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lislipG·v4·dataset

Background images for spotting lightning (TRMM satellite)

Lightning Imaging Sensor (LIS) on TRMM Backgrounds V4
atmosphere NASA GHRC_DAAC Level 1B HDF4netCDF-4
In plain English

What it measures. The steady background scenes that the lightning sensor sees, against which actual lightning flashes stand out.

How it's made. Recorded by the Lightning Imaging Sensor aboard the TRMM satellite, which watched tropical and subtropical regions both day and night.

How & where you'd use it. A supporting input for lightning detection: the background images help separate real lightning flashes from the ordinary brightness of the scene, so they are mainly used alongside the lightning data rather than on their own.

What's measured

Atmosphere › Atmospheric Electricity › LightningAtmosphere › Weather Events › Lightning

Coverage & cadence

  • Time span1998-01-01 → 2015-04-08
  • Measured byTRMM (LIS)
  • Processing levelLevel 1B
  • Spatial extent-180, -40, 180, 40
  • FormatsHDF4, netCDF-4
  • 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 Lightning Imaging Sensor (LIS) Backgrounds was collected by the LIS instrument on the Tropical Rainfall Measuring Mission (TRMM) satellite used to detect the distribution and variability of total lightning occurring in the Earth’s tropical and subtropical regions. This data can be used for severe storm detection and analysis, as well as for lightning-atmosphere interaction studies. The LIS instrument makes measurements during both day and night with high detection efficiency. These data are available in both HDF-4 and netCDF-4 formats.

Get the data

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

results = earthaccess.search_data(
    short_name="lislipG",
    version="4",
    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 GHRC_DAAC
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.