evaluateDroughtNemaPrecipitation: Evaluates Drought Conditions Relating to Precipitation Based...
In henningte/herdersWDA: Functions for Raster Based Weather Time Series Analysis

Description Usage Arguments Details Examples

evaluateDroughtNemaPrecipitation evaluates based on precipitation values for a target time period and representing long term mean values as raster based time series (RasterBrick or RasterStack object, if for a given spatial and temporal point drought or near drought conditions are prevalent or not (according to the classification of the NEMA). This function considers only criteria related to precipitation.

1 2	evaluateDroughtNemaPrecipitation(precipitation, ltmprecipitation, precipitation_t, ltmprecipitation_t)

`precipitation`	A `RasterBrick` or `RasterStack` object with (mean) total precipitation values for each time interval within the target time period. See the details section. Time intervals are supposed to represent fixed ten-day intervals.
`ltmprecipitation`	A `RasterBrick` or `RasterStack` object with long-term mean total precipitation values for fixed ten-day intervals within a year. See the details section.
`precipitation_t`	A `POSIXct` vector containing the time information for all layers in `precipitation` as returned by `weatherMean` (each element denoting the first day of the respective ten-day interval).
`ltmprecipitation_t`	A `POSIXct` vector containing the time information for all layers in `ltmprecipitation` as returned by `intervalMean` (each element denoting the first day of the respective ten-day interval).

The start and end time point of the target time interval are derived from timedate_daily. All time intervals of timedate_aggregated are supposed to fit perfectly within timedate_daily (i.e. there are no more or less days in timedate_daily). All Raster* time series data are supposed to have the same spatial extent and resolution.