<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Climate Services' Indicators Based on Sub-Seasonal to Decadal
Predictions</dc:title>
  <dc:title>R package CSIndicators version 1.2.0</dc:title>
  <dc:description>Set of generalised tools for the flexible computation of climate 
  related indicators defined by the user. Each method represents a specific 
  mathematical approach which is combined with the possibility to select an 
  arbitrary time period to define the indicator. This enables a wide range of 
  possibilities to tailor the most suitable indicator for each particular climate 
  service application (agriculture, food security, energy, water management, health...). 
  This package is intended for sub-seasonal, seasonal and decadal climate 
  predictions, but its methods are also applicable to other time-scales, 
  provided the dimensional structure of the input is maintained. Additionally, 
  the outputs of the functions in this package are compatible with 'CSTools'. 
  This package is described in Pérez-Zanón et al. (2023) 
  &lt;doi:10.1016/j.cliser.2023.100393&gt; and was developed in the context of the 
  H2020 projects MED-GOLD (776467) and S2S4E (776787) projects, as well as the 
  Horizon Europe project MEDEWSA (101121192) and the national project BOREAS 
  (PID2022-140673OA-I00). See Lledó et al. (2019) 
  &lt;doi:10.1016/j.renene.2019.04.135&gt; and Chou et al., 2023 
  &lt;doi:10.1016/j.cliser.2023.100345&gt; for details.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.6.0)</dc:relation>
  <dc:relation>Imports: multiApply (&gt;= 2.1.1), stats, ClimProjDiags, CSTools, SPEI,
lmom, lmomco, zoo, s2dv, lubridate, geosphere</dc:relation>
  <dc:relation>Suggests: testthat, knitr, markdown, rmarkdown</dc:relation>
  <dc:creator>Victòria Agudetse &lt;victoria.agudetse@bsc.es&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Nuria Perez-Zanon [aut] (ORCID:
    &lt;https://orcid.org/0000-0001-8568-3071&gt;),
  Chou Chihchung [aut],
  Llorenç Lledó [aut],
  Victòria Agudetse [ctb, cre],
  Eva Rifà [ctb],
  González-Reviriego Nube [ctb],
  Marcos Raül [ctb],
  Palma Lluis [ctb],
  An-Chi Ho [ctb],
  Javier Corvillo [ctb],
  Alberto Bojaly [ctb],
  Theertha Kariyathan [ctb],
  BSC-CNS [cph]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2026-03-11</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=CSIndicators</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.CSIndicators</dc:identifier>
</oai_dc:dc>
