@article{AgarwalCaesarMarwanetal.2019, author = {Agarwal, Ankit and Caesar, Levke and Marwan, Norbert and Maheswaran, Rathinasamy and Merz, Bruno}, title = {Network-based identification and characterization of teleconnections on different scales}, series = {Scientific Reports}, volume = {9}, journal = {Scientific Reports}, publisher = {Macmillan Publishers Limited}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-019-45423-5}, pages = {12}, year = {2019}, abstract = {Sea surface temperature (SST) patterns can - as surface climate forcing - affect weather and climate at large distances. One example is El Ni{\~n}o-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of - at a certain timescale - similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole.}, language = {en} } @article{GanguliMerz2019, author = {Ganguli, Poulomi and Merz, Bruno}, title = {Trends in Compound Flooding in Northwestern Europe During 1901-2014}, series = {Geophysical research letters}, volume = {46}, journal = {Geophysical research letters}, number = {19}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1029/2019GL084220}, pages = {10810 -- 10820}, year = {2019}, abstract = {We analyze trends in compound flooding resulting from high coastal water levels (HCWLs) and peak river discharge over northwestern Europe during 1901-2014. Compound peak discharge associated with 37 stream gauges with at least 70 years of record availability near the North and Baltic Sea coasts is used. Compound flooding is assessed using a newly developed index, compound hazard ratio, that compares the severity of river flooding associated with HCWL with the at-site, T-year (a flood with 1/T chance of being exceeded in any given year) fluvial peak discharge. Our findings suggest a spatially coherent pattern in the dependence between HCWL and river peaks and in compound flood magnitudes and frequency. For higher return levels, we find upward trends in compound hazard ratio frequency at midlatitudes (gauges from 47 degrees N to 60 degrees N) and downward trends along the high latitude (>60 degrees N) regions of northwestern Europe. Plain Language Summary Compound floods in delta areas, that is, the co-occurrence of high coastal water levels (HCWLs) and high river discharge, are a particular challenge for disaster management. Such events are caused by two distinct mechanisms: (1) HCWLs may affect river flows and water levels by backwater effects or by reversing the seaward flow of rivers, particularly in regions with elevation less than 10 m in northwestern Europe. (2) The correlation between HCWL and river flow peaks may also stem from a common meteorological driver. Severe storm periods may be associated with high winds leading to storm surges, and at the same time with high precipitation followed by inland flooding. Understanding the historical trends in compound flooding, owing to changes in relative sea levels, in river flooding and in the dependence between these two drivers, is essential for projecting future changes and disaster management. The risk assessment frameworks are often limited to assessing flood risk from a single driver only. We present a new approach to assess compound flood severity resulting from extreme coastal water level and peak river discharge. We find upward trends in compound flooding for midlatitude regions and downward trends for high latitudes in northwestern Europe.}, language = {en} } @article{SairamSchroeterRoezeretal.2019, author = {Sairam, Nivedita and Schroeter, Kai and R{\"o}zer, Viktor and Merz, Bruno and Kreibich, Heidi}, title = {Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes}, series = {Water resources research}, volume = {55}, journal = {Water resources research}, number = {10}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2019WR025068}, pages = {8223 -- 8237}, year = {2019}, abstract = {Flood damage processes are complex and vary between events and regions. State-of-the-art flood loss models are often developed on the basis of empirical damage data from specific case studies and do not perform well when spatially and temporally transferred. This is due to the fact that such localized models often cover only a small set of possible damage processes from one event and a region. On the other hand, a single generalized model covering multiple events and different regions ignores the variability in damage processes across regions and events due to variables that are not explicitly accounted for individual households. We implement a hierarchical Bayesian approach to parameterize widely used depth-damage functions resulting in a hierarchical (multilevel) Bayesian model (HBM) for flood loss estimation that accounts for spatiotemporal heterogeneity in damage processes. We test and prove the hypothesis that, in transfer scenarios, HBMs are superior compared to generalized and localized regression models. In order to improve loss predictions for regions and events for which no empirical damage data are available, we use variables pertaining to specific region- and event-characteristics representing commonly available expert knowledge as group-level predictors within the HBM.}, language = {en} } @article{GanguliMerz2019, author = {Ganguli, Poulomi and Merz, Bruno}, title = {Extreme Coastal Water Levels Exacerbate Fluvial Flood Hazards in Northwestern Europe}, series = {Scientific reports}, volume = {9}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-019-49822-6}, pages = {14}, year = {2019}, abstract = {Compound flooding, such as the co-occurrence of fluvial floods and extreme coastal water levels (CWL), may lead to significant impacts in densely-populated Low Elevation Coastal Zones. They may overstrain disaster management owing to the co-occurrence of inundation from rivers and the sea. Recent studies are limited by analyzing joint dependence between river discharge and either CWL or storm surges, and little is known about return levels of compound flooding, accounting for the covariance between drivers. Here, we assess the compound flood severity and identify hotspots for northwestern Europe during 1970-2014, using a newly developed Compound Hazard Ratio (CHR) that compares the severity of compound flooding associated with extreme CWL with the unconditional T-year fluvial peak discharge. We show that extreme CWL and stronger storms greatly amplify fluvial flood hazards. Our results, based on frequency analyses of observational records during 2013/2014's winter storm Xaver, reveal that the river discharge of the 50-year compound flood is up to 70\% larger, conditioned on the occurrence of extreme CWL, than that of the at-site peak discharge. For this event, nearly half of the stream gauges show increased flood hazards, demonstrating the importance of including the compounding effect of extreme CWL in river flood risk management.}, language = {en} } @article{SiegSchinkoVogeletal.2019, author = {Sieg, Tobias and Schinko, Thomas and Vogel, Kristin and Mechler, Reinhard and Merz, Bruno and Kreibich, Heidi}, title = {Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification}, series = {PLoS ONE}, volume = {14}, journal = {PLoS ONE}, number = {4}, publisher = {Public Library of Science}, address = {San Francisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0212932}, pages = {21}, year = {2019}, abstract = {Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.}, language = {en} } @article{SiegVogelMerzetal.2019, author = {Sieg, Tobias and Vogel, Kristin and Merz, Bruno and Kreibich, Heidi}, title = {Seamless Estimation of Hydrometeorological Risk Across Spatial Scales}, series = {Earth's Future}, volume = {7}, journal = {Earth's Future}, number = {5}, publisher = {Wiley-Blackwell}, address = {Hoboken, NJ}, issn = {2328-4277}, doi = {10.1029/2018EF001122}, pages = {574 -- 581}, year = {2019}, abstract = {Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.}, language = {en} }