A RESTful R client interface to the NWS National Digital Forecast Database
library(devtools)
install_github("BigelowLab/ndfd")You can use ndfd to both list available data lcoations as well as retrieve them. For each you must create a suitable query string suing either query_this() of list_this() which are each convenience wrappers. Once you have a query string you can pass it to NDFD() to get the response form the server and store it in an NDFDRefClass object. The contents of the NDFDRefClass will vary slightly depending upon your request.
Each NDFDRefClass has 4 fields...
+ uri character, the complete URI with your query string
+ version character, the response version
+ head DWMLHeadRefClass an object to contain the header section (not always populated)
+ data DWMLDataRefClass an object to contain the data section (not always populated)
+ latLonList DWMLLonLatListRefClass an object to contain the location listings (not always populated)
In this example we simply want to list available resources that fall within a specified boundary. Note that we only get a listing of locations where we can query for data.
library(ndfd)
my_query <- list_this(what = "points_in_subgrid", listLon1 = -72, listLon2 = -63, listLat1 = 39, listLat2 = 46)
X <- NDFD(my_query)
X
# URI:http://graphical.weather.gov/xml/sample_products/browser_interface/ndfdXMLclient.php?listLon1=-72.0000&listLon2=-63.0000&listLat1=39.0000&listLat2=46.0000&resolutionList=20.0000
# Reference Class: "NDFDRefClass"
# Reference Class: "DWMLLatLonListRefClass"
# locations (head and tail):
# lat lon
# 1 39.008394 -71.990669
# 2 39.139234 -71.961769
# 3 39.269988 -71.932797
# 4 39.400657 -71.903753
# 5 39.531239 -71.874636
# 6 39.661734 -71.845447
# lat lon
# 2555 45.403962 -63.198672
# 2556 45.528282 -63.156282
# 2557 45.652481 -63.113782
# 2558 45.776558 -63.071170
# 2559 45.900512 -63.028446
# 2560 46.024344 -62.985609
xy <- X$latLonList$get_location()
str(xy)
# 'data.frame': 1176 obs. of 2 variables:
# $ lat: num 43.1 43.2 43.3 43.4 43.6 ...
# $ lon: num -72.1 -72 -72 -72 -72 ...We can get forecast values by passing the above locations to a subsequent query.
# we can try to query like this, but it won't work if there are more than 200 points requested
loc <- X$latLonList$get_location(form = 'as_is')
my_query <- query_this(what = "multipoint", listLonLat = loc, element = 'temp', begin ='2016-05-14T12:00', end = '2016-05-16T12:00')
X <- NDFD(my_query)
# Error in curl::curl_fetch_memory(url, handle = handle) :
# Server returned nothing (no headers, no data)This limit could be an issue if a significant number of points are needed.
Alternatively, we can retrieve a subgrid of points by defining a bounding box. We can request results at any resolution, but a coarse resolution is required if to avoid the 200 (within box) point cap.
my_query <- query_this(what = "subgrid", lon1 = -72, lon2 = -63, lat1 = 39, lat2 = 46, product = 'time-series', element = 'temp', begin = '2016-05-14T12:00', end = '2016-05-17T12:00', resolutionSub = 75)
X <- NDFD(my_query)
X
# Reference Class: "NDFDRefClass"
# [ has head element ]
# Reference Class: "DWMLHeadRefClass"
# Title: NOAA's National Weather Service Forecast Data
# Concise name: time-series
# Creation date: 2016-05-17T12:43:39Z
# Refresh frequency: PT1H
# [ has data element ]
# Reference Class: "DWMLDataRefClass"
# locations (head and tail):
# location_key latitude longitude
# 1 point1 39.01 -71.99
# 2 point2 39.62 -71.86
# 3 point3 40.23 -71.72
# 4 point4 40.83 -71.58
# 5 point5 41.44 -71.44
# 6 point6 42.04 -71.30
# location_key latitude longitude
# 130 point130 43.45 -64.15
# 131 point131 44.04 -63.96
# 132 point132 44.62 -63.77
# 133 point133 45.20 -63.58
# 134 point134 45.78 -63.38
# 135 point135 46.36 -63.18
# timelayout(s): k-p3h-n36-1 k-p3h-n36-2
# parameter(s):
# point1
# Temperature, type = hourly, units = Celsius, time_layout = k-p3h-n36-1
# ...
# point135
# Temperature, type = hourly, units = Celsius, time_layout = k-p3h-n36-2
# [ no latLonList element ]
We retrieve the data associated with zip codes in Cumberland County, Maine.
library(ndfd)
zips <- "04003+04009+04011+04013+04107+04015+04017+04019+04021+04110+04024+04105+04032+04038+04039+04079+04040+04050+04055+04260+04057+04097+04066+04108+04101+04069+04071+04070+04029+04075+04077+04078+04106+04082+04084+04085+04091+04092+04062+04096"
my_query <- query_this(what = 'zipcodes', zipCodeList = zips, element = 'temp')
X <- NDFD(my_query)
x <- X$data$get_data(name = 'Temperature', by = 'location')
# each column 'Vn' is the parameter value at the time specified in the
# time-layout values.
head(x[1:5])
# location_key latitude longitude V1 V2
# point1 43.73 -70.00 -8 -6
# point2 44.07 -70.72 -10 -6
# point3 43.91 -69.97 -9 -7
# point4 43.80 -70.07 -9 -6
# point5 43.56 -70.20 -8 -6
# point6 44.01 -70.52 -11 -7
y <- X$data$get_data(name = 'Temperature', by = 'time')
# column 'pointN' is the parameter value at the listed time-layout window
# in this case, 'Temperature' is valid only at the start times listed
# (once every three hours)
head(y[1:5])
# start_valid_time end_valid_time point1 point2 point3
# 2016-03-03 10:00:00 <NA> -8 -10 -9
# 2016-03-03 13:00:00 <NA> -6 -6 -7
# 2016-03-03 16:00:00 <NA> -7 -8 -8
# 2016-03-03 19:00:00 <NA> -8 -11 -11
# 2016-03-03 22:00:00 <NA> -9 -13 -12
# 2016-03-04 01:00:00 <NA> -9 -15 -12