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A function that extract a time series of climate variables (1958-01-01T00:00:00Z - 2021-12-01T00:00:00).

Usage

get_climate(from, to, by, band, region, fun = "count", scale = 1000)

Arguments

to, from

it's a string object,starting and final date.

by

two types of increment of the sequence by month and year.

band

name of band.

region

is a feature or feature collection.

fun

function for extract statistic zonal (count, kurtosis, max, mean, median, min, mode, percentile, std, sum, variance, first).

scale

A nominal scale in meters of the projection to work in.

Value

a tibble object with the new variables.

Details

Name of some bands.

  • aet (mm): Actual evapotranspiration, derived using a one-dimensional soil water balance model.

  • def (mm): Climate water deficit, derived using a one-dimensional soil water balance model.

  • pdsi : Palmer Drought Severity Index.

  • pet(mm): Reference evapotranspiration (ASCE Penman-Montieth).

  • pr (mm): Precipitation accumulation.

  • ro (mm): Runoff, derived using a one-dimensional soil water balance model.

  • soil (mm): Soil moisture, derived using a one-dimensional soil water balance model.

  • srad (W/m²): Downward surface shortwave radiation.

  • swe (mm): Snow water equivalent, derived using a one-dimensional soil water balance model.

  • tmmn (°C): Minimum temperature.

  • tmmx (°C): Maximum temperature.

  • vap (kPa): Vapor pressure

  • vpd (kPa): Vapor pressure deficit.

  • vs (m/s): Wind-speed at 10m.

Examples

if (FALSE) {

library(tidyverse)
library(rgee)
library(innovar)
library(sf)
ee_Initialize()

# 1. Reading a sf object
data("Peru")
region <- Peru
region_ee <- pol_as_ee(region , id = 'distr' , simplify = 1000)
# 2. Extracting climate information
data <- region_ee %>% get_climate(
  from = "2001-02-01", to = "2002-12-31",
  by = "month", band = "tmmx", fun = "max")
}