ISIMIP3a simulation round simulation protocol - all sectors combined

Introduction

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:

ISIMIP3a

Historical model evaluation and attribution runs

The ISIMIP3a part of the third round framework is dedicated to i) impact model evaluation and improvement and ii) detection and attribution of observed impacts according to the framework of IPCC AR5 Working Group II Chapter 18. To this end all simulations are forced by observed climate and socio-economic information and a de-trended version of the observed climate allowing for the generation of a “no climate change” baseline (counterfactual).

You can find the ISIMIP3b protocol, which is dedicated to a quantification of climate-related risks at different levels of climate change and socio-economic conditions, here.

Simulation protocol

In this protocol we describe the scenarios & experiments in ISIMIP3a simulation round, the different input datasets, the output variables, and how to report model results specifically for all sectors combined. An overview of all sectors can be found at protocol.isimip.org.

Throughout the protocol we use specifiers that denote a particular scenario, 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.

Model versioning

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, see also reporting model results).

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.

Scenarios & Experiments

Scenario definitions

Table 1: Climate scenario specifiers (climate-scenario).
Scenario specifier Description
obsclim Observed climate and CO₂ forcing used for model evaluation and the detection and attribution task.
spinclim Detrended version of the observed climate forcing used to spin-up the simulations based on a stable 1900 climate (see explanation below for details regarding the design of the spin-up)
counterclim Detrended version of the observed climate forcing used for the "no climate change" baseline simulations in the context of the detection and attributions task.
Table 2: Socio-economic scenario specifiers (soc-scenario).
Scenario specifier Description
histsoc

Varying direct human influences in the historical period (1850-2014) (e.g. observed changes in historical land use, nitrogen deposition and fertilizer input, fishing effort).

Please label your model run histsoc even if it only partly accounts for varying direct human forcings while another part of the the direct human forcing is considered constant or is ignored.

2015soc

Fixed year-2015 direct human influences (e.g. land use, nitrogen deposition and fertilizer input, fishing effort).

Please label your simulations 2015soc if they do not at all account for historical changes in direct human forcing, but they do represent constant year-2015 levels of direct human forcing for at least some direct human forcings.

nat

No direct human influences (naturalized run).

Please only label your model run nat if it does not at all account for any direct human forcings, including e.g. human land use.

Table 3: Sensitivity scenario specifiers (sens-scenario).
Scenario specifier Description
default For all experiments other than the sensitivity experiments.
1901co2 CO₂ concentration fixed at 1901 levels as a deviation from the “obsclim” climate + CO₂ forcing.
nowatermgt No water management (e.g. no human water abstraction) while other direct human forcings such as land use changes are considered according to histsoc or 2015soc.

General note regarding sensitivity experiments

The sensitivity experiments are meant to be "artificial" 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 scenario for an experiment is given in the experiments table below. For most experiments no sensitivity scenario is given, so the default label applies.

Experiments

Table 4: Experiment set-up: Each experiment is specified by the climate forcing (CF) and the Direct Human Forcing (DHF).
Experiment Short description

Transition from Spin-up to experiment

1850-1900, only if spin-up is needed

Historical

1901-2018

model evaluation

histsoc

1st priority

CF: No climate change before 1901, observed forcing afterwards; constant 1850 levels of CO₂ before 1850 and based on observations afterwards

spinclim

obsclim

DHF: Fixed 1850 levels of direct human forcing before 1850, varying direct human influences according to observations afterwards

histsoc

histsoc

model evaluation

2015soc

1st priority

CF: No climate change before 1901, observed forcing afterwards; constant 1850 levels of CO₂ before 1850 and based on observations afterwards

spinclim

obsclim

DHF: Fixed 2015 levels of direct human forcing for the entire time period

2015soc

2015soc

model evaluation

nat

2nd priority

CF: No climate change before 1901, observed forcing afterwards; 1850 levels of CO₂ before 1850 and based on observations afterwards

spinclim

obsclim

DHF: No direct human influences

nat

nat

counterfactual climate

histsoc

1st priority

CF: de-trended observational climate forcing (counterfactual "no climate change" situation) + fixed CO₂ concentration at 1901 level "histsoc" version of the transition period of the model evaluation run

counterclim

DHF: 1850 levels of direct human forcing before 1850, varying direct human influences according to observations afterwards

histsoc

counterfactual climate

2015soc

1st priority

CF: de-trended observational climate forcing (counterfactual "no climate change" situation) "2015soc" version of the transition period of the model evaluation run

counterclim

DHF: fixed 2015 levels of direct human influences for the entire time period

2015soc

counterfactual climate

nat

2nd priority

CF: de-trended observational climate forcing (counterfactual "no climate change" situation) + fixed CO₂ concentration at 1901 level "nat" version of the transition period of the model evaluation run

counterclim

DHF: No direct human influences

nat

CO₂ sensitivity

histsoc

2nd priority

CF: no climate change before 1901, observed forcing afterwards + fixed CO₂ concentration at 1901 level "histsoc" version of the transition period of the model evaluation run

obsclim

Sensitivity scenario: 1901co2

DHF: 1850 levels of direct human forcing before 1850, varying direct human influences according to observations afterwards

histsoc

CO₂ sensitivity

2015soc

2nd priority

CF: no climate change before 1901, observed forcing afterwards + fixed CO₂ concentration at 1901 level "2015soc" version of the transition period of the model evaluation run

obsclim

Sensitivity scenario: 1901co2

DHF: fixed 2015 levels of direct human influences for the entire time period

2015soc

Water management sensitivity

histsoc

2nd priority

CF: no climate change before 1901, observed forcing afterwards + fixed CO₂ concentration at 1901 level "histsoc" version of the transition period of the model evaluation run

obsclim

DHF: no accounting for water management but representation of other direct human influences such as land use changes according to "histsoc"

histsoc

Sensitivity scenario: nowatermgt

Water management sensitivity

2015soc

2nd priority

CF: no climate change before 1901, observed forcing afterwards + fixed CO₂ concentration at 1901 level "2015soc" version of the transition period of the model evaluation run

obsclim

DHF: no accounting for water management but representation of other direct human influences such as land use patterns according to "2015soc"

2015soc

Sensitivity scenario: nowatermgt

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 (files climate/atmosphere/spinclim/<dataset>/<dataset>_spinclim_<variable>_global_daily_<start-year>_<start-year>.nc). If more than 100 years of spin-up are needed, these data can be repeated as often as needed. Use 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.

Input data

The base directory for input data at DKRZ is:

/work/bb0820/ISIMIP/ISIMIP3a/InputData/

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 alterntive 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).

Climate forcing

Table 5: Climate and climate-related forcing data (climate-forcing).
Title Specifier Time period Reanalysis Bias adjustment target Comments
GSWP3-W5E5 gswp3-w5e5 1901-2016 ERA5 GPCC, CRU Combination of W5E5 for 1979-2016 with GSWP3 homogenized to W5E5 for 1901-1978. The homogenization reduces discontinuities at the 1978/1979 transition and was done using the ISIMIP3BASD v2.3 bias adjustment method.
GSWP3 gswp3 1901-2010 20CR GPCC, GPCP, CPC-Unified, CRU, SRB Dynamically downscaled and bias-adjusted 20th Century Reanalysis (20CR) from the Global Soil Wetness Project Phase 3 (GSWP3).
Table 6: Climate forcing variables for ISIMIP3a simulations (climate-variable).
Variable Variable specifier Unit Resolution Datasets
Atmospheric variables mandatory
Near-Surface Relative Humidity hurs %
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Near-Surface Specific Humidity huss kg kg-1
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Precipitation pr kg m-2 s-1
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Surface Air Pressure ps Pa
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Surface Downwelling Longwave Radiation rlds W m-2
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Surface Downwelling Shortwave Radiation rsds W m-2
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Near-Surface Wind Speed sfcwind m s-1
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Near-Surface Air Temperature tas K
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Daily Maximum Near-Surface Air Temperature tasmax K
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)
Daily Minimum Near-Surface Air Temperature tasmin K
  • 0.5° grid
  • daily
  • GSWP3 (obsclim and counterclim, 1901-2010)
  • GSWP3-W5E5 (obsclim and counterclim, 1901-2016)

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

climate/atmosphere/<climate-scenario>/<climate-forcing>/<climate-forcing>_<climate-scenario>_<climate-variable>_global_daily_<start-year>_<end-year>.nc

Greenhouse gas forcing

Table 7: Greenhouse gas forcing for ISIMIP3a simulation round.
Variable Variable specifier Unit Resolution Datasets
Atmospheric composition mandatory

Atmospheric CO2 concentration

composition_atmosphere/co2/co2_historical_annual_1850_2018.txt
co2 ppm
  • global
  • annual

Meinshausen et al. (2011) for 1765-2005 and Dlugokencky & Tans (2019) from 2006-2018

Socioeconomic forcing

Table 8: Socioeconomic datasets for ISIMIP3a simulation round.
Dataset Included variables (specifier) Covered time period Resolution Reference/Source and Comments
Land use mandatory

Landuse totals

socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-totals_annual_<start_year>_<end_year>.nc
  • share of the total cropland (cropland_total)
  • all of the rainfed cropland (cropland_rainfed)
  • all of the irrigated cropland (cropland_irrigated)
  • share of managed pastures or rangeland (pastures)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual

Based on the HYDE 3.2 data set (Klein Goldewijk, 2016), but harmonized by Hurtt et al. (LUH2 v2h data set, see Hurtt, Chini, Sahajpal, Frolking, & et al, in review, see also https://luh.umd.edu).

Downscaling to 5 crops

socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-5crops_annual_<start_year>_<end_year>.nc
  • share of rainfed/irrigated C4 annual crops (c4ann_rainfed, c4ann_irrigated)
  • share of rainfed/irrigated C3 perennial crops (c3per_rainfed, c3per_irrigated)
  • share of rainfed/irrigated C3 N-fixing crops (c3nfx_rainfed, c3nfx_irrigated)
  • share of rainfed/irrigated C4 annual crops (c4ann_rainfed, c4ann_irrigated)
  • share of rainfed/irrigated C4 perennial crops (c4per_rainfed, c4per_irrigated)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual

Based on the HYDE 3.2 data set (Klein Goldewijk, 2016), but harmonized by Hurtt et al. (LUH2 v2h data set, see Hurtt, Chini, Sahajpal, Frolking, & et al., in review, see also https://luh.umd.edu).

Downscaling to 15 crops

socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-15crops_annual_<start_year>_<end_year>.nc
  • share of rainfed/irrigated maize (maize_rainfed, maize_irrigated)
  • share of rainfed/irrigated rice (rice_rainfed, rice_irrigated)
  • share of rainfed/irrigated oil crops (groundnut) (oil_crops_groundnut_rainfed, oil_crops_groundnut_irrigated)
  • share of rainfed/irrigated oil crops (rapeseed) (oil_crops_rapeseed_rainfed, oil_crops_rapeseed_irrigated)
  • share of rainfed/irrigated oil crops (soybean) (oil_crops_soybean_rainfed, oil_crops_soybean_irrigated)
  • share of rainfed/irrigated oil crops (sunflower) (oil_crops_sunflower_rainfed, oil_crops_sunflower_irrigated)
  • share of rainfed/irrigated pulses (pulses_rainfed, pulses_irrigated)
  • share of rainfed/irrigated temperate cereals (temperate_cereals_rainfed, temperate_cereals_irrigated)
  • share of rainfed/irrigated temperate roots (temperate_roots_rainfed, temperate_roots_irrigated)
  • share of rainfed/irrigated tropical cereals (tropical_cereals_rainfed, tropical_cereals_irrigated)
  • share of rainfed/irrigated tropical roots (tropical_roots_rainfed, tropical_roots_irrigated)
  • share of rainfed/irrigated C3 annual crops not covered by the above (others_c3ann_rainfed, others_c3ann_irrigated)
  • share of rainfed/irrigated C3 N-fixing crops not covered by the above (others_c3nfx_rainfed, others_c3nfx_irrigated)
  • share of rainfed/irrigated C3 perennial crops (c3per_rainfed, c3per_irrigated)
  • share of rainfed/irrigated C4 perennial crops (c4per_rainfed, c4per_irrigated)
  • share of pastures, both managed and rangeland (pastures)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual

The C4 perennial crops are not further downscaled from the "5 crops" data set and currently only include sugarcane. Similarly, the C3 perennial crops are not downscaled either. The data is derived from the "5 crops" LUH2 data, and the crops have been downscaled to 15 crops according to the ratios given by the Monfreda data set (Monfreda, Ramankutty, & Foley, 2008).

Managed pastures and rangeland

socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-pastures_annual_<start_year>_<end_year>.nc
  • share of managed pastures (managed_pastures)
  • share of rangeland (rangeland)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual

Based on the HYDE 3.2 data set (Klein Goldewijk, 2016), but harmonized by Hurtt et al. (LUH2 v2h data set, see Hurtt, Chini, Sahajpal, Frolking, & et al, in review., see also https://luh.umd.edu).

Urban areas

socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-urbanareas_annual_<start_year>_<end_year>.nc
  • share of urban areas (urbanareas)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual

Based on the HYDE 3.2 data set (Klein Goldewijk, 2016), but harmonized by Hurtt et al. (LUH2 v2h data set, see Hurtt, Chini, Sahajpal, Frolking, & et al., in review, see also https://luh.umd.edu).

N-fertilizer mandatory

Nitrogen deposited by fertilizers on croplands

socioeconomic/n-fertilizer/<soc_scenario>/<soc_scenario>_n-fertilizer-5crops_annual_<start_year>_<end_year>.nc
  • deposition of N through fertilizer on cropland with C3 annual crops (fertl_c3ann)
  • C3 perennial crops (fertl_c3per)
  • C3 N-fixing crops (fertl_c3nfx)
  • C4 annual crops (fertl_c4ann)
  • C4 perennial crops (fertl_c4per)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual (growing season)

Based on the LUH2 v2h data set (see Hurtt, Chini, Sahajpal, Frolking, & et al., in in review, see also https://luh.umd.edu).

N-deposition

Reduced nitrogen deposition

socioeconomic/n-deposition/<soc_scenario>/ndep-nhx_<soc_scenario>_monthly_<start_year>_<end_year>.nc
  • NHx deposition
  • 1850-1900
  • 1901-2016
  • 0.5° grid
  • monthly

Simulated by NCAR Chemistry-Climate Model Initiative (CCMI) during 1850-2014. Nitrogen deposition data was interpolated to 0.5° by 0.5° by the nearest grid. Data in 2015 and 2016 is assumed to be same as that in 2014 (Tian et al. 2018)

Oxidized nitrogen deposition

socioeconomic/n-deposition/<soc_scenario>/ndep-noy_<soc_scenario>_monthly_<start_year>_<end_year>.nc
  • NOy deposition
  • 1850-1900
  • 1901-2016
  • 0.5° grid
  • annual

Simulated by NCAR Chemistry-Climate Model Initiative (CCMI) during 1850-2014. Nitrogen deposition data was interpolated to 0.5° by 0.5° by the nearest grid. Data in 2015 and 2016 is assumed to be same as that in 2014 (Tian et al. 2018)

Reservoirs & dams

Reservoirs & dams

socioeconomic/reservoir_dams/reservoirs-dams_1850_2025.xls
  • Unique ID representing a dam and its associated reservoir corresponding to GRanD/KSU IDs (ID)
  • name (DAM_NAME)
  • original location (LON_ORIG, LAT_ORIG)
  • location adjusted to the DDM30 routing network (LON_DDM30, LAT_DDM30)
  • upstream area in DDM30 (CATCH_SKM_DDM30)
  • upstream area in GRanD (CATCH_SKM_GRanD)
  • maximum storage capacity of reservoir (CAP_MCM)
  • year of construction/commissioning (YEAR)
  • alternative year may indicate a multi-year construction or secondary dam (ALT_YEAR)
  • flag of correction if relocation was applied (FLAG_CORR)
  • river name which the dam impounds (RIVER)
  • height of dam (D_Hght_m)
  • maximum inundation area of reservoir (R_Area_km2)
  • length of reservoir (R_Lgth_km)
  • main purpose(s) of dam (PURPOSE)
  • source of information (SOURCE)
  • other notes (COMMENTS)
  • 1850-2025
  • 0.5° grid and original coordinates (degree)
  • annual

Lehner et al. (2011a, https://doi.org/10.7927/H4N877QK), Lehner et al. (2011b, https://dx.doi.org/10.1890/100125), and Jida Wang et al. (KSU/Kansas State University, personal communication). Because the data from KSU is yet unpublished, modeling teams using it are asked to offer co-authorship to the team at KSU on any resulting publications. Please contact info@isimip.org in case of questions.

Water abstraction

Water abstraction for domestic and industrial purposes

socioeconomic/water_abstraction/[domw|indw][w|c]_<soc_scenario>_annual_<start-year>_<end-year>.nc
  • domestic and industrial water withdrawal and consumption (domww, domwc, indww, indwc)
  • 1850-1900
  • 1901-2018
  • 0.5° grid
  • annual

For modelling groups that do not have their own representation, we provide files containing the multi-model mean of domestic and industrial water withdrawal and consumption generated by WaterGAP, PCR-GLOBWB, and H08. This data is based ISIMIP2a varsoc simulations for 1901-2005, and on RCP6.0 simulations from the Water Futures and Solutions project (Wada et al., 2016, http://www.geosci-model-dev.net/9/175/2016/) for after 2005. Years before 1901 have been filled with the value for year 1901.

Fishing mandatory

Fishing effort

Please contact the sectoral coordinators of the marine ecosystems and fisheries sector to gain access to this data.
  • fishing effort
  • 1950-2014
  • Marine ecosystems or exclusive economic zones
  • annual

Sea Around Us Project (SAUP; http://www.seaaroundus.org). Data can currently not be hosted on ISIMIP servers; for access please contact the sectoral coordinators of the marine ecosystems and fisheries sector.

Fish catch

Please contact the sectoral coordinators of the marine ecosystems and fisheries sector to gain access to this data.
  • fish catch
  • 1950-2014
  • Marine ecosystems or exclusive economic zones
  • annual

Regional Fisheries Management Organizations (RFMOs; https://ec.europa.eu/fisheries/cfp/international/rfmo_en) and/or local fisheries agencies. Data can currently not be hosted on ISIMIP servers; for access please contact the sectoral coordinators of the marine ecosystems and fisheries sector.

Forest management

Forest management mandatory

http://doi.org/10.5880/PIK.2019.008
  • stem numbers (stemno)
  • tree species (species)
  • Bily Kriz: 1997-2015
  • Collelongo: 1992-2012
  • Hyytiälä: 1995-2011
  • KROOF: 1997-2010
  • Le Bray: 1986-2009
  • Peitz: 1948-2011
  • Solling-beech: 1967-2014
  • Solling-spruce: 1967-2014
  • Soro: 1944-2010
  • plot-specific
  • annual

Reyer et al. 2019a, b management prescribes stem numbers remaining after harvest, management data is annual but not every year has data.

Wood harvesting

socioeconomic/wood_harvesting/<variable>_<soc_scenario>_national_annual_<start_year>_<end_year>.nc
  • wood harvest area from primary forest land (primf-harv)
  • wood harvest area from primary non forest land (primn-harv)
  • wood harvest area from secondary mature forest land (secmf-harv)
  • wood harvest area from secondary young forest land (secyf-harv)
  • wood harvest area from secondary non forest land (secnf-harv)
  • wood harvest biomass carbon from primary forest land (primf-bioh)
  • wood harvest biomass carbon from primary non forest land (primn-bioh)
  • wood harvest biomass carbon from secondary mature forest land (secmf-bioh)
  • wood harvest biomass carbon from secondary young forest land (secyf-bioh)
  • wood harvest biomass carbon from secondary non forest land (secnf-bioh)
  • 1850-2017
  • national
  • annual

Historic annual country-level wood harvesting data. Based on the LUH2 v2h Harmonization Data Set (see Hurtt, Chini et al. 2011; see also https://luh.umd.edu). Interpolated to a 0.5° grid using first-order conservative remapping and calculated over a fractional country mask (https://gitlab.pik-potsdam.de/isipedia/countrymasks/-/blob/master/) derived from ASAP-GAUL (https://data.europa.eu/euodp/data/dataset/jrc-10112-10004).

Lakes

socioeconomic/lakes/pctlake_<soc_scenario>_<start_year>_<end_year>.nc
  • percentage of lakes in grid cell (pct_lake)
  • 0.5° grid

HydroLAKES polygons dataset v1.0 June 2019 and GRanD v1.3, rasterized using the polygon_to_cellareafraction tool (https://github.com/VUB-HYDR/polygon_to_cellareafraction). Reference: Messager et al. (2016, https://dx.doi.org/10.1038/ncomms13603, Lehner et al. (2011b, https://dx.doi.org/10.1890/100125).

Population mandatory

Population 5' grid

socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_5arcmin_annual_<start-year>_<end-year>.nc
  • total number of people (popc)
  • rural number of people (rurc)
  • urban number of people (urbc)
  • 1850-1900
  • 1901-2020
  • 5' grid
  • annual

HYDE v3.2.1 (Klein Goldewijk et al., 2017). Decadal data prior to year 2000 have been linearly interpolated in time.

Population 0.5° grid

socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_30arcmin_annual_<start-year>_<end-year>.nc
  • total number of people (popc)
  • rural number of people (rurc)
  • urban number of people (urbc)
  • 1850-1900
  • 1901-2020
  • 0.5° grid
  • annual

HYDE v3.2.1 (Klein Goldewijk et al., 2017). Decadal data prior to year 2000 have been linearly interpolated in time. Aggregated to 0.5° spatial resolution

Population national

socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_national_annual_<start-year>_<end-year>.csv
  • total number of people per country
  • 1850-1900
  • 1901-2020
  • national
  • annual

HYDE v3.2.1 (based on WPP 2017 revision, following the methodology of Klein Goldewijk et al., 2017). Decadal data prior to year 1950 have been linearly interpolated in time.

GDP mandatory

GDP

socioeconomic/gdp/<soc_scenario>/<soc_scenario>_gdp_annual_<start-year>_<end-year>.nc
  • GDP PPP 2005 USD (gdp)
  • 1850-1900
  • 1901-2016
  • country-level
  • annual

Historic country-level GDP data are an extension of the data provided by Geiger, 2018 (https://www.earth-syst-sci-data.net/10/847/2018/essd-10-847-2018.html), and are derived mainly from the Maddison Project database. Gridded GDP data will be provided by c. 07/2021.

Geographic data and information

Table 9: Geographic data and information for ISIMIP3a simulation round.
Dataset Included variables (specifier) Resolution Reference/Source and Comments
Land/Sea masks

landseamask

geo_conditions/landseamask/landseamask.nc
  • land-sea mask (mask)
0.5° grid

This is the land-sea mask of the W5E5 dataset. Over all grid cells marked as land by this mask, all climate data that are based on W5E5 (GSWP3-W5E5 as well as climate data bias-adjusted using W5E5) are guaranteed to represent climate conditions over land.

landseamask_no-ant

geo_conditions/landseamask/landseamask_no-ant.nc
  • land-sea mask (mask)
0.5° grid

Same as landseamask but without Antarctica.

landseamask_water-global

geo_conditions/landseamask/landseamask_water-global.nc
  • land-sea mask (mask)
0.5° grid

This is the generic land-sea mask from ISIMIP2b that is to be used for global water simulations in ISIMIP3. It marks more grid cells as land than landseamask. Over those additional land cells, the climate data that are based on W5E5 (GSWP3-W5E5 as well as climate data bias-adjusted using W5E5) are not guaranteed to represent climate conditions over land. Instead they may represent climate conditions over sea or a mix of conditions over land and sea.

Soil

gswp3_hwsd

geo_conditions/soil/gswp3_hwsd.nc
  • soiltexture
0.5° grid

One fixed pattern to be used for all simulation periods. Upscaled Soil texture map (30 arc sec. to 0.5°x0.5° grid) based on Harmonized World Soil Database v1.1 (HWSD) using the GSWP3 upscaling method A (http://hydro.iis.u-tokyo.ac.jp/~sujan/research/gswp3/soil-texture-map.html)

ggcmi_soil_cropland

geo_conditions/soil/ggcmi_soil_cropland.nc
  • USDA soil texture class dominant HWSD on cropland (texture_class)
  • domiant HWSD soil mapping unit within dominant USDA soil texture class on cropland (mu_global)
  • Topsoil pH(H2O) (soil_ph)
  • Topsoil Calcium Carbonate (soil_caco3)
  • Topsoil Bulk Density (bulk_density)
  • Topsoil Cation Exchange Capacity (soil) (cec_soil)
  • Topsoil Organic Carbon (oc)
  • depth of Obstacles to Roots (ESDB) (root_obstacles)
  • depth of Impermeable Layer (ESDB) (impermeable_layer)
  • Available Water Content (awc)
  • Topsoil Sand Fraction (sand)
  • Topsoil Silt Fraction (silt)
  • Topsoil Clay Fraction (clay)
  • Topsoil Gravel Content (gravel)
  • Topsoil Salinity (ece)
  • Topsoil Base Saturation (bs_soil)
  • flag for valid soils (issoil)
0.5° grid

These data are based on the soil data from HWSD. The data originally sit on a 0°0'30" grid and were aggregated to the ISIMIP 0.5° grid. Only the top soil layer properties are given, however on request deeper soil layers could be provided. The aggregation has been performed with the agriculture sector in mind (the aggregation uses the MIRCA data set, see Portmann, F. T., Siebert, S., & Döll, P., 2010, http://doi.org/10.1029/2008GB003435). For further details please refer to the README in the ISIMIP3a/InputData/geo_conditions/soil/ folder.

River routing

basins

geo_conditions/river_routing/ddm30_basins_cru_neva.[nc|asc]
  • basin number (basinnumber)
0.5° grid

DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files.

flowdir

geo_conditions/river_routing/ddm30_flowdir_cru_neva.[nc|asc]
  • flow direction (flowdirection)
0.5° grid

DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files.

slopes

geo_conditions/river_routing/ddm30_slopes_cru_neva.[nc|asc]
  • slope (slope)
0.5° grid

DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files.

Lakes

lakemask

geo_conditions/lakes/lakemask.nc
  • total lake surface area in grid cell (tot_area)
  • average surface area of lakes in grid cell (avg_area)
0.5° grid

lakedepth

geo_conditions/lakes/lakedepth.nc
  • lake depth (lakedepth)
0.5° grid

For these variables, new forcing files will be provided soon: histsoc, accounting for reservoir expansion; and 2015soc.

Output data

Output variables

Table 10: Output variables for all sectors combined (variable).
Variable Variable specifier Unit Dimensions Resolution Comments
Full ISIMIP variable list
Runoff qtot kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • biomes: 0.5° grid
  • permafrost: 0.5° grid
  • biomes: monthly
  • permafrost: monthly
  • water_global: daily & monthly
  • water_regional: daily & monthly

Total (surface + subsurface) runoff (qtot = qs + qsb). Please provide both daily and monthly resolution.

Surface runoff qs kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • biomes: 0.5° grid
  • permafrost: 0.5° grid
  • monthly

Water that leaves the surface layer (top soil layer) e.g. as overland flow / fast runoff.

Subsurface runoff qsb kg m-2 s-1
  • 0.5° grid
  • monthly

Sum of water that flows out from subsurface layer(s) including the groundwater layer (if present). Equals qg in case of a groundwater layer below only one soil layer.

Groundwater recharge qr kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Water that percolates through the soil layer(s) into the groundwater layer. In case seepage is simulated but no groundwater layer is present, report seepage as qr and qg.

Groundwater runoff qg kg m-2 s-1
  • 0.5° grid
  • monthly

Water that leaves the groundwater layer. In case seepage is simulated but no groundwater layer is present, report seepage as qr and qg.

Discharge dis m3 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • daily & monthly

River discharge or streamflow. Please provide both daily and monthly resolution.

Evapotranspiration

biomes: evap-<pft/total>

forestry: evap-<species/total>

water_global: evap

water_regional: evap

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • biomes: daily, monthly
  • forestry: daily, monthly
  • water_global: monthly
  • water_regional: monthly

Sum of transpiration, evaporation, interception and sublimation.

Potential Evapotranspiration potevap kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

As evap, but with all resistances set to zero, except the aerodynamic resistance.

Soil moisture for each layer soilmoist kg m-2
  • agriculture: 0.5° grid
  • biomes: 0.5° grid
  • forestry: stand
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • permafrost: 0.5° grid
  • agriculture: daily
  • biomes: daily
  • forestry: daily
  • permafrost: daily
  • water_global: monthly
  • water_regional: monthly

Please provide soil moisture for all depth layers (i.e. 3D-field), and indicate depth in m. If depth varies over time or space, see instructions for depth layers on https://www.isimip.org/protocol/preparing-simulation-files.

Soil moisture, root zone rootmoist kg m-2
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • biomes: 0.5° grid
  • permafrost: 0.5° grid
  • monthly

Total simulated soil moisture available for evapotranspiration. Please indicate the depth of the root zone for each vegetation type in your model. If depth varies over time or space, see instructions for depth layers on https://www.isimip.org/protocol/preparing-simulation-files.

Frozen soil moisture for each layer soilmoistfroz kg m-2
  • 0.5° grid
  • monthly

Please provide soil moisture for all depth levels and indicate depth in m.

Temperature of Soil tsl K
  • biomes: 0.5° grid
  • forestry: stand
  • water_global: 0.5° grid
  • permafrost: 0.5° grid
  • biomes: daily, monthly
  • forestry: daily, monthly
  • water_global: daily, monthly
  • water_regional: daily, monthly
  • permafrost: daily, monthly

Temperature of each soil layer. Reported as "missing" for grid cells occupied entirely by "sea". This is the most important variable for the permafrost sector. If daily resolution not possible, please provide monthly. If depth varies over time or space, see instructions for depth layers on https://www.isimip.org/protocol/preparing-simulation-files.

Snow depth snd m
  • 0.5° grid
  • monthly

Grid cell mean depth of snowpack. This variable only for the purposes of the permafrost sector.

Snow water equivalent swe kg m-2
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • biomes: 0.5° grid
  • permafrost: 0.5° grid
  • monthly

Total water mass of the snowpack (liquid or frozen) averaged over grid cell. Please also deliver for the permafrost sector.

Total water storage tws kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in all compartments. Please indicate in the netcdf metadata which storage compartments are considered.

Canopy water storage canopystor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in the canopy.

Glacier storage glacierstor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in glaciers.

Groundwater storage groundwstor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in groundwater layer.

Lake storage lakestor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in lakes (except reservoirs).

Wetland storage wetlandstor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in wetlands.

River storage riverstor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in rivers.

Reservoir storage reservoirstor kg m-2
  • 0.5° grid
  • monthly

Mean monthly water storage in reservoirs.

Annual maximum thaw depth thawdepth m
  • 0.5° grid
  • biomes: annual
  • permafrost: annual
  • water_global: monthly

Calculated from daily thaw depths.

River temperature triver K
  • 0.5° grid
  • monthly

Mean monthly water temperature in river (representative of the average temperature across the channel volume).

Potential irrigation water withdrawal (assuming unlimited water supply)

agriculture: pirrww-<crop>-<irrigation>

water_global: pirrww

water_regional: pirrww

agriculture: mm per growing season

water_global: kg m-2 s-1

water_regional: kg m-2 s-1

  • agriculture: 0.5° grid
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • agriculture: seasonal
  • water_global: monthly
  • water_regional: monthly

Irrigation water withdrawn in case of optimal irrigation (in addition to rainfall), assuming no losses in conveyance and application.

Actual irrigation water withdrawal airrww kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Irrigation water withdrawal, taking water availability into account; please provide if computed.

Potential irrigation water consumption pirruse kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Portion of withdrawal that is evapo-transpired, assuming unlimited water supply.

Actual irrigation water consumption airruse kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Portion of withdrawal that is evapo-transpired, taking water availability into account; if computed.

Actual green water consumption on irrigated cropland airrusegreen kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Actual evapotranspiration from rainwater over irrigated cropland; if computed.

Potential green water consumption on irrigated cropland pirrusegreen kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Potential evapotranspiration from rainwater over irrigated cropland; if computed and different from AIrrUseGreen.

Actual green water consumption on rainfed cropland arainfusegreen kg m-2 s-1
  • water_global: 0.5° grid
  • water_regional: 0.5° grid if possible, otherwise at gauge location
  • monthly

Actual evapotranspiration from rainwater over rainfed cropland; if computed.

Actual domestic water withdrawal adomww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual domestic water consumption adomuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual manufacturing water withdrawal amanww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual manufacturing water consumption amanuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual electricity water withdrawal aelecww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual electricity water consumption aelecuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual livestock water withdrawal aliveww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual livestock water consumption aliveuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential domestic water withdrawal pdomww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential domestic water consumption pdomuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential manufacturing water withdrawal pmanww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential manufacturing water consumption pmanuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential electricity water withdrawal pelecww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential electricity water consumption pelecuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential livestock water withdrawal pliveww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Potential livestock water consumption pliveuse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Total (all sectors) actual water withdrawal atotww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Total (all sectors) actual water consumption atotuse kg m-2 s-1
  • 0.5° grid
  • monthly

Sum of actual water consumption from all sectors. Please indicate in metadata which sectors are included.

Total (all sectors) potential water withdrawal ptotww kg m-2 s-1
  • 0.5° grid
  • monthly

Sum of potential (i.e. assuming unlimited water supply) water withdrawal from all sectors. Please indicate in metadata which sectors are included.

Total (all sectors) potential water consumption ptotuse kg m-2 s-1
  • 0.5° grid
  • monthly

Sum of potential (i.e. assuming unlimited water supply) water consumption from all sectors. Please indicate in metadata which sectors are included.

Actual industrial water consumption ainduse kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Actual industrial water withdrawal aindww kg m-2 s-1
  • 0.5° grid
  • monthly

If computed.

Soil types soil
  • 0.5° grid
  • constant

Soil types or texture classes as used by your model. Please include a description of each type or class, especially if these are different from the standard HSWD and GSWP3 soil types. Please also include a description of the parameters and values associated with these soil types (parameter values could be submitted as spatial fields where appropriate).

Crop yields yield-<crop>-<irrigation> dry matter (t ha-1 per growing season)
  • 0.5° grid
  • seasonal

Crop-specific: Yield may be identical to above-ground biomass (biom) if the entire plant is harvested, e.g. for bioenergy production.

Actual evapotranspiration aet-<crop>-<irrigation> mm per growing season
  • 0.5° grid
  • seasonal

Portion of all water (including rain) that is evapo-transpired, the water amount should be accumulated over the entire growing period (not the calendar year)

Nitrogen application rate initr-<crop>-<irrigation> kg ha-1 per growing season
  • 0.5° grid
  • seasonal

Total nitrogen application rate. If organic and inorganic amendments are applied, rate should be reported as effective inorganic nitrogen input (ignoring residues).

Actual planting dates plantday-<crop>-<irrigation> day of year
  • 0.5° grid
  • seasonal

Julian dates.

Actual planting year plantyear-<crop>-<irrigation> year of planting
  • 0.5° grid
  • seasonal

This allows for clear identification of planting that is also easy to follow for potential users from outside the project

Anthesis dates anthday-<crop>-<irrigation> day of year of anthesis
  • 0.5° grid
  • seasonal

Together with the year of anthesis added to the list of outputs (see below) it allows for clear identification of anthesis that is also easy to follow for potential users from outside the project.

Year of anthesis anthyear-<crop>-<irrigation> year of anthesis
  • 0.5° grid
  • seasonal

It allows for clear identification of anthesis that is also easy to follow for potential users from outside the project.

Maturity dates matyday-<crop>-<irrigation> day of year of maturity
  • 0.5° grid
  • seasonal

Together with the year of maturity added to the list of outputs (see below) it allows for clear identification of maturity that is also easy to follow for potential users from outside the project.

Year of maturity matyyear-<crop>-<irrigation> year of maturity
  • 0.5° grid
  • seasonal

It allows for clear identification of maturity that is also easy to follow for potential users from outside the project.

Above ground biomass (dry matter) biom-<crop>-<irrigation> t ha-1 per growing season
  • 0.5° grid
  • seasonal

The whole plant biomass above ground.

Soil carbon emissions sco2-<crop>-<irrigation> kg C ha-1
  • 0.5° grid
  • seasonal

Ideally should be modeled with realistic land-use history and initial carbon pools. Subject to extra study.

Nitrous oxide emissions sn2o-<crop>-<irrigation> kg N2O-N ha-1
  • 0.5° grid
  • seasonal

Ideally should be modeled with realistic land-use history and initial carbon pools. Subject to extra study.

Total N uptake (total growing season sum) tnup-<crop>-<irrigation> kg ha -1 yr -1
  • 0.5° grid
  • monthly

Nitrogen balance: uptake

Total N inputs (total growing season sum) tnin-<crop>-<irrigation> kg ha -1 yr -1
  • 0.5° grid
  • monthly

Nitrogen balance: inputs

Total N losses (total growing season sum) tnloss-<crop>-<irrigation> kg ha -1 yr -1
  • 0.5° grid
  • monthly

Nitrogen balance: losses

leach
  • 0.5° grid
  • seasonal
Growing season precipitation gsprcp-<crop>-<irrigation> mm ha-1 yr-1
  • 0.5° grid
  • seasonal

Total growing season precipitation per crop

Growing season radiation gsrsds-<crop>-<irrigation> w m-2 yr-1
  • 0.5° grid
  • seasonal

Average growing season shortwave solar radiation

Growing season temperature sum sumt-<crop>-<irrigation> deg c-days yr-1
  • 0.5° grid
  • seasonal

Sum of daily mean temperature over growing season

Amphibian species probability of occurrence amphibianprob Probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Results from individual SDMs assuming no dispersal.

Terrestrial bird species probability of occurrence birdprob Probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Results from individual SDMs assuming no dispersal.

Terrestrial mammal species probability of occurrence mammalprob Probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Results from individual SDMs assuming no dispersal.

Amphibian summed probability of occurrence amphibiansumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Terrestrial bird summed probability of occurrence birdsumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Terrestrial mammal summed probability of occurrence mammalsumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Summed probability of endemic amphibian species endamphibiansumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Summed probability of endemic terrestrial bird species endbirdsumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Summed probability of endemic terrestrial mammal species endmammalsumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Summed probability of threatened amphibian species thramphibiansumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Summed probability of threatened terrestrial bird species thrbirdsumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Summed probability of threatened terrestrial mammal species thrmammalsumprob Summed probability of occurrence per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Aggregated results from individual SDMs assuming no dispersal.

Amphibian species richness amphibiansr Estimated number of species (species richness) per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Results from macroecological richness models

Terrestrial bird species richness birdsr Estimated number of species (species richness) per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Results from macroecological richness models

Terrestrial mammal species richness mammalsr Estimated number of species (species richness) per cell (time,lat,lon,?)
  • 0.5° grid
  • 30year-mean

Results from macroecological richness models

Carbon Mass in Vegetation

biomes: cveg-<pft/total>

forestry: cveg-<species/total>

permafrost: cveg-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

biomes: Grid cell total and PFT information is essential.

forestry: As kg carbon*m-2

permafrost: Grid cell total and PFT information is essential.

Carbon Mass in aboveground vegetation biomass

biomes: cvegag-<pft/total>

forestry: cvegag-<species/total>

permafrost: cvegag-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

biomes: Grid cell total and PFT information is essential.

forestry: As kg carbon*m-2

permafrost: Grid cell total and PFT information is essential.

Carbon Mass in belowground vegetation biomass

biomes: cvegbg-<pft/total>

forestry: cvegbg-<species/total>

permafrost: cvegbg-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

biomes: Grid cell total and PFT information is essential.

forestry: As kg carbon*m-2

permafrost: Grid cell total and PFT information is essential.

Carbon Mass in Litter Pool

biomes: clitter-<pft/total>

forestry: clitter-<species/total>

permafrost: clitter-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

biomes: Grid cell total and PFT information is essential.

forestry: As kg carbon*m-2, Info for each individual pool.

permafrost: Grid cell total and PFT information is essential.

Carbon Mass in Soil Pool

biomes: csoil-<pft/total>

forestry: csoil-<species/total>

permafrost: csoil-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

biomes: Grid cell total and PFT information is essential. If possible, provide soil carbon for all depth layers (i.e. 3D-field), and indicate depth in m. Otherwise, provide soil carbon integrated over entire soil depth.

forestry: As kg carbon*m-2, Info for each individual soil layer.

permafrost: Grid cell total and PFT information is essential.

Carbon in Products of Land Use Change

biomes: cproduct-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • annual

biomes: Products generated during Land-use change. Removed carbon should not go into the soil but into the product pool. Grid cell total and PFT information is essential.

Carbon in biomass harvested from natural vegetation

biomes: charv-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • annual

biomes: Refers to Carbon not going into soil. Grid cell total and PFT information is essential.

Carbon Mass Flux out of Atmosphere due to Gross Primary Production on Land

biomes: gpp-<pft/total>

forestry: gpp-<species/total>

permafrost: gpp-<pft/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • daily, monthly

biomes:

forestry: As kg carbon*m-2*s-1

Carbon Mass Flux into Atmosphere due to Autotrophic (Plant) Respiration on Land

biomes: ra-<pft/total>

forestry: ra-<species/total>

permafrost: ra-<pft/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • daily, monthly

biomes:

forestry: As kg carbon*m-2*s-1

Carbon Mass Flux out of Atmosphere due to Net Primary Production on Land

biomes: npp-<pft/total>

forestry: npp-<species/total>

permafrost: npp-<pft/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • daily, monthly

biomes:

forestry: As kg carbon*m-2*s-1

Net Primary Production on Land allocated to leaf biomass

biomes: nppleaf-<pft/total>

forestry: nppleaf-<species/total>

kg m-2 s-1
  • 0.5° grid
  • daily, monthly
Net Primary Production on Land allocated to fine root biomass

biomes: npproot-<pft/total>

forestry: npproot-<species/total>

kg m-2 s-1
  • 0.5° grid
  • daily, monthly
Net Primary Production on Land allocated to above ground woody biomass

biomes: nppagwood-<pft/total>

forestry: nppagwood-<species/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • daily, monthly
Net Primary Production on Land allocated to below ground wood biomass

biomes: nppbgwood-<pft/total>

forestry: nppbgwood-<species/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • daily, monthly
Carbon Mass Flux into Atmosphere due to Heterotrophic Respiration on Land

biomes: rh-<pft/total>

forestry: rh-<species/total>

permafrost: rh-<pft/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • daily, monthly

biomes:

forestry: As kg carbon*m-2*s-1

Carbon Mass Flux into Atmosphere due to CO₂ Emission from Fire fireint-<pft/total> kg m-2 s-1
  • 0.5° grid
  • daily, monthly
Burnt Area Fraction burntarea-<pft/total> %
  • 0.5° grid
  • daily, monthly

Fire should be only allowed to burn natural vegetation, rangelands and managed pastures but not croplands. Area percentage of grid cell that has burned at any time of the given day/month/year (for daily/monthly/annual resolution)

Carbon Mass Flux out of Atmosphere due to Net Biospheric Production on Land ecoatmflux-<pft/total> kg m-2 s-1
  • 0.5° grid
  • daily, monthly

This is the net mass flux of carbon between land and atmosphere calculated as photosynthesis MINUS the sum of plant and soil respiration, carbonfluxes from fire, harvest, grazing and land use change. Positive flux is into the land.

Root autotrophic respiration rr-<pft/total> kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • biomes: daily, monthly
  • forestry: daily

biomes:

forestry: As kg carbon*m-2*s-1

Fraction of absorbed photosynthetically active radiation

biomes: fapar-<pft/total>

forestry: fapar-<species/total>

permafrost: fapar-<pft/total>

%
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • daily, monthly

Value between 0 and 100.

Leaf Area Index

biomes: lai-<pft/total>

forestry: lai-<species/total>

permafrost: lai-<pft/total>

water_global: lai

water_regional: lai

1
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • water_global: 0.5° grid
  • biomes: daily, monthly
  • forestry: daily, monthly
  • permafrost: daily, monthly
  • water_global: constant or monthly

biomes:

forestry:

permafrost:

water_global: If used by, or computed by the model.

Plant Functional Type Grid Fraction pft-<pft/total> %
  • 0.5° grid
  • annual (or constant if static)

The categories may differ from model to model, depending on their PFT definitions. This may include natural PFTs, anthropogenic PFTs, bare soil, lakes, urban areas, etc. Sum of all should equal the fraction of the grid cell that is land.

Evaporation from Canopy (interception)

biomes: intercep-<pft/total>

forestry: intercep-<species/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • daily, monthly

The canopy evaporation+sublimation (if present in model).

Water Evaporation from Soil esoil kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • water_global: 0.5° grid
  • water_regional: 0.5° grid
  • daily, monthly

Includes sublimation.

Transpiration

biomes: trans-<pft/total>

forestry: trans-<species/total>

kg m-2 s-1
  • biomes: 0.5° grid
  • forestry: stand
  • biomes: daily, monthly
  • forestry: daily
Carbon Mass in Leaves

biomes: cleaf-<pft/total>

forestry: cleaf-<species/total>

permafrost: cleaf-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual
Carbon Mass in Wood

biomes: cwood-<pft/total>

forestry: cwood-<species/total>

permafrost: cwood-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

Including sapwood and hardwood.

Carbon Mass in Roots

biomes: croot-<pft/total>

forestry: croot-<species/total>

permafrost: croot-<pft/total>

kg m-2
  • biomes: 0.5° grid
  • forestry: stand
  • permafrost: 0.5° grid
  • annual

Including fine and coarse roots.

Mean DBH dbh-<species/total> cm
  • stand
  • annual
Mean DBH of 100 highest trees dbhdomhei cm
  • stand
  • annual

100 highest trees per hectare.

Stand Height hei-<species/total> ha-1
  • stand
  • annual

For models including natural regeneration this variable may not make sense, please report domhei.

Dominant Height domhei m2 ha-1
  • stand
  • annual

Mean height of the 100 highest trees per hectare.

Stand Density density-<species/total> m2 ha-1
  • stand
  • annual
Basal Area ba-<species/total> m2 ha-1
  • stand
  • annual
Volume of Dead Trees mort-<species/total> m3 ha-1
  • stand
  • annual
Harvest by DBH-class harv-<species/total> m3 ha-1
  • stand
  • annual

DBH class resolution: Either DBH classes or total per species

Remaining stem number after disturbance and management by dbh class stemno-<species/total> ha-1
  • stand
  • annual

DBH class resolution: Either DBH classes or total per species

Stand Volume vol-<species/total> m3 ha-1
  • stand
  • annual
Tree age by dbh class age-<species/total> yr
  • stand
  • annual

DBH class resolution: Either DBH classes or total per species

Net Ecosystem Exchange nee-<species/total> kg m-2 s-1
  • stand
  • daily, monthly

As kg carbonm-2s-1

Mean Annual Increment mai-<species/total> m3 ha-1
  • stand
  • annual
Species composition species-<species/total> %
  • per ha
  • monthly
Removed stem numbers by DBH class by natural mortality mortstemno-<species/total> ha-1
  • stand
  • annual

As trees per hectare. DBH class resolution: Either DBH classes or total per species

Removed stem numbers by DBH class by management harvstemno-<species/total> ha-1
  • stand
  • annual

As trees per hectare. DBH class resolution: Either DBH classes or total per species

Volume of disturbance damage dist-<dist-name>-<species/total> m3 ha-1
  • stand
  • annual
Nitrogen of annual Litter nlit-<species/total> g m-2 a-1
  • stand
  • annual

As g Nitrogen m-2 a-1

Nitrogen in Soil nsoil g m-2 a-1
  • stand
  • annual

As g Nitrogen m-2 a-1

Thermal stratification strat 1
  • Representative lake associated with grid cell
  • daily

1 if lake grid cell is thermally stratified, 0 if lake grid cell is not thermally stratified

Depth of Thermocline thermodepth m
  • Representative lake associated with grid cell
  • daily

Depth corresponding the maximum water density gradient

Water temperature watertemp K
  • Representative lake associated with grid cell
  • daily

Depth resolution: Full Profile. Simulated water temperature. Layer averages and full profiles.

Surface temperature surftemp K
  • Representative lake associated with grid cell
  • daily, monthly

Average of the upper layer in case not simulated directly.

Bottom temperature bottemp K
  • Representative lake associated with grid cell
  • daily, monthly

Average of the lowest layer in case not simulated directly.

Lake ice cover ice 1
  • Representative lake associated with grid cell
  • daily

1 if ice cover is present in lake grid cell, 0 if no ice cover is present in lake grid cell

Lake layer ice mass fraction lakeicefrac 1
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Mean epi. Fraction of mass of a given layer taken up by ice.

Ice thickness icethick m
  • Representative lake associated with grid cell
  • daily, monthly
Snow thickness snowthick m
  • Representative lake associated with grid cell
  • daily, monthly
Temperature at the ice upper surface icetemp K
  • Representative lake associated with grid cell
  • daily
Temperature at the snow upper surface snowtemp K
  • Representative lake associated with grid cell
  • daily
Sensible heat flux at the lake-atmosphere interface sensheatf W m-2
  • Representative lake associated with grid cell
  • daily, monthly

At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards.

Latent heat flux at the lake-atmosphere interface latentheatf W m-2
  • Representative lake associated with grid cell
  • daily, monthly

At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards.

Momentum flux at the lake-atmosphere interface momf kg m-1 s-2
  • Representative lake associated with grid cell
  • daily, monthly

At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards.

Upward shortwave radiation flux at the lake-atmosphere interface swup W m-2
  • Representative lake associated with grid cell
  • daily, monthly

At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. Not to be confused with net shortwave radiation.

Upward longwave radiation flux at the lake-atmosphere interface lwup W m-2
  • Representative lake associated with grid cell
  • daily, monthly

At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. Not to be confused with net longwave radiation.

Downward heat flux at the lake-atmosphere interface lakeheatf W m-2
  • Representative lake associated with grid cell

At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. the residual term of the surface energy balance, i.e. the net amount of energy that enters the lake on daily time scale: lakeheatf = swdown - swup + lwdown - lwup - sensheatf - latenheatf (terms defined positive when directed upwards)

Turbulent diffusivity of heat turbdiffheat m2 s-1
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Only if computed by the model.

Surface albedo albedo 1
  • Representative lake associated with grid cell
  • daily, monthly

Albedo of the surface interacting with the atmosphere (water, ice or snow).

Light extinction coefficient extcoeff m-1
  • Representative lake associated with grid cell
  • constant

Only to be reported for global models, local models should use extcoeff as input.

Sediment upward heat flux at the lake-sediment interface sedheatf W m-2
  • Representative lake associated with grid cell
  • daily, monthly

Positive if upwards. Only if computed by the model.

Chlorophyll Concentration chl g-3 m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Total water chlorophyll concentration – indicator of phytoplankton.

Phytoplankton Functional group biomass phytobio mole m-3 as carbon
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Different models will have different numbers of functional groups so that the reporting of these will vary by model.

Phytoplankton Functional group biomass zoobio mole m-3 as carbon
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Total simulated Zooplankton biomass.

Total Phosphorus tp mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo.

Particulate Phosphorus pp mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo.

Total Dissolved Phosphorus tpd mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Some models may also output data for soluble reactive phosphorus (SRP).

Total Nitrogen tn mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo.

Particulate Nitrogen pn mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo.

Total Dissolved Nitrogen tdn mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Some models may also output data for Nitrate (N02) nitrite (NO3) and ammonium (NH4).

Dissolved Oxygen do mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo.

Dissolved Organic Carbon doc mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Not always available.

Dissolved Silica si mole m-3
  • Representative lake associated with grid cell
  • daily, monthly

Depth resolution: Either full profile, or mean epi and mean hypo. Not always available.

TOTAL system biomass density tsb g C m-2
  • 0.5° grid
  • monthly

all primary producers and consumers

TOTAL consumer biomass density tcb g C m-2
  • 0.5° grid
  • monthly

all consumers (trophic level >1, vertebrates and invertebrates)

Biomass density of consumers >10cm b10cm g C m-2
  • 0.5° grid
  • monthly

if L infinity is >10 cm, include in >10 cm class

Biomass density of consumers >30cm b30cm g C m-2
  • 0.5° grid
  • monthly

if L infinity is >30 cm, include in >30 cm class

TOTAL Catch (all commercial functional groups / size classes) tc g m-2
  • 0.5° grid
  • monthly

catch at sea (commercial landings plus discards, fish and invertebrates)

TOTAL Landings (all commercial functional groups / size classes) tla g m-2
  • 0.5° grid
  • monthly

commercial landings (catch without discards, fish and invertebrates)

Biomass density of commercial species bcom g C m-2
  • 0.5° grid
  • monthly

Discarded species not included (Fish and invertebrates)

Biomass density of large consumers >90cm and <100kg blarge g C m-2
  • 0.5° grid
  • monthly
Biomass density of medium consumers >30cm and <90cm bmed g C m-2
  • 0.5° grid
  • monthly
Biomass density of small consumers <30cm bsmall g C m-2
  • 0.5° grid
  • monthly
Biomass density (by functional group / size class) b-<class>-<group> g C m-2
  • 0.5° grid
  • monthly

Provide name of each size class () and functional group () used, and provide a definition of each class/group.

Catch of large consumers >90cm and <100kg clarge g m-2
  • 0.5° grid
  • monthly
Catch of medium consumers >30cm and <90cm cmed g m-2
  • 0.5° grid
  • monthly
Catch of small consumers <30cm csmall g m-2
  • 0.5° grid
  • monthly
Catch (by functional group / size class) c-<class>-<group> g m-2
  • 0.5° grid
  • monthly

Provide name of each size class () and functional group () used, and provide a definition of each class/group.

TOTAL Catch of consumers >10cm tc10cm g m-2
  • 0.5° grid
  • monthly
TOTAL Catch of consumers >30cm tc30cm g m-2
  • 0.5° grid
  • monthly
Number of deaths attributable to cold ancold-<r> 1 (time,lat,lon), (time,location)
  • 0.5° grid, location
  • daily

For ERF models, this occurs when temperature is below threshold (e.g., minimum mortality temperature (MMT)). Report 0 if temperature above threshold. Can have gender, age, etc. dimensions; see below.

Number of deaths attributable to heat anheat-<r> 1 (time,lat,lon), (time,location)
  • 0.5° grid, location
  • daily

Temperature above threshold (ERFs). Report 0 if temperature below threshold. Can have gender, age, etc. dimensions; see below.

Baseline total mortality btm 1 (time,lat,lon), (time,location)
  • 0.5° grid, location
  • daily

To be reported as annual series of mean daily total mortality, or as a single number of mean daily mortality; to be used for computations of attributable fractions. Can have gender, age, etc. dimensions; see below.

Population pop 1 (time,lat,lon), (time,location)
  • 0.5° grid, location
  • annual, 5-year intervals

Baseline population data should be provided for computations of mortality rates (i.e. deaths per total population). See Section ‎5.1.6. Can have gender, age, etc. dimensions; see below.

Crops

Table 11: Crop naming and priorities (crop).
Crop Specifier
Major crops
Wheat whe
Maize mai
Soy soy
Rice ric
Other crops
Barley bar
Bean ben
Cassava cas
Cotton cot
Eucalyptus euc
Managed grass mgr
Millet mil
Miscanthus mis
Groundnuts nut
Field peas pea
Poplar pop
Potato pot
Rapeseed rap
Rye rye
Sugar beet sgb
Sorghum sor
Sugarcane sug
Sunflower sun

Irrigation

Table 12: Irrigation specifiers (irrigation).
Irrigation type Specifier
Full irrigation firr
Constrained irrigation cirr
No irrigation (rainfed land) noirr

Harmonization

Table 13: Harmonization specifiers (harmonization).
Simulation Specifier Description
Default default Model should use their individual “best representation” of the historical period with regard to sowing dates, harvesting dates, fertilizer application rates and crop varieties.
Fully harmonized fullharm Simulations based on prescribed “present day” fertilization rates (available for download) and fixed planting and harvesting dates (also available for download). Modelers should have planting as closely as possible to these dates, but it may be admissible to use these dates as indicators for planting windows (depending on model specifics).
Harmonized seasons with no N constraints harmnon For models with an explicit description of the nitrogen cycle: harmnon simulations should be run with nitrogen stress turned off completely or (if that’s not possible) with very high N application rates to make model results comparable between those GGCMs that have explicit N dynamics and those that do not. For models without the nitrogen cycle: harmnon and fullharm simulations are the same and do not need to be duplicated. Please contact the sector coordination to push on with this side branch.

Species

Table 14: Specifiers for species, disturbance names and DBH classes (species).
Specifier Species
fasy Fagus sylvatica
quro Quercus robur
qupe Quercus petraea
pisy Pinus sylvestris
piab Picea abies
pipi Pinus pinaster
lade Larix decidua
acpl Acer platanoides
eugl Eucalyptus globulus
bepe Betula pendula
bepu Betula pubescens
rops Robinia pseudoacacia
frex Fraxinus excelsior
poni Populus nigra
soau Sorbus aucuparia
c3gr C3 grass
hawo hard woods
fi fire
wi wind
ins Insects

Forest stands

Table 15: Overview of the forest stands (forrest-stand).
Stand Specifier Country Coordinates (Lat, Lon) Forest type Species Thinning during historical time period Comment
Hyytiälä hyytiala FI 61.8475, 24.295 Even-aged conifer pisy, piab below Note that an experimental plot of pine contains a lot of data while footprint of flux tower is larger. Please note that the deciduous admixtures only appear in the data at a later stage and hence do not need to be simulated. Only simulate pine and spruce (no hard-woods) and regenerate as pure pine stand
Peitz peitz DE 51.9166, 14.35 Even-aged conifer pisy below Managed using a weak thinning from below.
Solling (beech) solling-beech DE 51.77, 9.57 Even-aged deciduous fasy above
Solling (spruce) solling-spruce DE 51.77, 9.57 Even-aged conifer piab below
Sorø soro DK 55.485844, 11.644616 Even-aged deciduous fasy above
Kranzberg Roof Project kroof DE 48.25, 11.4 Mixed deciduous and conifers fasy, piab, acpl, lade, pisy, quro below Unmanaged/ thinning from below in past 20 years for all species.
Le Bray le-bray FR 44.71711, -0.7693 Even-aged conifer pipi below
Collelongo collelongo IT 41.8494, 13.5881 Even-aged deciduous fasy above
Bílý Kříž bily-kriz CZ 49.3, 18.32 Even-aged conifer piab below

Lake sites

Table 16: Lake site specifications for local lake models (lake-site).
Lake name Specifier Reservoir or lake Country Coordinates (Lat, Lon)
Alqueva Reservoir alqueva reservoir Portugal 38.2, -7.49
Lake Annecy annecy lake France 45.87, 6.17
Lake Annie annie lake USA 27.21, -81.35
Lake Argyle argyle reservoir Australia -16.31, 128.68
Lake Biel biel lake Switzerland 47.08, 7.16
Big Muskellunge Lake big-muskellunge lake USA 46.02, -89.61
Black Oak Lake black-oak lake USA 46.16, -89.32
Lake Bourget bourget lake France 45.76, 5.86
Lake Burley Griffin burley-griffin reservoir Australia -35.3, 149.07
Crystal Lake crystal-lake lake USA 46.0, -89.61
Crystal Bog crystal-bog lake USA 46.01, -89.61
Delavan Lake delavan lake USA 42.61, -88.6
Dickie Lake dickie lake Canada 45.15, -79.09
Eagle Lake eagle lake Canada 44.68, -76.7
Ekoln basin of Mälaren ekoln lake Sweden 59.75, 17.62
Lake Erken erken lake Sweden 59.84, 18.63
Esthwaite Water esthwaite-water lake United Kingdom 54.37, -2.99
Falling Creek Reservoir falling-creek reservoir USA 37.31, -79.84
Lake Feeagh feeagh lake Ireland 53.9, -9.5
Fish Lake fish lake USA 43.29, -89.65
Lake Geneva geneva lake France/Switzerland 46.45, 6.59
Great Pond great lake USA 44.53, -69.89
Green Lake green lake USA 43.81, -89.0
Harp Lake harp lake Canada 45.38, -79.13
Kilpisjärvi kilpisjarvi lake Finland 69.03, 20.77
Lake Kinneret kinneret lake Israel 32.49, 35.35
Lake Kivu kivu lake Rwanda/DR Congo -1.73, 29.24
Klicava Reservoir klicava reservoir Czechia 50.07, 13.93
Lake Kuivajarvi kuivajarvi lake Finland 60.47, 23.51
Lake Langtjern langtjern lake Norway 60.37, 9.73
Laramie Lake laramie lake USA 40.62, -105.84
Lower Lake Zurich lower-zurich lake Switzerland 47.28, 8.58
Lake Mendota mendota lake USA 43.1, -89.41
Lake Monona monona lake USA 43.06, -89.36
Mozhaysk reservoir mozhaysk reservoir Russia 55.59, 35.82
Mt Bold mt-bold reservoir Australia -35.12, 138.71
Lake Müggelsee mueggelsee lake Germany 52.43, 13.65
Lake Neuchâtel neuchatel lake Switzerland 46.54, 6.52
Ngoring ngoring lake China 34.9, 97.7
Lake Nohipalo Mustjärv nohipalo-mustjaerv lake Estonia 57.93, 27.34
Lake Nohipalo Valgejärv nohipalo-valgejaerv lake Estonia 57.94, 27.35
Okauchee Lake okauchee lake USA 43.13, -88.43
Lake Pääjärvi paajarvi lake Finland 61.07, 25.13
Rappbode Reservoir rappbode reservoir Germany 51.74, 10.89
Rimov Reservoir rimov reservoir Czechia 48.85, 14.49
Lake Rotorua rotorua lake New Zealand -38.08, 176.28
Lake Sammamish sammamish lake USA 47.59, -122.1
Sau Reservoir sau reservoir Spain 41.97, 2.4
Sparkling Lake sparkling lake USA 46.01, -89.7
Lake Stechlin stechlin lake Germany 53.17, 13.03
Lake Sunapee sunapee lake USA 43.23, -72.5
Lake Tahoe tahoe reservoir USA 39.09, -120.03
Lake Tarawera tarawera lake New Zealand -38.21, 176.43
Lake Taupo taupo lake New Zealand -38.8, 175.89
Toolik Lake toolik lake USA 68.63, -149.6
Trout Lake trout-lake lake USA 46.03, -89.67
Trout Bog trout-bog lake USA 46.04, -89.69
Two Sisters Lake two-sisters lake USA 45.77, -89.53
Lake Vendyurskoe vendyurskoe lake Russia 62.1, 33.1
lake Võrtsjärv vortsjaerv lake Estonia 58.31, 26.01
Lake Waahi waahi lake New Zealand 37.33, 175.07
Lake Washington washington lake USA 47.64, -122.27
Windermere windermere lake United Kingdom 54.31, -2.95
Lake Wingra wingra lake USA 43.05, -89.43
Zlutice Reservoir zlutice reservoir Czechia 50.09, 13.11

Ocean regions

Table 17: Ocean regions (ocean-region).
Ocean region Specifier Coordinates (west, south, east, north)
North Sea north-sea -4.5, 50.5, 9.5, 62.5
Baltic Sea baltic-sea 15.5, 55.5, 23.5, 64.5
North-west Meditteranean nw-med-sea -1.5, 36.5, 6.5, 43.5
Adriatic Sea adriatic-sea 11.5, 39.5, 20.5, 45.5
Mediterranean Sea med-glob -6.5, 29.5, 35.5, 45.5
South-East Australia se-australia 120.5, -47.5, 170.5, -23.5
Eastern Bass Strait east-bass-strait 145.5, -41.5, 151.5, -37.5
Cook Strait cook-strait 174.5, -46.5, 179.5, -40.5
North Humboldt Sea humboldt-n -93.5, -20.5, -69.5, 6.5

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.

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

Please name the files in the all sectors combined sector according to the following pattern:

<model>_<climate-forcing>_<climate-scenario>_<soc-scenario>_<sens-scenario>_<variable>_<region>_<timestep>_<start-year>_<end-year>.nc

and replace the identifiers with the specifiers given in the tables of this document. Examples would be:

lpjml_gswp3_obsclim_histsoc_default_qtot_global_annual_1901_1910.nc
lpjml_gwsp3_counterclim_2015soc_1901co2_yield-mai-noirr_global_annual_2006_2010.nc

The following regular expression can be used to validate and parse the file name for the all sectors combined sector:

(?P<model>[a-z0-9-+.]+)_(?P<climate_forcing>[a-z0-9-]+)_(?P<climate_scenario>[a-z0-9-]+)_(?P<soc_scenario>[a-z0-9-]+)_(?P<sens_scenario>[a-z0-9-]+)_(?P<variable>[a-z0-9]+)_(?P<region>(global))_(?P<timestep>[a-z0-9-]+)_(?P<start_year>\d{4})_(?P<end_year>\d{4}).nc

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

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