processClimateIndices: processClimateIndices
In aWhereAPI/aWhere-R-Charts: Make Charts using output from aWhere API

Description Usage Arguments Details Value References Examples

processClimateIndices Process aWhere weather data to generate climate indices

processClimateIndices(
  dataToUse,
  variable,
  variable_rightAxis = NULL,
  startYearOfSeasonToPlot = NULL,
  season.monthDay_start = "01-01",
  season.monthDay_end = "12-31",
  years.LTN = seq(2006, 2020, 1),
  title = NULL,
  e_precip = FALSE,
  e_threshold = 35,
  indexSpecificValue = NULL,
  offline_mode = FALSE
)

`variable`	character string denoting the variable to chart. Acceptable values are maxLenDrySpell, maxLenWetSpell, numFrostDays, numSummerDays, numIcingDays, numTropicalNights, minOfMaxTemp, maxOfMaxTemp, minOfMinTemp, maxOfMinTemp, dailyTempRange, maxSingleDayPrecip, max5ConsDayPrecip, simplePrecipIntensityIndex, precipSumExceedPercentile, warmSpellDurIndex, coldSpellDurIndex, countDaysPrecipExceedAmount, percentDaysMinTempBelowQuantile, percentDaysMaxTempBelowQuantile, percentDaysMinTempAboveQuantile, percentDaysMaxTempAboveQuantile, maxOfAccumulatedPet, sumOfGDD, sumOfPET, sumOfPrecip, sumOfSolar, sumOfPOverPET, averageMaxTemp, averageMinTemp, averageMaxRH, averageMinRH, averageWind, and maxWindGust
`variable_rightAxis`	What variable to plot over the primary variable. The right y-axis of the plot will be used to present its range. Note that it will always be plotted as a line chart. Same valid values as the variable param. (optional)
`startYearOfSeasonToPlot`	Specify the start year of the "season" you want plotted for the current time period. For example if you specify 2020 here and season.monthDay_start is '08-01' and season.monthDay_end is '12-15' the current time period will begin on '2020-01-01' and end on '2020-12-15'. Dates will be adjusted properly if the season goes over Jan 1st.
`season.monthDay_start`	Specify the start month-day combination of the "season" you want analyzed (optional)
`season.monthDay_end`	Specify the end month-day combination of the "season" you want analyzed (optional)
`years.LTN`	specify the years over which you want the LTN calculated. Defaults to 2006-2020 (optional)
`title`	character string of title to assign to the plot. (optional)
`e_precip`	logical, if set to TRUE, effective precipitation will be calculated and charted based on e_threshold. Default is set to FALSE. (optional)
`e_threshold`	numeric value (in milimeters) for the daily maximum used to calculate effective precipitation if e_precip is set to TRUE. (optional)
`indexSpecificValue`	For the Climate Indices this tool can plot the user can override the default value of the index using this parameter (optional)
`offline_mode`	Set to TRUE to work in offline mode and not attempt to fetch data from the aWhere API (optional)
`data`	data frame in which variables are named according to the schema output by generateaWhereDataset.R (required)

This function extends the aWhere charts package to generate the ETCCDI climate change indices (reference below). Most indices are implement with the default behavior described int he publication. Default values of the indices can be overriden using the "indexSpecificValue" parameter.

Also has helper functions including to automatically (with user permission) download missing but needed data and store in the aWhereEnv to persist it throughout a user R session.

list

http://etccdi.pacificclimate.org/list_27_indices.shtml

## Not run: processClimateIndices(data = weather_df
                                     ,variable = "seasonTotalPrecip"
                                     ,season.monthDay_start = '09-01'
                                     ,season.monthDay_end = '11-30'
                                     ,years.LTN = seq(2010,2019,1)
                                     ,e_precip = TRUE
                                     ,e_threshold = 10)
## End(Not run)