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Severe winter windstorms belong to the most damaging extreme events over Europe with damages costing over several millions of EUR. Hence, the understanding and skilful predictions would be of great value. On the other hand, the seasonal time scale is not only of interest for windstorm studies but is gaining more and more interest in general. This study investigates extreme event predictions on the seasonal time scale. Therefore, it is using the seasonal forecast model GloSea5, from the UK Met Office, validated with ECMWF ERA5 reanalyses. Windstorms are tracked with an impact-focused algorithm for 23 winter seasons, DJF, 1993-2015. The windstorm frequency shows skilful predictions over the British Isles and southern Scandinavia while the forecast skill of intensity depends on the measure used. An accumulated intensity of the season shows skilful areas downstream of the North Atlantic stormtrack. The significant spatial area for a normalised intensity decreases slightly, but still shows positive forecast skill. A multi-linear regression analysis shows that most of the windstorms over the North Atlantic and European area are connected to the NAO index, but there is also a gap of explanatory variance over the North Atlantic for the NAO. The Scandinavian and East Atlantic pattern are filling the gab exactly in this area. Those three large-scale patterns describe all together up to 80% of windstorm frequency and 60% of windstorm intensity variance. Besides large-scales patterns, dynamical factors, like Eady Growth Rate or the Jetstream Location, are also important drivers for seasonal forecasts of windstorm activity., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Earth orientation parameters (EOPs) are strongly influenced by atmospheric and oceanic mass and motion variations, and therefore may help provide an independent measure of climate variability. Coupled Atmosphere-Ocean General Circulation Models (GCMs) simulate the variations in the atmosphere and the ocean in a physically consistent way. Thus, the GCMs can be inter-compared with respect to the derived EOP variations. Global warming has been shown to exert a major effect on Length-of-Day, caused by an enhancement in atmospheric motion. However, a comprehensive assessment of the impact of climate change on polar motion excitation has not yet been presented. In this paper, an inter-model comparison of a Climate Change signal (A1B – 20C) in Polar Motion is provided for a set of model runs from the WCRP CMIP-3 campaign. The models used in the comparison are the ECHAM5/OM1, GFDL CM2, NCAR CCSM3, and UK MetOffice HadCM3. As an additional fifth model, we use tidal and non-tidal runs from the ECOCTH model, which consists of the ECHAM5/OM1 with a tidal coupler. First, a basic consistency check was performed for multi-century control runs of the models. The twodimensional excitation fields for atmospheric mass and motion, as well as oceanic mass and motion are compared. Also, the globally integrated EOPs are analysed both in time and spectral domain. The comparison yields, e.g., for the atmospheric mass component of polar motion excitation, very good agreement between the models with respect to the annual cycle. In the Taylor diagrams comparing the main EOFs from the two-dimensional excitation fields calculated from the atmospheric mass distribution, we also obtain good agreement. All five main EOFs show correlations in the range of 0.75 to 0.98 in the inter-model comparison. In a second step, the impact of climate change signal, i.e. the difference between two 30-year periods from the beginning and the end of the A1B run, is analysed.

Variations in the earth rotation parameters are strongly influenced by atmospheric and oceanic variability patterns. In order to develop a climate index from Earth rotation parameters, the influence of known large-scale climate variability features on Earth rotation must be assessed. This can be done using Atmosphere-Ocean General Circulation Models (CGCMs), simulating the climate system in a physically consistent way. The analysis performed is based on the computation of effective angular momentum functions derived from: a) an ocean model (OMCT) driven with ECMWF (ERA Interim/ERA40) atmospheric reanalysis data, and with a 500 year run of the ECHAM5/OM1 model, developing its climate without an observational forcing. Results obtained from re-analysis and the simulated ocean can be directly a compared with the observational IERS geodetic earth orientation data (C04 excitation functions). Data from the free model run shall demonstrate in how far the fully coupled model is able to reproduce the same features for the geodetic variations. One of the variability features investigated is the North Atlantic Oscillation (NAO), the dominant atmospheric winter teleconnection pattern for the Northern Hemisphere. Its influence on polar motion(e.g. Chao and Zhou, 1998) was thought to be caused largely by mass redistribution. This assumption is, however, inconsistent with the inverted barometer assumption, telling that atmospheric pressure anomalies over the ocean (where the larger part of the NAO anomalies lies) should be outweighed by an elastic response of the ocean surface. Our results suggest that, instead of atmospheric mass redistribution, the influence of the NAO on polar motion is exerted through changes in wind speed and resulting oceanic transport, mainly via the x1 motion components of the atmospheric (AAM) and oceanic (OAM) effective angular momentum (EAM) functions. As a second variability feature, the possible influence of the Quasi-Biannual Oscillation (QBO) on polar motion is examined. Because of the link between NAO and QBO (significantly correlated with r=0.22 in the ERA Interim dataset), an indirect influence of the QBO on earth orientation would be expected. However, no significant correlation between the EAM functions and the QBO index is found. To investigate this connection further, Granger causality is used, a statistical tool to determine whether the knowledge of past values of one timeseries (y) is useful in predicting future values of a second timeseries (x) over and above the knowledge of past values of x alone. It is shown that, for the ERA Interim period, the QBO “grangercauses” the winter AAM x-1 mass component as well as the OAM x-1 motion component at 99% significance level, meaning that previous QBO index values may influence the earth orientation. The comparison with data from the ECHAM5/OM1 model - which does not include a well resolved stratosphere and fails to reproduce correctly the QBO - is used to determine whether the influence of the NAO on earth rotation is modified by the existence of the QBO.

A range of possible changes in the frequency and characteristics of European wind storms under future climate conditions was investigated on the basis of a multi-model ensemble of 9 coupled global climate model (GCM) simulations for the 20th and 21st centuries following the IPCC SRES A1B scenario. A multi-model approach allowed an estimation of the (un)certainties of the climate change signals. General changes in large-scale atmospheric flow were analysed, the occurrence of wind storms was quantified, and atmospheric features associated with wind storm events were considered. Identified storm days were investigated according to atmospheric circulation, associated pressure patterns, cyclone tracks and wind speed patterns. Validation against reanalysis data revealed that the GCMs are in general capable of realistically reproducing characteristics of European circulation weather types (CWTs) and wind storms. Results are given with respect to frequency of occurrence, storm-associated flow conditions, cyclone tracks and specific wind speed patterns. Under anthropogenic climate change conditions (SRES A1B scenario), increased frequency of westerly flow during winter is detected over the central European investigation area. In the ensemble mean, the number of detected wind storm days increases between 19 and 33% for 2 different measures of storminess, only 1 GCM revealed less storm days. The increased number of storm days detected in most models is disproportionately high compared to the related CWT changes. The mean intensity of cyclones associated with storm days in the ensemble mean increases by about 10 (±10)% in the Eastern Atlantic, near the British Isles and in the North Sea. Accordingly, wind speeds associated with storm events increase significantly by about 5 (±5)% over large parts of central Europe, mainly on days with westerly flow. The basic conclusions of this work remain valid if different ensemble contructions are considered, leaving out an outlier model or including multiple runs of one particular model.

A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses.\ud \ud Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.

This study assesses whether variations in observed Earth orientation parameters (EOPs, IERS) such as length-of day (LOD EOP C04) and polar motion (PM EOP C04) can be applied as climate indicators. Data analyses suggest that observed EOPs are differently affected by parameters associated with the atmosphere and ocean. On interannual time scales the varying ocean-atmosphere effects on EOPs are in particular pronounced during episodes of the coupled ocean-atmosphere phenomenon El Niño–Southern Oscillation (ENSO). Observed ENSO anomalies of spatial patterns of parameters affected by atmosphere and ocean (climate indices and sea surface temperatures) are related to LOD and PM variability and associated with possible physical background processes. Present time analyses (1962 – 2000) indicate that the main source of the varying ENSO signal on observed LOD can be associated with anomalies of the relative angular momentum (AAM) related to variations in location and strength of jet streams of the upper troposphere. While on interannual time scales observed LOD and AAM are highly correlated (r=0.75), results suggest that strong El Niño events affect the observed LOD – AAM relation differently strong (explained variance 71%- 98%). Accordingly, the relation between AAM and ocean sea surface temperatures (SST) in the NIÑO 3.4 region differs (explained variances 15%-73%). Corresponding analysis is conducted on modelled EOPs (ERA40 reanalysis, ECHAM5-OM1) to obtain Earth rotation parameters undisturbed by core-mantle activities, and to study rotational variations under climate variability and change. A total of 91 strong El Niño events are analysed in coupled ocean-atmosphere ECHAM5-OM1 scenarios concerning the 20th century (20C), climate warming (A1B) and pre-industrial climate variability. Analyses on a total of 61 strong El Niño events covering a time period of 505 simulation years under pre-industrial climate conditions indicate a range of El Niño events with a strong or smaller effect on the AAM-SST relation corresponding to analyses on the 20th century (20C) (explained variance 19%-76%). The excitation of LOD and polar motion by the oceanic angular momentum (OAM) is assessed by applying the Ocean Model for Circulation and Tides (OMCT). While changes in atmospheric patterns dominate variations in observed LOD, the ocean mainly affects polar motion and the non-atmospheric LOD residual. Comparing the mean annual cycle of the non-atmospheric observed LOD and OMCT simulated OAMmass (IB) reveals a close similarity between their amplitudes. On interannual time scales OMCT simulated OAM time series correlates well with observed rotational variations corrected for atmospheric and hydrological effects with 82% with respect to polar motion. The OMCT modell is also able to reproduce with high accuracy Niño 3.4 SSTs close to observations on interannual time scales. Variations in simulated SSTs indicate a significant relation to changes in polar motion due to the excitation by the ocean. The second project phase will build on results from this study assessing LOD and PM interconnections concerning joint atmosphere-ocean-hydrosphere modes.

A simple storm loss model is applied to an ensemble of ECHAM5/MPI-OM1 GCM simulations in order to estimate changes of insured loss potentials over Europe in the 21st century. Losses are computed based on the daily maximum wind speed for each grid point. The calibration of the loss model is performed using wind data from the ERA40-Reanalysis and German loss data. The obtained annual losses for the present climate conditions (20C, three realisations) reproduce the statistical features of the historical insurance loss data for Germany.\ud \ud The climate change experiments correspond to the SRES-Scenarios A1B and A2, and for each of them three realisations are considered. On average, insured loss potentials increase for all analysed European regions at the end of the 21st century. Changes are largest for Germany and France, and lowest for Portugal/Spain. Additionally, the spread between the single realisations is large, ranging e.g. for Germany from −4% to +43% in terms of mean annual loss. Moreover, almost all simulations show an increasing interannual variability of storm damage. This assessment is even more pronounced if no adaptation of building structure to climate change is considered. The increased loss potentials are linked with enhanced values for the high percentiles of surface wind maxima over Western and Central Europe, which in turn are associated with an enhanced number and increased intensity of extreme cyclones over the British Isles and the North Sea.