Hi all,
I'm coming back to that subject because the GPM datas are finally available
since December 2014. The original data are stored in HDF5, which is
supported by GDAL.
However, I had a problem with the geo-referencing of the data. It seems
that the lat/long coordinates are flipped.
The problem seems to come from GDAL, as the HDF5 driver still don't support
GPM data:
http://www.gdal.org/frmt_hdf5.html
I've actually downloaded a regional extracts the data in NetCDF from a NASA
website, although I can't remember where exactly, as there are several
services. Those data suffer from the same problem of inverted coordinates.
So I used the ncpdq from NCO package to fix the NetCDF directly, and a tiny
Python script to batch process the files :
###
#!/usr/bin/env python
from os import listdir
import subprocess
for input_file in listdir(main_path):
output_file = input_file + '_fixed'
subprocess.call(['ncpdq','-a', 'lat,lon', input_file, output_file])
###
After batch import the data in GRASS, maintaining the original name
including timestep, which looks like this:
3B-HHR.MS.MRG.3IMERG.20140619-S000000-E002959.0000.V03D
A Python script to register the maps in temporal framework:
#####
#!/usr/bin/env python
import grass.script as grass
# retrieve the list of maps
maplist = grass.read_command('g.list', type = 'raster',
pattern = '*IMERG*')
# turn result in a list
maplist = maplist.split()
file_name = 'gpm_timestamp.txt'
# creating the file containing the timepstamp
list_file = open(file_name,'w')
# iterate through the maps
for input_map in maplist:
# split line to keep only the timestamp
raw_ts = input_map.split('.')[4]
# isolate the date
raw_mapdate = raw_ts.split('-')[0]
# put the date in form
mapdate = raw_mapdate[:4] + '-' + raw_mapdate[4:6] + \
'-' + raw_mapdate[6:]
# isolate the start time
raw_start_time = raw_ts.split('-')[1]
# put the date in form
start_time = raw_start_time[1:3] + ':' + \
raw_start_time[3:5] + ':' + raw_start_time[5:]
# isolate the end time
raw_end_time = raw_ts.split('-')[2]
# put the end time in form
end_time = raw_end_time[1:3] + ':' + \
raw_end_time[3:5] + ':' + raw_end_time[5:]
# put timestamp in form
timestamp = mapdate + ' ' + start_time + '|' + mapdate + \
' ' + end_time
# format the whole line
line = input_map + '|' + timestamp + '\n'
# write line to the file
list_file.write(line)
# close the file
list_file.close()
# register the maps in grass space_time dataset
grass.run_command('t.register', input = 'GPM_ZMCM', file = file_name)
#####
Hope it will help other peoples having trouble using those data.
Regards,
Laurent
2014-11-06 5:15 GMT-06:00 maning sambale <emmanuel.samb...@gmail.com>:
> Thanks Markus. Already registered and can access ftp. Unfortunately,
> processed (L3) rainfall data will be released by Dec 2014.
> Will just wait then. :)
>
> On Thu, Nov 6, 2014 at 4:27 PM, Markus Neteler <nete...@osgeo.org> wrote:
> > On Mon, Nov 3, 2014 at 10:18 AM, maning sambale
> > <emmanuel.samb...@gmail.com> wrote:
> >> Has anyone here able to archive and load GPM dataset into GRASS? I
> >> was able to get TRMM netcdf in my area of interest before, but I can't
> >> find the tools to automate GPM downloads.
> >>
> >> Thanks!
> >>
> >> [0] http://www.nasa.gov/mission_pages/GPM/main/
> >
> > They state
> >
> > "All data are freely available through the NASA's Precipitation
> > Processing System at http://pps.gsfc.nasa.gov";
> >
> > --> "Register and search for GPM and TRMM data, order custom subsets
> > and set up subscriptions using PPS Data Products Ordering Interface
> > (STORM)."
> >
> > At time the server seems to be down?
> >
> > Markus
>
>
>
> --
> cheers,
> maning
> ------------------------------------------------------
> "Freedom is still the most radical idea of all" -N.Branden
> wiki: http://esambale.wikispaces.com/
> blog: http://epsg4253.wordpress.com/
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