Getting Started



Here you will find information about participating in ISIMIP as an impacts modeller. If you cannot find information you need, have a look on the FAQ page.


How to join ISIMIP

A document describing what it means to participate in ISIMIP as an impact modeller can be found here.


Input Data & Bias Correction

The ISIMIP framework includes bias-corrected climate-input data sets on a 0.5°x0.5°C global grid and at daily time steps. Additional socio-economic and human-influence data are also available, and detailed in the table below.

For ISIMIP2b, the bias-correction method has been updated and improved. See here for more information. See here for information on the Fast-Track bias-correction method.

If published input data sets for any reason need to be replaced or updated, you will find details of these changes in the input data change log below.

Information about downloading climate and other input data can be found here.

Availability of ISIMIP2b input data

Use the table's serach box to limit input data sets to a chosen simulation round, data type, or to search for a specific data set.

Data Set Data Type Simulation round Description
None
Other human influences
ISIMIP2b
Water abstraction for domestic and industrial uses consistent with SSP2.
Simulated ocean climate
ISIMIP2b
Non bais-corrected 3D oceanic temperature fileds on original GCM grid with monthly resolution from the GCMs: IPSL-CM5A-LR, GFDL-ESM2M, MIROC5, HadGEM2-ES.
Simulated atmospheric climate
ISIMIP2b
Uncorrected daily 3d wind components on original GCM grid for the GCMs: GFDL-ESM2M, MIROC5, IPSL-CM5A-LR & HadGEM-ES.
Simulated atmospheric climate
ISIMIP2b
Non bais-corrected 3D humidity and wind fileds on original GCM grid with monthly resolution from the GCMs: IPSL-CM5A-LR, GFDL-ESM2M, MIROC5, HadGEM2-ES.
Emissions
ISIMIP2b
Atmospheric CO2 concentration for 1661-2299. Values are constant for 1661-1860, following observations from 1861-2005, and correspond to rcp26 and rcp60 from 2006-2299.
Observed atmospheric climate
ISIMIP2b
The EWEMBI dataset was compiled to support the bias correction of climate input data for ISIMIP2b. For a full technical description, see the DOI link below.
Socio-economic
ISIMIP2a
Country-level population, urban population and age structure in 5-year time steps based on SSP2 from IIASA (population & age structure) and NCAR (urbanshare).
Socio-economic
ISIMIP2b
Annual global population data at 0.5° and 5' resolutions for the years 2006-2099 based on the national SSP2 population projections as described in Samir and Lutz, (2014).
Simulated atmospheric climate
Fast Track
Daily-resolution, bias-corrected climate data from the global climate models MIROC-ESM-CHEM, NorES1-M, IPSL-CM5A-LR, GFDL-ESM2M, HadGEM2-ES covering the period 1950-2099 (historical run up to 2004, then split into 4 RCPs), downscaled to a 0.5°x0.5° lat-lon grid.
Simulated atmospheric climate
ISIMIP2b
Pre-industrial (1661-1860), historical (1861-2010), future (RCP2.6 and RCP6.0) and extended-future (2100-2299) conditions provided based on CMIP5 output from GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5. Output from two GCMs (GFDL-ESM2M and IPSL-CM5A-LR) includes the physical and biogeochemical ocean data required by the marine ecosystem sector of ISIMIP.
Simulated ocean climate
ISIMIP2a
The ESM2M run is a fully coupled free running climate model forced by historical and future scenario GHGaerosol, solar boundary conditions without flux adjustment or other restoring to observations using TOPAZv2 as in Dunne et al 2013. DOI: 10.1175/JCLI-D-12-00150.1
Simulated ocean climate
ISIMIP2a
The COBALT run is as described in: http://www.sciencedirect.com/science/article/pii/S0079661113001079. It uses the same basic ocean-ice setup as Dunne et al., 2013 but is forced with reanalysis.
Other
ISIMIP2b
ISIMIP2a
Fast Track
The dam data is based on GRanDv1.1, but adjusted to match the river-routing in DDM30. Use of these data sets is recommended but, if unfeasible, groups may use their default dataset. For a comparison of the GranD/ISIMIP dataset with the default WaterGAP and LPJmL datasets, see https://www.arcgis.com/home/item.html?id=d966db9c7b2949ac8380458d7020adf9
Observed atmospheric climate
ISIMIP2a
Daily-resolution observed climate data on a global (land and ocean) 0.5°x0.5° lat-lon grid from the Global Soil Wetness Project Phase 3 (GSWP3), based on the reanalysis data set 20CR and using the bias targets GPCC, GPCP, CPC-Unified, CRU and SRB. The data set covers the period 1901‐2010.
Socio-economic
ISIMIP2b
Annual data on a 0.5° and 5' grid. Historical data based on the HYDE3.2 database (Klein Goldewijk et al., 2010; Klein Goldewijk, 2011) for the years 1861-2005.
Socio-economic
ISIMIP2b
Annual country-level GDP data.
Observed atmospheric climate
ISIMIP2a
Daily-resolution observed climate data on a global (land and ocean) 0.5°x0.5° lat-lon grid. PGMFD v.2 (Princeton) is from he Terrestrial Hydrology Group at Princeton University, based on the reanalysis data set NCEP/NCAR Reanalysis I and using the bias targets CRU, SRB, TRMM, GPCP & WMO and validated against GSWP2. The PGMFD v.2 data set covers the period 1901‐2012. WATCH (WFD) Derived from the WATCH Project, based on the reanalysis data set ERA-40 and using the bias target GPCC. The data set covers the period 1901‐2001. WATCH+WFDEI Based on the reanalysis data set ERA-Interim and using the bias target GPCC. The data set covers the period 1901‐2012, where the data for 1901-1978 are taken from WFD, and from 1979 onwards from WFDEI.GPCC
Land use
ISIMIP2b
Historical land-use (LU) changes from the HYDE3.2 data (Klein Goldewijk, 2016) (see Figure 3).
Simulated ocean climate
ISIMIP2a
Ocean data from the GCM IPSL-CM5A-LR.
Land use
ISIMIP2a
Fast Track
Agricultural land and irrigated area based on the MIRCA data set, covering irrigated and rainfed landuse.
Other human influences
ISIMIP2b
Annual crop-specific input per ha of crop land for C3 and C4 annual, C3 and C4 perennial and C3 Nitrogen fixing.
Other human influences
ISIMIP2b
Annual, 0.5° gridded data for 1850-2099 derived from the average of three atmospheric chemistry models (i.e., GISS-E2-R, CCSM-CAM3.5, and GFDL-AM3) in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) (0.5° x 0.5°).
Observed atmospheric climate
ISIMIP2a
Daily-resolution observed climate data on a global (land and ocean) 0.5°x0.5° lat-lon grid from the Terrestrial Hydrology Group at Princeton University, based on the reanalysis data set NCEP/NCAR Reanalysis I and using the bias targets CRU, SRB, TRMM, GPCP & WMO and validated against GSWP2. The data set covers the period 1901‐2012
Socio-economic
Fast Track
Historical (1950-2009) and future projections (2010-2100) of country-level and gridded population data based on the Shared Socio-economic Pathways (SSPs) for SSP1-SSP5.
Simulated atmospheric climate
ISIMIP2b
Unvorrect pressure and wind fields at 3-hrly resolution for the GCMs IPSL-CM5A-LR (1861-2299), MIROC5 (1861-2099) and GFDL-ESM2M (1861-2099).
Other
ISIMIP2b
ISIMIP2a
Fast Track
DDM30 River-routing network data.
Other
ISIMIP2b
Total climate-driven regional sea level projections on a global 0.5x0.5° grid. Projection is a combination of ocean dynamic sea level fields and steric global contribution from the ISIMIP GCMs, and the fingerprints from glaciers and the Greenland and Antarctic ice sheets. Tthe time-dependent fingerpints were generated by scaling a time-independent fingerprint (see Bamber and Riva 2010) with the respective global timeseries for each contribution. Uncertainty for fingerprints is only from the global timeseries.
Observed atmospheric climate
ISIMIP2a
Daily resolution climate data on a global 0.5°x0.5° lat-lon grid: Derived from the WATCH Project, based on the reanalysis data set ERA-40 and using the bias target GPCC. The data set covers the period 1901‐2001. Related website: http://www.waterandclimatechange.eu/about/watch-forcing-data-20th-century When referring to the WATCH data set, the following paper should be cited: Weedon, G.P., Gomes, S., Viterbo, P., Österle, H., Adam, J.C., Bellouin, N., Boucher, O., and Best, M., 2010. The WATCH Forcing Data 1958-2001: a meteorological forcing dataset for land surface- and hydrological models. WATCH Tech. Rep. 22, 41p (available at www.eu-watch.org/publications , PDF).
Observed atmospheric climate
ISIMIP2a
Daily-resolution observed climate data on a global (land only) 0.5°x0.5° lat-lon grid, based on the reanalysis data set ERA-Interim and using the bias target GPCC. The data set covers the period 1901‐2012, where the data for 1901-1978 are taken from WFD, and from 1979 onwards from WFDEI.GPCC

Changelog

Feb. 18, 2016

The Princeton data set provided to you for use in the ISI-MIP2.1a simulations for the period 1901-1947 has been superceded by a corrected version. The problem was a mistake in the data provider's processing scripts for temperature and humidity. A decision has not yet been reached as to whether simulations using these data should be re-run wit..

Jan. 14, 2015

As a follow-up to the Version 2 bug, the WFDEI period was processed with an improper land-sea mask leading to about 200 grid cells holding zero values for the WFDEI Period (1979-2012). Mainly smaller islands and some coast lines were affected (see red points below). The detrended data and data before 1979 were not affected and are the sames a..

Dec. 19, 2014

WATCH and WATCH+WFDEI data have now been fixed and are ready for download on the DKRZ server from the input data folders WATCH and WATCH+WFDEI.combined, respectively.

Dec. 4, 2014

A truncation error during processing of the WATCH data resulted in daily values of total precipitation and snowfall for the period 1958-2001 being decreased to integer mm/day values. As a result, accumulated monthly precipitation has been reduced by up to 10mm in some months and regions. The problems were with the WATCH data set only, but bec..


Contact

Here you will find contact addresses for the ISIMIP management group and the ISIMIP sector coordinators (listed below by sector).

If you want to receive news about ISIMIP, join our mailing list here.

Management Team
Management Team

ISIMIP

Katja Frieler (Project Leader)

Lila Warszawski (Project Manager)

Matthias Büchner (Data Manager)

Jan Volkholz

Cross-Sectoral Science Team
Cross-Sectoral Science Team

Jacob Schewe

Fang Zhao

Sebastian Ostberg

Stefan Lange

Franziska Piontek

Water (global)
Water (global)

Simon Gosling

Hannes Müller Schmied

Water (regional)
Water (regional)

Valentina Krysanova

Fred Hattermann


Marine Ecosystems & Fisheries
Marine Ecosystems & Fisheries

Derek Tittensor (regional & global)

Tyler Eddy (regional)

Eric Galbraith (global)

Energy Supply & Demand
Energy Supply & Demand

Ioanna Mouratiadou

Michelle van Vliet

Robert Vautard

Franziska Piontek

Regional Forests
Regional Forests

Christopher Reyer

Global Biomes
Global Biomes

Philippe Ciais


Agriculture Sector
Agriculture Sector

Joshua Elliott

Agro-economic Modelling
Agro-economic Modelling

Hermann Lotze-Campen

Biodiversity
Biodiversity

Thomas Hickler

Permafrost
Permafrost

Kirsten Thonicke

Eleanor Burke


Coastal Infrastructure
Coastal Infrastructure

Jochen Hinkel

Health
Health

Kristie Ebi

Veronika Huber


Sector-specific information


Newsletter

Feb. 9, 2017

We’d like to follow up on progress in the ISIMIP2b simulations. It is great to see that simulation data from three models have already been uploaded, and to have heard from many of you that you are actively working on the simulations. To keep it short, here are the (revised) upcoming dates and stat..

Jan. 9, 2017

We hope you have started the year refreshed and well. This email contains information about: Paper ideas for ISIMIP2b data;Folder structure for your ISIMIP2b uploads; Published papers using ISIMIP input or output data (Fast Track or ISIMIP2a). Paper ideas for ISIMIP2b data Amongst the cross-sectoral science te..

Dec. 22, 2016

As the year comes to a close, we’d like to thank you for your invaluable contributions to ISIMIP in 2016. Whether conducting model runs, contributing to the development of the protocol and input data sets, participating in the workshop, analysing ISIMIP simulations, or supporting the organisation of ISIMIP,..