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.
| 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 |
Netcdf files are downloaded from the THREDDS web server, as recommended for rectangular subsets of the global data.
Using the function is easy enough:
library(datazoom.amazonia)
# Downloading maximum temperature data from 2000 to 2020
max_temp <- load_climate(dataset = "max_temperature", time_period = 2000:2020)
# Downloading precipitation data only for the legal Amazon in 2010
amz_precipitation <- load_climate(dataset = "precipitation",
time_period = 2010,
legal_amazon_only = TRUE)