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Full catalog/MACTWP_mean
MACTWP_mean·v1·dataset

How much liquid water clouds hold (monthly, 1 deg)

Multisensor Advanced Climatology Total Liquid Water Path L3 Monthly 1 degree x 1 degree V1 (MACTWP_mean) at GES DISC
atmosphere NASA GES_DISC Level 3
In plain English

What it measures. Monthly estimates over the oceans of how much liquid water is held in clouds, plus a 'total water' figure that includes rain. Provided at 1-degree resolution.

How it's made. Computed by the MAC-LWP algorithm, which combines and bias-corrects cloud-water measurements from a series of microwave satellite sensors and accounts for changing satellite overpass times.

How & where you'd use it. Helps scientists study cloud water content and the water cycle over the oceans, and serves as a quality check on the related cloud-water product.

What's measured

ATMOSPHERE › CLOUDS › CLOUD MICROPHYSICS › CLOUD LIQUID WATER/ICE

Coverage & cadence

  • Time span1988-01-01 → 2016-12-31
  • Measured byDMSP (SSMIS, SSM/I) · Aqua (AMSR-E) · GCOM-W1 (AMSR2) · GPM (GMI) · TRMM (TMI) · NPOESS (National Polar-orbiting Operational Environmental Satellite System ) (WINDSAT)
  • Processing levelLevel 3
  • Spatial extent180, -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

The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP) data set contains monthly 1.0-degree ocean-only estimates of cloud liquid water path (MACLWP_mean), total water path (MACTWP_mean) which includes both cloud and rain water, and monthly climatologies of cloud liquid water path diurnal cycle amplitudes and phases (MACLWP_diurnal). The MACTWP_mean field can also be used as a quality-control screen for the MACLWP_mean field as discussed in Elsaesser et al. (2017), where uncertainty increases as the ratio of cloud to total water path increases. The MAC-LWP algorithm uses as input the Remote Sensing Systems (RSS) Version 7 0.25 degree-resolution retrieval products (produced using the SSM/I, AMSR-E, TMI, AMSR-2, GMI, SSMIS, and WindSat satellite sensors), and performs a bias correction on all input RSS cloud water path products based on AMSR-E matchups to clear-sky MODIS scenes. The MAC-LWP algorithm ensures that spurious trends and variability in the cloud fields arising from drifting satellite overpass times are mitigated by simultaneously solving for the monthly average cloud and total water paths and monthly-mean diurnal cycles, as discussed in O’Dell et al. (2008). Additional details on the algorithm and data fields can be found in Elsaesser et al. (2017).

Get the data

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

results = earthaccess.search_data(
    short_name="MACTWP_mean",
    version="1",
    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.