-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathREADME.Rmd
132 lines (103 loc) · 4.9 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
---
output: github_document
---
<!-- date: "April 20, 2020" -->
## wrftools
This package does 3 things
1. help you to define domains
2. extract data as points of spatial features and bricks
3. returns st_bbox from wrf files
I'm not an expert in WRF but i need to use it. One of the very frustating and
tricky part was to make a correct namelist.wps. Hours and hours trying to
get the perfect domains. This functions solves this part while providing
a dynamic maps for actually viewing where are your domains.
## Install
```{r eval = FALSE}
remotes::install_github("atmoschem/wrftools")
```
## wrf_domains (better for low latitude regions)
wrf_domains returns a list of:
1. the map
2. the sf object
The arguments of wrf_domains are the same arguments of namelist.wps.
It include default values but you can change them accordingly.
```{r, eval = F}
library(wrftools)
a <- wrf_domains()
a[[1]] # leaflet
```
## xtractor
(inspired in NCL from DCA/IAG/USP)
Which returns data.frame ready for ggplot2. The class of Time is POSIXct
*points must have a column named "Stations"*
```{r eval = FALSE}
data(cetesb)
cetesb <- cetesb[!is.na(cetesb$Station), "Station"]
#use your wrfout
wrf <- "wrfoA.nc"
t2 = c("T2", "o3", "no", "no2", "PM10", "PM2_5_DRY")
df <- xtractor(atmos = wrf, vars = t2, points = cetesb)
head(df)
# Simple feature collection with 6 features and 31 fields
# geometry type: POINT
# dimension: XY
# bbox: xmin: -47.05721 ymin: -22.90252 xmax: -47.05721 ymax: -22.90252
# epsg (SRID): 4326
# proj4string: +proj=longlat +datum=WGS84 +no_defs
# Station o3 T2 co no no2
# 1 Campinas-Centro 0.0136891948 291.5070 0.6858493 1.186951e-03 0.017522896
# 2 Campinas-Centro 0.0016979938 291.0912 0.2327648 1.000002e-06 0.010418361
# 3 Campinas-Centro 0.0005303844 290.4462 0.1234838 1.000000e-06 0.006545659
# 4 Campinas-Centro 0.0005190288 290.2115 0.1193006 1.000000e-06 0.006521403
# 5 Campinas-Centro 0.0007871886 289.7922 0.1592883 1.000001e-06 0.008744552
# 6 Campinas-Centro 0.0007235801 289.3625 0.1483000 1.000000e-06 0.008334729
# U10 V10 o3_nei T2_nei co_nei no_nei no2_nei
# 1 -3.828670 1.6248466 0.0134919608 291.6059 0.6849796 7.290264e-04 0.017353176
# 2 -3.457098 1.3129230 0.0020016744 291.1794 0.2680614 1.000003e-06 0.011742138
# 3 -3.317390 1.3360039 0.0006680896 290.6286 0.1547405 1.000001e-06 0.008042991
# 4 -3.180607 0.5178746 0.0006177527 290.2608 0.1540482 1.000000e-06 0.008429846
# 5 -2.915890 0.1141155 0.0008107356 289.7930 0.1822766 1.000001e-06 0.010076069
# 6 -2.709186 -0.2479147 0.0008365429 289.3382 0.1891523 1.000000e-06 0.010676160
# U10_nei V10_nei o3_mean T2_mean co_mean no_mean no2_mean
# 1 -3.785948 1.6207790 0.0134919608 291.6059 0.6849796 7.290264e-04 0.017353176
# 2 -3.376240 1.2453150 0.0020016744 291.1794 0.2680614 1.000003e-06 0.011742138
# 3 -3.203223 1.1476679 0.0006680896 290.6286 0.1547405 1.000001e-06 0.008042991
# 4 -3.003846 0.5310050 0.0006177527 290.2608 0.1540482 1.000000e-06 0.008429846
# 5 -2.734402 0.1705305 0.0008107356 289.7930 0.1822766 1.000001e-06 0.010076069
# 6 -2.506655 -0.1514282 0.0008365429 289.3382 0.1891523 1.000000e-06 0.010676160
# U10_mean V10_mean o3_sd T2_sd co_sd no_sd no2_sd
# 1 -3.785948 1.6207790 8.958741e-04 NA 0.001191089 4.948589e-04 0.0001534891
# 2 -3.376240 1.2453150 2.975019e-04 NA 0.029171536 2.649172e-12 0.0011591850
# 3 -3.203223 1.1476679 1.706330e-04 NA 0.036130629 4.944615e-13 0.0017461727
# 4 -3.003846 0.5310050 1.354053e-04 NA 0.042510566 3.130691e-13 0.0023126512
# 5 -2.734402 0.1705305 5.089485e-05 NA 0.028024180 1.430528e-13 0.0016047246
# 6 -2.506655 -0.1514282 1.193552e-04 NA 0.043639222 2.625485e-13 0.0025344522
# U10_sd V10_sd Time geometry
# 1 NA NA 2018-04-19 00:00:00 POINT (-47.05721 -22.90252)
# 2 NA NA 2018-04-19 01:00:00 POINT (-47.05721 -22.90252)
# 3 NA NA 2018-04-19 02:00:00 POINT (-47.05721 -22.90252)
# 4 NA NA 2018-04-19 03:00:00 POINT (-47.05721 -22.90252)
# 5 NA NA 2018-04-19 04:00:00 POINT (-47.05721 -22.90252)
# 6 NA NA 2018-04-19 05:00:00 POINT (-47.05721 -22.90252)
# LT
# 1 2018-04-18 21:00:00
# 2 2018-04-18 22:00:00
# 3 2018-04-18 23:00:00
# 4 2018-04-19 00:00:00
# 5 2018-04-19 01:00:00
# 6 2018-04-19 02:00:00
```
and raster bricks
```{r eval = FALSE}
library(cptcity)
r <- xtractor(atmos = wrf, vars = t2, points = cetesb[1, ], return_list = T)
# A list with raster and data.frame
sp::spplot(r$raster[[2]], "layer.60",
scales = list(draw = T), col.regions = cpt(1224))
```
## Contributing
If you see any errors and know how to improve the function, or add new functions
write an issue and a pull request, please. I will be ver grateful, for sure,
100%.