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During the past century, several extreme summer floods in Central Europe were associated with so-called Vb-cyclones propagating from the Mediterranean Sea north-eastward to Central Europe. The processes intensifying the precipitation in synoptic situations with Vb-cyclones in the Danube, Elbe, and Odra catchments are only partially understood. Our study aims to investigate these processes with Lagrangian moisture-source diagnostics for 16 selected Vb-events. Moreover, we analyse the characteristics of typical moisture source regions during 1107 Vb-events from 1901 to 2010 based on ERA-20C reanalysis dynamically downscaled with COSMO-CLM+NEMO. We observe moisture contributions by various source regions highlighting the complex dynamical interplay of different air masses leading to moisture convergence in synoptic situations with Vb-cyclones. Overall, up to 80% of the precipitation originates from the European continent, indicating the importance of continental moisture recycling, especially within the respective river catchment. Other major moisture uptake regions are the North Sea, the Baltic Sea, the North Atlantic, and for a few events the Black Sea. Remarkably, anomalies in these oceanic source regions show no connection to precipitation amounts in synoptic situations with Vb-cyclones. In contrast, the Vb-cyclones with the highest precipitation are associated with anomalously high evaporation in the Mediterranean Sea, even though the Mediterranean Sea is only a minor moisture source region on average. Interestingly, the evaporation anomalies are not connected with sea-surface temperature but with wind-speed anomalies (Spearman’s rank correlation coefficient R ≈ 0.7, significant with p < 0.01) indicating mainly dynamically driven evaporation. The particular role of the Mediterranean Sea hints towards possible importance of Mediterranean moisture for the early-stage intensification of Vb-cyclones and the pre-moistening of the continental uptake regions upstream of the target catchments., Climate Dynamics, 59 (11-12), ISSN:0930-7575, ISSN:1432-0894

Rain-on-snow (ROS) floods are responsible for the overwhelming majority of floods affecting multiple major river basins simultaneously in Europe during the last century. These widespread floods have serious negative economical, social and ecological effects, and knowledge about their rate of occurrence is critical for future projections in the face of climate change.Recent studies have shown that ROS events (with flood-inducing potential) in Europe increase and decrease based on the elevation range considered since 1950 and there appears to be a clustering pattern of flood-poor and flood-rich periods since 1900. Our goal is to analyze if these changes in frequency can be realistically described by a stationary process (or a combination thereof) or if there must be hidden time-dependent driving factors to explain the observed clustering. To test this theory we analyze a simulation for the time period 1901-2010 based on ERA-20C dynamically downscaled using a coupled RCM. We apply a method from scan statistics and confirm the existence of significant periods poor and rich in ROS events with regards to the reference condition of independent and identically distributed random events and present their position in time. The same procedure is applied to the ROS event constituents (rainfall and snowmelt), where we identify such periods in the rainfall, but not in the snowmelt time series. We construct a stochastic ROS model by modelling precipitation and snowmelt via stationary gamma distributions fitted to our data but are unable to reproduce the observed clustering behaviour using the combined signal.This study confirms that the observed ROS floods in Central Europe are unlikely to be the result of stationary processes which hints at climate drivers for the compound rain-on-snow process in Europe.

DWD provides operational seasonal and decadal predictions of the German climate prediction system since 2016 and 2020, respectively. We plan to present these predictions together with post-processed ECMWF sub-seasonal forecast products on the DWD climate prediction website www.dwd.de/climatepredictions. In March 2020, this climate service was published with decadal predictions for the coming years; sub-seasonal and seasonal predictions for the coming weeks and months will follow.The user-oriented evaluation and design of this climate service has been developed in close cooperation with users from various sectors at workshops of the German MiKlip project and will be consistent across all time scales. The website offers maps, time series and tables of ensemble mean and probabilistic predictions in combination with the prediction skill for 1-year and 5-year means/ sums of temperature and precipitation for different regions (World, Europe, Germany, German regions).For Germany, the statistical downscaling EPISODES was applied to reach high spatial resolution required by several climate data users. Decadal predictions were statistically recalibrated in order to adjust bias, drift and standard deviation and optimize ensemble spread. We used the MSESS and RPSS to evaluate the skill of climate predictions in comparison to reference predictions, e.g. ‘observed climatology’ or ‘uninitialized climate projections’ (which are both applied by users until now as an alternative to climate predictions). The significance was tested via bootstraps.Within the ‘basic climate predictions’ section, a user-oriented traffic light indicates whether regional-mean climate predictions are significantly better (green), not significantly different (yellow) or significantly worse (red) than reference predictions. Within the ‘expert climate predictions’ section, prediction maps show per grid box the prediction itself (via the color of dots) and its skill (via the size of dots representing the skill categories of the traffic light). The co-development of this climate prediction application with users from different sectors strongly improves the comprehensibility and applicability by users in their daily work.In addition to sub-seasonal and seasonal predictions, plans for future extensions of this climate service include multi-year seasonal predictions, e.g. 5-year summer or winter means, combined products for climate predictions and climate projections, further user-oriented, extreme or large-scale variables, e.g. ENSO, or high-resolution applications for German cities based on statistically downscaled predictions.

Rain-on-Snow Hochwasser (ROS Hochwasser) können schwerwiegende negative wirtschaftliche, soziale und ökologische Auswirkungen haben und waren im letzten Jahrhundert für eine Vielzahl an Überschwemmungen verantwortlich, welche mehrere große Flusseinzugsgebiete in Europa gleichzeitig betrafen. Ein vertieftes Verständnis über die zeitliche Variabilität von ROS Hochwasser ist angesichts des Klimawandels für zukünftige Prognosen von entscheidender Bedeutung. Neuere Studien zeigten, dass ROS-Ereignisse (mit Hochwasserpotenzial) in Europa seit 1950 je nach betrachteter Geländehöhe zu- oder abnehmen, dabei scheint die Zeitreihe seit 1900 hochwasserarme und hochwasserreiche Perioden (Cluster) zu beinhalten. Unser Ziel ist es zu analysieren, ob diese Häufigkeitsänderungen durch eine Überlagerung von stationären Prozessen beschrieben werden können oder ob es zugrundeliegende zeitabhängige treibende Faktoren (z.B. die Nordatlantische Oszillation) geben muss, um die beobachtete Häufung zu erklären. Um dies zu testen, analysieren wir den Zeitraum 1901-2010 mithilfe von ERA-20C Reanalysedaten, welche mit einem gekoppelten regionalen Klimamodell dynamisch regionalisiert wurden. Wir wenden eine Methode aus der Scan-Statistik an und bestätigen die Existenz von Zeitperioden, welche signifikant weniger bzw. mehr ROS-Ereignisse beinhalten als unter der Referenzbedingung von unabhängig und identisch verteilten Zufallsereignissen erwartet wird. Dasselbe Verfahren wird auf die ROS-Ereigniskomponenten (Niederschlag und Schneeschmelze) angewandt, wobei nur der Niederschlag ein signifikantes Clustering aufweist. Wir konstruieren ein stochastisches ROS-Modell, indem wir Niederschlag- und Schneeschmelzereignisse aus stationären Gammaverteilungen ziehen, um zu untersuchen, ob das beobachtete Clustering-Verhalten unter Verwendung des kombinierten Signals reproduziert werden kann. Diese Studie liefert erste Hinweise darüber, dass das beobachtete Clustering-Verhalten der ROS-Hochwasser nicht das Ergebnis von überlappenden stationären Prozessen sein kann. Dies deutet auf zeitabhängige Klimatreiber für Niederschlag und Schneeschmelze in Europa hin und liefert einen entscheidenden Baustein für zukünftige ROS-Hochwasser Projektionen.

River floods are the most common and devastating natural hazard in Europe. In this study, we focus on a specific flood type which is associated with so-called Vb-cyclones. These extratropical cyclones are defined by their pathway from the western Mediterranean Sea north-eastward over northern Italy along the eastern fringe of the Alps towards Central Europe. Prominent examples of Vb-floods are the July 1954 and the August 2002 floods in the Elbe and Danube catchments as well as the Odra flooding during May/June 2010.Only a few Vb-cyclones cause extreme flooding in Central Europe, even though about 2-5 follow the Vb pathway on average per year. The processes which intensify these flood triggering Vb-cyclones are only partly understood. One potential mechanism could be the soil-precipitation feedback over the continent. Moreover, the resulting latent heat release could re-enforce the atmospheric blocking conditions, e.g., over eastern Europe, that foster cyclones to follow the Vb-like pathway.Our study aims to increase knowledge about potential feedback mechanisms by quantifying the role of specific moisture sources. We analysed the moisture uptake for selected extreme events in the 20th century based on backward trajectories in dynamically downscaled ERA-20C reanalysis. The downscaling was performed over Europe with a high-resolution and interactively coupled atmosphere-ocean model setup (COSMO-CLM+NEMO). The Mediterranean Sea contributed to rainfall in the affected river catchments often at the event start. Throughout the events, other main moisture uptake regions were the European continent pointing towards an important role of the soil-moisture precipitation feedback, but also other oceanic sources such as the North Atlantic, the North Sea, and the Baltic Sea were identified. The large variety of the identified sources highlights the complex dynamical interplay of different airmasses leading to convergence of moisture during particularly severe flood producing heavy precipitation events.

The seasonal and interannual variability of the quarterdiurnal tide is analysed using meteor radar wind observations at the two midlatitude sites Collm and Obninsk. Generally tidal amplitudes increase with height. Maximum tidal amplitudes are found in winter. Meridional amplitudes are smaller than zonal ones on an average. Phases mainly differ between summer and winter. Zonal and meridional phases differ by slightly less than 90°. The vertical wavelengths are very long in winter, but shorter and on the order of 20 km in summer. Collm and Obninsk amplitudes and phases agree well, indicating that the migrating quarterdiurnal tide may be responsible for a major part of the observed waves. Observations since 1980 show that the tidal amplitudes have increased on a whole, although the increase is not linear but mainly happening during the late 1990s and the early 2000s.

Solar tides such as the diurnal and semidiurnal tide, are forced in the lower and middle atmosphere through the diurnal cycle of solar radiation absorption. This is also the case with higher harmonics like the quarterdiurnal tide (QDT), but for these also non-linear interaction of tides such as the self-interaction of the semidiurnal tide, or the interaction of terdiurnal and diurnal tides, are discussed as possible forcing mechanism. To shed more light on the sources of the QDT, 12 years of meteor radar data at Collm (51.3∘ N, 13∘ E) have been analyzed with respect to the seasonal variability of the QDT at 82–97 km altitude, and bispectral analysis has been applied. The results indicate that non-linear interaction, in particular self-interaction of the semidiurnal tide probably plays an important role in winter, but to a lesser degree in summer. Numerical modelling of 6 h amplitudes qualitatively reproduces the gross seasonal structure of the observed 6 h wave at Collm. Model experiments with removed tidal forcing mechanisms lead to the conclusion that, although non-linear tidal interaction is one source of the QDT, the major forcing mechanism is direct solar forcing of the 6 h tidal components.

Vb-cyclones are extratropical cyclones propagating from the Western Mediterranean Sea and traveling across the Eastern Alps into the Baltic region. With these cyclones, extreme precipitation over Central Europe potentially triggers significant flood events. Understanding the prediction ability of Vb-cyclones would lower risks from adverse impacts. This study analyzes the robustness of an atmosphere–ocean regional coupled model, including interactive models for the Mediterranean Sea (MED) and North and Baltic Seas (NORDIC) in reproducing observed Vb-cyclone characteristics. We use the regional climate model (RCM) COSMO-CLM (CCLM) in stand-alone and coupled with the ocean model NEMO configurations for the EURO-CORDEX domain from 1979 to 2014, driven by the ERA-Interim reanalysis. Sea surface temperature (SST) is evaluated to demonstrate the stability and reliability of the coupled configurations. Compared to observations, simulated SSTs show biases (~ 1 °C), especially during winter and summer. Generally, all model configurations are able to replicate Vb-cyclones, their trajectories, and associated precipitation fields. Cyclone trajectories are comparably well simulated with the coupled models, as with the stand-alone simulation which is driven by the reanalysis SST in the MED and NORDIC seas. The cyclone intensity shows large deviations from reanalysis reference in the simulations with the interactive MED Sea, and smallest with CCLM. Precipitation characteristics are similarly simulated in the coupled and stand-alone (with reanalysis SST) simulations. The results suggest that our coupled RCM is useful for studying the impacts of highly resolved and interactively simulated SSTs on European extreme events and regional climate, a crucial prerequisite for understanding future climate conditions.

A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large‐scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph‐based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space–time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under:Science of Water > Water ExtremesScience of Water > Hydrological ProcessesScience of Water > Methods

Radar observations of mesosphere/lower thermosphere (MLT) winds at middle latitudes obtained from meteor radar 2004–date and the low-frequency drift method 1979–2008 have been combined to obtain a homogeneous long-term data set of MLT dynamics at 90 km altitude. The data are analyzed to obtain tendencies of prevailing winds during the last three decades. On a seasonal time scale, the zonal winds show positive trends towards more westerly winds throughout the year, while the meridional wind trends are negative in autumn/winter and positive in spring/summer. There is a tendency that the trends of both zonal and meridional summer prevailing winds are changing after 1995. Using a numerical circulation model with realistic ozone and carbon dioxide fields and with tropospheric/lower stratospheric circulation taken from ERA reanalyses, the observed trend changes can be reproduced qualitatively. The MLT wind trends are, according to the model, mainly due to the influence of changes in tropospheric and lower stratospheric dynamics.