README.md
In jdtatsch/inmetr: Import Historical Data from Brazilian Meteorological Stations
inmetr: Historical Data from Brazilian Meteorological Stations in R
Overview
inmetr provide access to historical data measured by meteorological stations available in the Meteorological Database for Education and Research (BDMEP) from National Institute of Meteorology (Instituto Nacional de Meteorologia - INMET), Brazil.
Installation
inmetr is easy to install from Git Hub using the devtools package.
library(devtools)
install_github('lhmet/inmetr')
Load package
library(inmetr)
Stations ID
To search a meteorological station from INMET we can use metadata of INMET stations included in inmetr package as bdmep_meta.
head(bdmep_meta)
#> id lon lat alt name state uf
#> 1 83010 -68.73333 -11.016667 260.00 Brasiléia Acre AC
#> 2 82704 -72.66667 -7.633333 170.00 Cruzeiro do Sul Acre AC
#> 3 82915 -67.80000 -9.966667 160.00 Rio Branco Acre AC
#> 4 82807 -70.76667 -8.166667 190.00 Tarauacá Acre AC
#> 5 83098 -36.16667 -10.150000 56.13 Coruripe Alagoas AL
#> 6 82994 -35.70000 -9.666667 64.50 Maceió Alagoas AL
#> time_zone offset_utc
#> 1 America/Rio_Branco -5
#> 2 America/Rio_Branco -5
#> 3 America/Rio_Branco -5
#> 4 America/Rio_Branco -5
#> 5 America/Maceio -3
#> 6 America/Maceio -3
tail(bdmep_meta)
#> id lon lat alt name state uf
#> 389 83033 -48.30000 -10.183333 280.00 Palmas Tocantins TO
#> 390 83231 -47.83333 -12.550000 275.00 Paranã Tocantins TO
#> 391 82863 -48.18333 -8.966667 187.00 Pedro Afonso Tocantins TO
#> 392 83228 -48.35000 -12.016667 242.49 Peixe Tocantins TO
#> 393 83064 -48.41667 -10.716667 239.20 Porto Nacional Tocantins TO
#> 394 83235 -46.41667 -12.400000 603.59 Taguatinga Tocantins TO
#> time_zone offset_utc
#> 389 America/Araguaina -3
#> 390 America/Araguaina -3
#> 391 America/Araguaina -3
#> 392 America/Araguaina -3
#> 393 America/Araguaina -3
#> 394 America/Araguaina -3
bdmep_meta data provide the id of stations, a numeric code defined by OMM. This id is a necessary argument to bdmep_import() function which allows to download data from meteorological stations into the R.
Here, we show how to find the OMM code for meteorological stations at two cities (randomly sampled).
#stations <- c("SANTA MARIA", "PORTO ALEGRE")
# random sample of two stations names
stations <- sample(bdmep_meta$name,2)
stations_rows <- pmatch(stations, bdmep_meta$name)
bdmep_meta[stations_rows, ]
#> id lon lat alt name state uf
#> 366 83774 -48.88333 -23.95000 707 Itapeva São Paulo SP
#> 77 83043 -40.73333 -20.63333 110 Alfredo Chaves Espírito Santo ES
#> time_zone offset_utc
#> 366 America/Sao_Paulo -3
#> 77 America/Sao_Paulo -3
stns_codes <- bdmep_meta[stations_rows, "id"]
stns_codes
#> [1] "83774" "83043"
Import data
Now we can import data for the two cities from 1961 to the current date.
start_date <- "01/01/1961"
end_date <- format(Sys.Date(), "%d/%m/%Y")
met_data <- bdmep_import(id = stns_codes,
sdate = start_date,
edate = end_date,
email = "your-email",
passwd = "your-password",
verbose = TRUE)
#>
#> ------------------------------
#> station: 83774
#> OK (HTTP 200).
#>
#> ------------------------------
#> station: 83043
#> OK (HTTP 200).
# check de start date
head(met_data)
#> date id prec tair tw tmax tmin urmax patm pnmm wd
#> 1 1961-01-01 00:00:00 83774 NA NA NA 26.0 NA NA NA NA NA
#> 2 1961-01-01 12:00:00 83774 NA 20.0 19.6 NA 17.2 96 934.2 NA 14
#> 3 1961-01-01 18:00:00 83774 NA 24.9 21.4 NA NA 73 932.3 NA 14
#> 4 1961-01-02 00:00:00 83774 NA 21.2 20.8 26.4 NA 96 933.2 NA 18
#> 5 1961-01-02 12:00:00 83774 31.9 20.6 20.2 NA 17.0 97 933.0 NA 0
#> 6 1961-01-02 18:00:00 83774 NA 24.4 21.8 NA NA 78 932.0 NA 32
#> wsmax n cc evap ur ws request_status
#> 1 NA NA NA 4.4 90.25 2.333333 Success: (200) OK
#> 2 3 NA 10 NA NA NA Success: (200) OK
#> 3 3 NA 10 NA NA NA Success: (200) OK
#> 4 1 NA 10 3.4 88.75 1.000000 Success: (200) OK
#> 5 0 NA 9 NA NA NA Success: (200) OK
#> 6 3 NA 10 NA NA NA Success: (200) OK
# check de end date
tail(met_data)
#> date id prec tair tw tmax tmin urmax patm pnmm wd
#> 45260 2007-01-13 12:00:00 83043 42.2 NA NA NA 20.2 NA NA NA NA
#> 45261 2007-01-14 00:00:00 83043 NA NA NA 26.2 NA NA NA NA NA
#> 45262 2007-01-14 12:00:00 83043 3.2 NA NA NA 22.0 NA NA NA NA
#> 45263 2007-01-15 00:00:00 83043 NA NA NA 30.6 NA NA NA NA NA
#> 45264 2007-01-15 12:00:00 83043 3.0 NA NA NA 21.6 NA NA NA NA
#> 45265 2007-01-16 00:00:00 83043 NA NA NA 24.6 NA NA NA NA NA
#> wsmax n cc evap ur ws request_status
#> 45260 NA NA NA NA NA NA Success: (200) OK
#> 45261 NA NA NA 1.5 NA NA Success: (200) OK
#> 45262 NA NA NA NA NA NA Success: (200) OK
#> 45263 NA NA NA 1.5 NA NA Success: (200) OK
#> 45264 NA NA NA NA NA NA Success: (200) OK
#> 45265 NA NA NA 2.5 NA NA Success: (200) OK
You can save data in a CSV file setting destdir = "path/to/write/files" in bdmep_import function. Data will be save one file per station.
A description of meteorological variables can be obtained by bdmep_description().
bdmep_description()
#> varname description unit
#> 1 date date and time information -
#> 2 id station ID -
#> 3 prec precipitation mm
#> 4 tair air temperature deg C
#> 5 tw wet bulb temperature deg C
#> 6 tmax maximum air temperature deg C
#> 7 tmin minimum air temperature deg C
#> 8 urmax maximum relative humidity %
#> 9 patm atmospheric pressure hPa
#> 10 pnmm mean sea level atmospheric pressure hPa
#> 11 wd wind direction deg
#> 12 wsmax wind gust m/s
#> 13 n sunshine hours h
#> 14 cc cloud cover -
#> 15 evap evaporation mm
#> 16 ur relative humidity %
#> 17 ws wind speed m/s
#> 18 request_status Information on the status of a request <NA>
Eventually, if the request failed a message will be prompted with the HTTP status code, for example:
------------------------
station: 83774
Bad Gateway (HTTP 502).
------------------------
station: 83043
Bad Gateway (HTTP 502).
In this case the outcome data frame will be filled with NA, except for request_status which will return information on the request status.
#> date id prec tair tw tmax tmin urmax patm pnmm wd wsmax n cc evap ur
#> 1 NA 83774 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#> 2 NA 83043 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#> ws request_status
#> 1 NA Bad Gateway (HTTP 502).
#> 2 NA Bad Gateway (HTTP 502).
To cite this software
citation("inmetr")
To cite package 'inmetr' in publications use:
Tatsch, J.D. 2017. inmetr R package (v 0.2.5): Historical Data
from Brazilian Meteorological Stations in R. Zenodo.
https://doi.org/10.5281/zenodo.580813.
A BibTeX entry for LaTeX users is
@Manual{,
title = {inmetr: Historical Data from Brazilian Meteorological Stations in R},
author = {Jonatan Tatsch},
year = {2017},
note = {R package version 0.2.5},
doi = {https://doi.org/10.5281/zenodo.580813},
institution = {Universidade Federal de Santa Maria-UFSM},
url = {https://github.com/lhmet/inmetr},
}
jdtatsch/inmetr documentation built on May 18, 2019, 11:37 p.m.
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inmetr: Historical Data from Brazilian Meteorological Stations in R
Overview
inmetr provide access to historical data measured by meteorological stations available in the Meteorological Database for Education and Research (BDMEP) from National Institute of Meteorology (Instituto Nacional de Meteorologia - INMET), Brazil.
Installation
inmetr is easy to install from Git Hub using the devtools package.
library(devtools)
install_github('lhmet/inmetr')
Load package
library(inmetr)
Stations ID
To search a meteorological station from INMET we can use metadata of INMET stations included in inmetr package as bdmep_meta.
head(bdmep_meta)
#> id lon lat alt name state uf
#> 1 83010 -68.73333 -11.016667 260.00 Brasiléia Acre AC
#> 2 82704 -72.66667 -7.633333 170.00 Cruzeiro do Sul Acre AC
#> 3 82915 -67.80000 -9.966667 160.00 Rio Branco Acre AC
#> 4 82807 -70.76667 -8.166667 190.00 Tarauacá Acre AC
#> 5 83098 -36.16667 -10.150000 56.13 Coruripe Alagoas AL
#> 6 82994 -35.70000 -9.666667 64.50 Maceió Alagoas AL
#> time_zone offset_utc
#> 1 America/Rio_Branco -5
#> 2 America/Rio_Branco -5
#> 3 America/Rio_Branco -5
#> 4 America/Rio_Branco -5
#> 5 America/Maceio -3
#> 6 America/Maceio -3
tail(bdmep_meta)
#> id lon lat alt name state uf
#> 389 83033 -48.30000 -10.183333 280.00 Palmas Tocantins TO
#> 390 83231 -47.83333 -12.550000 275.00 Paranã Tocantins TO
#> 391 82863 -48.18333 -8.966667 187.00 Pedro Afonso Tocantins TO
#> 392 83228 -48.35000 -12.016667 242.49 Peixe Tocantins TO
#> 393 83064 -48.41667 -10.716667 239.20 Porto Nacional Tocantins TO
#> 394 83235 -46.41667 -12.400000 603.59 Taguatinga Tocantins TO
#> time_zone offset_utc
#> 389 America/Araguaina -3
#> 390 America/Araguaina -3
#> 391 America/Araguaina -3
#> 392 America/Araguaina -3
#> 393 America/Araguaina -3
#> 394 America/Araguaina -3
bdmep_meta data provide the id of stations, a numeric code defined by OMM. This id is a necessary argument to bdmep_import() function which allows to download data from meteorological stations into the R.
Here, we show how to find the OMM code for meteorological stations at two cities (randomly sampled).
#stations <- c("SANTA MARIA", "PORTO ALEGRE")
# random sample of two stations names
stations <- sample(bdmep_meta$name,2)
stations_rows <- pmatch(stations, bdmep_meta$name)
bdmep_meta[stations_rows, ]
#> id lon lat alt name state uf
#> 366 83774 -48.88333 -23.95000 707 Itapeva São Paulo SP
#> 77 83043 -40.73333 -20.63333 110 Alfredo Chaves Espírito Santo ES
#> time_zone offset_utc
#> 366 America/Sao_Paulo -3
#> 77 America/Sao_Paulo -3
stns_codes <- bdmep_meta[stations_rows, "id"]
stns_codes
#> [1] "83774" "83043"
Import data
Now we can import data for the two cities from 1961 to the current date.
start_date <- "01/01/1961"
end_date <- format(Sys.Date(), "%d/%m/%Y")
met_data <- bdmep_import(id = stns_codes,
sdate = start_date,
edate = end_date,
email = "your-email",
passwd = "your-password",
verbose = TRUE)
#>
#> ------------------------------
#> station: 83774
#> OK (HTTP 200).
#>
#> ------------------------------
#> station: 83043
#> OK (HTTP 200).
# check de start date
head(met_data)
#> date id prec tair tw tmax tmin urmax patm pnmm wd
#> 1 1961-01-01 00:00:00 83774 NA NA NA 26.0 NA NA NA NA NA
#> 2 1961-01-01 12:00:00 83774 NA 20.0 19.6 NA 17.2 96 934.2 NA 14
#> 3 1961-01-01 18:00:00 83774 NA 24.9 21.4 NA NA 73 932.3 NA 14
#> 4 1961-01-02 00:00:00 83774 NA 21.2 20.8 26.4 NA 96 933.2 NA 18
#> 5 1961-01-02 12:00:00 83774 31.9 20.6 20.2 NA 17.0 97 933.0 NA 0
#> 6 1961-01-02 18:00:00 83774 NA 24.4 21.8 NA NA 78 932.0 NA 32
#> wsmax n cc evap ur ws request_status
#> 1 NA NA NA 4.4 90.25 2.333333 Success: (200) OK
#> 2 3 NA 10 NA NA NA Success: (200) OK
#> 3 3 NA 10 NA NA NA Success: (200) OK
#> 4 1 NA 10 3.4 88.75 1.000000 Success: (200) OK
#> 5 0 NA 9 NA NA NA Success: (200) OK
#> 6 3 NA 10 NA NA NA Success: (200) OK
# check de end date
tail(met_data)
#> date id prec tair tw tmax tmin urmax patm pnmm wd
#> 45260 2007-01-13 12:00:00 83043 42.2 NA NA NA 20.2 NA NA NA NA
#> 45261 2007-01-14 00:00:00 83043 NA NA NA 26.2 NA NA NA NA NA
#> 45262 2007-01-14 12:00:00 83043 3.2 NA NA NA 22.0 NA NA NA NA
#> 45263 2007-01-15 00:00:00 83043 NA NA NA 30.6 NA NA NA NA NA
#> 45264 2007-01-15 12:00:00 83043 3.0 NA NA NA 21.6 NA NA NA NA
#> 45265 2007-01-16 00:00:00 83043 NA NA NA 24.6 NA NA NA NA NA
#> wsmax n cc evap ur ws request_status
#> 45260 NA NA NA NA NA NA Success: (200) OK
#> 45261 NA NA NA 1.5 NA NA Success: (200) OK
#> 45262 NA NA NA NA NA NA Success: (200) OK
#> 45263 NA NA NA 1.5 NA NA Success: (200) OK
#> 45264 NA NA NA NA NA NA Success: (200) OK
#> 45265 NA NA NA 2.5 NA NA Success: (200) OK
You can save data in a CSV file setting destdir = "path/to/write/files" in bdmep_import function. Data will be save one file per station.
A description of meteorological variables can be obtained by bdmep_description().
bdmep_description()
#> varname description unit
#> 1 date date and time information -
#> 2 id station ID -
#> 3 prec precipitation mm
#> 4 tair air temperature deg C
#> 5 tw wet bulb temperature deg C
#> 6 tmax maximum air temperature deg C
#> 7 tmin minimum air temperature deg C
#> 8 urmax maximum relative humidity %
#> 9 patm atmospheric pressure hPa
#> 10 pnmm mean sea level atmospheric pressure hPa
#> 11 wd wind direction deg
#> 12 wsmax wind gust m/s
#> 13 n sunshine hours h
#> 14 cc cloud cover -
#> 15 evap evaporation mm
#> 16 ur relative humidity %
#> 17 ws wind speed m/s
#> 18 request_status Information on the status of a request <NA>
Eventually, if the request failed a message will be prompted with the HTTP status code, for example:
------------------------
station: 83774
Bad Gateway (HTTP 502).
------------------------
station: 83043
Bad Gateway (HTTP 502).
In this case the outcome data frame will be filled with NA, except for request_status which will return information on the request status.
#> date id prec tair tw tmax tmin urmax patm pnmm wd wsmax n cc evap ur
#> 1 NA 83774 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#> 2 NA 83043 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
#> ws request_status
#> 1 NA Bad Gateway (HTTP 502).
#> 2 NA Bad Gateway (HTTP 502).
To cite this software
citation("inmetr")
To cite package 'inmetr' in publications use:
Tatsch, J.D. 2017. inmetr R package (v 0.2.5): Historical Data
from Brazilian Meteorological Stations in R. Zenodo.
https://doi.org/10.5281/zenodo.580813.
A BibTeX entry for LaTeX users is
@Manual{,
title = {inmetr: Historical Data from Brazilian Meteorological Stations in R},
author = {Jonatan Tatsch},
year = {2017},
note = {R package version 0.2.5},
doi = {https://doi.org/10.5281/zenodo.580813},
institution = {Universidade Federal de Santa Maria-UFSM},
url = {https://github.com/lhmet/inmetr},
}
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