README.md

In CSIndicators: Climate Services' Indicators Based on Sub-Seasonal to Decadal Predictions

CSIndicators

Sectoral Indicators for Climate Services Based on Sub-Seasonal to Decadal Climate Predictions

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…). 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.

How to cite

Pérez-Zanón, N., Ho, A. Chou, C., Lledó, L., Marcos-Matamoros, R., Rifà, E. and González-Reviriego, N. (2023). CSIndicators: Get tailored climate indicators for applications in your sector. Climate Services. https://doi.org/10.1016/j.cliser.2023.100393

For details in the methodologies see:

Pérez-Zanón, N., Caron, L.-P., Terzago, S., Van Schaeybroeck, B., Lledó, L., Manubens, N., Roulin, E., Alvarez-Castro, M. C., Batté, L., Bretonnière, P.-A., Corti, S., Delgado-Torres, C., Domínguez, M., Fabiano, F., Giuntoli, I., von Hardenberg, J., Sánchez-García, E., Torralba, V., and Verfaillie, D.: Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information, Geosci. Model Dev., 15, 6115–6142, https://doi.org/10.5194/gmd-15-6115-2022, 2022. Chou, C., R. Marcos-Matamoros, L. Palma Garcia, N. Pérez-Zanón, M. Teixeira, S. Silva, N. Fontes, A. Graça, A. Dell'Aquila, S. Calmanti and N. González-Reviriego (2023). Advanced seasonal predictions for vine management based on bioclimatic indicators tailored to the wine sector. Climate Services, 30, 100343, https://doi.org/10.1016/j.cliser.2023.100343. Lledó, Ll., V. Torralba, A. Soret, J. Ramon and F.J. Doblas-Reyes (2019). Seasonal forecasts of wind power generation. Renewable Energy, 143, 91-100, https://doi.org/10.1016/j.renene.2019.04.135.

Installation

You can then install the public released version of CSIndicators from CRAN:

install.packages("CSIndicators")

Or the development version from the GitLab repository:

# install.packages("devtools")
devtools::install_git("https://earth.bsc.es/gitlab/es/csindicators.git")

Overview

To learn how to use the package see:

• Agricultural Indicators
• Wind Energy Indicators

Functions documentation can be found here.

| Function | CST version | Indicators | |--------------------------------|------------------------------------|---------------------------------| |PeriodMean |CST_PeriodMean |GST, SprTX, DTR | |PeriodAccumulation |CST_PeriodAccumulation |SprR, HarR, PRCPTOT | |AccumulationExceedingThreshold |CST_AccumulationExceedingThreshold |GDD, R95pTOT, R99pTOT | |TotalTimeExceedingThreshold |CST_TotalTimeExceedingThreshold |SU35, SU, FD, ID, TR, R10mm, Rnmm| |TotalSpellTimeExceedingThreshold|CST_TotalSpellTimeExceedingThreshold|WSDI, CSDI | |WindCapacityFactor |CST_WindCapacityFactor |Wind Capacity Factor | |WindPowerDensity |CST_WindPowerDensity |Wind Power Density |

| Auxiliar function | CST version | |-------------------|----------------------| |AbsToProbs |CST_AbsToProbs | |QThreshold |CST_QThreshold | |Threshold |CST_Threshold | |MergeRefToExp |CST_MergeRefToExp | |SelectPeriodOnData |CST_SelectPeriodOnData| |SelectPeriodOnDates| |

Find the current status of each function in this link.

Note: the CST version uses 's2dv_cube' objects as inputs and outputs while the former version uses multidimensional arrays with named dimensions as inputs and outputs

Note: All functions computing indicators allows to subset a time period if required, although this temporal subsetting can also be done with functions SelectPeriodOnData in a separated step.

Object class 's2dv_cube'

This package is designed to be compatible with other R packages such as CSTools through a common object: the s2dv_cube object class, used in functions with the prefix CST_. This object can be created from Start (startR package) and from Load (s2dv package) directly.

The class s2dv_cube is mainly a list of named elements to keep data and metadata in a single object. Basic structure of the object:

$ data: [data array]
$ dims: [dimensions vector]
$ coords: [List of coordinates vectors]
  $ sdate
  $ time
  $ lon
  [...]
$ attrs: [List of the attributes]
  $ Variable:
    $ varName
    $ metadata 
  $ Datasets
  $ Dates
  $ source_files
  $ when
  $ load_parameters

More information about the s2dv_cube object class can be found here: description of the s2dv_cube object structure document.

The current s2dv_cube object (CSIndicators 1.0.0 and CSTools 5.0.0) differs from the original object used in the previous versions of the packages. If you have questions on this change you can follow some of the points below:

• New s2dv_cube object discussion in CSTools
• How to deal with the compatibility break in CSIndicators

Contribute

1. Open an issue to ask for help or describe a function to be integrated
2. Agree with maintainers (@ngonzal2, @rmarcos, @nperez and @erifarov) on the requirements
3. Create a new branch from master with a meaningful name
4. Once the development is finished, open a merge request to merge the branch on master

Note: Remember to work with multidimensionals arrays with named dimensions when possible and use multiApply.

Add a function

To add a new function in this R package, follow this considerations:

1. Each function exposed to the users should be in separate files in the R folder
2. The name of the function should match the name of the file (e.g.: Function() included in file Function.R)
3. The documentation should be in roxygen2 format as a header of the function
4. Once, the function and the documentation is finished, run the command devtools::document() in your R terminal to automatically generate the Function.Rd file
5. Remember to use R 4.1.2 when doing the development
6. Code format: include spaces between operators (e.g. +, -, &), before and after ','. The maximum length of lines is of 100 characters (hard limit 80 characters). Number of indentation spaces is 2.
7. Functions computing Climate indicators should include a temporal subsetting option. Use the already existing functions to adapt your code.

CSIndicators documentation built on Nov. 20, 2023, 5:07 p.m.