rainy_season: Determine start and end date of the rainy season
In tpilz/LUMP: Landscape Unit Mapping Program for R

rainy_season

R Documentation

Determine start and end date of the rainy season

Description

Function calculates the yearly start and end dates of the rainy season from a precipitation time series based on a statistical approach as described by Gerstengarbe & Werner (1999).

Usage

rainy_season(prec_ts = NULL, dry_season = NULL, nodata = NA)

Arguments

`prec_ts`	Daily precipitation time series object of class `xts`. Data should be a numerical vector or a matrix with one named column per station a time series is available for.
`dry_season`	Day of year in the expected centre of dry season. This is the starting point of the stastical procedure to look for the next rainy season in the data set. Should be set approximately (+- 1 month) to the centre of the dry season.
`nodata`	No-data value in the time series. Default: `NA`.

Value

data.frame of rainy season start and end days in input format for the hydrological model WASA.

Columns are: station ID (column names of input xts object), year, start day of rainy season (negative values refer to the previous year), day of year the climax of the vegetation season is reached, end day of rainy season, last day of transition period from rainy to dry season (values greater than 365/366 refer to the next year).

Note

The first rainy season that can be identified by the function is the one that starts after the first dry season in the given time series. This means, for instance, that if the time series starts on Jan 1st 1978 and dry_season is set to 243 (conditions for NE Brazil), the first detectable rainy season is the one starting around Dec 78 to Feb 79. To get also the rainy season for year 1978 for this example, 365 daily values can be artifically inserted at the beginning of the time series, representing the hypothetical year 1977. Just copy the data of 1978.

Author(s)

Tobias Pilz tpilz@uni-potsdam.de

References

lumpR package introduction with literature study and sensitivity analysis:
Pilz, T.; Francke, T.; Bronstert, A. (2017): lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models. Geosci. Model Dev., 10, 3001-3023, doi: 10.5194/gmd-10-3001-2017

Function uses the FORTRAN 77 code developed by Gerstengarbe et al.. The algorithm is described in:

Gerstengarbe & Werner (1999): Estimation of the beginning and end of recurrent events within a climate regime. Climate Research, 11(2), 97-107.

Function further used by A. Guentner to simulate vegetation dynamics within the hydrological model WASA:

Guentner, A. (2002): Large-scale hydrological modelling in the semi-arid North-East of Brazil. PIK Report 77, Potsdam Institute for Climate Impact Research, Potsdam, Germany.

tpilz/LUMP documentation built on Aug. 5, 2023, 1:31 a.m.