download climate locations for a single location

get_forecast.R

library(lubridate)
library(dplyr)

####################################################################################
#' Download downscaled climate forecast data
#' 
#' Individual climate models available are are c('CFSv2','CMC1','CMC2','GFDL-FLOR','GFDL','NASA','NCAR'),
#' 'ENSMEAN' is the mean of all models.
#' lead_time is the months into the future to obtain forecasts. Max of 7
#' Default lat and lon are for Portal, AZ

get_climate_forecasts = function(climate_model = 'ENSMEAN', 
                                 lat = 31.9555, lon = -109.0744,
                                 lead_time = 6){

  if(!climate_model %in% c('CFSv2','CMC1','CMC2','GFDL-FLOR','GFDL','NASA','NCAR')) stop(paste0('Unknown climate model: ',climate_model))
  if(!lead_time %in% 1:7) stop(paste0('Lead time must an integer be between 1 and 7, got: ',lead_time))
  
  today = Sys.Date()
  start_time = strftime(today, format='%Y-%m-%d')
  end_time = strftime(today %m+% months(lead_time), format='%Y-%m-%d')
  
  # add in timestamps for URL
  start_time = paste0(start_time,'T00%3A00%3A00Z')
  end_time = paste0(end_time,'T00%3A00%3A00Z')
  
  full_url = paste0('https://tds-proxy.nkn.uidaho.edu/thredds/ncss/NWCSC_INTEGRATED_SCENARIOS_ALL_CLIMATE/bcsd-nmme/monthlyForecasts/bcsd_nmme_metdata_',climate_model,
                    '_forecast_1monthAverage.nc?var=prate&var=tmp2m&latitude=',lat,'&longitude=',lon,'&time_start=',start_time,'&time_end=',end_time,'&accept=csv')
  
  raw_download = RCurl::getURL(full_url)
  
  df=read.table(sep=',',skip=1,text=raw_download)
  colnames(df) = c('date','lat','lon','precip','temperature')
  
  df = df %>%
    mutate(date = as_date(date)) %>%
    mutate(year = year(date), month=month(date)) %>%
    select(-date, -lat, -lon)
  
  return(df)
  
}