Description: Interannual to decadal variability of Rhine river streamflow and their relationship with large-scale climate anomaly patterns for spring (MAM) and autumn (SON) are investigated through statistical analysis of observed streamflow data and global climate anomaly fields. A wavelet analysis reveals that spring streamflow variability is non-stationary with enhanced variability in the 8–16 years band from 1860 to 1900 and in the 2–8 years and 16–30 years after 1960. A composite analysis reveals that streamflow anomalies during spring are related with a sea surface temperature (SST) pattern which resembles the corresponding El Nino-Southern Oscillation (ENSO) SST pattern. The corresponding atmospheric circulation pattern favors enhanced moisture advection over Rhine catchment area during positive streamflow anomalies. During autumn the streamflow variability follows a distribution similar to spring streamflow but with a strong peak in the 30–60 year band. Autumn streamflow anomalies are significantly related only with the North Atlantic SST anomalies. The atmospheric circulation pattern associated to high streamflow during autumn, which is more regional than the corresponding spring pattern, shows a deep low-pressure system over the British Isles and the north-western part of Europe and a shift southward of the Atlantic jet axis. The orientation of the axis of the Atlantic and African Jet, as well as the advection of the moist air from the ocean, plays a crucial role in the variability of Rhine streamflow both in spring and autumn.

Description: Over the past decades Europe has experienced heavy floods with major consequences for thousands of people and billions of Euros worth of damage. In particular, the summer 2013 flood in Central Europe showed how vulnerable modern society is to hydrological extremes and emphasizes once more the need for improved forecast methods of such extreme climatic events. Based on a multiple linear regression model, it is shown here that 55% of the June 2013 Elbe River extreme discharge could have been predicted using May precipitation, soil moisture and sea level pressure. Moreover, our model was able to predict more than 75% of the total Elbe River discharge for June 2013 (in terms of magnitude) by incorporating also the amount of precipitation recorded during the days prior the flood, but the predicted discharge for the June 2013 event was still underestimated by 25%. Given that all predictors used in the model are available at the end of each month, the forecast scheme can be used to predict extreme events and to provide early warnings for upcoming floods. The forecast methodology could be efficient for other rivers also, depending on their location and their climatic background.

Description: Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months’ oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation.

Description: As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, 10.5880/GFZ.4.4.2023.001).

Description: The response of evapotranspiration to anthropogenic warming is of critical importance for the water and carbon cycle. Contradictory conclusions about evapotranspiration changes are caused primarily by their brevity in time and sparsity in space, as well as the strong influence of internal variability. Here, we present the first gridded reconstruction of the summer (June, July, and August) vapor pressure deficit (VPD) for the past 4 centuries at the European level. This gridded reconstruction is based on 26 European tree ring oxygen isotope records and is obtained using a random forest approach. According to validation scores obtained with the Nash-Sutcliffe model efficiency, our reconstruction is robust over large parts of Europe since 1600, in particular for the westernmost and northernmost regions, where most tree ring records are located. Based on our reconstruction, we show that from the mid-1700s a trend towards higher summer VPD occurred in central Europe and the Mediterranean region that is related to a simultaneous increase in temperature and decrease in precipitation. This increasing summer VPD trend continues throughout the observational period and in recent times. Moreover, our summer VPD reconstruction helps to visualize the local and regional impacts of the current climate change, as well as to minimize statistical uncertainties of historical VPD variability. This paper provides also new insights into the relationship between summer VPD and large-scale atmospheric circulation, and we show that summer VPD has two preferred modes of variability, namely a NW-SE dipole-like mode and a N-S dipole-like mode. Furthermore, the interdisciplinary use of the data should be emphasized, as summer VPD is a crucial parameter for many climatological feedback processes in the Earth's surface system. The reconstructed summer VPD gridded data over the last 400 years are available at the following link: 10.5281/zenodo.5958836 (Balting et al., 2022).