind conditions in a given season and dune migration velocities derived for that season. To some extent, the dune records can be seen as analogous to tree-ring width records, and hence we use a proxy validation method usually applied in dendrochronology, cross-validation with the leave-one-out method, when the observational record is short. The revealed correlations between the wind record from the reanalysis and the wind record derived from the dune structure is in the range between 0.28 and 0.63, yielding similar statistical validation skill as dendroclimatological records.

Abstract. We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and reanalysis products covering approximately the last 60 years. The focus of the study lies in identifying the link between the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. The climate simulations comprise three simulations, each conducted with a global climate model that includes a different version of the atmospheric model ECHAM. Two of these global simulations have been regionalised with the regional climate models MM5 and CCLM. The reanalysis products are the global NCEP/NCAR meteorological reanalysis version 1 and a regional reanalysis conducted with a regional atmospheric model driven at its domain boundaries by the NCEP/NCAR reanalysis. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. The links between wind speed and large-scale drivers derived from the reanalysis data sets overall tend to resemble those of the global models. In addition, considering multi-centennial time scales, we find in two global simulations a long term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understanding of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a~detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.

<p>The coastlines of the Baltic Sea and Indonesia are both relatively complex, so that the estimation of extreme sea levels caused by the atmospheric forcing becomes complex with conventional methods. Here, we explore whether Machine Learning methods can provide a model surrogate to compute more rapidly daily extremes in sea level from large-scale atmosphere-ocean fields. We investigate the connections between the atmospheric and ocean drivers of local extreme sea level in South East Asia and along the Baltic Sea based on statistical analysis by Random Forest Models, driven by large-scale meteorological predictors and daily extreme sea level measured by tide-gauge records over the last few decades.</p><p>First results show that in some Indonesian areas extremes are driven by large-scale climate fields; in other areas they are incoherently driven by local processes. An area where random forest predicted extremes show good correspondence to observed extremes is found to be the Malaysian coastline. For the Indonesian coasts, the Random Forest Algorithm was unable to predict extreme sea levels in line with observations. Along the Baltic Sea, in contrast, the Random Forest model is able to produce reasonable estimations of extreme sea levels based on the large-scale atmospheric fields. An analysis of the interrelations of extreme sea levels in the South Asia regions suggests that either the data quality may be compromised in some regions or that other forcing factors, distinct from the large-scale atmospheric fields, may also be involved.</p>

We statistically analyse the relationship between the structure of migrating dunes in the Southern Baltic and the driving wind conditions over the past 26 years, with the long-term aim of using migrating dunes as proxy for past wind conditions at interannual resolution. Dunes as wind proxies are not a totally new idea to the scientific community, but existing studies have so far analysed the link of dune structure and wind only on temporal resolutions of decades or millennia. The present analysis is based on the dune record derived from geo-radar measurements by Ludwig et al. (2016). The dune system is located at the 5 Baltic Sea coast of Poland and is migrating from west to east along the coast. Ludwig et al. (2016) suggested that the analysed dunes show an alternation in the sediment composition that can be used to determine the annual migration velocity which can be seen as a wind proxy. Here, we present a detailed statistical analysis of this record and calibrate it as a wind proxy. To our knowledge there are no adequate, homogeneous meteorological station data for this area available to validate this proxy.Therefore we based our analysis on a gridded regional meteorological reanalysis data set (coastDat2) over the recent decades. 10 We include precipitation and temperature into our analysis, in addition to wind, to learn more about the dependency between these three atmospheric factors and their common influence on the dune system. We set up a statistical linear model based on the correlation between the number of days with west and south-west wind directions above a pre-defined wind speed threshold and the dune migration velocities. To some extent, the dune intervals can be seen analogous to a tree ring widths, and hence we used a proxy-validation method usually applied in dendrochronology when the available meteorological record 15 is short, namely the cross-validation with the leave-one-out-method. This revealed correlations between the wind record from the reanalysis and the reconstructed wind record derived from the dune structure in the range of 0.28 and 0.63. Thus, our study verifies that this type of dunes can be validated with dendrochronological methods and derive acceptable validation values as a wind proxy.The identified link between the dune annual layers and wind conditions from the meteorological reanalysis was additionally 20 supported by the co-variability between dune layers and sea-level variations in the Southern Baltic Sea. Baltic Sea level variability in winter time is known to be strongly driven by westerly winds over this region. These results, therefore, provide an independent support, solely based on observations, of the link between annual dune layers and prevailing wind conditions.

We statistically analyse the relationship between the structure of migrating dunes in the Southern Baltic and the driving wind conditions over the past 26 years, with the long-term aim of using migrating dunes as proxy for past wind conditions at interannual resolution. Dunes as wind proxies are not a totally new idea to the scientific community, but existing studies have so far analysed the link of dune structure and wind only on temporal resolutions of decades or millennia. The present analysis is based on the dune record derived from geo-radar measurements by Ludwig et al. (2016). The dune system is located at the 5 Baltic Sea coast of Poland and is migrating from west to east along the coast. Ludwig et al. (2016) suggested that the analysed dunes show an alternation in the sediment composition that can be used to determine the annual migration velocity which can be seen as a wind proxy. Here, we present a detailed statistical analysis of this record and calibrate it as a wind proxy. To our knowledge there are no adequate, homogeneous meteorological station data for this area available to validate this proxy.Therefore we based our analysis on a gridded regional meteorological reanalysis data set (coastDat2) over the recent decades. 10 We include precipitation and temperature into our analysis, in addition to wind, to learn more about the dependency between these three atmospheric factors and their common influence on the dune system. We set up a statistical linear model based on the correlation between the number of days with west and south-west wind directions above a pre-defined wind speed threshold and the dune migration velocities. To some extent, the dune intervals can be seen analogous to a tree ring widths, and hence we used a proxy-validation method usually applied in dendrochronology when the available meteorological record 15 is short, namely the cross-validation with the leave-one-out-method. This revealed correlations between the wind record from the reanalysis and the reconstructed wind record derived from the dune structure in the range of 0.28 and 0.63. Thus, our study verifies that this type of dunes can be validated with dendrochronological methods and derive acceptable validation values as a wind proxy.The identified link between the dune annual layers and wind conditions from the meteorological reanalysis was additionally 20 supported by the co-variability between dune layers and sea-level variations in the Southern Baltic Sea. Baltic Sea level variability in winter time is known to be strongly driven by westerly winds over this region. These results, therefore, provide an independent support, solely based on observations, of the link between annual dune layers and prevailing wind conditions.