ISIMIP3 simulation protocol

Group III

Update: ISIMIP3b Group III (simulations accounting for future changes in the direct human forcing) input data are now available and simulations can be started for a set of sectors (indicated by III in the menu). For other sectors, some of the data are not available yet (indicated by III), but models not needing those data may already start. For a third group of sectors (indicated by III) Group III experiments have been defined but are not ready to begin because most of the data are still under construction.

With Group III we introduce new experiments (Table 2.1), new direct human forcing specifiers (Table 2.3), a new table of priorities (Table 2.5), a new table of requirements (Table 2.6), and the new input data are added to Tables 3.1 and 3.4.

Table of Contents

The simulation protocol describes the experiments, input data sets and output variables necessary to participate in the ISIMIP3 simulation round.

Please select the simulation round (ISIMIP3a, ISIMIP3b) and the sectors you are interested in from the menu on the right. The page will then adjust to your selection. The parts of the protocol, which are specific to a simulation round or sector are marked accordingly.

Last updated: 17 June 2025

Commit hash: 6d0e50ab86472d92ed4e259de9822fe326ebcb0f

Direct link for this selection:

1. Introduction

1.1 General concept

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a consistent set of climate impact data across sectors and scales. It also provides a unique opportunity for considering interactions between climate change impacts across sectors through consistent scenarios.

ISIMIP is intended to be structured in successive rounds connected to the different phases of the climate model intercomparison CMIP (ISIMIP Mission & Implementation document).

The main components of the ISIMIP framework are:

1.2 Simulation round

ISIMIP3a is dedicated to model evaluation or impact attribution. To this end simulations are forced by observed climate and direct human forcing. In addition, a de-trended version of the observed climate allows for the generation of a no climate change baseline (counterfactual, if available).

To ensure consistency between ISIMIP3a and ISIMIP3b as well as the different experiments within a simulation round, we require that modelling groups use the same version of an impact model for the experiments in ISIMIP3a and ISIMIP3b.

ISIMIP3b is dedicated to a quantification of climate-related risks at different levels of climate change and direct human forcing. The Group I simulations refer to the pre-industrial and historical period of the CMIP6-based climate simulations. Group II covers all future projections assuming fixed 2015 levels of direct human forcing and different future projections of climate (SSP1-2.6, SSP3-7.0 and SSP5-8.5). Group III simulations account for future changes in the direct human forcing and are intended to be started once the corresponding direct human forcing input data are available.

To ensure consistency between ISIMIP3a and ISIMIP3b as well as the different experiments within a simulation round, we require that modelling groups use the same version of an impact model for the experiments in ISIMIP3a and ISIMIP3b.

1.3 About this protocol

In this protocol we describe the experiments, the different input datasets, the output variables, and how to report model results.

Throughout the protocol we use specifiers that denote a particular experiment, variable or other parameter. We use these specifiers in the tables below, in the filenames of the input data sets, and ask you to use the same specifiers in your output files. More on reporting data can be found at the end of this document.

2. Experiments

2.1 Experiments

In Table 2.1, we describe the different experiments for ISIMIP3. Each default experiment is defined by its climate related forcing (CRF) and the assumptions regarding direct human forcing (DHF). The associated specifications all have a label such as obsclim or histsoc that are provided in Table 2.1 and further specified in Tables 2.2 and 2.3. These specifiers are used in the file names of the corresponding input files and should also be used for the names of the output files (see report model results report model results). Sensitivity experiments are described as deviation from a default experiment and represented by labels that are used as a third specifier of the experiments. Their specific meanings are defined in Table 2.4.

Please note that the experiments are different for ISIMIP3a and ISIMIP3b and some are sector specific. You can use the menu on the top-right of the page to select the simulation round and sectors you are interested in.

Note regarding models requiring spin-up

For models requiring spin-up, we provide 100 years of spinclim data which is identical with the first 100 years of the counterclim data. The files are located under ISIMIP3a/InputData/climate/atmosphere/spinclim at DKRZ and in the ISIMIP Repository. If more than 100 years of spin-up are needed, these data can be repeated as often as needed.

For historical runs, use the transclim climate time series, historical CO₂ concentration and varying DHF, for the transition period from spin-up to the start of the experiment (1850-1900). When using a longer spin-up period that (nominally) extends back further than 1850, please keep CO₂ concentration and DHF constant at 1850 level until reaching the year corresponding to 1850.

For experiments with fixed direct human influences (1901soc, 2015soc), the spin-up should be based on the 1901 DHF or 2015 DHF, respectively.

For sector-specific experiments without direct human influence (nat), the spin-up should not use any DHF. Likewise, the nofire experiment should include a spin-up without fire.

The model evaluation experiment starts in 1961. To capture historical fishing effort prior to 1961, we also provide input for a nominal spin-up (1841-1860, fishing held constant at 1861 levels) and pre-industrial transition period (1861-1960, reconstructed fishing effort).

To set-up climate-forcing variables for the entire 1841-1960 period, we ask modellers to use the "control run" (ctrlclim) monthly output for the years 1961-1980 (inclusive) on repeat for six cycles. These years have been selected because they correspond with an entire ENSO cycle and because no climate trend is detectable prior to 1980 from the GFDL model.

For models that require longer spin-up prior to 1841, please keep 1841 levels of fishing effort constant and, if needed, repeat the ENSO cycle (e.g. monthly values for 1961- 1980 inclusive from ctrlclim) for as many times necessary. For the ‘no fishing’ runs (nat), the spin-up and pre-industrial transition should not use any fishing effort.

We ask modellers to include all outputs from 1841 onwards for use in our analyses.

For models requiring spin-up, please use the pre-industrial control data and CO₂ concentration and DHF fixed at 1850 levels for the spin up as long as needed.

Please note that the "pre-industrial control run" from 1601-1849 is part of the regular experiments that should be reported and hence the spin-up has to be finished before that.

For experiments with fixed year-2015 direct human influences (2015soc), spin-up should be based on the 2015 DHF.

For sector-specific experiments without direct human influence (nat), the spin-up should not use any DHF.

Please note that there is no "pre-industrial control run" from 1601-1849 for these experiments (2015soc, nat) and hence the spin-up links directly to the historical period.

The simulations with nitrogen cycling turned off should also be spun up with nitrogen cycling turned off.

2.2 Experiment specifiers

Tables 2.2-2.4 describe the different specifiers for the different experiments as described in Table 2.1. They are used in the file names of the corresponding input files and should also be used for the names of the output files (see report model results).

General note regarding sensitivity experiments

The sensitivity experiments are meant to be deviations from the default settings. So for example if your model does not at all account for changes in CO₂ concentrations (no option to switch it on or off) the run should be labeled as “default” in the sensitivity specifier of the file name even if the run would be identical to the 1901co2 sensitivity setting.

The particular sensitivity specifier for an experiment is given in the experiments table above. For most experiments no sensitivity specifier is given, so the default label applies.

General note regarding sensitivity experiments

The sensitivity experiments are meant to be deviations from the default settings. So for example if your model does not at all account for changes in CO₂ concentrations (no option to switch it on or off) the run should be labeled as default in the sensitivity specifier of the file name even if the run would be comparable to the 2015co2 sensitivity setting.

The particular sensitivity specifier for an experiment is given in the experiments table above. For most experiments no sensitivity specifier is given, so the default label applies.

2.3 Group III experiment priorities

Table 2.5 lists the priorities for the different group III experiments in ISIMIP3b. We kindly ask you to run the experiments marked as Tier 1: Core set in any case and the other experiments with the priority given.

2.4 Group III requirements

Table 2.6 lists the direct human forcings (DHF) that are relevant for the different sectors for group III simulations in ISIMIP3b. Required means that the forcing has to be accounted for in the simulations in the given sectors to count as a group III simulation. In addition a forcing can be harmonized by e.g. prescribing the application of a specific forcing data set from Table 2.7, or the specific implementation of the forcing can be left to the individual modellers. The harmonization setting is closely connected to the mandatory / optional setting in Table 3.1 (mandatory means that all modelling teams must use the same forcings dataset and not an alternative one).

Note regarding Group III simulations for the Energy (demand) sector

In the no-adaptation runs (no-adapt), changes in the output variables such as the residential air conditioning penetration rate are driven by socioeconomic development only, whereas in the adaptation runs (adapt), these changes are additionally driven by climate change.

3. Input data

3.1 Forcing data

Table 3.1 describes the climate-related, direct human, static geographic, and biophysical forcing data provided for the different experiments. The datasets are grouped according to the main experiment specifiers described in 2.2 - 2.4. The different datasets and the variables they contain are described in more detail in Tables 3.3 - 3.6.

For each dataset, we provide the path where modellers can obtain the data at DKRZ. The base directory for this is:

levante:/work/bb0820/ISIMIP/

The data are also available at the ISIMIP Repository without login, or will be made available there in the future. Further information on accessing ISIMIP data can be found at ISIMIP - getting started.

Some of the datasets are tagged as mandatory. This does not mean that the data must be used in all cases, but if your models uses input data of this kind, we require to use the specified dataset. If an alternative data set is used instead, we cannot consider it an ISIMIP simulation. If the mandatory label is not given, you may use alternative data (please document this clearly).

The climate forcing input files can be found on DKRZ using the following pattern:

ISIMIP3a/InputData/climate/atmosphere/<climate-scenario>/global/daily/historical/<climate-forcing>/<climate-forcing>_<climate-scenario>_<climate-variable>_global_daily_<start-year>_<end-year>.nc

# ocean data for marine-fishery
ISIMIP3a/InputData/climate/ocean/<climate-scenario>/global/monthly/historical/<climate-forcing>/<climate-forcing>_<climate-scenario>_<climate-variable>_global_monthly_<start-year>_<end-year>.nc

The climate forcing input files can be found on DKRZ using the following pattern:

ISIMIP3b/InputData/climate/atmosphere/bias-adjusted/global/daily/<climate-scenario>/<climate-forcing>/<climate-forcing>_<ensemble-member>_<bias-adjustment>_<climate-scenario>_<climate-variable>_global_daily_<start-year>_<end-year>.nc

# ocean data for marine-fishery
ISIMIP3b/InputData/climate/ocean/uncorrected/global/monthly/<climate-scenario>/<climate-forcing>/<climate-forcing>_<ensemble-member>_<climate-scenario>_<climate-variable>_onedeg_global_monthly_<start-year>_<end-year>.nc  # 1° grid
ISIMIP3b/InputData/climate/ocean/uncorrected/global/monthly/<climate-scenario>/<climate-forcing>/<climate-forcing>_<ensemble-member>_<climate-scenario>_<climate-variable>_halfdeg_global_monthly_<start-year>_<end-year>.nc  # 0.5° grid

Note on ocean data availability

Variable availability is mainly based on the data published in ESGF and may vary between the CMIP experiments.

Some variables are available as extracted versions from vertically resolved data. Their variable names have been suffixed with -bot (ocean bottom), -surf (surface values) or -vint (vertically integrated), respectively.

Note on ocean data availability

Some variables are available as extracted versions from vertically resolved data. Their variable names have been suffixed with -bot (ocean bottom), -surf (surface values) or -vint (vertically integrated), respectively.

Climate forcing

Note on climate forcing priority

The priority for the different climate forcing datasets is given in the last column of Table 3.1. If you cannot use all climate forcing datasets, please concentrate on those with a higher priority. Please note, that for ISIMIP3b group III simulations we provide the priorities of the different experiments in Table 2.5.

3.2 Direct human forcing

3.3 Static geographic information

3.4 Biophysical forcing

No input data from other ISIMIP impact models are available for this selection of simulation round and sectors.

4. Output data

4.1 Output dimensions

ISIMIP output variables are usually reported with the dimensions (time,lat,lon). For variables with a number of levels (e.g. layers or depth), an alternative set of dimensions is given in the comment column in the table below. More information about level dimensions can be found here and here on the ISIMIP webpage.

Note on agriculture output

For agricultural output, variables are to be reported with the dimensions (time,lat,lon) where the time axis' unit is growing seasons since 1901-01-01 00:00:00 resp. growing seasons since 1601-01-01 00:00:00 for all variables unless these are reported on a monthly time axis, e.g. soilmoist. In many cases growing seasons are equivalent to years, as there is always only one planting event per year. However, due to temperature-sensitive growing season lengths, the growing seasons are not fully equivalent to years and users should note the difference. Reported variables on start and end of the growing season are supplied to allow allocating events to transient time axes if desired.

Many variables are defined per area (unit m-2). Typically, and unless otherwise defined, the corresponding reference area is the land area of the grid cell, excluding any water bodies. However, in some cases, it may be necessary or meaningful to report a variable relative to the continental area (including inland water bodies, lakes etc...). For example, evaporation could relate to the land area (excluding water bodies etc.), or to the continental area if the model evaporation occurs over both over land and over water. Also, for some variables, the "per PFT" reporting allows modellers to indicate whether inland water bodies are included in the model or not, and hence, what reference area the variable refers to. In such cases, please specify the reference area in a NetCDF global attribute (e.g. :reference_area = "continental area (including inland water bodies)").

4.2 Output variables

4.3 Sector specific identifiers

Crop priority and naming

Irrigation

Harmonization

Species

Forest stands

Lake sites

A document with additional information is maintained by the sector coordinators and provided at https://docs.google.com/spreadsheets/d/1UY_KSR02o7LtmNoOs6jOgOxdcFEKrf7MmhR2BYDlm-Q/edit#gid=555498854.

Catchment gauging stations

No sector specific identifiers are available for this selection of simulation round and sectors.

4.4 Sector specific notes

Reporting per growing seasons

To resolve potential double harvests within one year, crop yields should be reported per growing season and not per calendar year. Thus, in the NetCDF output files, do not use a time dimension but instead a unitless coordinate variable with integer values; more information on how to construct these files is given below and on the ISIMIP website (https://www.isimip.org/protocol/preparing-simulation-files/).

Cumulative growing season variables such as, e.g., actual evapotranspiration or precipitation are to be accumulated over the growing season. The first season in the file (level=0) is then the first complete growing season of the time period provided by the input data without any assumed spin-up data, which equates to the growing season with the first planting after this date. To ensure that data can be matched to individual years in post-processing, it is essential to also provide the actual planting dates (as day of the year), actual planting years (year), anthesis dates (as day of the year), year of anthesis (year), maturity dates (day of the year), and year of maturity (year). This procedure is identical to the GGCMI convention (Elliott et al., 2015, https://doi.org/10.5194/gmd-8-261-2015).

Information about PFT-specific outputs

  • Unless otherwise defined, variables in ISIMIP should be reported relative to the grid cell land area.
  • The output provided per Plant Functional Type (PFT) should be expressed relative to the respective PFT area so that e.g. sum(gpp-pft*pft-pft)=gpp-total.
  • When your model allows several PFTs to grow on the same area and hence the total cover fraction can be more than one, please scale the PFT area to one and report this step in the model documentation on the ISIMIP homepage.
  • When your model grows the same PFT on different land-use classes, e.g. the same c3-grass represents grasses growing on natural grasslands, pasture and possible even as crop, please differentiate this in your output by defining land-use specific PFT such as c3-grass-pasture, c3-grass-natural, c3-grass-crop and report this in model documentation on the ISIMIP homepage.
  • For better understanding the abbreviations in the filename please provide the full PFT name in a pft variable attribute.

Information about soil organic carbon pools of different turnover times

Some variables can be provided separately by soil organic carbon pools of different turnover times, if your model simulates those. This is done using the -<pool> extension. Please indicate them as -fast, -slow, and -passive and describe your definition of the turnover times in your model description. The extension is used in addition to the extension expressing the Plant Functional Type (PFT) and needs to put before it.

Information about peat outputs

All variables should be reported separately for the peat fraction of the grid cell if they are calculated separately for peat and non-peat grid-cell fractions, with a peattype (<pt>) extension to the variable name. This extension can be -naturalpeat, -drainpeat, -restorepeat, or -minl for the non-peat (mineral) gridcell fraction. It is used in addition to the extension expressing the Plant Functional Type (PFT) and needs to put before it.

Additional instructions for the health sector

  • If different realizations of the model are applied, then these should be indicated by the specifier <r>. E.g. to reflect a central, upper, and lower estimate of the ERF: <r> = lower, central, upper. Please explain the meaning of these realizations in the online model documentation; contact the ISIMIP coordination team in case of questions.
  • If data are disaggregated e.g. by age group, gender, etc., they should be reported along an additional dimension, described by an auxiliary coordinate variable, in the NetCDF files. See the example provided at https://www.isimip.org/protocol/preparing-simulation-files/.
  • For local (non-gridded) data, locations (cities/regions/countries) should be reported along an additional dimension called location, with the location name given as string in an auxiliary coordinate variable called location_name, in the NetCDF files. In addition, coordinates of the location should be reported in auxiliary variables called location_lat and location_lon. See the example provided at https://www.isimip.org/protocol/preparing-simulation-files/. The <region> specifier in the file name should be set to local. For gridded data, the <region> specifier in the file name should be global or indicate a region or country.

Additional instructions for the labour sector

  • The analysis uses a large collection of micro-survey data to estimate new, and robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply at both individual and sub-national regions across the world. The specifications control for income and both location (sub-national region/country) and temporal (week/month/year) fixed-effects along with extreme events such as droughts. In the case of country-specific studies using micro-surveys (Antonelli et al. 2020; Shahegh et al. 2020; Shahegh and Dasgupta 2022), specifications also include socioeconomic and demographic drivers such as gender, age, education, and total income. The response-functions are estimated separately for working conditions; high-exposure/outdoor in the sun (e.g. agricultural, hunting, forestry and fishing; mining and quarrying; and construction) and low-exposure/outdoor in the shade or indoor (e.g. manufacturing and utilities).
  • This sector uses an augmented mean function, created from an ensemble of five labour productivity response-functions reported in Dasgupta et al. 2021. M1) Pilcher et al., 2002: Psychological performance, e.g. reaction time, tracking or memory task, at global scale. M2) Dunne et al., 2013: Individual capacity to safely perform heavy labour under heat stress at global scale. M3) Kjellstrom et al., 2014: Reduction of hourly work capacity for heavy work following the ISO standard at global scale. M4) Sahu et al., 2013: Work output per hour of rice farmers calculated by number of rice bundles laid down, at country-level for India. M5) Li et al., 2016: Time efficiency measures; direct, indirect, and idle time of rebar construction workers, at country-level for China. Work is underway to estimate labour productivity response-functions using empirical analysis.

Additional instructions for the food-security and nutrition (FS-N) sector

  • This sector will use additional data: cereal import dependency from FAOSTAT (to prescribe dependence on trade or subsistence farming), age distribution and income level data. Econometric specifications will control for income and inequality (HDI). Data on trade dependency, subsistence farming, and age distribution will allow segregated projections considering vulnerability in terms of population dependency ratio and import dependency.
  • Please consider that for simulations based on empirical models, not all the socioeconomic variables are used for projections. This is standard practice to isolate the climate signal. In these cases, variables used should be specified in the model output documentation.

Note regarding additional forcings for the Water quality sector

Additional agricultural-related model inputs such as N biological fixation, crop uptake, grassland uptake, animal manure use in cropland and on grassland and livestock numbers are not available for ISIMIP3b Groups I+II. These additional forcings will be available to simulate ISIMIP3b (Group III). The same holds for additional human-related model inputs for point sources such as sewage connections of urban/rural population, treatment removal fractions, anthropogenic point source inputs to surface waters (total effluents), wastewater production, collection, treatment and reuse.

No sector specific notes are available for this selection of simulation round and sectors.

4.5 Bias adjustment

Depending on the used climate input data, the corresponding bias adjustment needs to be part of the output filename.

5. Reporting model results

The specification on how to submit the data, as well as further information and instructions are given on the ISIMIP website at:

https://www.isimip.org/protocol/preparing-simulation-files

It is important that you comply precisely with the formatting specified there, in order to facilitate the analysis of your simulation results in the ISIMIP framework. Incorrect formatting can seriously delay the analysis. The ISIMIP Team will be glad to assist with the preparation of these files if necessary.

To ensure consistency between ISIMIP3a and ISIMIP3b as well as the different experiments within a simulation round, we require that modelling groups use the same version of an impact model for the experiments in ISIMIP3a and ISIMIP3b. If you cannot fulfill this, please indicate that by using a suffix for your model name (e.g. simple version numbering: MODEL-v1, MODEL-v2 or following semantic versioning: MODEL-2.0.0).

This versioning does not only apply to changes in the computational logic of the model, but also to input parameters, calibration or setup. If model versions are not reported, we will name them according to the simulation round (e.g. MODEL-isimip3a). We require the strict versioning to ensure that differences between model results are fully attributable to the changes in model forcings.

File names consist of a series of identifier, separated by underscores. Things to note:

Please name the files according to a sector specific pattern:

and replace the identifiers with the specifiers given in the different tables of this document:

For questions or clarifications, please contact info@isimip.org or the data managers directly (isimip-data@pik‐potsdam.de) before submitting files.