Full catalog/OCO2_GEOS_L3CO2_MONTH
OCO2_GEOS_L3CO2_MONTH·v10r·dataset

Carbon dioxide in the air, monthly map (OCO-2 + model, 0.5 deg)

OCO-2 GEOS Level 3 monthly, 0.5x0.625 assimilated CO2 V10r (OCO2_GEOS_L3CO2_MONTH) at GES DISC
atmosphere NASA GES_DISC Level 3
In plain English

What it measures. A gap-free monthly global map of carbon dioxide in the atmosphere, filling in the many places and times where the satellite couldn't see directly.

How it's made. Combines OCO-2's CO2 retrievals with a NASA atmospheric model through data assimilation, which blends observations with simulations of how air and carbon move, on a roughly half-degree grid.

How & where you'd use it. Provides complete CO2 maps for studying the carbon cycle and tracking how carbon dioxide moves through the atmosphere.

What's measured

ATMOSPHERE › ATMOSPHERIC CHEMISTRY › CARBON AND HYDROCARBON COMPOUNDS › ATMOSPHERIC CARBON DIOXIDE

Coverage & cadence

  • Time span2014-06-01 → 2022-02-01
  • Measured byOCO-2 (OCO-2)
  • Processing levelLevel 3
  • 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

This is the Gridded Monthly OCO-2 Carbon Dioxide assimilated dataset. The OCO-2 mission provides the highest quality space-based XCO2 retrievals to date. However, the instrument data are characterized by large gaps in coverage due to OCO-2’s narrow 10-km ground track and an inability to see through clouds and thick aerosols. This global gridded dataset is produced using a data assimilation technique commonly referred to as state estimation within the geophysical literature. Data assimilation synthesizes simulations and observations, adjusting the state of atmospheric constituents like CO2 to reflect observed values, thus gap-filling observations when and where they are unavailable based on previous observations and short transport simulations by GEOS. Compared to other methods, data assimilation has the advantage that it makes estimates based on our collective scientific understanding, notably of the Earth’s carbon cycle and atmospheric transport. OCO-2 GEOS (Goddard Earth Observing System) Level 3 data are produced by ingesting OCO-2 L2 retrievals every 6 hours with GEOS CoDAS, a modeling and data assimilation system maintained by NASA’s Global Modeling and Assimilation Office (GMAO). GEOS CoDAS uses a high-performance computing implementation of the Gridpoint Statistical Interpolation approach for solving the state estimation problem. GSI finds the analyzed state that minimizes the three-dimensional variational (3D-Var) cost function formulation of the state estimation problem.

Get the data

oco2_geos_l3co2_month_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="OCO2_GEOS_L3CO2_MONTH",
    version="10r",
    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.