download all R files and wgrib.exe & cygwin1.dll in same one folder (e.g. called data in c:/)
then open R studio, set working directory in this folder (e.g. c:/data), install packages and import functions
setwd("c:/data")
install.packages("foreach")
install.packages("doParallel")
install.packages("RCurl")
source("Extract_GRIB.R")
extract temperature, Specific humidity, pressure and compute the dew point at a certain year, day and time from the GLDAS_NOAH025SUBP_3H dataset (GRIB) For example, after running
Extract_GRIB("2010",68,"09","c:/data/2010/")
A file named GLDAS_NOAH025SUBP_3H_2010_068_09.Rdata will be created in c:/data/2010/ if we open this file by R studio, 4 matrices will be loaded in working environment, they are: Tt,q,p,and dew, meaning global temperature, Specific humidity, pressure and dew point data at 9:00Z in the 68th day of 2010.
if we want to extract the data for a whole year, we can run the function GetYearData. For example, to 2006
GetYearData(2006,1, 365,"c:/data/2006/")
After the program ending, (8*365=) 2920 Rdata files will be created in c:/data/2006/
to speed the program up by using parallel computation
we can run the codes in GetYearData_dopar.R. For example, to 2010
# initialize
year<-2010
st_day<-1
ed_day<-365
folder<-"c:/data/2010/"
...
After the program ending, 2920 Rdata files will be created in c:/data/2010/
its performance is based on the real number of CPU’s cores. If the computer has only Mono-core, the performance is same as function GetYearData.
However, the stability of parallel computation GetYearData_dopar is worse than non-parallel GetYearData. Many reasons could cause data missing, such the unforeseen parallel computation problem, web connection problem, disk problem, etc. Therefore, we have a function to complement the missing Rdata files for one year.
The function complement_data in complement_data.R is used to complement the missing Rdata files for one year.
First, it runs the Get_missing function to check data files' completeness and find missing files' name; then it downloads these missing Rdata files by using Extract_GRIB function (non-parallel). For example, to 2006
complement_data("c:/data/2006/", 2006,1, 365)
If there is no missing file for this year, it will return words: "The dataset is already complete."
to speed the program up by using parallel computation
we can run the codes in complement_data_dopar.R. For example, to 2010
# initialize
year<-2010
st_day<-1
ed_day<-365
folder<-"c:/data/2010/"
...
After getting data files containing Tt,q,p,and dew, finally, we can compute the frost points from Tt and dew.
The Get_frost function opens Rdata files with Tt and dew in one folder, calculates frost points and save results in Rdata files of another folder. frost_point.R is needed.
For example, we have 2920 Rdata files for 2010 in the folder c:/data/2010/ and an empty folder c:/data/2010FP/ for Rdata files of frost points (output).
Get_frost("c:/data/2010/","c:/data/2010FP/")
When the program ends, we have 2920 Rdata files with frost points in folder 2010FP.
Similarly, we can speed the program up by using parallel computation.
we can run the codes in Get_frost_dopar.R. For example, to 2010
# initialize
folder_in<-"c:/data/2010/"
folder_out<-"c:/data/2010FP/"
...