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.
::: show sector=agriculture
#### Note on agriculture output
For agricultural output, variables are to be reported with the dimensions **(time,lat,lon)** where the time axis' unit is `growing seasons since 1901-01-01 00:00:00` resp. `growing seasons since 1601-01-01 00:00:00` for all variables unless these are reported on a monthly time axis, e.g. `soilmoist`. In many cases growing seasons are equivalent to years, as there is always only one planting event per year. However, due to temperature-sensitive growing season lengths, the growing seasons are not fully equivalent to years and users should note the difference. Reported variables on start and end of the growing season are supplied to allow allocating events to transient time axes if desired.
Many variables are defined per area (unit m-2). Typically, and unless otherwise defined, the corresponding reference area is the land area of the grid cell, excluding any water bodies. However, in some cases, it may be necessary or meaningful to report a variable relative to the continental area (including inland water bodies, lakes etc...). For example, evaporation could relate to the land area (excluding water bodies etc.), or to the continental area if the model evaporation occurs over both over land and over water. Also, for some variables, the "per PFT" reporting allows modellers to indicate whether inland water bodies are included in the model or not, and hence, what reference area the variable refers to. In such cases, please specify the reference area in a NetCDF global attribute (e.g. :reference_area = "continental area (including inland water bodies)").
::: table identifier=variable caption="Table 4.1: Output variables (variable)."
::: show sector=agriculture
#### Crop priority and naming
::: table identifier=crop caption="Table 4.2: Crop naming and priorities (`crop`)."
#### Irrigation
::: table identifier=irrigation caption="Table 4.3: Irrigation specifiers (`irrigation`)."
#### Harmonization
::: table identifier=harmonization caption="Table 4.4: Harmonization specifiers (`harmonization`)."
::: show sector=forestry
#### Species
::: table identifier=species caption="Table 4.5: Species specifiers (`species`)."
#### Forest stands
::: table identifier=forest_stand caption="Table 4.6: Forest stand specifiers (`forest-stand`)."
::: show sector=lakes_local
#### Lake sites
::: table identifier=lake_site caption="Table 4.7: Lake site specifications for local lake models (`lake-site`)."
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>.
::: show sector=water_regional
#### Catchment gauging stations
::: table identifier=river_basin caption="Table 4.9: Catchment gauging stations for reporting regional hydrological model results (`river-basin`)."
::: hide sector=agriculture,forestry,lakes_local,water_regional
No sector specific identifiers are available for this selection of simulation round and sectors.
::: show sector=agriculture
#### Reporting per growing seasons
To resolve potential double harvests within one year, crop yields should be reported per growing season and not per calendar year. Thus, in the NetCDF output files, do not use a time dimension but instead a unitless coordinate variable with integer values; more information on how to construct these files is given below and on the ISIMIP website (<https://www.isimip.org/protocol/preparing-simulation-files/>).
Cumulative growing season variables such as, e.g., actual evapotranspiration or precipitation are to be accumulated over the growing season. The first season in the file (level=0) is then the first complete growing season of the time period provided by the input data without any assumed spin-up data, which equates to the growing season with the first planting after this date. To ensure that data can be matched to individual years in post-processing, it is essential to also provide the actual planting dates (as day of the year), actual planting years (year), anthesis dates (as day of the year), year of anthesis (year), maturity dates (day of the year), and year of maturity (year). This procedure is identical to the GGCMI convention (Elliott et al., 2015, <https://doi.org/10.5194/gmd-8-261-2015>).
::: show sector=biomes,fire,permafrost,peat
#### Information about PFT-specific outputs
* Unless otherwise defined, variables in ISIMIP should be reported relative to the grid cell land area.
* The output provided per Plant Functional Type (PFT) should be expressed relative to the respective PFT area so that e.g. sum(gpp-pft\*pft-pft)=gpp-total.
* When your model allows several PFTs to grow on the same area and hence the total cover fraction can be more than one, please scale the PFT area to one and report this step in the model documentation on the ISIMIP homepage.
* When your model grows the same PFT on different land-use classes, e.g. the same c3-grass represents grasses growing on natural grasslands, pasture and possible even as crop, please differentiate this in your output by defining land-use specific PFT such as c3-grass-pasture, c3-grass-natural, c3-grass-crop and report this in model documentation on the ISIMIP homepage.
* For better understanding the abbreviations in the filename please provide the full PFT name in a `pft` variable attribute.
::: show sector=peat,permafrost
#### Information about soil organic carbon pools of different turnover times
Some variables can be provided separately by soil organic carbon pools of different turnover times, if your model simulates those. This is done using the `-<pool>` extension. Please indicate them as `-fast`, `-slow`, and `-passive` and describe your definition of the turnover times in your model description. The extension is used in addition to the extension expressing the Plant Functional Type (PFT) and needs to put before it.
::: show sector=peat
#### Information about peat outputs
All variables should be reported separately for the peat fraction of the grid cell if they are calculated separately for peat and non-peat grid-cell fractions, with a peattype (`<pt>`) extension to the variable name. This extension can be `-naturalpeat`, `-drainpeat`, `-restorepeat`, or `-minl` for the non-peat (mineral) gridcell fraction. It is used in addition to the extension expressing the Plant Functional Type (PFT) and needs to put before it.
::: show sector=health
#### Additional instructions for the health sector
* If different realizations of the model are applied, then these should be indicated by the specifier `<r>`.
E.g. to reflect a central, upper, and lower estimate of the ERF: `<r> = lower, central, upper`.
Please explain the meaning of these realizations in the online model documentation; contact the ISIMIP coordination team in case of questions.
* If data are disaggregated e.g. by age group, gender, etc., they should be reported along an additional
dimension, described by an auxiliary coordinate variable, in the NetCDF files. See the example provided
at <https://www.isimip.org/protocol/preparing-simulation-files/>.
* For local (non-gridded) data, locations (cities/regions/countries) should be reported along an additional
dimension called location, with the location name given as string in an auxiliary coordinate variable
called location_name, in the NetCDF files. In addition, coordinates of the location should be reported
in auxiliary variables called location_lat and location_lon. See the example provided at
<https://www.isimip.org/protocol/preparing-simulation-files/>. The `<region>` specifier in the
file name should be set to `local`. For gridded data, the `<region>` specifier in the file name
should be `global` or indicate a region or country.
::: show sector=labour
#### Additional instructions for the labour sector
* The analysis uses a large collection of micro-survey data to estimate new, and robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply at both individual and sub-national regions across the world. The specifications control for income and both location (sub-national region/country) and temporal (week/month/year) fixed-effects along with extreme events such as droughts. In the case of country-specific studies using micro-surveys (Antonelli et al. 2020; Shahegh et al. 2020; Shahegh and Dasgupta 2022), specifications also include socioeconomic and demographic drivers such as gender, age, education, and total income. The response-functions are estimated separately for working conditions; high-exposure/outdoor in the sun (e.g. agricultural, hunting, forestry and fishing; mining and quarrying; and construction) and low-exposure/outdoor in the shade or indoor (e.g. manufacturing and utilities).
* This sector uses an augmented mean function, created from an ensemble of five labour productivity response-functions reported in Dasgupta et al. 2021.
M1) Pilcher et al., 2002: Psychological performance, e.g. reaction time, tracking or memory task, at global scale.
M2) Dunne et al., 2013: Individual capacity to safely perform heavy labour under heat stress at global scale.
M3) Kjellstrom et al., 2014: Reduction of hourly work capacity for heavy work following the ISO standard at global scale.
M4) Sahu et al., 2013: Work output per hour of rice farmers calculated by number of rice bundles laid down, at country-level for India.
M5) Li et al., 2016: Time efficiency measures; direct, indirect, and idle time of rebar construction workers, at country-level for China.
Work is underway to estimate labour productivity response-functions using empirical analysis.
::: show sector=fs-n
#### Additional instructions for the food-security and nutrition (FS-N) sector
* This sector will use additional data: cereal import dependency from FAOSTAT (to prescribe dependence on trade or subsistence farming), age distribution and income level data. Econometric specifications will control for income and inequality (HDI). Data on trade dependency, subsistence farming, and age distribution will allow segregated projections considering vulnerability in terms of population dependency ratio and import dependency.
* Please consider that for simulations based on empirical models, not all the socioeconomic variables are used for projections. This is standard practice to isolate the climate signal. In these cases, variables used should be specified in the model output documentation.
::: show sector=water_quality
#### Note regarding additional forcings for the Water quality sector
Additional agricultural-related model inputs such as N biological fixation, crop uptake, grassland uptake, animal manure use in cropland and on grassland and livestock numbers are not available for ISIMIP3b Groups I+II. These additional forcings will be available to simulate ISIMIP3b (Group III). The same holds for additional human-related model inputs for point sources such as sewage connections of urban/rural population, treatment removal fractions, anthropogenic point source inputs to surface waters (total effluents), wastewater production, collection, treatment and reuse.
::: hide sector=agriculture,biomes,fire,peat,permafrost,health,water_quality
No sector specific notes are available for this selection of simulation round and sectors.
::: show simulation_round=ISIMIP3b
### 4.5 Bias adjustment
Depending on the used climate input data, the corresponding bias adjustment needs to be part of the output filename.
::: table identifier=bias_adjustment caption="Table 4.11: Bias adjustment specifiers."