[Data]: IMERG Precipitation Climatologies

[mccabete]

Dataset Name

IMERG Daily Precipitation Climatology

Dataset Description

IMERG releases pre-calculated precipitation climatologies at the Grand/annual scale, the monthly scale, and the daily scale.

These are extremely useful as pre-calculated reference datasets because calculating a climatology means taking an average over a long time-domain (usually 20 years). When we have a reference climatology dataset, it's easier to calculate the anomalies by subtracting the pre-calculated mean over a shorter time domain of interest. I am most interested in using the daily precipitation anomalies.

Requestor Name/Affiliation

Tempest McCabe, University of Maryland, NASA GSFC

Platform/Method/Sensor

The GPM satellite constellation.

URL or DOI to Dataset Description

https://gpm.nasa.gov/data/imerg/precipitation-climatology

URL to Download or Access the Data

https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip

Data License

Unknown, but is a NASA product

Intended Science Use Case

This would be used in combination with IMERG precipitation data to calculate precipitation anomalies.

Format of the Data

GeoTIFF, NetCDF

Approximate Size of the Data

8GB

Date Needed By

04/01/2026

Additional Information

I am most interested in daily climatologies, but I suspect the community would appreciate all the climatology datasets currently offered as netcdf and GeoTiff.

[wildintellect]

Quick look:

• the data comes in both NetCDF4/HDF5 (7GB), and GeoTIFF (8GB). In both cases they are inside of a Zip.
• It's a relatively static dataset, so a single import and hosting would suffice with an update if later versions are published.
• There is no authenticated required on the access.

Options:

• use /vsizip/vsicurl drivers with gdal based tools, it's nested zips, and super slow ... (see below)
• create a virtualizarr around the netcdf version
• import and convert either format to cloud optimized version and catalog in STAC or Virtualizarr with the MAAP or VEDA catalogs

@abarciauskas-bgse @hrodmn have thoughts on the best approach? cc: @smohiudd in case we want this in VEDA STAC instead of MAAP STAC.

$ gdalinfo /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip
ERROR 4: `/vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip' not recognized as being in a supported file format.
gdalinfo failed - unable to open '/vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip'.
Unable to open source `/vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip' directly.
The archive contains several files:
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth12GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth12GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth01GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth02GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth03GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth04GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth05GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth06GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth07GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth08GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth09GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth10GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/__MACOSX/._IMERGdailyClimatology2001to2022forMonth11GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth01GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth02GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth03GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth04GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth05GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth06GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth07GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth08GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth09GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth10GeoTIFF.zip
       /vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth11GeoTIFF.zip

Just confirming you can in fact get to the file with gdal, but it's not cloud optimized

gdalinfo /vsizip/vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth10GeoTIFF.zip/IMERG-Final.CLIM.2001-2022.1001.V07B.tif
Driver: GTiff/GeoTIFF
Files: /vsizip/vsizip/vsicurl/https://gpm.nasa.gov/sites/default/files/data/climatologies/2024/IMERGdailyClimatology2001to2022_GeoTIFF_V07B.zip/IMERGdailyClimatology2001to2022forMonth10GeoTIFF.zip/IMERG-Final.CLIM.2001-2022.1001.V07B.tif
Size is 3600, 1800
Coordinate System is:
GEOGCRS["WGS 84",
    ENSEMBLE["World Geodetic System 1984 ensemble",
        MEMBER["World Geodetic System 1984 (Transit)"],
        MEMBER["World Geodetic System 1984 (G730)"],
        MEMBER["World Geodetic System 1984 (G873)"],
        MEMBER["World Geodetic System 1984 (G1150)"],
        MEMBER["World Geodetic System 1984 (G1674)"],
        MEMBER["World Geodetic System 1984 (G1762)"],
        MEMBER["World Geodetic System 1984 (G2139)"],
        MEMBER["World Geodetic System 1984 (G2296)"],
        ELLIPSOID["WGS 84",6378137,298.257223563,
            LENGTHUNIT["metre",1]],
        ENSEMBLEACCURACY[2.0]],
    PRIMEM["Greenwich",0,
        ANGLEUNIT["degree",0.0174532925199433]],
    CS[ellipsoidal,2],
        AXIS["geodetic latitude (Lat)",north,
            ORDER[1],
            ANGLEUNIT["degree",0.0174532925199433]],
        AXIS["geodetic longitude (Lon)",east,
            ORDER[2],
            ANGLEUNIT["degree",0.0174532925199433]],
    USAGE[
        SCOPE["Horizontal component of 3D system."],
        AREA["World."],
        BBOX[-90,-180,90,180]],
    ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
Origin = (-180.000000000000000,90.000000000000000)
Pixel Size = (0.100000001490116,-0.100000001490116)
Metadata:
  TIFFTAG_DOCUMENTNAME=/PANFS/user/data/okelley/202402_imerg/v7climRedo/daily_netCDF4/IMERG-Final.CLIM.2001-2022.1001.V07B.tif
  TIFFTAG_IMAGEDESCRIPTION=IDL TIFF file
  TIFFTAG_SOFTWARE=IDL 8.7.2, Harris Geospatial Solutions, Inc.
  TIFFTAG_DATETIME=2024:06:07 18:27:44
  TIFFTAG_XRESOLUTION=100
  TIFFTAG_YRESOLUTION=100
  TIFFTAG_RESOLUTIONUNIT=2 (pixels/inch)
  AREA_OR_POINT=Area
Image Structure Metadata:
  COMPRESSION=LZW
  INTERLEAVE=BAND
Corner Coordinates:
Upper Left  (-180.0000000,  90.0000000) (180d 0' 0.00"W, 90d 0' 0.00"N)
Lower Left  (-180.0000000, -90.0000027) (180d 0' 0.00"W, 90d 0' 0.01"S)
Upper Right ( 180.0000054,  90.0000000) (180d 0' 0.02"E, 90d 0' 0.00"N)
Lower Right ( 180.0000054, -90.0000027) (180d 0' 0.02"E, 90d 0' 0.01"S)
Center      (   0.0000027,  -0.0000013) (  0d 0' 0.01"E,  0d 0' 0.00"S)
Band 1 Block=3600x1 Type=Float32, ColorInterp=Gray

[mccabete]

Maybe relevant, but I would want to work with this dataset in combination with the "DOI:10.5067/GPM/IMERGDF/DAY/07" dataset, which is stored on us-west-2. I was accessing using the earthaccess.search_data python function.

[jsignell]

It looks like the zip files technically use Defl:N. I think this means Deflate: Normal, but I'd love to find a doc that unambiguously states this. The compression ratio for both the netcdfs and the tiffs is 0%. I'm not sure if that means that the compression on the underlying files exactly matches the one on the zip.

This is the command I was using to investigate
!unzip -v IMERG-Daily-Final.CLIM.2001-2022.V07B_NetCDF.zip

[wildintellect]

If you try to zip an already compressed file, the compression ratio doesn't change (ie zip is unable to achieve better results)

[hrodmn]

We could easily convert to COGs but this seems like great candidate for virtualizarr (unless there are R users who need it ASAP). We would be able to visualize it with titiler-multidim if we ever need to do that.

[tylanderson]

@mccabete do you have a specific way you need to access the climatology product? e.g. only need one days climatology product or reducing multiple daily climatology products before combining with something else (e.g. IMERG daily)

We can product a Zarr product from the netcdfs, which would provide easy access to multiple timestamps, but usage would help guide how we'd choose to chunk the data

[mccabete]

@tylanderson Great question! I am developing my methods now (based around what is available), but here is the rough outline. Because I have the attention of so many data-ingest experts, if you see a simpler way to do what I am doing, I am all ears.

I will be looking at precipitation anomalies over fires while those fires are burning. I have a dataset from 2012-2026 of fires and when they started and stopped. My plan is to:

• extract the daily precipitation values from IMERG using the earthaccess tools on a per-fire bases (~ 4050 fires).
• • This involves a bounding-box based spatial clip to the extent of the fire, and a temporal slice from the start and end date of the fire (a few days - 2 months)
• Then write the output into a giant parquet that I can merge with a dataframe of daily fire spread data
• If I had daily climatologies, I would performa a similar extraction. First I would clip to the bounding box of each fire, perform an aggrigation function (mean or max), and then get the timeseries from the start to the end of the fire. Per fire.
• • Finally I would subtract the climatology numbers I extracted from the raw precipitation value I extracted to get the per-fire precipitation anomalies.
• I would put that in a geodataframe, and do a bunch of visualization, science, and statistics on it.

[mccabete]

Does that answer your question?

[mccabete]

If it helps: all of the fire are in CONUS. So a sampling within a limited spatial range.