> On Oct 15, 2017, at 2:02 PM, Miluji Sb <miluj...@gmail.com> wrote:
>
> Dear all,
>
> i am trying to download time-series climatic data from GES DISC (NASA)
> Hydrology Data Rods web-service. Unfortunately, no wget method is
> available.
>
> Five parameters are needed for data retrieval: variable, location,
> startDate, endDate, and type. For example:
>
> ###
> https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=GLDAS2:GLDAS_NOAH025_3H_v2.0:Tair_f_inst&startDate=1970-01-01T00&endDate=1979-12-31T00&location=GEOM:POINT(-71.06,%2042.36)&type=asc2
> ###
>
> In this case, variable: Tair_f_inst (temperature), location: (-71.06,
> 42.36), startDate: 01 January 1970; endDate: 31 December 1979; type: asc2
> (output 2-column ASCII).
>
> I am trying to download data for 100 US cities, data for which I have in
> the following data.frame:
>
> ###
> cities <- dput(droplevels(head(cities, 5)))
> structure(list(city = structure(1:5, .Label = c("Boston", "Bridgeport",
> "Cambridge", "Fall River", "Hartford"), class = "factor"), state =
> structure(c(2L,
> 1L, 2L, 2L, 1L), .Label = c(" CT ", " MA "), class = "factor"),
> lon = c(-71.06, -73.19, -71.11, -71.16, -72.67), lat = c(42.36,
> 41.18, 42.37, 41.7, 41.77)), .Names = c("city", "state",
> "lon", "lat"), row.names = c(NA, 5L), class = "data.frame")
> ###
>
> Is it possible to download the data for the multiple locations
> automatically (e.g. RCurl) and save them as csv? Essentially, reading
> coordinates from the data.frame and entering it in the URL.
>
> I would also like to add identifying information to each of the data files
> from the cities data.frame. I have been doing the following for a single
> file:
Didn't seem that difficult:
library(downloader) # makes things easier for Macs, perhaps not needed
# if not used will need to use download.file
for( i in 1:5) {
target1 <-
paste0("https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=GLDAS2:GLDAS_NOAH025_3H_v2.0:Tair_f_inst&startDate=1970-01-01T00&endDate=1979-12-31T00&location=GEOM:POINT(",
cities[i, "lon"],
",%20", cities[i,"lat"],
")&type=asc2")
target2 <- paste0("~/", # change for whatever destination directory you
may prefer.
cities[i,"city"],
cities[i,"state"], ".asc")
download(url=target1, destfile=target2)
}
Now I have 5 named files with extensions ".asc" in my user directory (since I'm
on a Mac). It is a slow website so patience is needed.
--
David
>
> ###
> x <- readLines(con=url("
> https://hydro1.gesdisc.eosdis.nasa.gov/daac-bin/access/timeseries.cgi?variable=GLDAS2:GLDAS_NOAH025_3H_v2.0:Tair_f_inst&startDate=1970-01-01T00&endDate=1979-12-31T00&location=GEOM:POINT(-71.06,%2042.36)&type=asc2
> "))
> x <- x[-(1:13)]
>
> mydata <- data.frame(year = substr(x,1,4),
> month = substr(x, 6,7),
> day = substr(x, 9, 10),
> hour = substr(x, 12, 13),
> temp = substr(x, 21, 27))
>
> mydata$city <- rep(cities[1,1], nrow(mydata))
> mydata$state <- rep(cities[1,2], nrow(mydata))
> mydata$lon <- rep(cities[1,3], nrow(mydata))
> mydata$lat <- rep(cities[1,4], nrow(mydata))
> ###
>
> Help and advice would be greatly appreciated. Thank you!
>
> Sincerely,
>
> Milu
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
______________________________________________
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