Valores normales climáticos mensuales usando ClimateR
Jose Gerardo Bermudez Diaz
08/06/22
1. Introducción.
En este cuaderno se desarrollará la ilustración de valores mensuales de precipitación y temperatura “normales”. Se estudia, con ayuda de la biblioteca ClimateR, un periodo de 29 años (1981-2010). Se tiene que la precipitación normal no es igual al valor esperado, si no que es un promedio de los valores obtenidos durante esos años. Los valores reales de precipitación en un año dado puede ser superior o inferior al promedio estacional o ser “normal”.
2. Configuración.
rm(list=ls())library(AOI)
library(climateR)
library(sf)## Linking to GEOS 3.9.1, GDAL 3.3.2, PROJ 7.2.1; sf_use_s2() is TRUElibrary(raster)## Loading required package: splibrary(rasterVis)## Loading required package: latticelibrary(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:raster':
##
## intersect, select, union## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(leaflet)
library(leafem)
library(RColorBrewer)
library(stars)## Loading required package: abind3. Leer y estudiar el área.
(stder <- st_read("C:/Users/Gerardo/Desktop/GB2022/datos/15_BOYACA/Administrativo/MGN_MPIO_POLITICO.shp"))## Reading layer `MGN_MPIO_POLITICO' from data source
## `C:\Users\GERARDO\Desktop\GB2022\Datos\15_BOYACA\ADMINISTRATIVO\MGN_MPIO_POLITICO.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 123 features and 9 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -74.66496 ymin: 4.655196 xmax: -71.94885 ymax: 7.055557
## Geodetic CRS: WGS 84## Simple feature collection with 123 features and 9 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -74.66496 ymin: 4.655196 xmax: -71.94885 ymax: 7.055557
## Geodetic CRS: WGS 84
## First 10 features:
## DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC
## 1 15 15001 TUNJA 1541
## 2 15 15022 ALMEIDA 1908
## 3 15 15047 AQUITANIA 1789
## 4 15 15051 ARCABUCO 1856
## 5 15 15087 BELÉN 1756
## 6 15 15090 BERBEO Ordenanza 28 de Abril 9 de 1913
## 7 15 15092 BETÉITIVA 1754
## 8 15 15097 BOAVITA 1613
## 9 15 15104 BOYACÁ 1537
## 10 15 15106 BRICEÑO Ordenanza 14 del 25 de Julio de 1890
## MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area
## 1 119.68957 2017 BOYACÁ 0.5723744 0.009766301
## 2 57.67212 2017 BOYACÁ 0.3484692 0.004701759
## 3 942.14660 2017 BOYACÁ 1.8003115 0.076843504
## 4 137.89859 2017 BOYACÁ 0.7527090 0.011256738
## 5 163.08822 2017 BOYACÁ 0.6293489 0.013314920
## 6 58.01301 2017 BOYACÁ 0.4291743 0.004730850
## 7 101.89955 2017 BOYACÁ 0.4738184 0.008317810
## 8 145.30529 2017 BOYACÁ 0.6597822 0.011867743
## 9 48.02287 2017 BOYACÁ 0.3256140 0.003918022
## 10 64.59970 2017 BOYACÁ 0.4849753 0.005273255
## geometry
## 1 POLYGON ((-73.34014 5.58308...
## 2 POLYGON ((-73.36793 5.01349...
## 3 POLYGON ((-72.76242 5.63856...
## 4 POLYGON ((-73.50487 5.84347...
## 5 POLYGON ((-72.91692 6.08612...
## 6 POLYGON ((-73.0677 5.27048,...
## 7 POLYGON ((-72.81796 5.97422...
## 8 POLYGON ((-72.64907 6.43640...
## 9 POLYGON ((-73.34806 5.47411...
## 10 POLYGON ((-73.89118 5.73749...4. Obtener las precipitaciones normales mensuales.
oneyear = seq(1,12)precip = getTerraClimNormals(stder, param = "prcp", period = "19812010", month=oneyear)## Spherical geometry (s2) switched off## Spherical geometry (s2) switched onprecip## $terraclim_19812010_prcp
## class : RasterStack
## dimensions : 59, 66, 3894, 12 (nrow, ncol, ncell, nlayers)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## names : X01, X02, X03, X04, X05, X06, X07, X08, X09, X10, X11, X12
## min values : 0.0, 5.0, 18.7, 111.5, 100.1, 78.4, 39.3, 44.8, 61.6, 73.2, 76.2, 11.8
## max values : 128.2, 172.0, 286.7, 413.7, 618.8, 582.1, 638.9, 441.7, 392.0, 460.4, 366.8, 273.1capas <-names(precip)par(mfcol=c(12,12), mfrow=c(4,3), oma=c(1,1,0,0),
mar=c(1,1,1,0), tcl=-0.1, mgp=c(0,0,0))
for (penta in capas) {
hist(precip[[penta]], ylab=NA, cex.axis=0.5, font.main=1, cex.main=0.8)
}
year_precip <- sum(precip$terraclim_19812010_prcp)
year_precip## class : RasterLayer
## dimensions : 59, 66, 3894 (nrow, ncol, ncell)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## source : memory
## names : layer
## values : 872.2, 3780.9 (min, max)ppal <- colorNumeric(c("#e66b00", "yellow", "#a1d99b", "#deebf7", "#9ecae1","#3182bd", "darkblue"), values(year_precip$layer),
na.color = "transparent")library(rgdal)## Please note that rgdal will be retired by the end of 2023,
## plan transition to sf/stars/terra functions using GDAL and PROJ
## at your earliest convenience.
##
## rgdal: version: 1.5-32, (SVN revision 1176)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 3.4.3, released 2022/04/22
## Path to GDAL shared files: C:/Users/GERARDO/AppData/Local/R/win-library/4.2/rgdal/gdal
## GDAL binary built with GEOS: TRUE
## Loaded PROJ runtime: Rel. 7.2.1, January 1st, 2021, [PJ_VERSION: 721]
## Path to PROJ shared files: C:/Users/GERARDO/AppData/Local/R/win-library/4.2/rgdal/proj
## PROJ CDN enabled: FALSE
## Linking to sp version:1.5-0
## To mute warnings of possible GDAL/OSR exportToProj4() degradation,
## use options("rgdal_show_exportToProj4_warnings"="none") before loading sp or rgdal.leaflet() %>% addTiles() %>%
addRasterImage(year_precip, colors = ppal, opacity = 0.8) %>%
addLegend(pal = ppal, values = values(year_precip$layer),
title = "Precipitación anual")## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
## prefer_proj): Discarded ellps WGS 84 in Proj4 definition: +proj=merc +a=6378137
## +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null
## +wktext +no_defs +type=crs## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
## prefer_proj): Discarded datum World Geodetic System 1984 in Proj4 definition5. Obtener la temperatura normal anual.
tmax = getTerraClimNormals(stder, param = "tmax", period = "19812010", month=oneyear)## Spherical geometry (s2) switched off## Spherical geometry (s2) switched ontmax## $terraclim_19812010_tmax
## class : RasterStack
## dimensions : 59, 66, 3894, 12 (nrow, ncol, ncell, nlayers)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## names : X01, X02, X03, X04, X05, X06, X07, X08, X09, X10, X11, X12
## min values : 6.4, 6.4, 6.4, 5.7, 5.3, 3.9, 3.3, 4.1, 4.9, 5.1, 5.5, 6.1
## max values : 33.7, 34.9, 34.3, 32.9, 33.0, 33.0, 34.3, 34.1, 33.1, 32.1, 31.9, 32.6(year_tmax = max(tmax$terraclim_19812010_tmax))## class : RasterLayer
## dimensions : 59, 66, 3894 (nrow, ncol, ncell)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## source : memory
## names : layer
## values : 6.4, 34.9 (min, max)tmin = getTerraClimNormals(stder, param = "tmin", period = "19812010", month=oneyear)## Spherical geometry (s2) switched off## Spherical geometry (s2) switched ontmin## $terraclim_19812010_tmin
## class : RasterStack
## dimensions : 59, 66, 3894, 12 (nrow, ncol, ncell, nlayers)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## names : X01, X02, X03, X04, X05, X06, X07, X08, X09, X10, X11, X12
## min values : -3.6, -3.7, -2.4, -1.8, -2.1, -1.9, -2.4, -2.3, -2.3, -2.2, -2.1, -2.6
## max values : 23.9, 24.0, 24.3, 24.1, 23.8, 23.9, 23.4, 23.6, 23.4, 23.5, 23.8, 24.2(year_tmin = min(tmin$terraclim_19812010_tmin))## class : RasterLayer
## dimensions : 59, 66, 3894 (nrow, ncol, ncell)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## source : memory
## names : layer
## values : -3.7, 23.4 (min, max)(tempera <- stack(year_tmin, year_tmax))## class : RasterStack
## dimensions : 59, 66, 3894, 2 (nrow, ncol, ncell, nlayers)
## resolution : 0.04166667, 0.04166667 (x, y)
## extent : -74.66667, -71.91667, 4.625, 7.083333 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## names : layer.1, layer.2
## min values : -3.7, 6.4
## max values : 23.4, 34.9names(tempera) <- c("tmin", "tmax")tvals <- sort(c(values(tempera$tmin),values(tempera$tmax)))pal <- colorNumeric(rev(c("red", "orange", "#fff9ae",
"#77ab59", "#dcf3ff", "#a2d2df", "#257ca3")),
tvals, na.color = "transparent")capas <- names(tempera)m <- leaflet() %>%
addTiles(group = "OSM (default)") %>%
addRasterImage(year_tmin, colors = pal, opacity = 0.8, group= capas[1]) %>%
addRasterImage(year_tmax, colors = pal, opacity = 0.8, group= capas[2])
#
# Additional leaflet options
m <- m %>%
# Add layers controls
addLayersControl(
overlayGroups = rev(capas),
options = layersControlOptions(collapsed = FALSE)
) %>%
# Add common legend
addLegend(pal = pal, values = tvals,
title = "Temperatura anual")msessionInfo()## R version 4.2.0 (2022-04-22 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19043)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Spanish_Colombia.utf8 LC_CTYPE=Spanish_Colombia.utf8
## [3] LC_MONETARY=Spanish_Colombia.utf8 LC_NUMERIC=C
## [5] LC_TIME=Spanish_Colombia.utf8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] rgdal_1.5-32 stars_0.5-5 abind_1.4-5 RColorBrewer_1.1-3
## [5] leafem_0.2.0 leaflet_2.1.1 dplyr_1.0.9 rasterVis_0.51.2
## [9] lattice_0.20-45 raster_3.5-15 sp_1.5-0 sf_1.0-7
## [13] climateR_0.1.0 AOI_0.2.1
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.3 rnaturalearth_0.1.0 sass_0.4.1
## [4] jsonlite_1.8.0 viridisLite_0.4.0 foreach_1.5.2
## [7] bslib_0.3.1 assertthat_0.2.1 highr_0.9
## [10] latticeExtra_0.6-29 yaml_2.3.5 pillar_1.7.0
## [13] glue_1.6.2 digest_0.6.29 rvest_1.0.2
## [16] colorspace_2.0-3 htmltools_0.5.2 pkgconfig_2.0.3
## [19] s2_1.0.7 purrr_0.3.4 scales_1.2.0
## [22] terra_1.5-21 jpeg_0.1-9 tibble_3.1.7
## [25] proxy_0.4-27 farver_2.1.0 generics_0.1.2
## [28] ellipsis_0.3.2 hexbin_1.28.2 cli_3.3.0
## [31] fipio_1.1.1 magrittr_2.0.3 crayon_1.5.1
## [34] evaluate_0.15 fansi_1.0.3 doParallel_1.0.17
## [37] xml2_1.3.3 lwgeom_0.2-8 class_7.3-20
## [40] tools_4.2.0 lifecycle_1.0.1 stringr_1.4.0
## [43] munsell_0.5.0 compiler_4.2.0 jquerylib_0.1.4
## [46] e1071_1.7-11 RNetCDF_2.5-2 rlang_1.0.2
## [49] classInt_0.4-7 units_0.8-0 grid_4.2.0
## [52] iterators_1.0.14 rstudioapi_0.13 htmlwidgets_1.5.4
## [55] crosstalk_1.2.0 base64enc_0.1-3 rmarkdown_2.14
## [58] wk_0.6.0 codetools_0.2-18 DBI_1.1.3
## [61] R6_2.5.1 zoo_1.8-10 knitr_1.39
## [64] fastmap_1.1.0 utf8_1.2.2 KernSmooth_2.23-20
## [67] stringi_1.7.6 parallel_4.2.0 Rcpp_1.0.8.3
## [70] vctrs_0.4.1 png_0.1-7 tidyselect_1.1.2
## [73] xfun_0.31