ISIMIP3b 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:
- A common set of climate and other forcing data which will be distributed via a central database;
- A common modelling protocol to ensure consistency across sectors and scales in terms of data, format and scenario set-up;
- A central archive where the output data will be collected and made available to the scientific community.
ISIMIP3b
GCM-based simulations assuming fixed 2015 direct human influences for the future
The ISIMIP3b part of the third simulation round is dedicated to a quantification of climate-related risks at different levels of climate change and socio-economic conditions. The group 1 simulations refer to the pre-industrial and historical period of the CMIP6-based climate simulations. Group 2 covers all future projections assuming fixed 2015 levels of socio-economic forcing and different future projections of climate (SSP126, SSP37 and SSP585). Group3 simulations account for future changes in socio-economic drivers and are intended to be started in summer 2021.
You can find the ISIMIP3a protocol, which is is dedicated to impact model evaluation and improvement and detection and attribution of observed impacts, here.
Simulation protocol
In this protocol we describe the scenarios & experiments in ISIMIP3b 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
| Scenario specifier | Description |
|---|---|
| picontrol | Pre-industrial climate as simulated by the GCMs. |
| historical | Historical climate as simulated by the GCMs. |
| ssp126 | SSP1-RCP2.6 climate as simulated by the GCMs. |
| ssp370 | SSP3-RCP7 climate as simulated by the GCMs. |
| ssp585 | SSP5-RCP8.5 climate as simulated by the GCMs. |
| Scenario specifier | Description |
|---|---|
| 1850soc |
Fixed year-1850 direct human influences (e.g. land use, nitrogen deposition and fertilizer input, fishing effort). Please label your simulations |
| histsoc |
Varying direct human influences in the historical period (e.g. observed changes in historical land use, nitrogen deposition and fertilizer input, fishing effort). Please label your model run |
| 2015soc |
Fixed year-2015 direct human influences (e.g. land use, nitrogen deposition and fertilizer input, fishing effort). Please label your simulations |
| nat |
No direct human influences (naturalized run). Please only label your model run |
| Scenario specifier | Description |
|---|---|
| default | For all experiments other than the sensitivity experiments. |
| 2015co2 | CO₂ concentration fixed at 2015 levels. |
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 1850co2 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
| Experiment | Short description |
Pre-industrial 1601-1849 |
Historical 1850-2014 |
Future 2015-2100 |
|---|---|---|---|---|
pre-industrial controlhistsoc 1st priority |
CF: no climate change, pre-industrial CO₂ fixed at 1850 levels |
picontrol |
picontrol |
picontrol |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
1850soc |
histsoc |
2015soc |
|
pre-industrial control2015soc 1st priority |
CF: no climate change, pre-industrial CO₂ fixed at 1850 levels | does not have to be simulated as the following year already provide a large sample of years with stable climate and constant (2015soc) / no (nat) DHF for period |
picontrol |
picontrol |
| DHF: fixed at 2015 levels for all periods |
2015soc |
2015soc |
||
pre-industrial controlnat 2nd priority |
CF: no climate change, pre-industrial CO₂ fixed at 1850 levels | does not have to be simulated as the following year already provide a large sample of years with stable climate and constant (2015soc) / no (nat) DHF for period |
picontrol |
picontrol |
| DHF: No direct human influences |
nat |
nat |
||
RCP2.6histsoc 1st priority |
CF: Simulated historical climate and CO₂ in historical period, then SSP1-RCP2.6 climate & CO₂ | "histsoc" version of the pre-industrial period of the pre-industrial control experiment |
historical |
ssp126 |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
histsoc |
2015soc |
||
RCP2.62015soc 1st priority |
CF: Simulated historical climate and CO₂ in historical period, then SSP1-RCP2.6 climate & CO₂ | "2015soc" version of the pre-industrial period of the pre-industrial control experiment |
historical |
ssp126 |
| DHF: fixed at 2015 levels for all periods |
2015soc |
2015soc |
||
RCP2.6nat 2nd priority |
CF: Simulated historical climate and CO₂ in historical period, then SSP1-RCP2.6 climate & CO₂ | "nat" version of the pre-industrial period of the pre-industrial control experiment |
historical |
ssp126 |
| DHF: No direct human influences |
nat |
nat |
||
CO₂ sensitivity RCP2.6histsoc 2nd priority |
CF: RCP2.6 climate, CO2 after 2015 fixed at 2015 levels | "histsoc" version of the pre-industrial period of the pre-industrial control experiment | "histsoc" version of the historical period of the RCP2.6 experiment, as described above |
ssp126 Sensitivity scenario: 2015co2 |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
2015soc |
|||
RCP7histsoc 1st priority |
CF: SSP3-RCP7 climate & CO₂ | "histsoc" version of pre-industrial of pre-industrial control experiment runs | "histsoc" version of the historical period of the RCP2.6 experiment |
ssp370 |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
2015soc |
|||
RCP72015soc 1st priority |
CF: SSP3-RCP7 climate & CO₂ | "2015soc" version of pre-industrial of pre-industrial control experiment runs | "2015soc" version of the historical period of the RCP2.6 experiment |
ssp370 |
| DHF: fixed at 2015 levels for all periods |
2015soc |
|||
RCP7nat 2nd priority |
CF: SSP3-RCP7 climate & CO₂ | "nat" version of pre-industrial of pre-industrial control experiment runs | "nat" version of the historical period of the RCP2.6 experiment |
ssp370 |
| DHF: No direct human influences |
nat |
|||
CO₂ sensitivity RCP7histsoc 2nd priority |
CF: RCP7 climate, CO2 after 2015 fixed at 2015 levels | "histsoc" version of the pre-industrial period of the pre-industrial control experiment | "histsoc" version of the historical period of the RCP7 experiment, as described above |
ssp370 Sensitivity scenario: 2015co2 |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
2015soc |
|||
RCP8.5histsoc 1st priority |
CF: SSP5-RCP8.5 climate & CO₂ | "histsoc" version of pre-industrial of pre-industrial control experiment runs | "histsoc" version of the historical period of the RCP2.6 experiment |
ssp585 |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
2015soc |
|||
RCP8.52015soc 1st priority |
CF: SSP5-RCP8.5 climate & CO₂ | "2015soc" version of pre-industrial of pre-industrial control experiment runs | "2015soc" version of the historical period of the RCP2.6 experiment |
ssp585 |
| DHF: fixed at 2015 levels for all periods |
2015soc |
|||
RCP8.5nat 2nd priority |
CF: SSP5-RCP8.5 climate & CO₂ | "nat" version of pre-industrial of pre-industrial control experiment runs | "nat" version of the historical period of the RCP2.6 experiment |
ssp585 |
| DHF: No direct human influences |
nat |
|||
CO₂ sensitivity RCP8.5histsoc 1st priority |
CF: Historical climate and CO₂ forcing up to 2015, fixed 2015 CO₂ afterwards | "histsoc" version of the pre-industrial period of the pre-industrial control experiment | "histsoc" version of the historical period of the RCP2.6 experiment |
ssp585 Sensitivity scenario: 2015co2 |
| DHF: varying management before 2015, then fixed at 2015 levels thereafter |
2015soc |
|||
CO₂ sensitivity RCP8.52015soc 1st priority |
CF: Historical climate and CO₂ forcing up to 2015, fixed 2015 CO₂ afterwards | "2015soc" version of the pre-industrial period of the pre-industrial control experiment | "2015soc" version of the historical period of the RCP2.6 experiment |
ssp585 Sensitivity scenario: 2015co2 |
| DHF: fixed direct human forcing at 2015 levels for the entire simulation period |
2015soc |
|||
CO₂ sensitivity RCP8.5nat 1st priority |
CF: Historical climate and CO₂ forcing up to 2015, fixed 2015 CO₂ afterwards | "nat" version of the pre-industrial period of the pre-industrial control experiment | "nat" version of the historical period of the RCP2.6 experiment |
ssp585 Sensitivity scenario: 2015co2 |
| DHF: No direct human influences |
nat |
Note regarding models requiring spin-up
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.
Input data
The base directory for input data at DKRZ is:
/work/bb0820/ISIMIP/ISIMIP3b/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
The climate forcing input files can be found on DKRZ using the following pattern:
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
| Title | Specifier | Institution | Native resolution | Ensemble member | Priority |
|---|---|---|---|---|---|
| GFDL-ESM4 | gfdl-esm4 | National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA |
Atmosphere: 288x180 Ocean: 720x576 |
r1i1p1f1 | 1 |
| UKESM1-0-LL | ukesm1-0-ll | Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK |
Atmosphere: 192x144 Ocean: 360x330 |
r1i1p1f2 | 2 |
| MPI-ESM1-2-HR | mpi-esm1-2-hr | Max Planck Institute for Meteorology, Hamburg 20146, Germany |
Atmosphere: 384x192 Ocean: 802x404 |
r1i1p1f1 | 3 |
| IPSL-CM6A-LR | ipsl-cm6a-lr | Institut Pierre Simon Laplace, Paris 75252, France |
Atmosphere: 144x143 Ocean: 362x332 |
r1i1p1f1 | 4 |
| MRI-ESM2-0 | mri-esm2-0 | Meteorological Research Institute, Tsukuba, Ibaraki 305-0052, Japan |
Atmosphere: 320x160 |
r1i1p1f1 | 5 |
Note on climate forcing priority
The priority for the different climate forcing datasets is from top to bottom. If you cannot use all climate forcing datasets, please concentrate on those at the top of the table.
| Variable | Variable specifier | Unit | Resolution | Models | ||
|---|---|---|---|---|---|---|
| Atmospheric variables mandatory | ||||||
| Near-Surface Relative Humidity | hurs | % |
|
|
||
| Near-Surface Specific Humidity | huss | kg kg-1 |
|
|
||
| Precipitation | pr | kg m-2 s-1 |
|
|
||
| Snowfall Flux | prsn | kg m-2 s-1 |
|
|
||
| Surface Air Pressure | ps | Pa |
|
|
||
| Surface Downwelling Longwave Radiation | rlds | W m-2 |
|
|
||
| Surface Downwelling Shortwave Radiation | rsds | W m-2 |
|
|
||
| Near-Surface Wind Speed | sfcwind | m s-1 |
|
|
||
| Near-Surface Air Temperature | tas | K |
|
|
||
| Daily Maximum Near-Surface Air Temperature | tasmax | K |
|
|
||
| Daily Minimum Near-Surface Air Temperature | tasmin | K |
|
|
||
| Ocean variables mandatory | ||||||
| Mass Concentration of Total Phytoplankton Expressed as Chlorophyll | chl | kg m-3 |
|
|
||
| Sea Floor Depth | deptho | m |
|
|
||
| Downward Flux of Particulate Organic Carbon | expc-bot | mol m-2 s-1 |
|
|
||
| Particulate Organic Carbon Content | intpoc | kg m-2 |
|
|
||
| Primary Organic Carbon Production by All Types of Phytoplankton | intpp | mol m-2 s-1 |
|
|
||
| Net Primary Organic Carbon Production by Diatoms | intppdiat | mol m-2 s-1 |
|
|
||
| Net Primary Mole Productivity of Carbon by Diazotrophs | intppdiaz | mol m-2 s-1 |
|
|
||
| Maximum Ocean Mixed Layer Thickness Defined by Sigma T | mlotstmax | m |
|
|
||
| Dissolved Oxygen Concentration | o2, o2-bot, o2-surf | mol m-3 |
|
|
||
| pH | ph, ph-bot, ph-surf | 1 |
|
|
||
| Phytoplankton Carbon Concentration | phyc, phyc-vint | mol m-3 |
|
|
||
| Mole Concentration of Diatoms expressed as Carbon in sea water | phydiat, phydiat-vint | mol m-3 |
|
|
||
| Mole Concentration of Diazotrophs Expressed as Carbon in Sea Water | phydiaz, phydiaz-vint | mol m-3 |
|
|
||
| Primary Carbon Production by Total Phytoplankton | pp | mol m-3 s-1 |
|
|
||
| Sea Water Salinity | so, so-bot, so-surf | 0.001 |
|
|
||
| Net Downward Shortwave Radiation at Sea Water Surface | rsntds | W m-2 |
|
|
||
| Sea Ice Area Fraction | siconc | % |
|
|
||
| Sea Water Potential Temperature | thetao | °C |
|
|
||
| Ocean Model Cell Thickness | thkcello | m |
|
|
||
| Sea Water Potential Temperature at Sea Floor | tob | °C |
|
|
||
| Sea Surface Temperature | tos | °C |
|
|
||
| Sea Water X Velocity | uo | m s-1 |
|
|
||
| Sea Water Y Velocity | vo | m s-1 |
|
|
||
| Sea Water Z Velocity | wo | m s-1 |
|
|
||
| Mole Concentration of Mesozooplankton expressed as Carbon in sea water | zmeso, zmeso-vint | mol m-3 |
|
|
||
| Mole Concentration of Microzooplankton expressed as Carbon in sea water | zmicro, zmicro-vint | mol m-3 |
|
|
||
| Zooplankton Carbon Concentration | zooc, zooc-vint | mol m-3 |
|
|
||
Other climate datasets
| Variable | Variable specifier | Unit | Resolution | Datasets | ||
|---|---|---|---|---|---|---|
| Atmospheric composition mandatory | ||||||
|
Atmospheric CO2 concentration |
climate/atmosphere_composition/co2/<climate-scenario>/co2_<climate-scenario>_annual_<start_year>_<end_year>.txt
|
|||||
| co2 | ppm |
|
Meinshausen, Raper, & Wigley (2011) for 1850-2005 and 2016-2100 and Dlugokencky & Tans (2019) from 2006-2015 |
|||
| Lightning mandatory | ||||||
|
Flash Rate Monthly Climatology |
climate/lightning/lightning_fixed.nc
|
|||||
| lightning | km-2 d-1 |
|
Cecil, Daniel J. 2006. LIS/OTD 0.5 Degree High Resolution Monthly Climatology (HRMC) [indicate subset used]. Dataset available online from the NASA Global Hydrology Resource Center DAAC, Huntsville, Alabama, U.S.A., DOI: http://dx.doi.org/10.5067/LIS/LIS-OTD/DATA303 |
|||
Socioeconomic forcing
| 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
|
|||||
|
|
|
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. (2020), see also https://luh.umd.edu). For further information on the land use data refer to https://www.isimip.org/gettingstarted/input-data-bias-correction/details/82/. |
|||
|
Downscaling to 5 crops |
socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-5crops_annual_<start_year>_<end_year>.nc
|
|||||
|
|
|
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. (2020), see also https://luh.umd.edu). |
|||
|
Downscaling to 15 crops |
socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-15crops_annual_<start_year>_<end_year>.nc
|
|||||
|
|
|
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
|
|||||
|
|
|
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
|
|||||
|
|
|
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. (2020), 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
|
|||||
|
|
|
Based on the LUH2 v2h data set (see Hurtt, Chini, Sahajpal, Frolking, & et al. (2020), see also https://luh.umd.edu). For further information refer also to https://www.isimip.org/gettingstarted/input-data-bias-correction/details/28/. |
|||
| N-deposition | ||||||
|
Reduced nitrogen deposition |
socioeconomic/n-deposition/<soc_scenario>/ndep-nhx_<soc_scenario>_monthly_<start_year>_<end_year>.nc
|
|||||
|
|
|
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). For further information refer also to https://www.isimip.org/gettingstarted/input-data-bias-correction/details/24/. |
|||
|
Oxidized nitrogen deposition |
socioeconomic/n-deposition/<soc_scenario>/ndep-noy_<soc_scenario>_monthly_<start_year>_<end_year>.nc
|
|||||
|
|
|
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). For further information refer also to https://www.isimip.org/gettingstarted/input-data-bias-correction/details/24/. |
|||
| Reservoirs & dams | ||||||
|
Reservoirs & dams |
socioeconomic/reservoir_dams/reservoirs-dams_1850_2015.xls
|
|||||
|
|
|
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, data starting in 2016). 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
|
|||||
|
|
|
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 |
socioeconomic/fishing/effort_histsoc_1950_2014.csv
|
|||||
|
|
|
Data comprise the nominal effort of industrial and artisanal fleets aggregated into 6 functional groups. Source: Rousseau et al., 2019, PNAS 116 (25) 12238-12243. |
|||
|
Fish catch |
socioeconomic/fishing/catch_histsoc_1950_2014.csv
|
|||||
|
|
|
Data comprise the nominal effort of industrial and artisanal fleets aggregated into 6 functional groups. Reference for data source: Watson and Tidd, 2018, Marine Policy, 93: 171-177. |
|||
| Forest management | ||||||
|
Forest management mandatory |
http://doi.org/10.5880/PIK.2019.008 | |||||
|
|
|
Reyer et al. 2019, 2020 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
|
|||||
|
|
|
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). For further information see https://www.isimip.org/gettingstarted/input-data-bias-correction/details/83/ |
|||
| Lakes | ||||||
|
Lake area fraction |
socioeconomic/lakes/pctlake_<soc_scenario>_<start_year>_<end_year>.nc
|
|||||
|
|
|
Accounts for growing lake area fraction due to reservoir construction. 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). |
|||
|
Lake mask |
socioeconomic/lakes/lakemask_<soc_scenario>_<start_year>_<end_year>.nc
|
|||||
|
|
|
Accounts for growing lake area fraction due to reservoir construction. 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
|
|||||
|
|
|
HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2014, data are based on the 2008 Revision of the United Nations World Population Prospects, which transits from estimates to projections in 2010. 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
|
|||||
|
|
|
HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2014, data are based on the 2008 Revision of the United Nations World Population Prospects, which transits from estimates to projections in 2010. 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
|
|||||
|
|
|
HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2014, data are based on the 2008 Revision of the United Nations World Population Prospects, which transits from estimates to projections in 2010. Decadal data prior to year 1950 have been linearly interpolated in time. |
|||
|
Population density 5' grid |
socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_5arcmin_annual_<start-year>_<end-year>.nc
|
|||||
|
|
|
HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2014, data are based on the 2008 Revision of the United Nations World Population Prospects, which transits from estimates to projections in 2010. Decadal data prior to year 2000 have been linearly interpolated in time. |
|||
|
Population density 0.5° grid |
socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_30arcmin_annual_<start-year>_<end-year>.nc
|
|||||
|
|
|
HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2014, data are based on the 2008 Revision of the United Nations World Population Prospects, which transits from estimates to projections in 2010. Decadal data prior to year 2000 have been linearly interpolated in time. Aggregated to 0.5° spatial resolution |
|||
|
Population density national |
socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_national_annual_<start-year>_<end-year>.csv
|
|||||
|
|
|
HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2014, data are based on the 2008 Revision of the United Nations World Population Prospects, which transits from estimates to projections in 2010. 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
|
|||||
|
|
|
Historic country-level GDP data are an extension of the historical data provided by Geiger, 2018 (https://www.earth-syst-sci-data.net/10/847/2018/essd-10-847-2018.html). They are derived mainly from Penn World Tables (PWT) for recent decades, and from the Maddison Project database (2018 version, https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2018) for earlier periods where no PWT data is available. Gaps were filled using World Bank data (WDI). No interpolation to SSPs is performed for this historical dataset. |
|||
Static geographic information
| Dataset | Included variables (specifier) | Resolution | Reference/Source and Comments | |||
|---|---|---|---|---|---|---|
| Land/Sea masks | ||||||
|
landseamask |
geo_conditions/landseamask/landseamask.nc
|
|||||
|
0.5° grid | This is the land-sea mask of the W5E5 dataset (Cucchi et al., 2020; Lange et al., 2021). 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. For further information see also https://www.isimip.org/gettingstarted/input-data-bias-correction/details/41/. |
||||
|
landseamask_no-ant |
geo_conditions/landseamask/landseamask_no-ant.nc
|
|||||
|
0.5° grid | Same as landseamask but without Antarctica. |
||||
|
landseamask_water-global |
geo_conditions/landseamask/landseamask_water-global.nc
|
|||||
|
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
|
|||||
|
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) |
||||
|
hwsd_soil_data_all_land |
geo_conditions/soil/hwsd_soil_data_all_land.nc
|
|||||
|
0.5° grid | GGCMI Phase 3 soil input data set for usage in ISIMIP/GGCMI Phase 3 simulations, data aggregated by dominant soil profile (MU_GLOBAL) within dominant soil texture class from HWSD on all land. |
||||
|
hwsd_soil_data_on_cropland |
geo_conditions/soil/hwsd_soil_data_on_cropland.nc
|
|||||
|
0.5° grid | GGCMI Phase 3 soil input data set for usage in ISIMIP/GGCMI Phase 3 simulations, data aggregated by dominant soil profile (MU_GLOBAL) within dominant soil texture class from HWSD on current cropland (MIRCA2000 at 5 arc-minutes). |
||||
| River routing | ||||||
|
basins |
geo_conditions/river_routing/ddm30_basins_cru_neva.[nc|asc]
|
|||||
|
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]
|
|||||
|
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]
|
|||||
|
0.5° grid | DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files. |
||||
| Lakes | ||||||
|
lakedepth |
geo_conditions/lakes/lakedepth.nc
|
|||||
|
0.5° grid | |||||
Output data
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.
Please note that unless otherwise defined, the variables in ISIMIP should be reported relative to the grid cell land area.
Output variables
| Variable long name | Variable specifier | Unit | Resolution | Comments | ||
|---|---|---|---|---|---|---|
| Full ISIMIP variable list | ||||||
| Total Runoff | qtot | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost, water_global, water_regional. Total (surface + subsurface) runoff (qtot = qs + qsb). Please provide both daily and monthly resolution. |
||
| Surface Runoff | qs | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost, water_global, water_regional. Water that leaves the surface layer (top soil layer) e.g. as overland flow / fast runoff. |
||
| Subsurface Runoff | qsb | kg m-2 s-1 |
|
Sectors: water_global. 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 |
|
Sectors: water_global, water_regional. 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 |
|
Sectors: water_global. 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 |
|
Sectors: water_global, water_regional. River discharge or streamflow. Please provide both daily and monthly resolution. |
||
| Evapotranspiration |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry, water_global, water_regional. Sum of transpiration, evaporation, interception and sublimation. |
||
| Potential Evapotranspiration | potevap | kg m-2 s-1 |
|
Sectors: water_global, water_regional. As evap, but with all resistances set to zero, except the aerodynamic resistance. |
||
| Total Soil Moisture Content | soilmoist | kg m-2 |
|
Sectors: agriculture, biomes, fire, forestry, permafrost, water_global, water_regional. Level dimensions: (time, depth, lat, lon). 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 Content at Root Zone | rootmoist | kg m-2 |
|
Sectors: water_global, water_regional. Level dimensions: (time, depth, lat, lon). 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 Content | soilmoistfroz | kg m-2 |
|
Sectors: biomes, fire, permafrost, water_global. Level dimensions: (time, depth, lat, lon). Please provide soil moisture for all depth levels and indicate depth in m. |
||
| Temperature of Soil | tsl | K |
|
Sectors: biomes, fire, forestry, permafrost, water_global. Level dimensions: (time, depth, lat, lon). 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 |
|
Sectors: biomes, fire, permafrost, water_global. Grid cell mean depth of snowpack. This variable only for the purposes of the permafrost sector. |
||
| Snow Water Equivalent | swe | kg m-2 |
|
Sectors: biomes, fire, permafrost, water_global, water_regional. 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 |
|
Sectors: water_global. 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 |
|
Sectors: water_global. Mean monthly water storage in the canopy. |
||
| Glacier Water Storage | glacierstor | kg m-2 |
|
Sectors: water_global. Mean monthly water storage in glaciers. |
||
| Groundwater Storage | groundwstor | kg m-2 |
|
Sectors: water_global. Mean monthly water storage in groundwater layer. |
||
| Lake Water Storage | lakestor | kg m-2 |
|
Sectors: water_global. Mean monthly water storage in lakes (except reservoirs). |
||
| Wetland Water Storage | wetlandstor | kg m-2 |
|
Sectors: water_global. Mean monthly water storage in wetlands. |
||
| River Water Storage | riverstor | kg m-2 |
|
Sectors: water_global. Mean monthly water storage in rivers. |
||
| Reservoir Water Storage | reservoirstor | kg m-2 |
|
Sectors: water_global. Mean monthly water storage in reservoirs. |
||
| Annual Maximum Thaw Depth | thawdepth | m |
|
Sectors: biomes, fire, permafrost, water_global. Calculated from daily thaw depths. |
||
| River Water Temperature | triver | K |
|
Sectors: water_global. Mean monthly water temperature in river (representative of the average temperature across the channel volume). |
||
| Potential Irrigation Water Withdrawal (assuming unlimited water supply) | pirrww | kg m-2 s-1 |
|
Sectors: water_global, water_regional. Irrigation water withdrawn in case of optimal irrigation (i.e. eliminating water stress for the plants). This includes the plant's water requirements over and above precipitation and soil moisture, as well as any losses due to conveyance or irrigation inefficiencies considered. |
||
| Actual Irrigation Water Withdrawal | airrww | kg m-2 s-1 |
|
Sectors: water_global, water_regional. Irrigation water withdrawal, taking water availability into account; please provide if computed. |
||
| Potential Irrigation Water Consumption | pirruse | kg m-2 s-1 |
|
Sectors: water_global, water_regional. Portion of withdrawal that is evapo-transpired, assuming unlimited water supply. |
||
| Cumulative Potential Net Irrigation Water Requirement | pirnreqcum-<crop>-<irrigation> | kg m-2 |
|
Sectors: agriculture, biomes, water_global. Soil water demand required to avoid water stress accumulated across the growing season, excluding any water losses associated with application or transport and without constraints due to water availability; only needed for |
||
| Actual Irrigation Water Consumption | airruse | kg m-2 s-1 |
|
Sectors: water_global, water_regional. Portion of withdrawal that is evapo-transpired, taking water availability into account; if computed. |
||
| Actual Irrigation Green Water Consumption on Irrigated Cropland | airrusegreen | kg m-2 s-1 |
|
Sectors: water_global, water_regional. Actual evapotranspiration from rainwater over irrigated cropland; if computed. |
||
| Potential Irrigation Green Water Consumption on Irrigated Cropland | pirrusegreen | kg m-2 s-1 |
|
Sectors: water_global, water_regional. 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 |
|
Sectors: water_global, water_regional. Actual evapotranspiration from rainwater over rainfed cropland; if computed. |
||
| Actual Domestic Water Withdrawal | adomww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual Domestic Water Consumption | adomuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual Manufacturing Water Withdrawal | amanww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual Manufacturing Water Consumption | amanuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual Electricity Water Withdrawal | aelecww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual Electricity Water Consumption | aelecuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual Livestock Water Withdrawal | aliveww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Actual livestock Water Consumption | aliveuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential Domestic Water Withdrawal | pdomww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential Domestic Water Consumption | pdomuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential Manufacturing Water Withdrawal | pmanww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential manufacturing Water Consumption | pmanuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential electricity Water Withdrawal | pelecww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential electricity Water Consumption | pelecuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential livestock Water Withdrawal | pliveww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Potential livestock Water Consumption | pliveuse | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Total Actual Water Withdrawal (all sectors) | atotww | kg m-2 s-1 |
|
Sectors: water_global. If computed. |
||
| Total Actual Water Consumption (all sectors) | atotuse | kg m-2 s-1 |
|
Sectors: water_global. Sum of actual consumptive water use from all sectors. Please indicate in metadata which sectors are included. |
||
| Total Potential Water Withdrawal (all sectors) | ptotww | kg m-2 s-1 |
|
Sectors: water_global. Sum of potential (i.e. assuming unlimited water supply) water withdrawal from all sectors. Please indicate in metadata which sectors are included. |
||
| Total Potential Water Consumption (all sectors) | ptotuse | kg m-2 s-1 |
|
Sectors: water_global. Sum of potential (i.e. assuming unlimited water supply) consumptive water use from all sectors. Please indicate in metadata which sectors are included. |
||
| Actual Industrial Water Consumption | ainduse | kg m-2 s-1 |
|
Sectors: water_global. If computed. There is no need to submit ainduse if its components are being submitted separately (ainduse = amanuse + aelecuse). |
||
| Actual Industrial Water Withdrawal | aindww | kg m-2 s-1 |
|
Sectors: water_global. If computed. There is no need to submit aindww if its components are being submitted separately (aindww = amanww + aelecww). |
||
| Potential Industrial Water Consumption | pinduse | kg m-2 s-1 |
|
Sectors: water_global. If computed. There is no need to submit pinduse if its components are being submitted separately (pinduse = pmanuse + pelecuse). |
||
| Potential Industrial Water Withdrawal | pindww | kg m-2 s-1 |
|
Sectors: water_global. If computed. There is no need to submit pindww if its components are being submitted separately (pindww = pmanww + pelecww). |
||
| Potential Irrigation Water Withdrawal (assuming unlimited water supply) from groundwater resources | pirrwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of pirrww that is extracted from groundwater resources. |
||
| actual irrigation water withdrawal from groundwater resources | airwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of airww that is extracted from groundwater resources. |
||
| Potential Irrigation Water Consumption from groundwater resources | pirrusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of pirruse that is extracted from groundwater resources. |
||
| Actual Irrigation Water Consumption from groundwater resources | airrusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of airruse that is extracted from groundwater resources. |
||
| Potential Domestic Water Withdrawal from groundwater resources | pdomwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of pdomww that is extracted from groundwater resources. |
||
| Actual Domestic Water Withdrawal from groundwater resources | adomwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of adomww that is extracted from groundwater resources. |
||
| Potential Domestic Water Consumption from groundwater resources | pdomusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of pdomuse that is extracted from groundwater resources. |
||
| Actual Domestic Water Consumption from groundwater resources | adomusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of adomuse that is extracted from groundwater resources. |
||
| Potential Manufacturing Water Withdrawal from groundwater resources | pmanwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of pmanww that is extracted from groundwater resources. |
||
| Actual Manufacturing Water Withdrawal from groundwater resources | amanwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of amanww that is extracted from groundwater resources. |
||
| Potential manufacturing Water Consumption from groundwater resources | pmanusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of pmanuse that is extracted from groundwater resources. |
||
| Actual Manufacturing Water Consumption from groundwater resources | amanusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of amanuse that is extracted from groundwater resources. |
||
| Potential electricity Water Withdrawal from groundwater resources | pelecwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of pelecww that is extracted from groundwater resources. |
||
| Actual Electricity Water Withdrawal from groundwater resources | aelecwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of aelecww that is extracted from groundwater resources. |
||
| Potential electricity Water Consumption from groundwater resources | pelecusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of pelecuse that is extracted from groundwater resources. |
||
| Actual Electricity Water Consumption from groundwater resources | aelecusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of aelecuse that is extracted from groundwater resources. |
||
| Potential Industrial Water Withdrawal from groundwater resources | pindwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of pindww that is extracted from groundwater resources. |
||
| Actual Industrial Water Withdrawal from groundwater resources | aindwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of aindww that is extracted from groundwater resources. |
||
| Potential Industrial Water Consumption from groundwater resources | pindusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of pinduse that is extracted from groundwater resources. |
||
| Actual Industrial Water Consumption from groundwater resources | aindusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of ainduse that is extracted from groundwater resources. |
||
| Potential livestock Water Withdrawal from groundwater resources | plivwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of plivww that is extracted from groundwater resources. |
||
| Actual Livestock Water Withdrawal from groundwater resources | alivwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of alivww that is extracted from groundwater resources. |
||
| Potential livestock Water Consumption from groundwater resources | plivusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of plivuse that is extracted from groundwater resources. |
||
| Actual livestock Water Consumption from groundwater resources | alivusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of alivuse that is extracted from groundwater resources. |
||
| Total Potential Water Withdrawal (all sectors) from groundwater resources | ptotwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of ptotww that is extracted from groundwater resources. |
||
| Total Actual Water Withdrawal (all sectors) from groundwater resources | atotwwgw | kg m-2 s-1 |
|
Sectors: water_global. Part of atotww that is extracted from groundwater resources. |
||
| Total Potential Water Consumption (all sectors) from groundwater resources | ptotusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of ptotuse that is extracted from groundwater resources. |
||
| Total Actual Water Consumption (all sectors) from groundwater resources | atotusegw | kg m-2 s-1 |
|
Sectors: water_global. Part of atotuse that is extracted from groundwater resources. |
||
| Soil Types | soil | - |
|
Sectors: biomes, forestry, water_global. 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) |
|
Sectors: agriculture, biomes, water_global. Yield may be identical to above-ground biomass (biom) if the entire plant is harvested, e.g. for bioenergy production. Yields are reported per growing seasons and not per year. |
||
| Cumulative Evapotranspiration | evapcum-<crop>-<irrigation> | kg m-2 |
|
Sectors: agriculture, biomes, water_global. Evapotranspiration = sum of transpiration, evaporation, interception and sublimation aggregated across the growing season. |
||
| Cumulative Nitrogen Application | initrcum-<crop>-<irrigation> | kg ha-1 |
|
Sectors: agriculture, biomes, water_global. Integral of the total nitrogen application rate over the growing season. If organic and inorganic amendments are applied, the nitrogen application should be reported as effective inorganic nitrogen input (ignoring residues). |
||
| Planting Date | plantday-<crop>-<irrigation> | day of year |
|
Sectors: agriculture, biomes, water_global. As Julian dates. The planting date reported here corresponds to the actual planting date in the simulation and may diverge from the planting calendar used for harmonization. |
||
| Planting Year | plantyear-<crop>-<irrigation> | calendar year |
|
Sectors: agriculture, biomes, water_global. |
||
| Anthesis Date | anthday-<crop>-<irrigation> | days from planting |
|
Sectors: agriculture, biomes, water_global. Together with the day and year of planting it allows for clear identification of anthesis. |
||
| Maturity Date | matyday-<crop>-<irrigation> | days from planting |
|
Sectors: agriculture, biomes, water_global. Together with the day and year of planting it allows for clear identification of maturity. |
||
| Harvest Year | harvyear-<crop>-<irrigation> | calendar year |
|
Sectors: agriculture, biomes, water_global. Usually the year when maturity is reached. Can also be computed from planting and maturuty day. |
||
| Total Above Ground Biomass Dry Matter Yields | biom-<crop>-<irrigation> | t ha-1 |
|
Sectors: agriculture, biomes, water_global. The whole plant biomass above ground. |
||
| Cumulative Nitrogen Uptake | nupcum-<crop>-<irrigation> | kg ha-1 |
|
Sectors: agriculture, biomes, water_global. Nitrogen balance: Uptake (growing season sum) |
||
| Cumulative Nitrogen Inputs | nincum-<crop>-<irrigation> | kg ha-1 |
|
Sectors: agriculture, biomes, water_global. Nitrogen balance: Inputs (growing season sum) |
||
| Cumulative Nitrogen Losses | nlosscum-<crop>-<irrigation> | kg ha-1 |
|
Sectors: agriculture, biomes, water_global. Nitrogen balance: Losses (growing season sum) |
||
| Cumulative Nitrogen Leached | leachcum-<crop>-<irrigation> | kg ha-1 |
|
Sectors: agriculture, biomes, water_global. Nitrogen balance: Leaching (growing season sum) |
||
| Amphibian Species Probability of Occurrence | amphibianprob | Probability of occurrence per cell |
|
Sectors: biodiversity. Results from individual SDMs assuming no dispersal. |
||
| Terrestrial Bird Species Probability of Occurrence | birdprob | Probability of occurrence per cell |
|
Sectors: biodiversity. Results from individual SDMs assuming no dispersal. |
||
| Terrestrial Mammal Species Probability of Occurrence | mammalprob | Probability of occurrence per cell |
|
Sectors: biodiversity. Results from individual SDMs assuming no dispersal. |
||
| Amphibian Summed Probability of Occurrence | amphibiansumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Terrestrial Bird Summed Probability of Occurrence | birdsumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Terrestrial Mammal Summed Probability of Occurrence | mammalsumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Summed Probability of Endemic Amphibian Species | endamphibiansumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Summed Probability of Endemic Terrestrial Bird Species | endbirdsumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Summed Probability of Endemic Terrestrial Mammal Species | endmammalsumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Summed Probability of Threatened Amphibian Species | thramphibiansumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Summed Probability of Threatened Terrestrial Bird Species | thrbirdsumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Summed Probability of Threatened Terrestrial Mammal Species | thrmammalsumprob | Summed probability of occurrence per cell |
|
Sectors: biodiversity. Aggregated results from individual SDMs assuming no dispersal. |
||
| Amphibian Species Richness | amphibiansr | Estimated number of species (species richness) per cell |
|
Sectors: biodiversity. Results from macroecological richness models |
||
| Terrestrial Bird Species Richness | birdsr | Estimated number of species (species richness) per cell |
|
Sectors: biodiversity. Results from macroecological richness models |
||
| Terrestrial Mammal Species Richness | mammalsr | Estimated number of species (species richness) per cell |
|
Sectors: biodiversity. Results from macroecological richness models |
||
| Carbon Mass in Vegetation |
|
kg m-2 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Grid cell total and PFT information is essential. fire: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻². Stand total and PFT information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass in Above Ground Vegetation Biomass |
|
kg m-2 |
|
Sectors: biomes, forestry, permafrost. biomes: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻²Stand total and PFT information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass in Below Ground Vegetation Biomass |
|
kg m-2 |
|
Sectors: biomes, forestry, permafrost. biomes: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻². Stand total and PFT information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass in Above Ground Litter Pool |
|
kg m-2 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Grid cell total and PFT information is essential. fire: Grid cell total and PFT information is essential. forestry: Species information is essential. Stand total and PFT information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass in Below Ground Litter Pool |
|
kg m-2 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Only if models separates below-ground litter and soil carbon. If not, only report csoil and document this in the model documentation. Grid cell total and PFT information is essential. fire: Only if models separates below-ground litter and soil carbon. If not, only report csoil and document this in the model documentation. Grid cell total and PFT information is essential. forestry: Only if models separates below-ground litter and soil carbon. Species information is essential. permafrost: Only if models separates below-ground litter and soil carbon. If not, only report csoil and document this in the model documentation. Grid cell total and PFT information is essential. |
||
| Carbon Mass in Soil Pool |
|
kg m-2 |
|
Sectors: biomes, fire, forestry, permafrost. Level dimensions: (time, depth, lat, lon). biomes: Soil carbon excluding belowground litter if your model reports clitter. If not including below-ground litter, i.e. only report csoil and document this in the model documentation. 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. fire: Soil carbon excluding belowground litter if your model reports clitter. If not including below-ground litter, i.e. only report csoil and document this in the model documentation. 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: Soil carbon excluding belowground litter if your model reports clitter. If not including below-ground litter, i.e. only report csoil and document this in the model documentation. Grid cell total and species 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. permafrost: Soil carbon excluding belowground litter if your model reports clitter. If not including below-ground litter, i.e. only report csoil and document this in the model documentation. 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. |
||
| Carbon in Products of Land Use Change |
|
kg m-2 |
|
Sectors: biomes, fire, forestry. biomes: Products generated during Land-use change. Removed carbon should not go into the soil but into the product pool. Please use the product classes used within your model and document them in the model documentation on the ISIMIP homepage. fire: Products generated during Land-use change. Removed carbon should not go into the soil but into the product pool. Please use the product classes used within your model and document them in the model documentation on the ISIMIP homepage. forestry: Products generated during Land-use change. Removed carbon should not go into the soil but into the product pool. Please use the product classes used within your model and document them in the model documentation on the ISIMIP homepage. |
||
| Carbon Mass Flux out of Atmosphere due to Gross Primary Production on Land |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Grid cell total and PFT information is essential. fire: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻² s⁻¹. Stand total and Species information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass Flux into Atmosphere due to Autotrophic (plant) Respiration on Land |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Grid cell total and PFT information is essential. fire: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻² s⁻¹. Stand total and species information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass Flux out of Atmosphere due to Net Primary Production on Land |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Grid cell total and PFT information is essential. fire: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻² s⁻¹. Stand total and species information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass Flux into Atmosphere due to Heterotrophic Respiration on Land |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry, permafrost. biomes: Grid cell total and PFT information is essential. fire: Grid cell total and PFT information is essential. forestry: As kg carbon m⁻² s⁻¹. Stand total and Species information is essential. permafrost: Grid cell total and PFT information is essential. |
||
| Carbon Mass Flux into Atmosphere due to CO₂ Emission from Fire | ffire-total, ffire-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. |
||
| Burnt Area Fraction | burntarea-total, burntarea-<pft> | % |
|
Sectors: biomes, fire, permafrost. biomes: Area percentage of grid cell that has burned at any time of the given day/month/year (for daily/monthly/annual resolution) fire: Report <total> daily, <pft/total> monthly permafrost: 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 | nbp-total, nbp-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. 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-total, rr-<pft> | kg m-2 s-1 |
|
Sectors: biomes, forestry. biomes: forestry: As kg carbon*m-2*s-1 |
||
| CO2 Flux to Atmosphere from Land Use Change | fluc-total, fluc-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. For wood products only. Sum of CO₂ fluxes to wood production and wood storage turnover emsissions from previous years. |
||
| CO2 Flux to Atmosphere from Grazing | fgrazing-total, fgrazing-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. Grid cell total and PFT information is essential. |
||
| CO2 Flux to Atmosphere from Crop Harvesting | fcropharvest-total, fcropharvest-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. Grid cell total and PFT information is essential. |
||
| Total Carbon Flux from Vegetation to Litter | flitter-total, flitter-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. Grid cell total and PFT information is essential. |
||
| Total Carbon Flux from Litter to Soil | flittersoil-total, flittersoil-<pft> | kg m-2 s-1 |
|
Sectors: biomes, permafrost. Grid cell total and PFT information is essential. |
||
| Total Carbon Flux from Vegetation Directly to Soil | fvegsoil-total, fvegsoil-<pft> | kg m-2 s-1 |
|
Sectors: biomes, fire, permafrost. Carbon going directly into the soil pool without entering litter (e.g., root exudate). Grid cell total and PFT information is essential. |
||
| Fraction of Absorbed Photosynthetically Active Radiation |
|
% |
|
Sectors: biomes, fire, forestry, permafrost. Value between 0 and 100. Grid cell total and PFT information is essential. |
||
| Leaf Area Index |
|
1 |
|
Sectors: biomes, fire, forestry, permafrost, water_global. biomes: Grid cell total and PFT information is essential. If lai is static, the timestep specifier "fixed" can used. fire: Grid cell total and PFT information is essential. If lai is static, the timestep specifier "fixed" can used. forestry: Stand total and species information is essential. If lai is static, the timestep specifier "fixed" can used. permafrost: Grid cell total and PFT information is essential. If lai is static, the timestep specifier "fixed" can used. water_global: If used by, or computed by the model. If lai is static, the timestep specifier "fixed" can used. |
||
| Plant Functional Type Grid Fraction | pft-total, pft-<pft> | % |
|
Sectors: biomes, fire, permafrost. 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. For models that have grid cells partially covered by land and ocean, please document this in the model documentation and provide your land-sea mask along the data uploads. |
||
| Evaporation from Canopy (interception) |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry. The canopy evaporation+sublimation (if present in model). |
||
| Water Evaporation from Soil |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry. Includes sublimation. |
||
| Transpiration |
|
kg m-2 s-1 |
|
Sectors: biomes, fire, forestry. |
||
| Carbon Mass in Leaves |
|
kg m-2 |
|
Sectors: biomes, forestry, permafrost. |
||
| Carbon Mass in Wood |
|
kg m-2 |
|
Sectors: biomes, forestry, permafrost. Including sapwood and hardwood. |
||
| Carbon Mass in Roots |
|
kg m-2 |
|
Sectors: biomes, forestry, permafrost. Including fine and coarse roots. |
||
| Carbon Mass in Coarse Woody Debris |
|
kg m-2 |
|
Sectors: biomes, forestry, permafrost. |
||
| Mean DBH | dbh-total, dbh-<species> | cm |
|
Sectors: forestry. |
||
| Mean DBH of 100 Highest Trees | dbhdomhei | cm |
|
Sectors: forestry. 100 highest trees per hectare. |
||
| Stand Height | hei-total, hei-<species> | m ha-1 |
|
Sectors: forestry. For models including natural regeneration this variable may not make sense, please report domhei. |
||
| Dominant Height | domhei | m2 ha-1 |
|
Sectors: forestry. Mean height of the 100 highest trees per hectare. |
||
| Stand Density | density-total, density-<species> | m2 ha-1 |
|
Sectors: forestry. |
||
| Basal Area | ba-total, ba-<species> | m2 ha-1 |
|
Sectors: forestry. |
||
| Volume of Dead Trees | mort-total, mort-<species> | m3 ha-1 |
|
Sectors: forestry. |
||
| Harvest by DBH-Class | harv-total, harv-<species> | m3 ha-1 |
|
Sectors: forestry. Level dimensions: (time, dbhclass, lat, lon). DBH class resolution: Either DBH classes or total per species |
||
| Remaining Stem Number after Disturbance and Management by DBH-Class | stemno-total, stemno-<species> | ha-1 |
|
Sectors: forestry. Level dimensions: (time, dbhclass, lat, lon). DBH-Class Resolution: Either DBH-Classes or Total per Species |
||
| Stand Volume | vol-total, vol-<species> | m3 ha-1 |
|
Sectors: forestry. |
||
| Tree Age by DBH-Class | age-total, age-<species> | yr |
|
Sectors: forestry. Level dimensions: (time, dbhclass, lat, lon). DBH class resolution: Either DBH classes or total per species |
||
| Net Ecosystem Exchange | nee-total, nee-<species> | kg m-2 s-1 |
|
Sectors: forestry. As kg carbon m⁻² s⁻¹ |
||
| Mean Annual Increment | mai-total, mai-<species> | m3 ha-1 |
|
Sectors: forestry. |
||
| Species Composition | species-total, species-<species> | % |
|
Sectors: forestry. |
||
| Removed Stem Numbers by DBH-Class by Natural Mortality | mortstemno-total, mortstemno-<species> | ha-1 |
|
Sectors: forestry. Level dimensions: (time, dbhclass, lat, lon). As trees per hectare. DBH class resolution: Either DBH classes or total per species |
||
| Removed Stem Numbers by DBH-Class by Management | harvstemno-total, harvstemno-<species> | ha-1 |
|
Sectors: forestry. Level dimensions: (time, dbhclass, lat, lon). 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 |
|
Sectors: forestry. |
||
| Nitrogen of Annual Litter | nlit-total, nlit-<species> | g m-2 a-1 |
|
Sectors: forestry. As g Nitrogen m-2 a-1 |
||
| Nitrogen in Soil | nsoil | g m-2 a-1 |
|
Sectors: forestry. As g Nitrogen m-2 a-1 |
||
| Thermal Stratification | strat | 1 |
|
Sectors: lakes_global, lakes_local. 1 if lake grid cell is thermally stratified, 0 if lake grid cell is not thermally stratified |
||
| Depth of Thermocline | thermodepth | m |
|
Sectors: lakes_global, lakes_local. Depth corresponding the maximum water density gradient |
||
| Temperature of Lake Water | watertemp | K |
|
Sectors: lakes_global, lakes_local. Depth resolution: Full Profile. Simulated water temperature. Layer averages and full profiles. |
||
| Temperature of Lake Surface Water | surftemp | K |
|
Sectors: lakes_global, lakes_local. Average of the upper layer in case not simulated directly. |
||
| Temperature of Lake Bottom Water | bottemp | K |
|
Sectors: lakes_global, lakes_local. Average of the lowest layer in case not simulated directly. |
||
| Lake Ice Cover | ice | 1 |
|
Sectors: lakes_global, lakes_local. 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 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Mean epi. Fraction of mass of a given layer taken up by ice. |
||
| Ice Thickness | icethick | m |
|
Sectors: lakes_global, lakes_local. |
||
| Snow Thickness | snowthick | m |
|
Sectors: lakes_global, lakes_local. |
||
| Ice Temperature at Upper Surface | icetemp | K |
|
Sectors: lakes_global, lakes_local. |
||
| Snow Temperature at Upper Surface | snowtemp | K |
|
Sectors: lakes_global, lakes_local. |
||
| Sensible Heat Flux at Lake-Atmosphere Interface |
|
W m-2 |
|
Sectors: fire, lakes_global, lakes_local. At the surface of the layer in contact with the atmosphere. Positive if upwards. |
||
| Latent Heat Flux at Lake-Atmosphere Interface | latentheatf | W m-2 |
|
Sectors: lakes_global, lakes_local. At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. |
||
| Momentum Flux at Lake-Atmosphere Interface | momf | kg m-1 s-2 |
|
Sectors: lakes_global, lakes_local. At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. |
||
| Upward Short-Wave Radiation Flux at Lake-Atmosphere Interface | swup | W m-2 |
|
Sectors: lakes_global, lakes_local. 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 Long-Wave Radiation Flux at Lake-Atmosphere Interface | lwup | W m-2 |
|
Sectors: lakes_global, lakes_local. 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 Lake-Atmosphere Interface | lakeheatf | W m-2 |
|
Sectors: lakes_global, lakes_local. 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 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. Only if computed by the model. |
||
| Surface Albedo of Lake | lakealbedo | 1 |
|
Sectors: lakes_global, lakes_local. Albedo of the lake surface interacting with the atmosphere (water, ice or snow). |
||
| Surface Albedo of Land | landalbedo | 1 |
|
Sectors: biomes, fire, permafrost. Albedo of the land surface interacting with the atmosphere. Average of pfts, snow cover, bare ground. |
||
| Light Extinction Coefficient | extcoeff | m-1 |
|
Sectors: lakes_global, lakes_local. Only to be reported for global models, local models should use extcoeff as input. |
||
| Sediment Upward Heat Flux at Lake-Sediment Interface | sedheatf | W m-2 |
|
Sectors: lakes_global, lakes_local. Positive if upwards. Only if computed by the model. |
||
| Chlorophyll Concentration | chl | g-3 m-3 |
|
Sectors: lakes_global, lakes_local. 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 |
|
Sectors: lakes_global, lakes_local. 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 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. Total simulated Zooplankton biomass. |
||
| Total Phosphorus | tp | mole m-3 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. |
||
| Particulate Phosphorus | pp | mole m-3 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. |
||
| Total Dissolved Phosphorus | tpd | mole m-3 |
|
Sectors: lakes_global, lakes_local. 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 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. |
||
| Particulate Nitrogen | pn | mole m-3 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. |
||
| Total Dissolved Nitrogen | tdn | mole m-3 |
|
Sectors: lakes_global, lakes_local. 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 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. |
||
| Dissolved Organic Carbon | doc | mole m-3 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. Not always available. |
||
| Dissolved Silica | si | mole m-3 |
|
Sectors: lakes_global, lakes_local. Depth resolution: Either full profile, or mean epi and mean hypo. Not always available. |
||
| Total Consumer Biomass Density | tcb | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. All consumers (trophic level >1, vertebrates and invertebrates) |
||
| Total Consumer Biomass Density in log10 Weight Bins | tcblog10 | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Level dimensions: (time, bins, lat, lon). If the model is size-structured, please provide biomass in equal log 10 g weight bins (1-10g, 10-100g, 100g-1kg, 1-10kg, 10-100kg, >100kg) |
||
| Total Pelagic Biomass Density | tpb | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. All pelagic consumers (trophic level >1, vertebrates and invertebrates) |
||
| Biomass Density of Small Pelagics <30cm | bp30cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. If a pelagic species and L infinity is <30 cm, include in this variable |
||
| Biomass Density of Medium Pelagics >=30cm and <90cm | bp30to90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. If a pelagic species and L infinity is >=30 cm and <90cm, include in this variable |
||
| Biomass Density of Large Pelagics >=90cm | bp90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. If a pelagic species and L infinity is >=90cm, include in this variable |
||
| Total Demersal Biomass Density | tdb | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. All demersal consumers (trophic level >1, vertebrates and invertebrates) |
||
| Biomass Density of Small Demersals <30cm | bd30cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. If a demersal species and L infinity is <30 cm, include in this variable |
||
| Biomass Density of Medium Demersals >=30cm and <90cm | bd30to90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. If a demersal species and L infinity is >=30 cm and <90cm, include in this variable |
||
| Biomass Density of Large Demersals >=90cm | bd90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. If a demersal species and L infinity is >=90cm, include in this variable |
||
| Total Catch (all commercial functional groups / size classes) | tc | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea (commercial landings plus discards, fish and invertebrates) |
||
| Total Catch in log10 Weight Bins | tclog10 | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Level dimensions: (time, bins, lat, lon). If the model is size-structured, please provide biomass in equal log 10 g weight bins (1-10g, 10-100g, 100g-1kg, 1-10kg, 10-100kg, >100kg) |
||
| Total Pelagic Catch | tpc | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of all pelagic consumers (trophic level >1, vertebrates and invertebrates) |
||
| Catch Density of Small Pelagics <30cm | cp30cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of pelagic species with L infinity <30 cm |
||
| Catch Density of Medium Pelagics >=30cm and <90cm | cp30to90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of pelagic species with L infinity >=30 cm and <90 cm |
||
| Catch Density of Large Pelagics >=90cm | cp90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of pelagic species with L infinity >=90 cm |
||
| Total Demersal Catch | tdc | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of all demersal consumers (trophic level >1, vertebrates and invertebrates) |
||
| Catch Density of Small Demersals <30cm | cd30cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of demersal species with L infinity <30 cm |
||
| Catch Density of Medium Demersals >=30cm and <90cm | cd30to90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of demersal species with L infinity >=30 cm and <90 cm |
||
| Catch Density of Large Demersals >=90cm | cd90cm | g m-2 |
|
Sectors: marine-fishery_global, marine-fishery_regional. Catch at sea of demersal species with L infinity >=90 cm |
||
| Number of Deaths Attributable to Cold | ancold-<r> | 1 |
|
Sectors: health. Level dimensions: (time, location). 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 |
|
Sectors: health. Level dimensions: (time, location). Temperature above threshold (ERFs). Report 0 if temperature below threshold. Can have gender, age, etc. dimensions; see below. |
||
| Baseline Total Mortality | btm | 1 |
|
Sectors: health. Level dimensions: (time, location). 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 |
|
Sectors: health. Level dimensions: (time, location). 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. |
||
| Burnt Area Fraction from Fire Mediated Land-Cover Change | burntarealuc-total | % |
|
Sectors: fire. Deforestation fires |
||
| Carbon emitted from peat fires | ffirepeat-total | kg m-2 s-1 |
|
Sectors: fire. Should not be part of ffire |
||
| Carbon Mass Flux into Atmosphere from Fire Mediated Land-Cover Change | ffireluc-total | kg m-2 s-1 |
|
Sectors: fire. C emitted from deforestation fires (if simulated). |
||
| Weighted Mean Fireline Intensity | fireints-total | kW m-1 |
|
Sectors: fire. If calculated, weighted by burned area. Grid cell total and PFT information is essential. |
||
| Carbon in Different Fuel Classes | cfuel-total | kg m-2 |
|
Sectors: fire. Level dimensions: (time, fuelclass, lat, lon). as appropriate for your model |
||
| Combustion Completeness of Different Fuel Classes | ccfuel-total | 1 |
|
Sectors: fire. Level dimensions: (time, fuelclass, lat, lon). (between 0 and 1), fraction of fuel combusted in a fire |
||
| Fuel Moisture for Different Fuel Classes | mfuel-total | 1 |
|
Sectors: fire. Level dimensions: (time, fuelclass, lat, lon). as a fraction of fuel dry mass (not percentage) |
||
| Mean Number of Fires | firenr-total | km-2 day-1 |
|
Sectors: fire. |
||
| 95th Percentile of Number of Fires | firenrperc95-total | km-2 day-1 |
|
Sectors: fire. 95th percentile of number of fires in one day during the month |
||
| Tree Mortality Caused by Fire | firemortality-total | 1 |
|
Sectors: fire. fraction of area covered by trees |
||
| Weighted Mean Fire Size | firesize-total | km-2 |
|
Sectors: fire. Monthly mean weighted with the number of fires of each day |
||
| 95th Percentile of Fire Size | firesizeperc95-total | km-2 |
|
Sectors: fire. 95th percentile of fire size computed during the month |
||
| Weighted Mean Fire Duration | fireduration-total | s |
|
Sectors: fire. Mean needs to be weighted with the number of fires |
||
| Weighted Mean Fire Rate of Spread | fireros-total | m s-1 |
|
Sectors: fire. Mean needs to be weighted with burned area |
||
| Ignitions Caused by Human | ignhuman-total | km-2 day-1 |
|
Sectors: fire. |
||
| Ignitions Caused by Lightning | ignlight-total | km-2 day-1 |
|
Sectors: fire. |
||
| Mean Canopy Height | canopyheight-total | m |
|
Sectors: fire. mean height of canopy formed by trees over 5m. Vegetation of less than 5m should be excluded from the canopy height calculation (i.e. not contributing with zero) |
||
| Low Vegetation Cover | lowcover-total | 1 |
|
Sectors: fire. fraction of grid cell covered with vegetation less than 5 m tall |
||
| High Vegetation Cover | highcover-total | 1 |
|
Sectors: fire. fraction of grid cell covered with vegetation more than 5 m tall |
||
| Grid Cell Area | cellarea | km**2 |
|
Sectors: water_global. The total area associated with each grid cell in the model. |
||
| Continental Fraction of Grid Cell | contfrac | 1 |
|
Sectors: water_global. The fraction of each grid cell that is assumed to be continent, i.e., not ocean. Should be 0 if the entire cell is assumed to be ocean, 1 if the entire cell is assumed to be covered by land or inland water bodies. |
||
Crops
| Crop | Specifier | ||||
|---|---|---|---|---|---|
| Major crops | |||||
| Wheat | whe | ||||
| Maize | mai | ||||
| Soy | soy | ||||
| Rice | ric | ||||
| Other crops | |||||
| Rice (first growing period) | ric1 | ||||
| Rice (second growing period) | ric2 | ||||
| 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
| Irrigation type | Specifier |
|---|---|
| Full irrigation | firr |
| Constrained irrigation | cirr |
| No irrigation (rainfed land) | noirr |
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
| 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
| 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
| 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
| 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 |
| Hawaii | hawaii | 0.0, 0.0, 0.0, 0.0 |
| Benguela Current | benguela | 0.0, 0.0, 0.0, 0.0 |
| Eastern Bering Sea | east-bering-sea | 0.0, 0.0, 0.0, 0.0 |
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:
- Report one variable per file.
- In filenames, use lowercase letters only.
- Use underscore (
_) to separate identifiers. - Variable names consist of a single word without hyphens or underscores.
- Use hyphens (
-) to separate strings within an identifier, e.g. in a model name. - If no specific
sens-scenariois given in the experiments table, usedefault. - Data model is NETCDF4_CLASSIC with minimum compression level of
5. - NetCDF file extension is
.nc. - The relative time axis' reference year for ISIMIP3b is
1601. - for daily data use
standard,proleptic_gregorian,366_day,365_dayor360_daycalendar depending on the temporal resolution of your model and the360_daycalendar for non-daily data.
Please name the files in the all sectors combined sector according to the following pattern:
<model>_<climate-forcing>_<bias-adjustment>_<climate-scenario>_<soc-scenario>_<sens-scenario>_<variable>_<region>_<time-step>_<start-year>_<end-year>.nc
and replace the identifiers with the specifiers given in the tables of this document. Examples would be:
lpjml_gfdl-esm4_w5e5_picontrol_histsoc_default_qtot_global_annual_2001_2010.nc
lpjml_ukesm1-0-ll_w5e5_ssp585_2015soc_2015co2_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<bias_adjustment>[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<time_step>[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.
References
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman, P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri, M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L., Woodruff, S. D. and Worley, S. J.: The twentieth century reanalysis project, Quarterly Journal of the Royal Meteorological Society, 137(654), 1–28, doi:10.1002/qj.776, 2011.
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H. and Buontempo, C.: WFDE5: Bias-adjusted ERA5 reanalysis data for impact studies, Earth System Science Data, 12(3), 2097–2120, doi:10.5194/essd-12-2097-2020, 2020.
Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T. and Hanasaki, N.: GSWP-2: Multimodel Analysis and Implications for Our Perception of the Land Surface, Bulletin of the American Meteorological Society, 87(10), 1381–1398, doi:10.1175/BAMS-87-10-1381, 2006.
Dlugokencky, E. and Tans, P.: Trends in atmospheric carbon dioxide, Natl. Ocean. Atmos. Adm. Earth Syst. Res. Lab. [online] Available from: https://www.esrl.noaa.gov/gmd/ccgg/trends/, 2019.
Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: Past observations (1850–2005) harmonized with future projections according to the Shared Socio-economic Pathways (2006–2100), Earth System Science Data, 10(2), 847–856, doi:10.5194/essd-10-847-2018, 2018.
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Goldewijk, K. K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J., Kennedy, J., Kristzin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., Vuuren, D. P. van and Zhang, X.: Harmonization of Global Land-Use Change and Management for the Period 850–2100 (LUH2) for CMIP6, Geoscientific Model Development Discussions, 1–65, doi:https://doi.org/10.5194/gmd-2019-360, 2020.
Klein Goldewijk, K., Beusen, A., Doelman, J. and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth System Science Data, 9(2), 927–953, doi:10.5194/essd-9-927-2017, 2017.
Lange, S.: Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0), Geoscientific Model Development, 12(7), 3055–3070, doi:10.5194/gmd-12-3055-2019, 2019a.
Lange, S., Menz, C., Gleixner, S., Cucchi, M., Weedon, G.P., Amici, A., Bellouin, N., Müller Schmied, H., Hersbach, H., Buontempo, C. and Cagnazzo, C.: WFDE5 over land merged with ERA5 over the ocean (W5E5 v2.0), ISIMIP Repository, doi:10.48364/ISIMIP.342217, 2021.
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J. C., Rödel, R., Sindorf, N. and Wisser, D.: Global Reservoir and Dam Database, Version 1 (GRanDv1): Dams, Revision 01. Palisades, NY, NASA Socioeconomic Data and Applications Center (SEDAC), doi:10.7927/H4N877QK, 2011a.
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J. C., Rödel, R., Sindorf, N. and Wisser, D.: High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management, Frontiers in Ecology and the Environment, 9(9), 494–502, doi:10.1890/100125, 2011b.
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J.-F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K., Thomson, A., Velders, G. J. M. and Vuuren, D. P. P. van: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300, Climatic Change, 109(1), 213, doi:10.1007/s10584-011-0156-z, 2011.
Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J. G., Daniel, J. S., John, A., Krummel, P. B., Luderer, G., Meinshausen, N., Montzka, S. A., Rayner, P. J., Reimann, S., Smith, S. J., Berg, M. van den, Velders, G. J. M., Vollmer, M. K. and Wang, R. H. J.: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500, Geoscientific Model Development, 13(8), 3571–3605, doi:10.5194/gmd-13-3571-2020, 2020.
Messager, M. L., Lehner, B., Grill, G., Nedeva, I. and Schmitt, O.: Estimating the volume and age of water stored in global lakes using a geo-statistical approach, Nature Communications, 7(1), 13603, doi:10.1038/ncomms13603, 2016.
Murakami, D. and Yamagata, Y.: Estimation of Gridded Population and GDP Scenarios with Spatially Explicit Statistical Downscaling, Sustainability, 11(7), 2106, doi:10.3390/su11072106, 2019.
Portmann, F. T., Siebert, S. and Döll, P.: MIRCA2000—global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling, Global Biogeochemical Cycles, 24(1), doi:10.1029/2008GB003435, 2010.
Reyer, C., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y., Noack, M., Lasch-Born, P., Rötzer, T., Pretzsch, H., Meesenburg, H., Fleck, S., Wagner, M., Bolte, A., Sanders, T., Kolari, P., Mäkelä, A., Vesala, T., Mammarella, I., Pumpanen, J., Matteucci, G., Collalti, A., D’Andrea, E., Foltýnová, L., Krejza, J., Ibrom, A., Pilegaard, K., Loustau, D., Bonnefond, J.-M., Berbigier, P., Picart, D., Lafont, S., Dietze, M., Cameron, D., Vieno, M., Tian, H., Palacios-Orueta, A., Cicuendez, V., Recuero, L., Wiese, K., Büchner, M., Lange, S., Volkholz, J., Kim, H., Weedon, G., Sheffield, J., Vega del Valle, I., Suckow, F., Horemans, J., Martel, S., Bohn, F., Steinkamp, J., Chikalanov, A. and Frieler, K.: The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests. V. 0.1.12., GFZ Data Services, doi:10.5880/PIK.2019.008, 2019.
Reyer, C. P. O., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y., Noack, M., Lasch-Born, P., Rötzer, T., Pretzsch, H., Meesenburg, H., Fleck, S., Wagner, M., Bolte, A., Sanders, T. G. M., Kolari, P., Mäkelä, A., Vesala, T., Mammarella, I., Pumpanen, J., Collalti, A., Trotta, C., Matteucci, G., D’Andrea, E., Foltýnová, L., Krejza, J., Ibrom, A., Pilegaard, K., Loustau, D., Bonnefond, J.-M., Berbigier, P., Picart, D., Lafont, S., Dietze, M., Cameron, D., Vieno, M., Tian, H., Palacios-Orueta, A., Cicuendez, V., Recuero, L., Wiese, K., Büchner, M., Lange, S., Volkholz, J., Kim, H., Horemans, J. A., Bohn, F., Steinkamp, J., Chikalanov, A., Weedon, G. P., Sheffield, J., Babst, F., Vega del Valle, I., Suckow, F., Martel, S., Mahnken, M., Gutsch, M. and Frieler, K.: The PROFOUND database for evaluating vegetation models and simulating climate impacts on european forests, Earth System Science Data, 12(2), 1295–1320, doi:10.5194/essd-12-1295-2020, 2020.
Tian, H., Yang, J., Lu, C., Xu, R., Canadell, J. G., Jackson, R. B., Arneth, A., Chang, J., Chen, G., Ciais, P., Gerber, S., Ito, A., Huang, Y., Joos, F., Lienert, S., Messina, P., Olin, S., Pan, S., Peng, C., Saikawa, E., Thompson, R. L., Vuichard, N., Winiwarter, W., Zaehle, S., Zhang, B., Zhang, K. and Zhu, Q.: The Global N2O Model Intercomparison Project, Bulletin of the American Meteorological Society, 99(6), 1231–1251, doi:10.1175/BAMS-D-17-0212.1, 2018.