ISIMIP2b Simulation Data from Water (global) Sector

DOI

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate impacts across sectors.

ISIMIP2b is the second simulation round of the second phase of ISIMIP. ISIMIP2b considers impacts on different sectors at the global and regional scales: water, fisheries and marine ecosystems, energy supply and demand, forests, biomes, agriculture, agro-economic modeling, terrestrial biodiversity, permafrost, coastal infrastructure, health and lakes.

ISIMIP2b simulations focus on separating the impacts and quantifying the pure climate change effects of historical warming (1861-2005) compared to pre-industrial reference levels (1661-1860); and on quantifying the future (2006-2099) and extended future (2006-2299) impact projections accounting for low (RCP2.6), mid-high (RCP6.0) and high (RCP8.5) greenhouse gas emissions, assuming either constant (year 2005) or dynamic population, land and water use and -management, economic development, bioenergy demand, and other societal factors. The scientific rationale for the scenario design is documented in Frieler et al. (2017).

The ISIMIP2b bias-corrected observational climate input data (Lange, 2018; Frieler et al., 2017) consists of an updated version of the observational dataset EWEMBI at daily temporal and 0.5° spatial resolution, which better represents the CMIP5 GCM ensemble in terms of both spatial model resolution and equilibrium climate sensitivity. The bias correction methods (Lange, 2018; Frieler et al., 2017; Lange, 2016) were applied to CMIP5 output of GDFL-ESM2M, HadGEM2-ES, IPSL-CM5A-LP and MIROC5. Access to the input data for the impact models, and further information on bias correction methods, is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/isimip2b-bias-correction).

This entry refers to the ISIMIP2b simulation data from thirteen global hydrology models:
CLM4.5,
CLM5.0,
CWatM,
DBH,
H08,
JULES-W1 (formerly JULES_TUC),
LPJmL,
MATSIRO,
MPI-HM,
ORCHIDEE,
ORCHIDEE-DGVM,
PCR-GLOBWB,
WaterGAP2.


The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/ (ISIMIP Changelog) and https://www.isimip.org/outputdata/dois-isimip-data-sets/ (ISIMIP DOI publications).


The ISIMIP2b water (global) outputs are based on simulations from 13 global hydrology models (see listing) according to the ISIMIP2b protocol (https://www.isimip.org/protocol/#isimip2b). The models simulate hydrological processes and dynamics (some of the models also consider human water abstractions and reservoir regulation) based on climate and physio-geographical information. A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/

Identifier
DOI https://doi.org/10.5880/PIK.2020.004
Related Identifier https://www.earthsystemcog.org/projects/cog/tutorials_web
Related Identifier https://www.isimip.org/outcomes/publications-overview-page/
Related Identifier https://www.isimip.org/protocol/#isimip2b
Related Identifier https://www.isimip.org/impactmodels
Related Identifier https://www.isimip.org/gettingstarted/#input-data-bias-correction
Related Identifier https://www.isimip.org/outputdata/output-data-changelog/
Related Identifier https://www.isimip.org/outputdata/dois-isimip-data-sets/
Related Identifier http://dx.doi.org/10.5194/gmd-10-4321-2017
Related Identifier http://dx.doi.org/10.5194/esd-9-627-2018
Related Identifier http://dx.doi.org/10.5880/pik.2016.004
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:7024
Provenance
Creator Gosling, Simon Newland ORCID logo; Müller Schmied, Hannes ORCID logo; Burek, Peter ORCID logo; Chang, Jinfeng ORCID logo; Ciais, Philippe ORCID logo; Döll, Petra ORCID logo; Eisner, Stephanie ORCID logo; Flörke, Martina ORCID logo; Gerten, Dieter ORCID logo; Grillakis, Manolis ORCID logo; Hanasaki, Naota ORCID logo; Koutroulis, Aristeidis ORCID logo; Leng, Guoyong (ORCID: 0000-0001-6345-143X); Liu, Xingcai ORCID logo; Oki, Taikan ORCID logo; Ostberg, Sebastian ORCID logo; Pokhrel, Yadu (ORCID: 0000-0002-1367-216X); Satoh, Yusuke ORCID logo; Schaphoff, Sibyll ORCID logo; Seneviratne, Sonia I. ORCID logo; Stacke, Tobias ORCID logo; Tang, Qiuhong ORCID logo; Thiery, Wim ORCID logo; Wada, Yoshihide ORCID logo; Büchner, Matthias ORCID logo; Vega, Iliusi ORCID logo; Volkholz, Jan; Schewe, Jacob ORCID logo; Zhao, Fang ORCID logo
Publisher GFZ Data Services
Contributor Gosling, Simon Newland; Müller Schmied, Hannes; Büchner, Matthias; Schewe, Jacob; Zhao, Fang; Seiradakis, Konstantinos D.; Guimberteau, Matthieu; Ducharne, Agnès; ISIMIP Coordination Team; Thiery, Wim; Leng, Guoyong; Tang, Qiuhong; Hanasaki, Naota; Koutroulis, Aristeidis; Gerten, Dieter; Stacke, Tobias; Chang, Jinfeng; Wada, Yoshihide; Burek, Peter; Satoh, Yusuke
Publication Year 2020
Rights Model data are licensed under CC BY 4.0; EXCEPTIONS: (1) Data from models CWatM, MATSIRO and WaterGAP2 are licensed under CC BY-NC 4.0;; (2) Data from model MPI-HM are licensed under CC BY-SA 4.0; https://creativecommons.org/licenses/by/4.0/; https://creativecommons.org/licenses/by-nc/4.0/; https://creativecommons.org/licenses/by-sa/4.0/
OpenAccess true
Contact ISIMIP Coordination Team (Potsdam-Institute for Climate Impact Research (PIK), Germany); Schewe, Jacob (Potsdam-Institute for Climate Impact Research (PIK), Germany); Zhao, Fang (Potsdam-Institute for Climate Impact Research (PIK), Germany); Gosling, Simon Newland (School of Geography, University of Nottingham, UK); Müller Schmied, Hannes (Institute of Physical Geography (IPG), Goethe-University Frankfurt, Germany); Thiery, Wim (Vrije Universiteit Brussel, Belgium; ETH Zurich, Switzerland); Leng, Guoyong (Environmental Change Institute (ECI), University of Oxford, UK); Tang, Qiuhong (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China); Hanasaki, Naota (National Institute for Environmental Studies, Japan); Koutroulis, Aristeidis (Technical University of Crete, Greece); Gerten, Dieter (Potsdam-Institute for Climate Impact Research (PIK), Germany); Stacke, Tobias (Max Planck Institute for Meteorology (MPI-M), Germany); Chang, Jinfeng (Laboratoire des Sciences du Climat et de l'Environnement (LSCE), France); Wada, Yoshihide (International Institute for Applied Systems Analysis, Austria; Department of Physical Geography, Utrecht University, The Netherlands); Burek, Peter (International Institute for Applied Systems Analysis (IIASA), Austria); Satoh, Yusuke (International Institute for Applied Systems Analysis (IIASA), Austria)
Representation
Resource Type Dataset
Discipline Earth System Research
Spatial Coverage (-179.750W, -89.750S, 179.750E, 89.750N); global, daily, monthly, yearly; global, daily, monthly, yearly; global, daily, monthly, yearly; global, daily, monthly, yearly