ISIMIP3a simulation round simulation protocol - Lakes (local)
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.
ISIMIP3a
Historical model evaluation and attribution runs
The ISIMIP3a part of the third round framework is dedicated to i) impact model evaluation and improvement and ii) detection and attribution of observed impacts according to the framework of IPCC AR5 Working Group II Chapter 18. To this end all simulations are forced by observed climate and socio-economic information and a de-trended version of the observed climate allowing for the generation of a “no climate change” baseline (counterfactual).
You can find the ISIMIP3b protocol, which is dedicated to a quantification of climate-related risks at different levels of climate change and socio-economic conditions, here.
Simulation protocol
In this protocol we describe the scenarios & experiments in ISIMIP3a simulation round, the different input datasets, the output variables, and how to report model results specifically for Lakes (local). 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 |
---|---|
obsclim | Observed climate and CO₂ forcing used for model evaluation and the detection and attribution task. |
spinclim | Detrended version of the observed climate forcing used to spin-up the simulations based on a stable 1900 climate (see explanation below for details regarding the design of the spin-up) |
counterclim | Detrended version of the observed climate forcing used for the "no climate change" baseline simulations in the context of the detection and attributions task. |
Scenario specifier | Description |
---|---|
histsoc |
Varying direct human influences in the historical period (1850-2014) (e.g. observed changes in historical land use, nitrogen deposition and fertilizer input, fishing effort). Please label your model run |
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. |
General note regarding sensitivity experiments
The sensitivity experiments are meant to be "artificial" deviations from the default settings. So for example if your model does not at all account for changes in CO₂ concentrations (no option to switch it on or off) the run should be labeled as “default” in the sensitivity specifier of the file name even if the run would be identical to the 1901co2
sensitivity setting.
The particular sensitivity scenario for an experiment is given in the experiments table below. For most experiments no sensitivity scenario is given, so the default
label applies.
Experiments
Experiment | Short description |
Transition from Spin-up to experiment 1850-1900, only if spin-up is needed |
Historical 1901-2016 |
---|---|---|---|
model evaluationhistsoc 1st priority |
CF: No climate change before 1901, observed forcing afterwards; constant 1850 levels of CO₂ before 1850 and based on observations afterwards |
spinclim |
obsclim |
DHF: Fixed 1850 levels of direct human forcing before 1850, varying direct human influences according to observations afterwards |
histsoc |
histsoc |
|
model evaluation2015soc 1st priority |
CF: No climate change before 1901, observed forcing afterwards; constant 1850 levels of CO₂ before 1850 and based on observations afterwards |
spinclim |
obsclim |
DHF: Fixed 2015 levels of direct human forcing for the entire time period |
2015soc |
2015soc |
|
model evaluationnat 2nd priority |
CF: No climate change before 1901, observed forcing afterwards; 1850 levels of CO₂ before 1850 and based on observations afterwards |
spinclim |
obsclim |
DHF: No direct human influences |
nat |
nat |
|
counterfactual climatehistsoc 1st priority |
CF: de-trended observational climate forcing (counterfactual "no climate change" situation) + fixed CO₂ concentration at 1901 level | "histsoc" version of the transition period of the model evaluation run |
counterclim |
DHF: 1850 levels of direct human forcing before 1850, varying direct human influences according to observations afterwards |
histsoc |
||
counterfactual climate2015soc 1st priority |
CF: de-trended observational climate forcing (counterfactual "no climate change" situation) + fixed CO₂ concentration at 1901 level | "2015soc" version of the transition period of the model evaluation run |
counterclim |
DHF: fixed 2015 levels of direct human influences for the entire time period |
2015soc |
||
counterfactual climatenat 2nd priority |
CF: de-trended observational climate forcing (counterfactual "no climate change" situation) + fixed CO₂ concentration at 1901 level | "nat" version of the transition period of the model evaluation run |
counterclim |
DHF: No direct human influences |
nat |
||
CO₂ sensitivityhistsoc 2nd priority |
CF: no climate change before 1901, observed forcing afterwards + fixed CO₂ concentration at 1901 level | "histsoc" version of the transition period of the model evaluation run |
obsclim Sensitivity scenario: 1901co2 |
DHF: 1850 levels of direct human forcing before 1850, varying direct human influences according to observations afterwards |
histsoc |
||
CO₂ sensitivity2015soc 2nd priority |
CF: no climate change before 1901, observed forcing afterwards + fixed CO₂ concentration at 1901 level | "2015soc" version of the transition period of the model evaluation run |
obsclim Sensitivity scenario: 1901co2 |
DHF: fixed 2015 levels of direct human influences for the entire time period |
2015soc |
Note regarding models requiring spin-up
For models requiring spin-up, we provide 100 years of spinclim data which is identical with the first 100 years of the counterclim data (files climate/atmosphere/spinclim/<dataset>/<dataset>_spinclim_<variable>_global_daily_<start-year>_<start-year>.nc
). If more than 100 years of spin-up are needed, these data can be repeated as often as needed.
- For
historical
runs, use historical CO2 concentration and varying DHF, for the transition period from spin-up to the start of the experiment (1850-1900). When using a longer spin-up period that (nominally) extends back further than 1850, please keep CO2 concentration and DHF constant at 1850 level until reaching the year corresponding to 1850. - For experiments with fixed year-2015 direct human influences (
2015soc
), the spin-up should be based on the 2015 DHF. - For experiments with no direct human influences (
nat
), the spin-up should be not using DHF as well.
Input data
The base directory for input data at DKRZ is:
/work/bb0820/ISIMIP/ISIMIP3a/InputData/
Further information on accessing ISIMIP data can be found at ISIMIP - getting started.
Some of the datasets are tagged as mandatory. This does not mean that the data must be used in all cases, but if your models uses input data of this kind, we require to use the specified dataset. If an alterntive data set is used instead, we cannot consider it an ISIMIP simulation. If the mandatory label is not given, you may use alternative data (please document this clearly).
Climate forcing
The climate forcing input files can be found on DKRZ using the following pattern:
climate/atmosphere/<climate-scenario>/<climate-forcing>/<climate-forcing>_<climate-scenario>_<climate-variable>_global_daily_<start-year>_<end-year>.nc
Title | Specifier | Time period | Reanalysis | Bias adjustment target | Comments | Priority |
---|---|---|---|---|---|---|
GSWP3-W5E5 | gswp3-w5e5 | 1901-2016 | ERA5 | GPCC, CRU | Combination of W5E5 (Lange, 2019a; Cucchi et al., 2020) for 1979-2016 with GSWP3 (Dirmeyer et al., 2006) homogenized to W5E5 for 1901-1978. The homogenization reduces discontinuities at the 1978/1979 transition and was done using the ISIMIP3BASD v2.4.1 bias adjustment method (Lange, 2019b; Lange, 2020). | 1 |
GSWP3 | gswp3 | 1901-2010 | 20CR | GPCC, GPCP, CPC-Unified, CRU, SRB | Dynamically downscaled and bias-adjusted 20th Century Reanalysis (20CR; Compo et al., 2011) from the Global Soil Wetness Project Phase 3 (GSWP3; Dirmeyer et al., 2006). | 2 |
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 | Datasets | ||
---|---|---|---|---|---|---|
Atmospheric variables mandatory | ||||||
Near-Surface Relative Humidity | hurs | % |
|
|
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Near-Surface Specific Humidity | huss | kg kg-1 |
|
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Precipitation | pr | kg m-2 s-1 |
|
|
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Surface Air Pressure | ps | Pa |
|
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Surface Downwelling Longwave Radiation | rlds | W m-2 |
|
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Surface Downwelling Shortwave Radiation | rsds | W m-2 |
|
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Near-Surface Wind Speed | sfcwind | m s-1 |
|
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Near-Surface Air Temperature | tas | K |
|
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Daily Maximum Near-Surface Air Temperature | tasmax | K |
|
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Daily Minimum Near-Surface Air Temperature | tasmin | K |
|
|
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 et al. (2011) for 1850-2005 and Dlugokencky & Tans (2019) from 2006-2018. |
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
|
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|
|
|
Based on the HYDE 3.2 data set (Klein Goldewijk, 2016), but harmonized by Hurtt et al. (LUH2 v2h data set, see Hurtt, Chini, Sahajpal, Frolking, & et al, in review, see also https://luh.umd.edu). |
|||
Downscaling to 5 crops |
socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-5crops_annual_<start_year>_<end_year>.nc
|
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|
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|
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). |
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Downscaling to 15 crops |
socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-15crops_annual_<start_year>_<end_year>.nc
|
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|
|
|
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). |
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Managed pastures and rangeland |
socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-pastures_annual_<start_year>_<end_year>.nc
|
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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). |
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Urban areas |
socioeconomic/landuse/<soc_scenario>/<soc_scenario>_landuse-urbanareas_annual_<start_year>_<end_year>.nc
|
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|
|
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). |
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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
|
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|
|
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Based on the LUH2 v2h data set (see Hurtt, Chini, Sahajpal, Frolking, & et al., in in review, see also https://luh.umd.edu). |
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N-deposition | ||||||
Reduced nitrogen deposition |
socioeconomic/n-deposition/<soc_scenario>/ndep-nhx_<soc_scenario>_monthly_<start_year>_<end_year>.nc
|
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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) |
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Oxidized nitrogen deposition |
socioeconomic/n-deposition/<soc_scenario>/ndep-noy_<soc_scenario>_monthly_<start_year>_<end_year>.nc
|
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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) |
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Reservoirs & dams | ||||||
Reservoirs & dams |
socioeconomic/reservoir_dams/reservoirs-dams_1850_2025.xls
|
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|
|
|
Lehner et al. (2011a, https://doi.org/10.7927/H4N877QK), Lehner et al. (2011b, https://dx.doi.org/10.1890/100125), and Jida Wang et al. (KSU/Kansas State University, personal communication). Because the data from KSU is yet unpublished, modeling teams using it are asked to offer co-authorship to the team at KSU on any resulting publications. Please contact info@isimip.org in case of questions. |
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Water abstraction | ||||||
Water abstraction for domestic and industrial purposes |
socioeconomic/water_abstraction/[domw|indw][w|c]_<soc_scenario>_annual_<start-year>_<end-year>.nc
|
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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. |
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Lakes | ||||||
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socioeconomic/lakes/pctlake_<soc_scenario>_<start_year>_<end_year>.nc
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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). |
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Population mandatory | ||||||
Population 5' grid |
socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_5arcmin_annual_<start-year>_<end-year>.nc
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HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2020, 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. |
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Population 0.5° grid |
socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_30arcmin_annual_<start-year>_<end-year>.nc
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HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2020, 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 |
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Population national |
socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_national_annual_<start-year>_<end-year>.csv
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HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2020, 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. |
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Population density 5' grid |
socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_5arcmin_annual_<start-year>_<end-year>.nc
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HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2020, 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. |
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Population density 0.5° grid |
socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_30arcmin_annual_<start-year>_<end-year>.nc
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HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2020, 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 |
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Population density national |
socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_national_annual_<start-year>_<end-year>.csv
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HYDE v3.2.1 (Klein Goldewijk et al., 2017). For 1950-2020, 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. |
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GDP mandatory | ||||||
GDP |
socioeconomic/gdp/<soc_scenario>/<soc_scenario>_gdp_annual_<start-year>_<end-year>.nc
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Historic country-level GDP data are an extension of the data provided by Geiger, 2018 (https://www.earth-syst-sci-data.net/10/847/2018/essd-10-847-2018.html), and are derived mainly from the Maddison Project database. Gridded GDP data will be provided by c. 07/2021. |
Geographic data and information
Dataset | Included variables (specifier) | Resolution | Reference/Source and Comments | |||
---|---|---|---|---|---|---|
Land/Sea masks | ||||||
landseamask |
geo_conditions/landseamask/landseamask.nc
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0.5° grid | This is the land-sea mask of the W5E5 dataset (Lange, 2019a; Cucchi et al., 2020). 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. |
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landseamask_no-ant |
geo_conditions/landseamask/landseamask_no-ant.nc
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0.5° grid | Same as landseamask but without Antarctica. |
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landseamask_water-global |
geo_conditions/landseamask/landseamask_water-global.nc
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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. |
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Soil | ||||||
gswp3_hwsd |
geo_conditions/soil/gswp3_hwsd.nc
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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) |
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hwsd_soil_data_all_land |
geo_conditions/soil/hwsd_soil_data_all_land.nc
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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. |
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hwsd_soil_data_on_cropland |
geo_conditions/soil/hwsd_soil_data_on_cropland.nc
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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). |
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River routing | ||||||
basins |
geo_conditions/river_routing/ddm30_basins_cru_neva.[nc|asc]
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0.5° grid | DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files. |
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flowdir |
geo_conditions/river_routing/ddm30_flowdir_cru_neva.[nc|asc]
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0.5° grid | DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files. |
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slopes |
geo_conditions/river_routing/ddm30_slopes_cru_neva.[nc|asc]
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0.5° grid | DDM30 (Döll & Lehner, 2002). Documentation (pdf) is provided alongside data files. |
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Lakes | ||||||
lakemask |
geo_conditions/lakes/lakemask.nc
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0.5° grid | |||||
lakedepth |
geo_conditions/lakes/lakedepth.nc
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0.5° grid | For these variables, new forcing files will be provided soon: histsoc, accounting for reservoir expansion; and 2015soc. |
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 | ||
---|---|---|---|---|---|---|
Hydrothermal Variables | ||||||
Thermal Stratification | strat | 1 |
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1 if lake grid cell is thermally stratified, 0 if lake grid cell is not thermally stratified |
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Depth of Thermocline | thermodepth | m |
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Depth corresponding the maximum water density gradient |
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Temperature of Lake Water | watertemp | K |
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Depth resolution: Full Profile. Simulated water temperature. Layer averages and full profiles. |
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Temperature of Lake Surface Water | surftemp | K |
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Average of the upper layer in case not simulated directly. |
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Temperature of Lake Bottom Water | bottemp | K |
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Average of the lowest layer in case not simulated directly. |
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Lake Ice Cover | ice | 1 |
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1 if ice cover is present in lake grid cell, 0 if no ice cover is present in lake grid cell |
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Lake Layer Ice Mass Fraction | lakeicefrac | 1 |
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Depth resolution: Mean epi. Fraction of mass of a given layer taken up by ice. |
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Ice Thickness | icethick | m |
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Snow Thickness | snowthick | m |
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Ice Temperature at Upper Surface | icetemp | K |
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Snow Temperature at Upper Surface | snowtemp | K |
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Sensible Heat Flux at Lake-Atmosphere Interface | sensheatf-total | W m-2 |
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At the surface of the layer in contact with the atmosphere. Positive if upwards. |
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Latent Heat Flux at Lake-Atmosphere Interface | latentheatf | W m-2 |
|
At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. |
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Momentum Flux at Lake-Atmosphere Interface | momf | kg m-1 s-2 |
|
At the surface of snow, ice or water depending on the layer in contact with the atmosphere. Positive if upwards. |
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Upward Short-Wave Radiation Flux at Lake-Atmosphere Interface | swup | W m-2 |
|
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. |
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Upward Long-Wave Radiation Flux at Lake-Atmosphere Interface | lwup | W m-2 |
|
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. |
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Downward Heat Flux at Lake-Atmosphere Interface | lakeheatf | W m-2 |
|
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) |
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Turbulent Diffusivity of Heat | turbdiffheat | m2 s-1 |
|
Depth resolution: Either full profile, or mean epi and mean hypo. Only if computed by the model. |
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Light Extinction Coefficient | extcoeff | m-1 |
|
Only to be reported for global models, local models should use extcoeff as input. |
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Sediment Upward Heat Flux at Lake-Sediment Interface | sedheatf | W m-2 |
|
Positive if upwards. Only if computed by the model. |
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Water Quality Variables | ||||||
Chlorophyll Concentration | chl | g-3 m⁻³ |
|
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 |
|
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 |
|
Depth resolution: Either full profile, or mean epi and mean hypo. Total simulated Zooplankton biomass. |
||
Total Phosphorus | tp | mole m⁻³ |
|
Depth resolution: Either full profile, or mean epi and mean hypo. |
||
Particulate Phosphorus | pp | mole m⁻³ |
|
Depth resolution: Either full profile, or mean epi and mean hypo. |
||
Total Dissolved Phosphorus | tpd | mole m⁻³ |
|
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 |
|
Depth resolution: Either full profile, or mean epi and mean hypo. |
||
Particulate Nitrogen | pn | mole m⁻³ |
|
Depth resolution: Either full profile, or mean epi and mean hypo. |
||
Total Dissolved Nitrogen | tdn | mole m⁻³ |
|
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 |
|
Depth resolution: Either full profile, or mean epi and mean hypo. |
||
Dissolved Organic Carbon | doc | mole m⁻³ |
|
Depth resolution: Either full profile, or mean epi and mean hypo. Not always available. |
||
Dissolved Silica | si | mole m⁻³ |
|
Depth resolution: Either full profile, or mean epi and mean hypo. Not always available. |
||
Other | ||||||
Surface Albedo of Lake | lakealbedo | 1 |
|
Albedo of the lake surface interacting with the atmosphere (water, ice or snow). |
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 |
A document with additional information is maintained by the sector coordinators and provided at https://docs.google.com/spreadsheets/d/1UY_KSR02o7LtmNoOs6jOgOxdcFEKrf7MmhR2BYDlm-Q/edit#gid=555498854.
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-scenario
is given in the experiments table, usedefault
. - NetCDF file extension is
.nc
. - The reference year for the NetCDF files for ISIMIP3a is
1901
.
Please name the files in the Lakes (local) sector according to the following pattern:
<model>_<climate-forcing>_<climate-scenario>_<soc-scenario>_<sens-scenario>_<variable>_<lake-site>_<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_gswp3_obsclim_histsoc_default_qtot_global_annual_1901_1910.nc
lpjml_gwsp3_counterclim_2015soc_1901co2_yield-mai-noirr_global_annual_2006_2010.nc
The following regular expression can be used to validate and parse the file name for the lakes (local) sector:
(?P<model>[a-z0-9-+.]+)_(?P<climate_forcing>[a-z0-9-]+)_(?P<climate_scenario>[a-z0-9-]+)_(?P<soc_scenario>[a-z0-9-]+)_(?P<sens_scenario>[a-z0-9-]+)_(?P<variable>[a-z0-9]+)_(?P<lake_site>[a-z0-9-]+)_(?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.
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