rnoaa (version 0.6.0)

gefs: Get GEFS ensemble forecast data for a specific lat/lon.

Description

Fetches GEFS forecast data for every 6 hours out to 384 hours past selected date. GEFS is an ensemble of 21 models that can be summarized to estimate likelihoods of forecasts.

Usage

gefs(var, lat, lon, ...)
gefs_CONNECT(date = format(Sys.time(), "%Y%m%d"), forecast_time = c("0000", "0600", "1200", "1800"))
gefs_GET(var, lat, lon, date = format(Sys.time(), "%Y%m%d"), forecast_time = c("0000", "0600", "1200", "1800"), ens_idx = 1:21, time_idx = 1:65, dims = NULL, raw = FALSE, ...)
gefs_latitudes(con = NULL, ...)
gefs_longitudes(con = NULL, ...)
gefs_variables(con = NULL, ...)
gefs_dimensions(con = NULL, ...)
gefs_dimension_values(dim, con = NULL, ...)

Arguments

var

the variable to get. Must be one of the variables listed in gefs_variables().

lat, lon

the longitude. Will be converted to the nearest GEFS available longitude. If lon is a list of vlaues, it must be a sequential list, and data are returned for the number of longitudes in the list starting with the maximum value and incrementing through the indexed values for the length of the list.

...

additional parameters passed to ncvar_get.

date

A date/string formatted as YYYYMMDD.

forecast_time

a string indicating which time of day UTC the forecast is from. Options are "0000", "0600", "1200", "1800".

ens_idx

sequential list of ensembles to fetch. Default is all 21. Note that the ensembles are labelled 0-20, so ens_idx=1:3 will return ensembles 0, 1, and 2.

time_idx

sequential list of time increments to return. List is the index of times, which are in 6 hour increments. (e.g. c(1,2) fetches the 6 and 12 hour forecast.)

dims

(not implemented) indices for additional dimensions to be included between lat, lon, ens, and time.

raw

logical to indicate whether to return raw data matrix or reshaped data frame.

con

an ncdf4 connection.

dim

(character) the dimension.

Value

a list containing metadata and accompanying data frame of forecast values. If lat/lon are not specified, the $data is an unprocessed matrix.

References

• Data description - http://bit.ly/noaagefs.
• Adapted from Python code written by Von P. Walden, Washington State University.

Examples

## Not run: 
# 
# #avialable latitudes and longitudes
# gefs_latitudes()
# gefs_longitudes()
# 
# #get a list of all gefs variables
# gefs_variables()
# 
# #All GEFS dimensions
# gefs_dimensions()
# 
# #values for a specific dimension
# gefs_dimension_values("height_above_ground")
# 
# #example location.
# lat <- 46.28125
# lon <- -116.2188
# 
# #Get forecast for a certain variable.
# forecast <- gefs("Total_precipitation_surface_6_Hour_Accumulation_ens", lat, lon)
# 
# #Fetch a different date (available up to 10 days prior to today)
# forecast_yesterday_prec <- gefs("Total_precipitation_surface_6_Hour_Accumulation_ens",
#                                lat,
#                                lon,
#                                date=format(as.Date(Sys.time()) - 1, "%Y%m%d"))
# 
# #specific ensemble and times, for the 1800 forecast.
# # here ensembles 1-3 (ensembles are numbered starting with 0)
# # and time for 2 days from today at 1800
# date=format(as.Date(Sys.time()) - 1, "%Y%m%d")
# var <- "Temperature_height_above_ground_ens"
# gefs(var, lat, lon, date = date, forecast_time = "1800", ens_idx=2:4, time_idx=1:8)
# 
# #One ensemble, all latitudes and longitudes (this is a big file) for the
# # next 3 days.
# # gefs(var, ens=1, time=1:12)
# ## End(Not run)