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Accessing Station Data
The function dataInventory is intended for a quick overview of the data contained in the dataset. In the case of stations data, the main argument to be provided is the path to the directory where the dataset (stations.txt, variables.txt and associated data) are stored (see this link for details on station data format).
For instance, this is a quick overview of the built-in dataset in the downscaleR
package using dataInventory
:
# First the path to the directory containing the data is retrieved:
gsn <- file.path(find.package("downscaleR"), "datasets/observations/GSN_Iberia")
di <- dataInventory(gsn)
## [2014-06-03 09:36:27] Doing inventory ...
## [2014-06-03 09:36:27] Done.
The object loaded contains all the necessary information in order to make a call to the loading function loadStationData
, including station codes, geolocation and details on the variable names, units ... :
str(di)
## List of 3
## $ Stations :List of 4
## ..$ station_id : chr [1:6] "SP000008027" "SP000008181" "SP000008202" "SP000008215" ...
## ..$ xyCoords : num [1:6, 1:2] -2.04 2.07 -5.5 -4.01 -1.86 ...
## .. ..- attr(*, "dimnames")=List of 2
## .. .. ..$ : chr [1:6] "SP000008027" "SP000008181" "SP000008202" "SP000008215" ...
## .. .. ..$ : chr [1:2] "lon" "lat"
## ..$ times :List of 3
## .. ..$ startDate: POSIXlt[1:1], format: "1979-01-01"
## .. ..$ endDate : POSIXlt[1:1], format: "2012-12-31"
## .. ..$ timeStep :Class 'difftime' atomic [1:1] 24
## .. .. .. ..- attr(*, "units")= chr "hours"
## ..$ other.metadata:List of 4
## .. ..$ altitude : int [1:6] 251 4 790 1894 704 90
## .. ..$ location : chr [1:6] "SAN SEBASTIAN - IGUELDO" "BARCELONA/AEROPUERTO" "SALAMANCA AEROPUERTO" "NAVACERRADA" ...
## .. ..$ WMO_Id : int [1:6] 8027 8181 8202 8215 8280 8410
## .. ..$ Koppen.class: chr [1:6] "Cfb" "Csa" "BSk" "Csb" ...
## $ Variables :'data.frame': 3 obs. of 4 variables:
## ..$ variable : Factor w/ 3 levels "precip","tmax",..: 1 3 2
## ..$ longname : Factor w/ 3 levels "maximum daily temperature",..: 3 2 1
## ..$ unit : Factor w/ 2 levels "0.1 degC","0.1 mm": 2 1 1
## ..$ missing.code: Factor w/ 1 level "NaN": 1 1 1
## $ Summary.stats: NULL
Note that the last element of the inventory, named Summary.stats
is NULL. Bt default, the inventory will return the basic information, but setting the argument return.stats
to TRUE will return also a table summarizing the characteristics of the data (percentage of missing data, mean, min and max values):
di2 <- dataInventory(gsn, return.stats= TRUE)
## [2014-06-03 09:51:18] Doing inventory ...
## [2014-06-03 09:51:19] Done.
di2$Summary.stats
## $missing.percent
## precip tmin tmax
## SP000008027 0.6 2.3 4.2
## SP000008181 0.7 1.7 1.1
## SP000008202 0.5 4.5 0.8
## SP000008215 0.6 2.7 2.3
## SP000008280 0.5 17.8 4.1
## SP000008410 0.9 10.1 6.0
##
## $min
## precip tmin tmax
## SP000008027 -0.3 -10.0 -3.5
## SP000008181 0.0 -7.2 0.0
## SP000008202 0.0 -12.0 -1.4
## SP000008215 0.0 -17.5 -11.0
## SP000008280 0.0 -13.4 -1.8
## SP000008410 0.0 -8.2 0.0
##
## $max
## precip tmin tmax
## SP000008027 93.0 25.2 38.6
## SP000008181 175.1 26.8 37.4
## SP000008202 50.3 22.0 41.0
## SP000008215 111.8 20.6 31.8
## SP000008280 146.6 23.4 42.0
## SP000008410 154.3 27.0 46.6
##
## $mean
## precip tmin tmax
## SP000008027 1.2266499 10.621573 16.58673
## SP000008181 1.5895889 11.803554 20.44687
## SP000008202 1.0108198 5.791200 18.73546
## SP000008215 1.5650255 3.303088 10.94361
## SP000008280 0.9700607 7.756689 20.23754
## SP000008410 1.5544916 11.311057 24.63882
A more concise summary of the available stations can be obtained using the stationInfo
command. By default, it also returns a map with the locations of the available stations, labelled by their identification codes.
print(stationInfo(gsn))
## [2014-08-30 14:26:48] Doing inventory ...
## [2014-08-30 14:26:48] Done.
## stationID longitude latitude altitude location WMO_Id Koppen.class
## 1 SP000008027 -2.0392 43.3075 251 SAN SEBASTIAN - IGUELDO 8027 Cfb
## 2 SP000008181 2.0697 41.2928 4 BARCELONA/AEROPUERTO 8181 Csa
## 3 SP000008202 -5.4981 40.9592 790 SALAMANCA AEROPUERTO 8202 BSk
## 4 SP000008215 -4.0103 40.7806 1894 NAVACERRADA 8215 Csb
## 5 SP000008280 -1.8631 38.9519 704 ALBACETE LOS LLANOS 8280 BSk
## 6 SP000008410 -4.8458 37.8442 90 CORDOBA AEROPUERTO 8410 Csa
The function loadStationData
is the interface to acces observational datasets. There are several ways in which observations data can be queried. The most common cases are next presented.
Given the station codes provided by the inventory, it is possible to retrieve a time series for a selected station or several time series for several stations directly by the identification codes. This will load summer temperature data (JJA) for the period 1981-2000 for two stations: Albacete - Los Llanos and Cordoba - Aeropuerto:
example1 <- loadStationData(dataset = gsn, var="tmax", stationID = c("SP000008280", "SP000008410"), season = 6:8, years = 1981:2000)
## [2014-06-03 10:13:30] Loading data ...
## [2014-06-03 10:13:30] Retrieving metadata ...
## [2014-06-03 10:13:30] Done.
str(example1)
## List of 6
## $ variable : chr "tmax"
## $ station_id : chr [1:2] "SP000008280" "SP000008410"
## $ xyCoords: num [1:2, 1:2] -1.86 -4.85 38.95 37.84
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:2] "SP000008280" "SP000008410"
## .. ..$ : chr [1:2] "longitude" "latitude"
## $ time :List of 2
## ..$ Start: POSIXlt[1:1840], format: "1981-06-01" "1981-06-02" "1981-06-03" "1981-06-04" ...
## ..$ End : POSIXlt[1:1840], format: "1981-06-02" "1981-06-03" "1981-06-04" "1981-06-05" ...
## $ metadata :List of 4
## ..$ altitude : int [1:2] 704 90
## ..$ location : chr [1:2] "ALBACETE LOS LLANOS" "CORDOBA AEROPUERTO"
## ..$ WMO_Id : int [1:2] 8280 8410
## ..$ Koppen.class: chr [1:2] "BSk" "Csa"
## $ Data :'data.frame': 1840 obs. of 2 variables:
## ..$ SP000008280: num [1:1840] 27.4 26.6 23.2 26.4 30.2 33.6 34.6 35.6 35 32.4 ...
## ..$ SP000008410: num [1:1840] 26.8 26.8 26.4 31 33.6 35.6 37.4 37 36.6 39.6 ...
Alternatively, we can choose a location by its coordinates. From the stationInfo
output, we know the geographical coordinates of the Albacete - Los Llanos station (-1.8631E, 38.9519N). We can introduce these coordinates in the lonLim
and latLim
arguments. Note that it is not necessary to specify all the decimals, as the function will take care of finding the closest station to the given coordinate:
example2 <- loadStationData(dataset = gsn, var="tmax", lonLim = -1.9, latLim = 39, season = 6:8, years = 1981:2000)
## [2014-06-03 10:36:26] Closest station located at 0.0606 spatial units from the specified [lonLim,latLim] coordinate
## [2014-06-03 10:36:26] Loading data ...
## [2014-06-03 10:36:26] Retrieving metadata ...
## [2014-06-03 10:36:26] Done.
str(example2)
## List of 6
## $ variable : chr "tmax"
## $ station_id : chr "SP000008280"
## $ xyCoords: num [1, 1:2] -1.86 38.95
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr "SP000008280"
## .. ..$ : chr [1:2] "longitude" "latitude"
## $ time :List of 2
## ..$ Start: POSIXlt[1:1840], format: "1981-06-01" "1981-06-02" "1981-06-03" "1981-06-04" ...
## ..$ End : POSIXlt[1:1840], format: "1981-06-02" "1981-06-03" "1981-06-04" "1981-06-05" ...
## $ metadata :List of 4
## ..$ altitude : int 704
## ..$ location : chr "ALBACETE LOS LLANOS"
## ..$ WMO_Id : int 8280
## ..$ Koppen.class: chr "BSk"
## $ Data :'data.frame': 1840 obs. of 1 variable:
## ..$ SP000008280: num [1:1840] 27.4 26.6 23.2 26.4 30.2 33.6 34.6 35.6 35 32.4 ...
A particular case of selection by coordinates is when all data within a given bounding box is desired. In this case, the lonLim
and latLim
arguments are filled with a vector of length two, defining the corners of the bounding box. For instance:
example3 <- loadStationData(dataset = gsn, var="tmax", lonLim = c(-5,5), latLim = c(37,40), season = 6:8, years = 1981:2000)
## [2014-06-03 10:43:59] Loading data ...
## [2014-06-03 10:44:00] Retrieving metadata ...
## [2014-06-03 10:44:00] Done.
str(example3)
## List of 6
## $ variable : chr "tmax"
## $ station_id : chr [1:2] "SP000008280" "SP000008410"
## $xyCoords: num [1:2, 1:2] -1.86 -4.85 38.95 37.84
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:2] "SP000008280" "SP000008410"
## .. ..$ : chr [1:2] "longitude" "latitude"
## $ time :List of 2
## ..$ Start: POSIXlt[1:1840], format: "1981-06-01" "1981-06-02" "1981-06-03" "1981-06-04" ...
## ..$ End : POSIXlt[1:1840], format: "1981-06-02" "1981-06-03" "1981-06-04" "1981-06-05" ...
## $ metadata :List of 4
## ..$ altitude : int [1:2] 704 90
## ..$ location : chr [1:2] "ALBACETE LOS LLANOS" "CORDOBA AEROPUERTO"
## ..$ WMO_Id : int [1:2] 8280 8410
## ..$ Koppen.class: chr [1:2] "BSk" "Csa"
## $ Data :'data.frame': 1840 obs. of 2 variables:
## ..$ SP000008280: num [1:1840] 27.4 26.6 23.2 26.4 30.2 33.6 34.6 35.6 35 32.4 ...
## ..$ SP000008410: num [1:1840] 26.8 26.8 26.4 31 33.6 35.6 37.4 37 36.6 39.6 ...
By default, the arguments defining the spatial domain of the query (lonLim
and latLim
or stationID
) are NULL. If none of them is indicated, the function will load all available stations for the time domain selected:
example4 <- loadStationData(dataset = gsn, var="tmax", season = 6:8, years = 1981:2000)
## [2014-06-03 10:47:09] Loading data ...
## [2014-06-03 10:47:09] Retrieving metadata ...
## [2014-06-03 10:47:09] Done.
str(example4)
## List of 6
## $ variable : chr "tmax"
## $ station_id : chr [1:6] "SP000008027" "SP000008181" "SP000008202" "SP000008215" ...
## $ xyCoords: num [1:6, 1:2] -2.04 2.07 -5.5 -4.01 -1.86 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:6] "SP000008027" "SP000008181" "SP000008202" "SP000008215" ...
## .. ..$ : chr [1:2] "longitude" "latitude"
## $ time :List of 2
## ..$ Start: POSIXlt[1:1840], format: "1981-06-01" "1981-06-02" "1981-06-03" "1981-06-04" ...
## ..$ End : POSIXlt[1:1840], format: "1981-06-02" "1981-06-03" "1981-06-04" "1981-06-05" ...
## $ metadata :List of 4
## ..$ altitude : int [1:6] 251 4 790 1894 704 90
## ..$ location : chr [1:6] "SAN SEBASTIAN - IGUELDO" "BARCELONA/AEROPUERTO" "SALAMANCA AEROPUERTO" "NAVACERRADA" ...
## ..$ WMO_Id : int [1:6] 8027 8181 8202 8215 8280 8410
## ..$ Koppen.class: chr [1:6] "Cfb" "Csa" "BSk" "Csb" ...
## $ Data :'data.frame': 1840 obs. of 6 variables:
## ..$ SP000008027: num [1:1840] 29 22.4 15.2 18.2 23 20 27.4 28.8 17.6 16.8 ...
## ..$ SP000008181: num [1:1840] 23.6 23.4 26 22.2 23.4 24.4 24.8 26.8 28 27.4 ...
## ..$ SP000008202: num [1:1840] 22.6 19 18 22.4 25.7 28.4 29 29 26.7 29.8 ...
## ..$ SP000008215: num [1:1840] 12.6 11.8 7.4 14.6 18.2 19.4 21.6 21.4 19.8 23.2 ...
## ..$ SP000008280: num [1:1840] 27.4 26.6 23.2 26.4 30.2 33.6 34.6 35.6 35 32.4 ...
## ..$ SP000008410: num [1:1840] 26.8 26.8 26.4 31 33.6 35.6 37.4 37 36.6 39.6 ...
The same behaviour can be expected with the time definition of the query. For instance, when season
and/or years
are left to their default value NULL, all months and/or years within the dataset will be returned.
The next example plots the time series retrieved in the example 1. Note that time is defined by lower and upper time bounds, rather than one single verification date:
time <- as.POSIXlt(example1$time$Start)
plot(time, example1$Data$SP000008410, ty = 'l', col = "blue", xlab = "time", ylab = "T (ºC)")
lines(time, example1$Data$SP000008280, ty = 'l', col = "red")
legend("bottomright", c("Albacete", "Cordoba"), col = c("red", "blue"), lty = 1)
title("Tmax - JJA (1981-2000)")
downscaleR - Santander MetGroup (Univ. Cantabria - CSIC)