Publications
Following publications have been announced by our Institute of Coastal Systems – Analysis and Modeling. For further information please contact the marked authors resp. co-authors of the publications:
Hagemann, S., Nguyen, T.T., & Ho-Hagemann, H.T.M. (2024): A three-quantile bias correction with spatial transfer for the correction of simulated European river runoff to force ocean models. Ocean Sci., 20, 1457–1478, doi:10.5194/os-20-1457-2024
Abstract:
In ocean or Earth system model applications, the riverine freshwater inflow is an important flux affecting salinity and marine stratification in coastal areas. However, in climate change studies, the river runoff based on climate model output often has large biases on local, regional, or even basin-wide scales. If these biases are too large, the ocean model forced by the runoff will drift into a different climate state compared to the observed state, which is particularly relevant for semi-enclosed seas such as the Baltic Sea. To achieve low biases in riverine freshwater inflow in large-scale climate applications, a bias correction is required that can be applied in periods where runoff observations are not available and that allows spatial transferability of its correction factors. In order to meet these requirements, we have developed a three-quantile bias correction that includes different correction factors for low-, medium-, and high-percentile ranges of river runoff over Europe. Here, we present an experimental setup using the Hydrological Discharge (HD) model and its high-resolution () grid. First, bias correction factors are derived at the locations of the downstream stations with available daily discharge observations for many European rivers. These factors are then transferred to the respective river mouths and mapped to neighbouring grid boxes belonging to ungauged catchments. The results show that the bias correction generally leads to an improved representation of river runoff. Especially over northern Europe, where many rivers are regulated, the three-quantile bias correction provides an advantage compared to a bias correction that only corrects the mean bias of the river runoff. Evaluating two NEMO (Nucleus for European Modelling of the Ocean) model simulations in the German Bight indicated that the use of the bias-corrected discharges as forcing leads to an improved simulation of sea surface salinity in coastal areas. Although the bias correction is tailored to the high-resolution HD model grid over Europe in the present study, the methodology is suitable for any high-resolution model region with a sufficiently high coverage of river runoff observations. It is also noted that the methodology is applicable to river runoff based on climate hindcasts, as well as on historical climate simulations where the sequence of weather events does not match the actual observed history. Therefore, it may also be applied in climate change simulations.
Feser, F., van Garderen, L., & Hansen, F. (2024): The Summer Heatwave 2022 over Western Europe: An Attribution to Anthropogenic Climate Change. Bull. Amer. Meteor. Soc., 105, E2175–E2179, doi:10.1175/BAMS-D-24-0017.1
Introduction:
For most of the Eurasian continent and North America, the summer 2022 was unparalleled in temperature, characterized by persistent heatwaves and droughts over Europe, the United States, and China (Lu et al. 2022). The summer heatwave over Europe featured record-breaking temperatures in many countries across western Europe and lead to more than 60 000 heat-related deaths (Ballester et al. 2023). The Copernicus Climate Change Service (C3S) ranked it the hottest European summer on record with average temperatures being 1.34°C higher than the 1991–2020 climatology (Copernicus 2022). Many of the 2022 local European heatwaves were characterized by long durations and large spatial extensions with regionally intense heat and drought periods (Imbery et al. 2023; Lentze 2023). The exceptional summer 2022 started off with high temperatures in southern Europe in May, leading to new temperature records, for instance, in France and Portugal (Copernicus Observer 2022). A number of heatwaves followed in June and continued into July and August, spreading from southwestern Europe northeastwards toward the United Kingdom and Scandinavia. Extreme temperatures of over 40°C were recorded in Hamburg, Germany, on the 20 July. This was the first time that temperatures exceeding 40°C were measured north of 53°N in central Europe (Imbery et al. 2023). The World Weather Attribution project states that temperatures of more than 40°C in the United Kingdom were extremely unlikely without anthropogenic influence (Zachariah et al. 2022; Christidis et al. 2020). Persistent high pressure over western Europe in combination with advected hot air masses from North Africa, moving northeastwards from west of Portugal ahead of a trough, caused heatwaves over large areas of western Europe (Copernicus Observer 2022). The summer heatwave 2022 is exemplary for the latest IPCC report results, which state that heatwaves have become not only more intense and persistent but also more frequent in recent decades (Seneviratne et al. 2021). The last decades revealed a rapid shift toward hotter summers in Europe (Lhotka and Kyselý 2022). Future scenarios project a further increase in frequency, duration, and intensification of heatwaves over most land areas [for an overview, see Barriopedro et al. (2023)] due to global warming. It is crucial to understand how human activities have influenced these heatwaves for both mitigation and adaptation.
In this article, we apply a holistic attribution approach combining long-term statistics and event-based storylines, allowing for both an attribution to anthropogenic climate change and a historical classification. We attribute the summer heatwave over western Europe 2022 to anthropogenic climate change using spectrally nudged storylines (van Garderen et al. 2021; van Garderen and Mindlin 2022). With this method, van Garderen et al. (2021) showed that the 2003 heatwave in Europe was 0.6°C and the 2010 heatwave in Russia was even 1°C stronger due to anthropogenic climate change. The storylines enable us to quantify the anthropogenic climate change influence on the event as it was observed, for past, present, and future climate states, despite the presence of possible large-scale natural variability. To put the heatwave into historical context, we analyze ERA5 (Hersbach et al. 2020) reanalysis data and a 2000-yr paleo simulation using a sophisticated clustering method (Philipp et al. 2007; Hansen and Belušić 2021), so that long-term statistics add value to the event-specific attribution method.
Jia, B., Xu, L., Chen, X., & Zhang, W. (2024): Spatio-temporal variations of the heat fluxes at the ice-ocean interface in the Bohai Sea. Front. Mar. Sci., 11:1471061, doi:10.3389/fmars.2024.1471061
Abstract:
Thermodynamic process between the ice and the ocean plays a critical role in the evolution of sea-ice growth and melting in marginal seas. At the ice-ocean interface, the oceanic heat flux and the conductive heat flux transmitted through the ice layer jointly determine the latent heat flux driving the phase change (i.e., ice freezing/melting). In this study, the determination of two important thermal parameters in the ice module of the HAMSOM ice-ocean coupled model, namely the mixed layer thickness and the heat exchange coefficient at the ice-ocean interface, has been adjusted to improve the model performance. Spatio-temporal variations of heat fluxes at the ice-ocean interface in the Bohai Sea are investigated, based on the validated sea ice simulation in the 2011/2012 ice season. The relationships between the interfacial heat fluxes and oceanic and atmospheric conditioning factors are identified. We found that the surface conductive heat flux through ice shows short-term fluctuations corresponding to the atmospheric conditions, the magnitude of these fluctuations decreases with depth in the ice layer, likely due to reduced influence from atmospheric conditions at greater depths. Atmospheric conditions are the key controlling factors of the conductive heat flux through ice, while the oceanic heat flux is mainly controlled by the oceanic conditions (i.e., mixed layer temperature). Spatially, the value of the oceanic heat flux is larger in the marginal ice zone with relatively thin ice than in the inner ice zone with relatively thick ice. In the Bohai Sea, when ice is growing, heat within the ice layer is transferred upward from the ice base, and the heat is losing at the ice-ocean interface. This heat loss in the inner ice zone is obviously greater than that in the marginal ice zone. Whereas when ice is melting, the opposite is true.
Enayatighadikolaei, H., Suzuki, T., Soltanpour, M., & Thilakarathne, S. (2024): Application of the Bruun rule in evaluating the effect of water level fall on the Caspian Sea profile evolution. Coastal Engineering Journal, 1–15, doi:10.1080/21664250.2024.2422167
Abstract:
The combined effects of climate change and anthropogenic activities induce significant sea-level alterations, changing beach morphologies. While the effects of water level rise on coastal regions have been extensively studied, the consequences caused by water level fall, particularly in enclosed water basins, have received limited attention. The Bruun rule is an empirical approach for estimating the erosion of sandy beaches in response to sea level rise. This study evaluates the efficacy of the Bruun rule and associated methods under water-level fall conditions. An extensive investigation was followed to understand Bruun’s rule application and its hypotheses in this context. Cross-shore profiles were collected from three stations: Larim, Farahabad, and Miankaleh, located along the southeastern coast of the Caspian Sea between 2013 and 2021. Results indicate that Bruun’s predictions are more reliable, considering their accuracy and applicability. Additionally, active zone bed slope emerges as the most significant factor influencing Bruun prediction, performing well with slopes between 0.013 and 0.016. Moreover, Bruun’s hypotheses were assessed by comparing the observed profiles and water levels over 7 months, 2 years, and 3 years, revealing a lag time contradicting Bruun’s hypothesis. Results further indicate that the Bruun rule overlooks the impacts of water level fluctuations.
