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PLEASE READ:
This data is a preliminary version of what has been produced. It has not been
peer reviewed or published in any way. It is provided AS-IS and should be used
with care. The data has been produced using an experimental version of
relative humidity as well as experimental versions of the models.
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The files are organized below this level by type of climate model (era5wrf or
historical, wrf_bc or WRF bias corrected, and loca2). Each is available through
the Analytics Engine at CalAdapt. The next level in the tree will be a climate
model name that include the GCM, the SSP value, and the run ID.

<climate group>/<climate name>/<model>/<model specific layout and data>

where
    <climate group> is one of era5wrf, wrf_bc, or loca2
    <climate name> is the name of the climate mode (GCM, SSP, and run ID)
    <model> is the name of the model producing data (one of LANDIS-II, WesterlingFireModel, or LUCAS)

The <model specific layout and data> depends on which model is being looked
at. This will be broken down by model below.

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WesterlingFireModel:

The Westerling Lab Fire Model has models for fire presence/absence, fire size,
fire severity fractions, and a 30m downscaling model. The presence/absence,
fire size, and fire fractions are combined in the data in this section to
produce lists of fires based on 2020 LUCAS historical vegetation estimations.
The fire lists are based on a 3km grid (Teale Albers projection) and include
size in Ha (also a "clean" size that has capped the size to a maximum of
3,000,000 Ha) and severity fractions (low, moderate, high) for both the
uncapped and "cleaned" size and in Ha or percentage [0,1). There is also a
unique ID for each fire in the list, x and y coordinates of the centroid pixel,
year/month/day (semimonthly) of the fire, and the EPA L3 ecoregion code and
name.

There are also 3km burned area maps that annualize and spread fires in the fire
lists into one burned area map per year. Each pixel shows an expected number of
hectares burned within that pixel over all 2000 iterations. A particular pixel
that receives more fires over the course of the iterations can have a value
greater than the possible area of that pixel. The spread is approximated by
using circular fires and a maximum area of 85% of any pixel to be burned.

The fire lists are found in the WesterlingFireModel directory as fireList_*.csv
(or .rda for R data table format). The * could include a shorthand for the GCM
(such as CESM2 or CNRM) and also the range of iterations of the fire lists. The
burned rasters are in the subdirectory BurnRasters and have the name format of
burned_3km_TA_<year>.tif


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LANDIS-II

The LANDIS-II data containss both vegetation statistic maps and fire intensity
maps. These are on a 150m grid. The original processing was by region, but
these have been merged into a statewide map. Each replicate has annual data for
various statistics:

    AG_NPP - aboveground net primary productivity (g/m^2)
    ANEE_proc - aboveground net ecosystem exchange (g/m^2)
    CWHR_fortype - species or mix of species that has the most biomass in a cell (categorical)
    TotalBiomass - aboveground biomass (g/m^2)
    TotalC - above and belowground biomass stocks, all sources (g/m^2)
    bda_insects - insect or disease vector (categorical)
    biomass-removed - amount of aboveground biomass removed from the cell from a given management activity (g/m^2)
    fire_severity - categorical fire severity (categorical)
    prescripts - management activity (categorical)

These data are sorted within any given climate scenario by vegetaion management
ambition (Veg-BAU for business as usual or low ambition and Veg-HighAmbition
for high ambition management). Within these vegetation management directories
will be directories for each full replicate (all regions). The data maps are
found in these replicate directories as CA_<statistic>_<year>.tif where
the <statistic> is as above

Specific categorical values for these rasters (especially categorical) can be
found in the landis_combinedoutput_metadata.csv file.