Earth Data School
About
Full catalog/MUR-JPL-L4-GLOB-v4.1
MUR-JPL-L4-GLOB-v4.1·v4.1·dataset

How warm the sea surface is, gap-free daily (1 km)

GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)
ocean NASA POCLOUD Level 4 netCDF-4
In plain English

What it measures. A gap-free daily map of sea surface temperature for the whole globe at very fine 1-kilometer detail, with no missing pixels from clouds. Some files also include how unusual that day's temperature was compared to normal.

How it's made. Created at JPL by blending nighttime sea surface temperature readings from many satellite sensors (including MODIS, AMSR, AVHRR, and WindSat) plus ship and buoy measurements, filled in with a mathematical interpolation method.

How & where you'd use it. Widely used for weather and climate studies, marine forecasting, tracking marine heatwaves and ocean currents, and supporting fisheries and ecosystem work. The gap-free, high-resolution coverage makes it especially convenient.

What's measured

OCEANS › OCEAN TEMPERATURE › SEA SURFACE TEMPERATURE › FOUNDATION SEA SURFACE TEMPERATURE

Coverage & cadence

  • Time span2002-05-31 → ongoing
  • Measured byAqua (MODIS, AMSR-E) · CORIOLIS (WINDSAT) · Terra (MODIS) · NOAA-19 (AVHRR-3) · GCOM-W1 (AMSR2) · BUOYS (DRIFTING BUOYS)
  • Processing levelLevel 4
  • Spatial extent-180, -90, 180, 90
  • FormatsnetCDF-4
  • StatusACTIVE

What you can do with it

  • Watch sea-surface temperature and marine heatwaves
  • Spot algal blooms and ocean-colour shifts
  • Support fisheries and coastal monitoring
Official description

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset (four day latency) and near-real-time dataset (one day latency) at the JPL Physical Oceanography DAAC using wavelets as basis functions in an optimal interpolation approach on a global 0.01 degree grid. The version 4 Multiscale Ultrahigh Resolution (MUR) L4 analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several instruments including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. The ice concentration data are from the archives at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) High Latitude Processing Center and are also used for an improved SST parameterization for the high-latitudes. The dataset also contains additional variables for some granules including the SST anomaly (variable sst_anomaly) derived from a MUR climatology, and the temporal distance in hours to the nearest IR measurement for each pixel (variable dt_1km_data). Variable dt_1km_data first appears in the time series on October 4, 2015, while sst_anomaly starts July 23, 2019. This dataset was originally funded by the NASA MEaSUREs program (http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects), and created by a team led by Dr. Toshio M. Chin from JPL. It adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications. Use the file global metadata "history:" attribute to determine if a granule is near-realtime or retrospective.

Get the data

mur-jpl-l4-glob-v4.1_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MUR-JPL-L4-GLOB-v4.1",
    version="4.1",
    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 POCLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.