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License: Other
Unofficial R client for FetchClimate service
License: Other
Hi,
Shouldn't fcTimeSeriesHourly
retrieve data for every single hour within a period of days (and years)?
For example:
fcTimeSeriesHourly(variable="airt",latitude=55.5, longitude=37.3,
firstDay=183,lastDay=213,
firstYear=2008,lastYear=2008,
startHour=0,stopHour=24)
gives
$values
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
[1,] 15.2346 15.65923 16.08386 16.50849 16.93312 17.35775 17.91059 18.59164 19.2727 19.95375 20.63481
[,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 21.31586 21.44146 21.01161 20.58175 20.15189 19.72203 19.29217 18.73169 18.04059 17.3495 16.6584
[,23] [,24]
[1,] 15.9673 15.2762
$sd
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
[1,] 3.460771 3.460087 3.459745 3.459745 3.460087 3.460771 3.460771 3.460087 3.459745 3.459745 3.460087
[,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 3.460771 3.460771 3.460087 3.459745 3.459745 3.460087 3.460771 3.460771 3.460087 3.459745 3.459745
[,23] [,24]
[1,] 3.460087 3.460771
$provenance
[1] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[3] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[5] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[7] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[9] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[11] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[13] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[15] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[17] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[19] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[21] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
[23] NCEP/NCAR Reanalysis 1 (regular grid) NCEP/NCAR Reanalysis 1 (regular grid)
Levels: NCEP/NCAR Reanalysis 1 (regular grid)
$hours
[1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
That is, only 24 values, when I would expect 24 * 31 values (hours * days), as are in fact obtained if doing the same search through the website.
Thanks
Hello,
Thanks for the package! Very useful. I ran some quick examples and it worked perfectly.
But I cannot find out how to specify a given source dataset. The default (dataSets = "ANY") seems to download data from just one (NCEP/NCAR in my examples). I can't find (either in the function documentation or FetchClimate website) how to name each dataset.
It would be nice if these dataset names were given in the documentation (and perhaps those for the different climatic variables too - although these can indeed be obtained from the website).
Again, thanks a lot
Paco
When executing the examples in ?fcTimesSeriesYearly
an error appears:
fcTimeSeriesYearly(variable="airt",latitude=75.5, longitude=57.7,firstYear=1950,lastYear=2000)
No encoding supplied: defaulting to UTF-8.
Error in x[sapply(x, is.null)] <- NA : invalid subscript type 'list'
It worked before, but not since the last few days (I don't know exactly when started to fail).
My session info:
sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.5 LTS
locale:
[1] LC_CTYPE=es_ES.UTF-8 LC_NUMERIC=C LC_TIME=es_ES.UTF-8 LC_COLLATE=es_ES.UTF-8
[5] LC_MONETARY=es_ES.UTF-8 LC_MESSAGES=es_ES.UTF-8 LC_PAPER=es_ES.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] RFc_0.1-2 sp_1.2-3 httr_1.2.1 jsonlite_1.0 sapfluxnetr_0.0.7
loaded via a namespace (and not attached):
[1] Rcpp_0.12.7 magrittr_1.5 munsell_0.4.3 colorspace_1.2-6 xtable_1.8-2 lattice_0.20-34 R6_2.1.3
[8] plyr_1.8.4 dplyr_0.5.0 tools_3.3.1 grid_3.3.1 gtable_0.2.0 logging_0.7-103 tpldata_0.1
[15] DBI_0.5 htmltools_0.3.5 assertthat_0.1 digest_0.6.10 tibble_1.2 shiny_0.13.2 ggplot2_2.1.0
[22] curl_1.2 mime_0.5 scales_0.4.0 tpl_0.1 httpuv_1.3.3
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