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Full catalog/AIRS_CPR_IND
AIRS_CPR_IND·v4.0·dataset

Index linking matched cloud views (AIRS + CloudSat)

AIRS-CloudSat cloud mask and radar reflectivities collocation indexes V4.0 (AIRS_CPR_IND) at GES_DISC
atmosphere NASA GES_DISC Level 2
In plain English

What it measures. Not measurements themselves, but a lookup table that matches up where CloudSat, AIRS, and AMSU instruments were all looking at the same place and time.

How it's made. Built by computing space-and-time overlaps between the A-train satellites' footprints for each AIRS observing window, stored as collocation indexes.

How & where you'd use it. A behind-the-scenes input that lets scientists merge water-vapor and cloud measurements from several A-train instruments into one combined climate record.

What's measured

ATMOSPHERE › CLOUDS

Coverage & cadence

  • Time span2006-06-15 → 2015-01-30
  • Measured byAqua (AIRS) · CloudSat (CloudSat-CPR)
  • Processing levelLevel 2
  • Spatial extent-180, -90, 180, 90
  • StatusCOMPLETE

What you can do with it

  • Map air pollutants — NO₂, aerosols, ozone
  • Track greenhouse gases and Earth's energy budget
  • Feed weather and air-quality analysis
Official description

Version 4.1 is the current version of the data set. Previous versions are no longer available and have been superseded by Version 4.1. This is AIRS-AMSU-CloudSat collocation indexes, in netCDF-4 format. These data map CloudSat profile indexes to the collocated AMSU field of views, and AIRS IR footprints, per AIRS 6-min granule time. Hence it can be considered as Level 1. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple "A-train" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, & CloudSat), classify each "scene" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time "matchups" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_IND

Get the data

airs_cpr_ind_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="AIRS_CPR_IND",
    version="4.0",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from GES_DISC
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.