Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations
This dataset comprises time series of 6-hourly surges and the daily streamflow records simulated from hydrodynamic-hydrologic modelling to quantify the compound effects of surges and peak river discharge over northwestern Europe. We simulate the surge height (m) and river discharge (m3/s) at the vic...
Main Authors: | , , , , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
GFZ Data Services
2019
|
Subjects: | |
Online Access: | https://dx.doi.org/10.5880/gfz.4.4.2019.003 http://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=escidoc:4851894 |
id |
ftdatacite:10.5880/gfz.4.4.2019.003 |
---|---|
record_format |
openpolar |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
storm surge river floods urban coastal management compound floods deltas and estuaries dynamical downscaling land > landform > coast science > natural science > water science > hydrology science > natural science > atmospheric science > meteorology > hydrometeorology climate effect > environmental damage > water damage EARTH SCIENCE SERVICES > MODELS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > DELTAS EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT > WATER MANAGEMENT EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > FLOODS |
spellingShingle |
storm surge river floods urban coastal management compound floods deltas and estuaries dynamical downscaling land > landform > coast science > natural science > water science > hydrology science > natural science > atmospheric science > meteorology > hydrometeorology climate effect > environmental damage > water damage EARTH SCIENCE SERVICES > MODELS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > DELTAS EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT > WATER MANAGEMENT EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > FLOODS Ganguli, Poulomi Paprotny, Dominik Hasan, Mehedi Güntner, Andreas Merz, Bruno Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations |
topic_facet |
storm surge river floods urban coastal management compound floods deltas and estuaries dynamical downscaling land > landform > coast science > natural science > water science > hydrology science > natural science > atmospheric science > meteorology > hydrometeorology climate effect > environmental damage > water damage EARTH SCIENCE SERVICES > MODELS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > DELTAS EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT > WATER MANAGEMENT EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > FLOODS |
description |
This dataset comprises time series of 6-hourly surges and the daily streamflow records simulated from hydrodynamic-hydrologic modelling to quantify the compound effects of surges and peak river discharge over northwestern Europe. We simulate the surge height (m) and river discharge (m3/s) at the vicinity of the coast in the reference (1981–2005) and projected (2040–2069) periods using time series of high-resolution (0.11⁰, which is about 12 km) regional dynamically downscaled meteorological forcings from the World Climate Research Program CORDEX (COordinated Regional Climate Downscaling EXperiment) framework (Nikulin et al., 2011) (https://esg-dn1.nsc.liu.se/search/esgf-liu/) for Europe, forced by five host (or parent)-GCMs from the CMIP5 project. Given data availability, we use meteorological forcing dataset from SHMI’s Rossby Centre regional atmospheric model (RCA4; Strandberg et al., 2015) driven by five host GCMs participating in CMIP5, i.e., CNRM-CERFACS-CNRM-CM5, ICHEC-EC-EARTH, IPSL-IPSL-CM5A-MR, MOHC-HadGEM2-ES, and MPI-M-MPI-ESM-LR. For each host GCM, the first ensemble member (r1i1p1) of climate realization has been used except the ICHEC-EC-EARTH model, r12i1p1 realization has been used. All simulations have the same physical version (p1) and initialization method (i1) but differ in initial states (i.e., r1 and r12). After 2005, the future scenarios diverge, and we investigate projected change in compound flood climatology during 2040 – 2069 using business as usual RCP8.5 scenario to cover extremes. While we simulate surge at 33 tide gauges using hydrodynamic model Delft3D (Delft3D-FLOW, 2014), the simulation of discharge from 39 stream gauges is performed using the global hydrological and water use model, WaterGAP 2.2d (Müller Schmied et al., 2014). Since we are mostly interested in the meteorological phenomena that drive the compound flood mechanism, we focus on modeling of surges and do not simulate tides. The individual datasets of the surge and discharge time series for each host GCMs in the GCM-RCM chains are available in the sub-folders ‘Discharge’ and ‘Surge’ under the zip-file ‘CF_drivers’. : To simulate surge from meteorological forcing, we use hydrodynamic model Delft3D (Delft3D-FLOW, 2014) that uses depth-averaged shallow water equations. The model was previously calibrated and validated against observed skew surges for the Euro-CORDEX domain in Paprotny et al. (2016). Details of hydrodynamic model parameters (such as wind drag coefficients and channel roughness) and boundary conditions are discussed in Paprotny et al. (2016). The simulation is driven by 6-hourly resolution sea level pressure and winds (See Data processing section for details) available at 0.11⁰ resolution. To accurately simulate extreme storm surges (for example, annual maxima), the time step of calculations is kept as 30-minutes. We simulate the global hydrological and water use model, WaterGAP 2.2d (Müller Schmied et al., 2014) to simulate current and future runoff at daily time steps from each river basin. WaterGAP simulates runoff, groundwater recharge and water use with a spatial resolution of 0.5⁰ (approximately 55 km) for all land areas except Antarctica. The WaterGAP is calibrated (Müller Schmied et al., 2014) using daily reanalysis-based WFDEI-GPCC (Watch Forcing Data based on ERA-Interim) (Weedon et al., 2014) meteorological forcing. WaterGAP is tuned based on observed river discharge at stations around the world individually and for each ‘first-order’ sub-basin using a tuning parameter, runoff coefficient. For simulating river discharge using WaterGAP, we select locations of stream gauges from medium to large-sized basins with a catchment area between 1000 and 1,05,000 km2 located at a radial distance of within 200 km distance from the tide gauges (Ganguli & Merz, 2019b, 2019a). For more information, please consult the data description document. |
format |
Dataset |
author |
Ganguli, Poulomi Paprotny, Dominik Hasan, Mehedi Güntner, Andreas Merz, Bruno |
author_facet |
Ganguli, Poulomi Paprotny, Dominik Hasan, Mehedi Güntner, Andreas Merz, Bruno |
author_sort |
Ganguli, Poulomi |
title |
Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations |
title_short |
Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations |
title_full |
Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations |
title_fullStr |
Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations |
title_full_unstemmed |
Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations |
title_sort |
compound flood drivers for northwestern europe in high-resolution euro-cordex simulations |
publisher |
GFZ Data Services |
publishDate |
2019 |
url |
https://dx.doi.org/10.5880/gfz.4.4.2019.003 http://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=escidoc:4851894 |
long_lat |
ENVELOPE(-61.061,-61.061,-72.311,-72.311) |
geographic |
Merz |
geographic_facet |
Merz |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://oss.deltares.nl/documents/183920/185723/Delft3D-FLOW_User_Manual.pdf http://urn.kb.se/resolve?urn=urn:nbn:se:smhi:diva-2839 https://dx.doi.org/doi of paper when available https://dx.doi.org/10.1038/s41561-018-0262-x https://oss.deltares.nl/documents/183920/185723/Delft3D-FLOW_User_Manual.pdf https://dx.doi.org/10.1038/s41598-019-49822-6 https://dx.doi.org/10.1029/2019gl084220 https://dx.doi.org/10.5194/nhess-13-2017-2013 https://dx.doi.org/10.1002/wcc.252 https://dx.doi.org/10.1073/pnas.1604386113 https://dx.doi.org/10.1007/s10584-019-02431-8 https://dx.doi.org/10.5194/hess-18-3511-2014 https://dx.doi.org/10.1371/journal.pone.0118571 https://dx.doi.org/10.1002/2016wr019752 https://dx.doi.org/10.1175/jamc-d-11-0161.1 https://dx.doi.org/10.5194/hess-17-5061-2013 https://dx.doi.org/10.1002/2015jd024411 https://dx.doi.org/10.1111/j.1600-0870.2010.00466.x https://dx.doi.org/10.1051/e3sconf/20160702001 http://urn.kb.se/resolve?urn=urn:nbn:se:smhi:diva-2839 https://dx.doi.org/10.1002/2014wr015638 https://dx.doi.org/10.5285/3b602f74-8374-1e90-e053-6c86abc08d39 https://dx.doi.org/10.1175/jhm-d-17-0180.1 |
op_rights |
CC BY 4.0 http://creativecommons.org/licenses/by/4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5880/gfz.4.4.2019.003 https://doi.org/doi of paper when available https://doi.org/10.1038/s41561-018-0262-x https://doi.org/10.1038/s41598-019-49822-6 https://doi.org/10.1029/2019gl084220 https://doi.org/10.5194/nhess-13-2017- |
_version_ |
1766262528421134336 |
spelling |
ftdatacite:10.5880/gfz.4.4.2019.003 2023-05-15T13:55:42+02:00 Compound flood drivers for northwestern Europe in high-resolution EURO-CORDEX Simulations Ganguli, Poulomi Paprotny, Dominik Hasan, Mehedi Güntner, Andreas Merz, Bruno 2019 application/octet-stream https://dx.doi.org/10.5880/gfz.4.4.2019.003 http://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=escidoc:4851894 en eng GFZ Data Services https://oss.deltares.nl/documents/183920/185723/Delft3D-FLOW_User_Manual.pdf http://urn.kb.se/resolve?urn=urn:nbn:se:smhi:diva-2839 https://dx.doi.org/doi of paper when available https://dx.doi.org/10.1038/s41561-018-0262-x https://oss.deltares.nl/documents/183920/185723/Delft3D-FLOW_User_Manual.pdf https://dx.doi.org/10.1038/s41598-019-49822-6 https://dx.doi.org/10.1029/2019gl084220 https://dx.doi.org/10.5194/nhess-13-2017-2013 https://dx.doi.org/10.1002/wcc.252 https://dx.doi.org/10.1073/pnas.1604386113 https://dx.doi.org/10.1007/s10584-019-02431-8 https://dx.doi.org/10.5194/hess-18-3511-2014 https://dx.doi.org/10.1371/journal.pone.0118571 https://dx.doi.org/10.1002/2016wr019752 https://dx.doi.org/10.1175/jamc-d-11-0161.1 https://dx.doi.org/10.5194/hess-17-5061-2013 https://dx.doi.org/10.1002/2015jd024411 https://dx.doi.org/10.1111/j.1600-0870.2010.00466.x https://dx.doi.org/10.1051/e3sconf/20160702001 http://urn.kb.se/resolve?urn=urn:nbn:se:smhi:diva-2839 https://dx.doi.org/10.1002/2014wr015638 https://dx.doi.org/10.5285/3b602f74-8374-1e90-e053-6c86abc08d39 https://dx.doi.org/10.1175/jhm-d-17-0180.1 CC BY 4.0 http://creativecommons.org/licenses/by/4.0 CC-BY storm surge river floods urban coastal management compound floods deltas and estuaries dynamical downscaling land > landform > coast science > natural science > water science > hydrology science > natural science > atmospheric science > meteorology > hydrometeorology climate effect > environmental damage > water damage EARTH SCIENCE SERVICES > MODELS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > DELTAS EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT > WATER MANAGEMENT EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > FLOODS dataset Dataset 2019 ftdatacite https://doi.org/10.5880/gfz.4.4.2019.003 https://doi.org/doi of paper when available https://doi.org/10.1038/s41561-018-0262-x https://doi.org/10.1038/s41598-019-49822-6 https://doi.org/10.1029/2019gl084220 https://doi.org/10.5194/nhess-13-2017- 2021-11-05T12:55:41Z This dataset comprises time series of 6-hourly surges and the daily streamflow records simulated from hydrodynamic-hydrologic modelling to quantify the compound effects of surges and peak river discharge over northwestern Europe. We simulate the surge height (m) and river discharge (m3/s) at the vicinity of the coast in the reference (1981–2005) and projected (2040–2069) periods using time series of high-resolution (0.11⁰, which is about 12 km) regional dynamically downscaled meteorological forcings from the World Climate Research Program CORDEX (COordinated Regional Climate Downscaling EXperiment) framework (Nikulin et al., 2011) (https://esg-dn1.nsc.liu.se/search/esgf-liu/) for Europe, forced by five host (or parent)-GCMs from the CMIP5 project. Given data availability, we use meteorological forcing dataset from SHMI’s Rossby Centre regional atmospheric model (RCA4; Strandberg et al., 2015) driven by five host GCMs participating in CMIP5, i.e., CNRM-CERFACS-CNRM-CM5, ICHEC-EC-EARTH, IPSL-IPSL-CM5A-MR, MOHC-HadGEM2-ES, and MPI-M-MPI-ESM-LR. For each host GCM, the first ensemble member (r1i1p1) of climate realization has been used except the ICHEC-EC-EARTH model, r12i1p1 realization has been used. All simulations have the same physical version (p1) and initialization method (i1) but differ in initial states (i.e., r1 and r12). After 2005, the future scenarios diverge, and we investigate projected change in compound flood climatology during 2040 – 2069 using business as usual RCP8.5 scenario to cover extremes. While we simulate surge at 33 tide gauges using hydrodynamic model Delft3D (Delft3D-FLOW, 2014), the simulation of discharge from 39 stream gauges is performed using the global hydrological and water use model, WaterGAP 2.2d (Müller Schmied et al., 2014). Since we are mostly interested in the meteorological phenomena that drive the compound flood mechanism, we focus on modeling of surges and do not simulate tides. The individual datasets of the surge and discharge time series for each host GCMs in the GCM-RCM chains are available in the sub-folders ‘Discharge’ and ‘Surge’ under the zip-file ‘CF_drivers’. : To simulate surge from meteorological forcing, we use hydrodynamic model Delft3D (Delft3D-FLOW, 2014) that uses depth-averaged shallow water equations. The model was previously calibrated and validated against observed skew surges for the Euro-CORDEX domain in Paprotny et al. (2016). Details of hydrodynamic model parameters (such as wind drag coefficients and channel roughness) and boundary conditions are discussed in Paprotny et al. (2016). The simulation is driven by 6-hourly resolution sea level pressure and winds (See Data processing section for details) available at 0.11⁰ resolution. To accurately simulate extreme storm surges (for example, annual maxima), the time step of calculations is kept as 30-minutes. We simulate the global hydrological and water use model, WaterGAP 2.2d (Müller Schmied et al., 2014) to simulate current and future runoff at daily time steps from each river basin. WaterGAP simulates runoff, groundwater recharge and water use with a spatial resolution of 0.5⁰ (approximately 55 km) for all land areas except Antarctica. The WaterGAP is calibrated (Müller Schmied et al., 2014) using daily reanalysis-based WFDEI-GPCC (Watch Forcing Data based on ERA-Interim) (Weedon et al., 2014) meteorological forcing. WaterGAP is tuned based on observed river discharge at stations around the world individually and for each ‘first-order’ sub-basin using a tuning parameter, runoff coefficient. For simulating river discharge using WaterGAP, we select locations of stream gauges from medium to large-sized basins with a catchment area between 1000 and 1,05,000 km2 located at a radial distance of within 200 km distance from the tide gauges (Ganguli & Merz, 2019b, 2019a). For more information, please consult the data description document. Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) Merz ENVELOPE(-61.061,-61.061,-72.311,-72.311) |