O objetivo principal deste html é gerar arquivos com dados na escala de 3 horas.

1 Pacotes e diretório

##       xts  dygraphs   openair     dplyr      plyr lubridate   lattice   ggplot2 
##      TRUE     FALSE      TRUE      TRUE      TRUE      TRUE      TRUE      TRUE 
##  magrittr     knitr     tidyr 
##      TRUE      TRUE      TRUE

Diretório de trabalho

Carregando scripts adicionais

2 SANTA MARIA

##                      date    Rn_f SWout LE_orig   H_orig     Fg_f Rg_f Tair_f
## 54528 2017-01-01 00:00:00 -34.111    NA      NA       NA  0.36193    0  22.60
## 54529 2017-01-01 00:30:00 -33.119    NA      NA -19.9170  0.07310    0  22.35
## 54530 2017-01-01 01:00:00 -32.126    NA      NA  -8.2767 -0.54883    0  22.10
## 54531 2017-01-01 01:30:00 -33.226    NA 18.4140  68.3960 -1.41680    0  22.40
## 54532 2017-01-01 02:00:00 -34.326    NA  5.9685  26.8770 -1.93160    0  22.70
## 54533 2017-01-01 02:30:00 -34.531    NA  5.2106 -20.2590 -2.03190    0  22.55
##        VPD_f
## 54528 2.4719
## 54529 2.0289
## 54530 1.5986
## 54531 1.8994
## 54532 2.2106
## 54533 2.1906
##                       date    Rn_f     SWout LE_orig  H_orig   Fg_f Rg_f
## 142170 2021-12-31 21:00:00 -60.829 -1.099795 22.1240 -52.186 9.1263    0
## 142171 2021-12-31 21:30:00 -56.909 -0.594773 29.0150 -58.508 7.2704    0
## 142172 2021-12-31 22:00:00 -55.869 -0.948700      NA -24.818 5.7146    0
## 142173 2021-12-31 22:30:00 -54.717 -1.702538 16.6270 -29.922 4.3000    0
## 142174 2021-12-31 23:00:00 -47.154 -0.767892 11.3300 -34.556 3.1264    0
## 142175 2021-12-31 23:30:00 -45.607 -1.190439  2.2567  -9.021 2.0338    0
##          Tair_f   VPD_f
## 142170 26.43671 13.9330
## 142171 25.57455 11.9690
## 142172 24.72725  9.9517
## 142173 24.62941  9.9079
## 142174 23.89577  8.2061
## 142175 23.40633  6.9144
## [1] "2017-01-01 00:00:00 GMT" "2021-12-31 23:30:00 GMT"
## [1] "POSIXct" "POSIXt"

2.1 Verificando dados x horário

2.2 Verificando série

2.3 Dados na escala 3 HORAS

##                      date    Rn_f SWout LE_orig   H_orig     Fg_f Rg_f Tair_f
## 54528 2017-01-01 00:00:00 -34.111    NA      NA       NA  0.36193    0  22.60
## 54529 2017-01-01 00:30:00 -33.119    NA      NA -19.9170  0.07310    0  22.35
## 54530 2017-01-01 01:00:00 -32.126    NA      NA  -8.2767 -0.54883    0  22.10
## 54531 2017-01-01 01:30:00 -33.226    NA 18.4140  68.3960 -1.41680    0  22.40
## 54532 2017-01-01 02:00:00 -34.326    NA  5.9685  26.8770 -1.93160    0  22.70
## 54533 2017-01-01 02:30:00 -34.531    NA  5.2106 -20.2590 -2.03190    0  22.55
##        VPD_f
## 54528 2.4719
## 54529 2.0289
## 54530 1.5986
## 54531 1.8994
## 54532 2.2106
## 54533 2.1906
## # A tibble: 6 × 9
##   date                 Rn_f SWout LE_orig H_orig   Fg_f    Rg_f Tair_f VPD_f
##   <dttm>              <dbl> <dbl>   <dbl>  <dbl>  <dbl>   <dbl>  <dbl> <dbl>
## 1 2017-01-01 00:00:00 -33.6   NaN    9.86   9.36 -0.916   0       22.4  2.07
## 2 2017-01-01 03:00:00 -35.9   NaN   -4.21 -17.2  -3.08    0.311   21.8  1.38
## 3 2017-01-01 06:00:00 107.    NaN   62.2   15.9  -2.19  257.      25.7  6.26
## 4 2017-01-01 09:00:00 494.    NaN  189.    88.8   6.25  716.      29.4 11.4 
## 5 2017-01-01 12:00:00 559.    NaN  295.    98.8  17.2   852.      32.2 16.9 
## 6 2017-01-01 15:00:00 290.    NaN  175.    36.7  18.7   461.      31.9 17.0
## # A tibble: 16 × 9
##    date                 Rn_f   SWout LE_orig  H_orig  Fg_f  Rg_f Tair_f VPD_f
##    <dttm>              <dbl>   <dbl>   <dbl>   <dbl> <dbl> <dbl>  <dbl> <dbl>
##  1 2020-02-28 00:00:00 -52.1   -1.74   -9.03 -12.8     NaN   0     17.1  3.02
##  2 2020-02-28 03:00:00 -28.7   -1.63   13.2    0.233   NaN   0     14.6  1.18
##  3 2020-02-28 06:00:00 128.   -38.9    92.9   24.0     NaN  94.8   16.5  2.29
##  4 2020-02-28 09:00:00 553.  -131.    184.   146.      NaN 630.    24.4 12.4 
##  5 2020-02-28 12:00:00 677.  -149.    336.   195.      NaN 937.    28.6 24.3 
##  6 2020-02-28 15:00:00 341.   -99.9   249.   121.      NaN 666.    29.1 25.5 
##  7 2020-02-28 18:00:00 -35.3  -10.9    39.4   -9.17    NaN 138.    24.4 14.4 
##  8 2020-02-28 21:00:00 -45.6   -1.29    1.96  -6.58    NaN  11.6   18.4  3.49
##  9 2020-03-01 00:00:00 -48.7   -1.07    1.61  -4.67    NaN   0     18.8  5.62
## 10 2020-03-01 03:00:00 -29.1   -1.25    4.90   6.60    NaN   0     15.6  1.17
## 11 2020-03-01 06:00:00 122.   -40.1    52.9   14.4     NaN  94.1   15.9  2.00
## 12 2020-03-01 09:00:00 547.  -134.    170.   165.      NaN 631.    24.1 10.8 
## 13 2020-03-01 12:00:00 675.  -151.    310.   220.      NaN 935.    28.9 24.0 
## 14 2020-03-01 15:00:00 340.  -100.    235.   131.      NaN 670.    30.2 28.2 
## 15 2020-03-01 18:00:00 -36.3  -10.5    29.9   -9.66    NaN 131.    25.8 17.8 
## 16 2020-03-01 21:00:00 -70.5   -1.51   14.5  -46.4     NaN  10.5   22.0  9.40

2.4 Percentual de dados faltantes

Percentual de dados faltantes (NAs) para cada uma das colunas

## [1] 9455
variaveis perc.NA
date 0.00
Rn_f 0.00
SWout 11.01
LE_orig 41.11
H_orig 30.13
Fg_f 10.12
Rg_f 0.00
Tair_f 0.00
VPD_f 0.00

2.5 Exportando dados na escala horária, 3 horas e diária (eval=F)

3 PEDRAS ALTAS

##                      date    Rn_f    LE_f     H_f   Fg_f     Rg_f   Tair_f
## 57233 2017-01-01 00:00:00 -52.897  5.6197 -29.178 13.057 0.095922 23.10839
## 57234 2017-01-01 00:30:00 -55.318  4.0316 -27.646 12.499 0.092054 22.85231
## 57235 2017-01-01 01:00:00 -54.842 -1.8671 -27.997 12.015 0.098243 22.43333
##        VPD_f
## 57233 2.6233
## 57234 2.1105
## 57235 1.5235
##                      date    Rn_f    LE_f     H_f   Fg_f     Rg_f   Tair_f
## 66628 2017-07-15 17:30:00 -30.718 36.8450 -58.972 19.413  4.35440 22.65923
## 66629 2017-07-15 18:00:00 -25.239 44.0680 -53.754 19.014  0.41168 22.38926
## 66630 2017-07-15 18:30:00 -26.667  9.8289 -33.904 13.033 14.72000 16.23636
##         VPD_f
## 66628 11.4260
## 66629 10.9660
## 66630  2.4478
## [1] "2017-01-01 00:00:00 GMT" "2017-07-15 18:30:00 GMT"
## [1] "POSIXct" "POSIXt"
## [1] "date"   "Rn_f"   "LE_f"   "H_f"    "Fg_f"   "Rg_f"   "Tair_f" "VPD_f"

3.1 Verificando dados x horário

3.2 Verificando série

3.3 Dados na escala horária, 3 HORAS e diária

## # A tibble: 16 × 8
##    date                 Rn_f   LE_f    H_f  Fg_f   Rg_f Tair_f VPD_f
##    <dttm>              <dbl>  <dbl>  <dbl> <dbl>  <dbl>  <dbl> <dbl>
##  1 2017-02-28 00:00:00 -56.9   6.80 -12.2   11.8   0      20.7  1.89
##  2 2017-02-28 03:00:00 -52.8   6.60 -12.3   12.0   0      20.2  1.92
##  3 2017-02-28 06:00:00  39.6  39.4    5.41  12.4 113.     21.3  2.75
##  4 2017-02-28 09:00:00 434.  218.    71.1   15.8 593.     26.8  7.71
##  5 2017-02-28 12:00:00 646.  304.   123.    23.2 891.     29.1 12.1 
##  6 2017-02-28 15:00:00 376.  181.    58.5   21.0 480.     29.1  8.54
##  7 2017-02-28 18:00:00  21.3  36.0    4.09  14.6  86.2    25.7  3.05
##  8 2017-02-28 21:00:00 -35.7   6.27 -12.9   12.1   7.40   23.2  1.74
##  9 2017-03-01 00:00:00 -41.4   6.32 -13.1   12.1   0      21.5  1.72
## 10 2017-03-01 03:00:00 -42.8   5.98 -13.2   12.3   0      20.3  1.64
## 11 2017-03-01 06:00:00  56.4  54.8   10.9   13.4 123.     21.3  3.45
## 12 2017-03-01 09:00:00 422.  211.    75.1   14.6 387.     24.8 10.7 
## 13 2017-03-01 12:00:00 635.  278.   111.    22.6 759.     28.4 11.4 
## 14 2017-03-01 15:00:00 327.  174.    67.2   20.2 472.     28.8  6.65
## 15 2017-03-01 18:00:00  22.8  82.7   31.3   14.9 164.     26.8  3.63
## 16 2017-03-01 21:00:00 -37.6   1.66 -12.9   11.9   6.96   22.8  1.44

3.4 Percentual de dados faltantes

Percentual de dados faltantes (NAs) para cada uma das colunas

## [1] 0
variaveis perc.NA
date 0
Rn_f 0
LE_f 0
H_f 0
Fg_f 0
Rg_f 0
Tair_f 0
VPD_f 0

3.5 Exportando dados na escala horária, 3 horas e diária (eval=F)

4 ACEGUÁ

##                  date    Rn_f SWout LE_orig H_orig    Fg_f      Rg_f   Tair_f
## 1 2018-09-06 00:30:00      NA    NA      NA     NA      NA        NA       NA
## 2 2018-09-06 01:00:00 -10.385    NA      NA     NA -15.919 0.0000000 10.36310
## 3 2018-09-06 01:30:00 -10.491    NA      NA     NA -16.726 0.0011359 10.39493
##    VPD_f
## 1     NA
## 2 1.6484
## 3 1.6184
##                      date    Rn_f SWout LE_orig H_orig     Fg_f     Rg_f
## 55198 2021-10-29 23:00:00  50.483    NA      NA     NA -0.66245 110.0400
## 55199 2021-10-29 23:30:00  50.483    NA      NA     NA -0.66245 111.3400
## 55200 2021-10-30 00:00:00 -31.643    NA      NA     NA  2.85050   9.4244
##         Tair_f  VPD_f
## 55198 19.05918 4.3504
## 55199 18.81939 3.9104
## 55200 17.39223 5.9967
## [1] "2018-09-06 00:30:00 GMT" "2021-10-30 00:00:00 GMT"
## [1] "POSIXct" "POSIXt"
## [1] "date"    "Rn_f"    "SWout"   "LE_orig" "H_orig"  "Fg_f"    "Rg_f"   
## [8] "Tair_f"  "VPD_f"

4.1 Verificando dados x horário

4.2 Verificando série

4.3 Dados na escala horária, 3 HORAS e diária

4.4 Percentual de dados faltantes

Percentual de dados faltantes (NAs) para cada uma das colunas

## [1] 10731
variaveis perc.NA
date 0.00
Rn_f 0.00
SWout 100.00
LE_orig 25.08
H_orig 18.97
Fg_f 0.00
Rg_f 0.00
Tair_f 0.00
VPD_f 0.00

4.5 Exportando dados na escala horária, 3 horas e diária (eval=F)

5 RESUMO

As datas são:

Santa Maria: de 2017-01-01 a 2021-12-31 23:30:00.
Pedras Altas: de 2017-01-01 a 2017-07-15 18:30:00.
Aceguá: de 2018-09-06 00:30:00 a 2021-10-30.

!!!!!!! T H E E N D!!!!!!!!!!!