Skip to contents

Function wraps get_climate_data() and returns precipitation by basin or country in mm as output from all 15 models, for the a1 and b2 scenarios.

Usage

get_model_precip(locator, type, start, end)

Arguments

locator

A vector of either watershed basin ID's from http://data.worldbank.org/sites/default/files/climate_data_api_basins.pdf It can be just a single basin id, or a vector of ids. ids should be strings.

type

the type of data to retrieve, must be "mavg" for monthly averages, "annualavg" for annual averages, "manom" for monthly anomaly, and "annualanom" for annual anomaly.

start

the start year to gather data for.

end

the end year to gather data to.

Value

a dataframe with precipitation predictions in mm for all scenarios, gcms, for each time period.

Details

start and end year can be any years, but all years will be coerced into periods outlined by the API (http://data.worldbank.org/developers/climate -data-api) anomaly periods are only valid for future scenarios and based on a reference period of 1969 - 1999, see API for full details.

Examples

if (FALSE) {
# Get data for 2 basins, annual average precipitation for all valid time periods
# then subset them, and plot
precip_dat <- get_model_precip(c("2","231"),"annualavg",1900,3000)
precip_dat <- subset(precip_dat,precip_dat$gcm=="ukmo_hadcm3")
precip_dat <- subset(precip_dat,precip_dat$scenario!="b1")
ggplot(precip_dat,aes(x=fromYear,y=annualData,group=locator,colour=locator))+geom_path()

### Get data for 4 countries with monthly precipitation values
precip_dat <- get_model_precip(c("USA","BRA","CAN","YEM"),"mavg",2020,2030)
precip_dat <- subset(precip_dat,precip_dat$gcm=="ukmo_hadcm3")
precip_dat <- subset(precip_dat,precip_dat$scenario!="b1")
ggplot(precip_dat,aes(x=as.factor(month),y=monthVals,group=locator,colour=locator))+geom_path()
}