doi:10.1007/s12517-019-4454-5>. It supports different aggregation methods, such as sum, min, max, mean, and standard deviation. These functions are designed for spatio-temporal analysis of rainfall patterns, trend analysis,geostatistical modeling of rainfall variability, identifying rainfall anomalies and extreme events and can be an input for hydrological and agricultural models.">

CLimd: Generating Rainfall Rasters from IMD NetCDF Data (original) (raw)

The developed function is a comprehensive tool for the analysis of India Meteorological Department (IMD) NetCDF rainfall data. Specifically designed to process high-resolution daily gridded rainfall datasets. It provides four key functions to process IMD NetCDF rainfall data and create rasters for various temporal scales, including annual, seasonal, monthly, and weekly rainfall. For method details see, Malik, A. (2019).<doi:10.1007/s12517-019-4454-5>. It supports different aggregation methods, such as sum, min, max, mean, and standard deviation. These functions are designed for spatio-temporal analysis of rainfall patterns, trend analysis,geostatistical modeling of rainfall variability, identifying rainfall anomalies and extreme events and can be an input for hydrological and agricultural models.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: raster, ncdf4, qpdf
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-01-10
DOI: 10.32614/CRAN.package.CLimd
Author: Nirmal Kumar [aut, cph], Nobin Chandra Paul [aut, cre], G.P. Obi Reddy [aut]
Maintainer: Nobin Chandra Paul <nobin.paul at icar.gov.in>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: no
CRAN checks: CLimd results

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