# TerraClimate

Spatial data on several climate variables, extracted from Climatology Lab’s TerraClimate. The table below shows all possible variables to be extracted, which are chosen through the “dataset” parameter. Data ranges from 1958 to 2020.

Netcdf files are downloaded from the THREDDS web server, as recommended for rectangular subsets of the global data.

Click to see all dataset options

Dataset | Code | Description | Units
--- | --- | --- | ---
max_temperature | tmax | Maximum 2-m Temperature | degC
min_temperature | tmin | Minimum 2-m Temperature | degC
wind_speed | ws | Wind Speed at 10-m | m/s
vapor_pressure_deficit | vpd | Vapor Pressure Deficit | kPa
vapor_pressure | vap | 2-m Vapor Pressure | kPa
snow_water_equivalent | swe | Snow Water Equivalent at End of Month | mm
shortwave_radiation_flux | srad | Downward Shortwave Radiation Flux at the Surface | W/m^2
soil_moisture | soil | Soil Moisture at End of Month | mm
runoff | q | Runoff | mm
precipitation | ppt | Accumulated Precipitation | mm
potential_evaporation | pet | Reference Evapotranspiration | mm
climatic_water_deficit | def | Climatic Water Deficit | mm
water_evaporation | aet | Actual Evapotranspiration | mm
palmer_drought_severity_index | PDSI | Palmer Drought Severity Index | unitless

Options:

1. dataset: picks the variable to be read. Possible options are shown in the table above.

2. raw_data: there are two options:

   - `TRUE`: if you want the data as it is originally.
   - `FALSE`: if you want the treated version of the data.

3. time_period: picks the years for which the data will be downloaded

4. language: you can choose between Portuguese `("pt")` and English `("eng")`

5. legal_amazon_only: if set to `TRUE`, only downloads data from the Legal Amazon region

OBS: A good internet connection is needed, because the data is heavy.

Examples:

    # Downloading maximum temperature data from 2000 to 2001
    max_temp <- load_climate(dataset = "max_temperature", time_period = 2000:2001)

    # Downloading precipitation data only for the legal Amazon in 2010
    amz_precipitation <- load_climate(
      dataset = "precipitation",
      time_period = 2010,
      legal_amazon_only = TRUE
    )