Access to several Numerical Weather Prediction services both in raster format and as a time series for a location.

Description

meteoForecast is a package to access outputs from Numerical Weather Prediction models both in raster format and as a time series for a location. Currenty it works with GFS, MeteoGalicia, NAM, and RAP.

Details

getRaster, getRasterDay, and getRasterDays get data inside a bounding box and provide a multilayer raster data using the RasterBrick class defined in the package raster.

getPoint, getPointDays, and getPointRuns get data for a certain location and produce a time series using the zoo class.

Author(s)

Oscar Perpiñán, with contributions from Marcelo Almeida

References

https://www.meteogalicia.gal/web/modelos/threddsIndex.action?request_locale=es

https://www.ncei.noaa.gov/thredds/catalog/model-gfs-003-files/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-nam218/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-rap130/catalog.html

See Also

raster zoo

Forecast Variables available in each model.

Description

The grepVar retrieves the XML file with the names, description, and labels of each variable available in the service, and searches for matches in the description field.

Usage

grepVar(x, service, day = Sys.Date() - 1, complete = FALSE)

Arguments

Value

If complete = TRUE this function provides a data.frame with three columns, name, label, and description. Use the elements of the name column to choose a variable with the argument var of getRaster and getPoint.

Source

https://mandeo.meteogalicia.es/thredds/catalogos/WRF_2D/catalog.html

https://mandeo.meteogalicia.es/thredds/catalog/gfs_0p25/fmrc/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-nam218/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-rap130/catalog.html

Examples

## Not run: 
## Variables available recently
grepVar('cloud', service = 'gfs', complete = TRUE)

## Variables available some days ago
grepVar('cloud', service = 'nam',
        day = Sys.Date() - 10,
        complete = TRUE)

## You can get the complete list with x = ""
grepVar("", service = 'meteogalicia', complete = TRUE)

## End(Not run)

NWP forecasts for a location

Description

The getPoint* functions get outputs of the NWP models run by MeteoGalicia and NCEP (GFS, RAP, NAM) for a single location.

Usage

getPoint(point, vars = "swflx", day = Sys.Date(), run = "00",
         resolution = NULL, vertical = NA, service = mfService())

getPointDays(point, vars = "swflx", start = Sys.Date(), end,
             service = mfService(), ...)

getPointRuns(point, var = "swflx",
             start = Sys.Date() - 1, end = Sys.Date(),
             service = mfService(), ...) 

Arguments

Details

These functions download data from the MeteoGalicia and NCEP (GFS, RAP, NAM) servers using the NetCDF Subset Service. The result is returned as a zoo time series object, with one or more csv files stored in the temporary folder (as defined by tempdir()).

Value

getPoint and getPointDays produce a zoo time series with a column for each variable included in vars.

The time series returned by getPoint starts at 01UTC of day if run = '00' or 13UTC if run = '12'. It spans over 4 days (96 hours) if run = '00' or 84 hours if run = '12'.

The time series returned by getPointDays starts at 01UTC of start and finishes at 00UTC of end + 1. Each day comprised in the time period is constructed with the forecast outputs corresponding to the 00UTC run of that day. Therefore, only the first 24 values obtained with getPoint are used for each day.

The time series returned by getPointRuns starts at 01UTC of start and finishes at 00UTC of end + 1. It has 4 columns, named "D3_00", "D2_00", "D1_00" and "D0_00". The column "D3_00" corresponds to the forecast results produced 3 days before the time stamp of each row, and so on.

Author(s)

Oscar Perpiñán Lamigueiro with contributions from Marcelo Almeida

References

https://mandeo.meteogalicia.es/thredds/catalogos/WRF_2D/catalog.html

https://mandeo.meteogalicia.es/thredds/catalog/gfs_0p25/fmrc/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-nam218/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-rap130/catalog.html

See Also

getRaster

Examples

## Not run: 
  ## If some of the next examples do not work, try using a different
  ## date. Check availability for each service with the links included in
  ## the references section.
  testDay <- Sys.Date() - 1

  ## temperature (Kelvin) forecast from meteogalicia
  tempK <- getPoint(c(0, 40), vars = 'temp', day = testDay)
  ## Cell does not coincide exactly with request
  attr(tempK, 'lat')
  attr(tempK, 'lon')
  ## Units conversion
  tempC <- tempK - 273

  library(lattice)
  ## Beware: the x-axis labels display time using your local timezone.
  Sys.timezone()

  ## Use Sys.setenv(TZ = 'UTC') to produce graphics with the timezone
  ## of the objects provided by meteoForecast.
  xyplot(tempC)

  ## Multiple variables
  vars <- getPoint(c(0, 40), vars = c('swflx', 'temp'), day = testDay)
  xyplot(vars)

  ## Vertical coordinates
  tempK1000 <- getPoint(c(0,40),
                        vars = "Temperature_surface",
                        day = testDay,
                        service ="gfs", vertical = 1000)

  ## Time sequence
  radDays <- getPointDays(c(0, 40),
                          start = testDay - 3,
                          end = testDay)
  
  xyplot(radDays)

  ## Variability between runs
  radRuns <- getPointRuns(c(0, 40),
                          start = testDay - 3,
                          end = testDay)
  xyplot(radRuns, superpose = TRUE)
  
  ## variability around the average
  radAv <- rowMeans(radRuns)
  radVar <- sweep(radRuns, 1, radAv)
  xyplot(radVar, superpose = TRUE)

## End(Not run)

NWP forecasts for a region

Description

The getRaster* functions get outputs of the NWP models for a region.

Usage

getRaster(var = "swflx", day = Sys.Date(), run = "00",
          frames = 'complete', box, resolution = NULL,
          names, remote = TRUE, service = mfService(),
          dataDir = ".", use00H = FALSE, ...)

getRasterDays(var = "swflx", start = Sys.Date(), end,
              remote = TRUE, dataDir = ".", ...)

getRasterDay(var = "swflx", day = Sys.Date(),
              remote = TRUE, dataDir = ".", ...)

checkDays(start, end, vars, remote = FALSE,
          service = mfService(), dataDir = '.')

Arguments

Details

getRaster downloads data from the MeteoGalicia and NCDC (GFS, RAP, and NAM) servers using the NetCDF Subset Service. The result is returned as a RasterBrick object, with one or more NetCDF files stored in the temporary folder (as defined by tempdir()). Each frame or layer of the RasterBrick corresponds to a certain hour of the forecast.

getRasterDay uses getRaster to download the results corresponding to a certain day. If the day is in the future, the most recent forecast is downloaded with getRaster, and the corresponding frames are extracted. If the day is in the past, getRaster is used to download the corresponding frames of the forecast produced that day.

getRasterDays uses getRaster to download the results cast each day comprised between start and end using the 00UTC run. Then it subsets the first 24 frames of each result, and binds them together to produce a RasterBrick. Therefore, each frame of this RasterBrick is a forecast for an hour of the day when the forecast was cast.

checkDays explores a local folder looking for NetCDF files corresponding to a time sequence and a set of variables. It returns a Date vector comprising the days with files available for the requested variables. If remote = TRUE it only checks that start is after 2008-01-01 (first date of the archived forecasts of MeteoGalicia.)

Value

The getRaster* functions return a RasterBrick with a layer for each hour of the NWP forecast.

The time zone of the time index of this RasterBrick, stored in its z slot (accesible with getZ) is UTC.

MeteoGalicia, NAM, and RAP use the Lambert Conic Conformal projection. GFS files use longitude-latitude coordinates.

Author(s)

Oscar Perpiñán with contributions from Marcelo Almeida.

References

https://mandeo.meteogalicia.es/thredds/catalogos/WRF_2D/catalog.html

https://mandeo.meteogalicia.es/thredds/catalog/gfs_0p25/fmrc/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-nam218/catalog.html

https://www.ncei.noaa.gov/thredds/catalog/model-rap130/catalog.html

Examples

## Not run: 

## If some of the next examples do not work, try using a different
## date. Check availability for each service with the links included in
## the references section.

testDay <- Sys.Date() - 1

## Retrieve raster data
wrf <- getRaster('temp', day = testDay)

## Display results with rasterVis
library(rasterVis)

levelplot(wrf, layers = 10:19)

hovmoller(wrf)

## Using box and frames specification
mfExtent('gfs')

cloudGFS <- getRaster('Temperature_surface',
                      day = testDay,
                      box = c(-30, 30, 30, 50),
                      service = 'gfs')

levelplot(cloudGFS, layout = c(1, 1))

mfExtent('nam')
cloudNAM <- getRaster('Temperature_surface',
                      day = testDay,
                      box = c(-100, -80, 30, 50),
                      frames = 10,
                      service = 'nam')
mfExtent('rap')
cloudRAP <- getRaster('Temperature_surface',
                      day = testDay,
                      box = c(-100, -80, 30, 50),
                      frames = 10,
                      service = 'rap')


## Day sequence of cloud cover
wrfDays <- getRasterDays('cft',
                         start = testDay - 3,
                         end = testDay + 2,
                         box = c(-2, 35, 2, 40))

levelplot(wrfDays, layers = 10:19)

## animation
levelplot(wrfDays, layout = c(1, 1), par.settings = BTCTheme)

## Hövmoller graphic
hovmoller(wrfDays, par.settings = BTCTheme, contour = TRUE, cuts = 10)

NAMDays <- getRasterDays('Temperature_surface',
                         start = testDay - 3,
                         end = testDay,
                         box = c(-100, -80, 30, 50),
                         service = 'nam')

## Extract data at some locations

st <- data.frame(name=c('Almeria','Granada','Huelva','Malaga','Caceres'),
               elev=c(42, 702, 38, 29, 448))

coordinates(st) <- cbind(c(-2.46, -3.60, -6.94, -4.42, -6.37),
                         c(36.84, 37.18, 37.26, 36.63, 39.47)
                         )
proj4string(st) <- '+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0'


## Extract values for some locations
vals <- extract(wrf, st)
vals <- zoo(t(vals), getZ(wrf))
names(vals) <- st$name

xyplot(vals)

## End(Not run)

Options and Internal Variables

Description

Functions to get or set options, and to access internal parameters of the package.

Usage

getMFOption(name = NULL)
setMFOption(name, value)
mfService(service = NULL)
mfExtent(service, resolution = 12)
mfProj4(service, resolution = 12)

Arguments

Details

Use getMFOption to list the options of the package. Only one option, service, is available with this version. With setMFOption the option defined with name can be modified.

mfService, a wrapper around getMFOption and setMFOption, displays the default service if used without arguments. It modifies the default service to the value of its argument.

mfExtent and mfProj4 provides the extent and the proj4 string of the corresponding service.

Author(s)

Oscar Perpiñán Lamigueiro

Examples

mfService()

mfExtent('meteogalicia', 36)

mfExtent('nam')

mfProj4('rap')