ISIMIP3b simulation round simulation protocol - Fisheries and Marine Ecosystems (global)

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:

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 Fisheries and Marine Ecosystems (global). An overview of all sectors can be found at protocol.isimip.org.

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

Model versioning

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

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

Scenarios & Experiments

Scenario definitions

Table 1: Climate scenario specifiers (climate-scenario).
Scenario specifier Description
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.
Table 2: Socio-economic scenario specifiers (soc-scenario).
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 1850soc if they do not at all account for historical changes in direct human forcing, but they do represent constant year-1850 levels of direct human forcing for at least some direct human forcings.

histsoc

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

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

2015soc

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

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

nat

No direct human influences (naturalized run).

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

Table 3: Sensitivity scenario specifiers (sens-scenario).
Scenario specifier Description
default For all experiments other than the sensitivity experiments.

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

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

Pre-industrial

1601-1849

Historical

1850-2014

Future

2015-2100

pre-industrial control

histsoc

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 control

2015soc

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 control

nat

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

RCP2.6

histsoc

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

RCP2.6

2015soc

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

RCP2.6

nat

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

RCP7

histsoc

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

RCP7

2015soc

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

RCP7

nat

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

RCP8.5

histsoc

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

RCP8.5

2015soc

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

RCP8.5

nat

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

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/ocean/uncorrected/global/monthly/<climate-scenario>/<climate-forcing>/<climate-forcing>_<ensemble-member>_<climate-scenario>_<climate-variable>_onedeg_global_daily_<start-year>_<end-year>.nc  # 1° grid

climate/ocean/uncorrected/global/monthly/<climate-scenario>/<climate-forcing>/<climate-forcing>_<ensemble-member>_<climate-scenario>_<climate-variable>_halfdeg_global_daily_<start-year>_<end-year>.nc  # 0.5° grid

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

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

Table 5: Climate and climate-related forcing data (climate-forcing).
Title Specifier Institution Original resolution Ensemble member Priority
GFDL-ESM4 gfdl-esm4 National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA 720x576 r1i1p1f1 1
UKESM1-0-LL ukesm1-0-ll Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK 360x330 r1i1p1f2 2
MPI-ESM1-2-HR mpi-esm1-2-hr Max Planck Institute for Meteorology, Hamburg 20146, Germany 802x404 r1i1p1f1 3
IPSL-CM6A-LR ipsl-cm6a-lr Institut Pierre Simon Laplace, Paris 75252, France 362x332 r1i1p1f1 4

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.

Table 6: Climate forcing variables for ISIMIP3b simulations (climate-variable).
Variable Variable specifier Unit Resolution Models
Ocean variables mandatory
Mass Concentration of Total Phytoplankton Expressed as Chlorophyll chl kg m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Floor Depth deptho m
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • fixed
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Downward Flux of Particulate Organic Carbon expc-bot mol m-2 s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Particulate Organic Carbon Content intpoc kg m-2
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • GFDL-ESM4
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Primary Organic Carbon Production by All Types of Phytoplankton intpp mol m-2 s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Net Primary Organic Carbon Production by Diatoms intppdiat mol m-2 s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • UKESM1-0-LL
Net Primary Mole Productivity of Carbon by Diazotrophs intppdiaz mol m-2 s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • MPI-ESM1-2-HR
Maximum Ocean Mixed Layer Thickness Defined by Sigma T mlotstmax m
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Dissolved Oxygen Concentration o2, o2-bot, o2-surf mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
pH ph, ph-bot, ph-surf 1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Phytoplankton Carbon Concentration phyc, phyc-vint mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Mole Concentration of Diatoms expressed as Carbon in sea water phydiat, phydiat-vint mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • UKESM1-0-LL
Mole Concentration of Diazotrophs Expressed as Carbon in Sea Water phydiaz, phydiaz-vint mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • MPI-ESM1-2-HR
Primary Carbon Production by Total Phytoplankton pp mol m-3 s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
Sea Water Salinity so, so-bot, so-surf 0.001
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Net Downward Shortwave Radiation at Sea Water Surface rsntds W m-2
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
Sea Ice Area Fraction siconc %
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Water Potential Temperature thetao °C
  • 1° grid
  • 2° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Ocean Model Cell Thickness thkcello m
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Water Potential Temperature at Sea Floor tob °C
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Surface Temperature tos °C
  • 1° grid
  • 2° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Water X Velocity uo m s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Water Y Velocity vo m s-1
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Sea Water Z Velocity wo m s-1
  • 1° grid
  • 2° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL
Mole Concentration of Mesozooplankton expressed as Carbon in sea water zmeso, zmeso-vint mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • UKESM1-0-LL
Mole Concentration of Microzooplankton expressed as Carbon in sea water zmicro, zmicro-vint mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • UKESM1-0-LL
Zooplankton Carbon Concentration zooc, zooc-vint mol m-3
  • 1° grid
  • 0.5° grid (only MPI-ESM1-2-HR)
  • monthly
  • CESM2
  • GFDL-ESM4
  • IPSL-CM6A-LR
  • MPI-ESM1-2-HR
  • UKESM1-0-LL

Other climate datasets

Table 7: Other climate datesets for ISIMIP3b simulation round.
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
  • global
  • annual

Meinshausen, Raper, & Wigley (2011) for 1850-2005 and 2016-2100 and Dlugokencky & Tans (2019) from 2006-2015

Socioeconomic forcing

Table 8: Socioeconomic datasets for ISIMIP3b simulation round.
Dataset Included variables (specifier) Covered time period Resolution Reference/Source and Comments
Fishing mandatory

Fishing effort

socioeconomic/fishing/effort_historical_1950_2014.csv
  • fishing effort
  • 1950-2014
  • Marine ecosystems or exclusive economic zones
  • annual

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_historical_1950_2014.csv
  • fish catch
  • 1950-2014
  • Marine ecosystems or exclusive economic zones
  • annual

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.

Population mandatory

Population 5' grid

socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_5arcmin_annual_<start-year>_<end-year>.nc
  • total number of people (popc)
  • rural number of people (rurc)
  • urban number of people (urbc)
  • 1850-1900
  • 1901-2014
  • 5' grid
  • annual

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

Population 0.5° grid

socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_30arcmin_annual_<start-year>_<end-year>.nc
  • total number of people (popc)
  • rural number of people (rurc)
  • urban number of people (urbc)
  • 1850-2014
  • 0.5° grid
  • annual

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

Population national

socioeconomic/pop/<soc_scenario>/population_<soc_scenario>_national_annual_<start-year>_<end-year>.csv
  • total number of people per country
  • 1850-2014
  • national
  • annual

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

Population density 5' grid

socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_5arcmin_annual_<start-year>_<end-year>.nc
  • total number of people per square kilometer (popc)
  • rural number of people per square kilometer (rurc)
  • urban number of people per square kilometer (urbc)
  • 1850-1900
  • 1901-2014
  • 5' grid
  • annual

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

Population density 0.5° grid

socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_30arcmin_annual_<start-year>_<end-year>.nc
  • total number of people per square kilometer (popc)
  • rural number of people per square kilometer (rurc)
  • urban number of people per square kilometer (urbc)
  • 1850-2014
  • 0.5° grid
  • annual

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

Population density national

socioeconomic/pop/<soc_scenario>/population-density_<soc_scenario>_national_annual_<start-year>_<end-year>.csv
  • total number of people per square kilometer
  • 1850-2014
  • national
  • annual

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

GDP mandatory

GDP

socioeconomic/gdp/<soc_scenario>/<soc_scenario>_gdp_annual_<start-year>_<end-year>.nc
  • GDP PPP 2005 USD (gdp)
  • 1850-2014
  • country-level
  • annual

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

Geographic data and information

Table 9: Geographic data and information for ISIMIP3b simulation round.
Dataset Included variables (specifier) Resolution Reference/Source and Comments
Land/Sea masks

landseamask

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

This is the land-sea mask of the W5E5 dataset (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.

landseamask_no-ant

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

Same as landseamask but without Antarctica.

landseamask_water-global

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

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

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

Table 10: Output variables for Fisheries and Marine Ecosystems (global) (variable).
Variable long name Variable specifier Unit Resolution Comments
Mandatory output from global and regional models (provide as many as possible). All biomasses are in wet weight, not g C.
Total Consumer Biomass Density tcb g m-2
  • 0.5° grid
  • monthly

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

Total Consumer Biomass Density in log10 Weight Bins tcblog10 g m-2
  • 0.5° grid
  • monthly

Level dimensions: (time, bins, lat, lon).

If the model is size-structured, please provide biomass in equal log10 g C weight bins (1g, 10g, 100g, 1kg, 10kg, 100kg) and use the dimensions stucture mentioned above

Total Pelagic Biomass Density tpb g m-2
  • 0.5° grid
  • monthly

All pelagic consumers (trophic level >1, vertebrates and invertebrates)

Total Demersal Biomass Density tdb g m-2
  • 0.5° grid
  • monthly

All demersal consumers (trophic level >1, vertebrates and invertebrates)

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

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

Total Catch in log10 Weight Bins tclog10 g m-2
  • 0.5° grid
  • monthly

Level dimensions: (time, bins, lat, lon).

If the model is size-structured, please provide catch in equal log10 g C weight bins (1g, 10g, 100g, 1kg, 10kg, 100kg) and use the dimensions stucture mentioned above.

Total Pelagic Catch tpc g m-2
  • 0.5° grid
  • monthly

Catch at sea of all pelagic consumers (trophic level >1, vertebrates and invertebrates)

Total Demersal Catch tdc g m-2
  • 0.5° grid
  • monthly

Catch at sea of all demersal consumers (trophic level >1, vertebrates and invertebrates)

Optional output from global and regional models. All biomasses are in wet weight, not g C.
Biomass Density of Small Pelagics <30cm bp30cm g m-2
  • 0.5° grid
  • monthly

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
  • 0.5° grid
  • monthly

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
  • 0.5° grid
  • monthly

If a pelagic species and L infinity is >=90cm, include in this variable

Biomass Density of Small Demersals <30cm bd30cm g m-2
  • 0.5° grid
  • monthly

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
  • 0.5° grid
  • monthly

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
  • 0.5° grid
  • monthly

If a demersal species and L infinity is >=90cm, include in this variable

Catch Density of Small Pelagics <30cm cp30cm g m-2
  • 0.5° grid
  • monthly

Catch at sea of pelagic species with L infinity <30 cm

Catch Density of Medium Pelagics >=30cm and <90cm cp30to90cm g m-2
  • 0.5° grid
  • monthly

Catch at sea of pelagic species with L infinity >=30 cm and <90 cm

Catch Density of Large Pelagics >=90cm cp90cm g m-2
  • 0.5° grid
  • monthly

Catch at sea of pelagic species with L infinity >=90 cm

Catch Density of Small Demersals <30cm cd30cm g m-2
  • 0.5° grid
  • monthly

Catch at sea of demersal species with L infinity <30 cm

Catch Density of Medium Demersals >=30cm and <90cm cd30to90cm g m-2
  • 0.5° grid
  • monthly

Catch at sea of demersal species with L infinity >=30 cm and <90 cm

Catch Density of Large Demersals >=90cm cd90cm g m-2
  • 0.5° grid
  • monthly

Catch at sea of demersal species with L infinity >=90 cm

Reporting model results

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

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

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

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

Please name the files in the Fisheries and Marine Ecosystems (global) 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 fisheries and marine ecosystems (global) 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.

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