Remote sensing rainfall products: part 4:TAMSAT

This is the fourth rainfall products i am looking at for hydrological research. TAMSAT stands for Tropical Applications of Meteorology using SATellite data and ground-based observations. TAMSAT is rainfall products designed for africa, calibrated with ground measurments. Detal description about it can be found here. While the dekadal and monthly estimation is avaliable for the whole of africa with 1km resolution, since 1983, the daily estimation is only avalaible 2013 onwards. Here I would like to use this products, and compare with other estimates.As usual, i downloaded the data in my harddisk, and process using R.

loading packages

library(raster)
## Loading required package: sp
library(ncdf4)
library(rgdal)
## rgdal: version: 0.9-1, (SVN revision 518)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 1.9.2, released 2012/10/08
## Path to GDAL shared files: /Library/Frameworks/R.framework/Versions/3.1/Resources/library/rgdal/gdal
## Loaded PROJ.4 runtime: Rel. 4.8.0, 6 March 2012, [PJ_VERSION: 480]
## Path to PROJ.4 shared files: /Library/Frameworks/R.framework/Versions/3.1/Resources/library/rgdal/proj
library(lattice)
library(rasterVis)
## Loading required package: latticeExtra
## Loading required package: RColorBrewer
## Loading required package: hexbin
library(ncdf)

Next, let’s load the raster into R.

setwd("/Users/administrator/Documents/PHDResearch/UBN_rainfall/TAMSAT/Project/")
tamsatlist<-list.files(pattern ='.nc', full.names = TRUE)

Next, let’s create a raster stack all two years of daily raster file.

#create raster stack
tamsat.stack <- stack(tamsatlist)
tamsat.stack
## class       : RasterStack 
## dimensions  : 1974, 1894, 3738756, 730  (nrow, ncol, ncell, nlayers)
## resolution  : 0.0375, 0.0375  (x, y)
## extent      : -19.03125, 51.99375, -35.98125, 38.04375  (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
## names       : Rain.Fall.Estimate.1, Rain.Fall.Estimate.2, Rain.Fall.Estimate.3, Rain.Fall.Estimate.4, Rain.Fall.Estimate.5, Rain.Fall.Estimate.6, Rain.Fall.Estimate.7, Rain.Fall.Estimate.8, Rain.Fall.Estimate.9, Rain.Fall.Estimate.10, Rain.Fall.Estimate.11, Rain.Fall.Estimate.12, Rain.Fall.Estimate.13, Rain.Fall.Estimate.14, Rain.Fall.Estimate.15, ...

These are time series raster data for the whole africa region, however, i would like to extract at some stations in my study area. let me do just for a single station. First I need to create spatialpoint object, then extract the time series layer at this location.

ADET<-cbind(37.47,11.27); ADET<-SpatialPoints(ADET) 

TAMSAT_station<-data.frame(
time=seq(as.Date('2013-01-01'), as.Date('2014-12-31'), 'day'),
ADET=as.vector(extract(tamsat.stack, ADET))
)

the time series rainfall at ADET

xyplot(ADET~time|equal.count(as.numeric(time), 1, overlap = 0.1),
TAMSAT_station,  
type = c("l","g"),  lw=2, strip = FALSE,
xlab="time", ylab="TAMSAT rainfall[mm]",
scales = list(x = list(relation = "sliced", axs = "i"),
              y = list(alternating = FALSE)))