For now, it is limited to IMERGHH data.
Hope it could help people working with those data.
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.sambale@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 <neteler@osgeo.org> wrote:
On Mon, Nov 3, 2014 at 10:18 AM, maning sambale
<emmanuel.sambale@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
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