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Full catalog/clms_npp_global_300m_10daily_v2
clms_npp_global_300m_10daily_v2·dataset

How much carbon plants store, 2014-present (Copernicus)

CLMS NPP Global 300m 10-daily V2
biosphere ESA ESA Copernicus active COGNetCDF
In plain English

What it measures. Estimates the net amount of carbon (biomass) plants produce per area each day, after accounting for the energy they use to breathe, measured in grams of carbon per square meter per day. It runs from January 2014 to the present.

How it's made. Built by ESA Copernicus from PROBA-V and Sentinel-3 OLCI observations at roughly 300-meter resolution, updated every ten days in near real time.

How & where you'd use it. Useful for tracking ecosystem productivity and carbon uptake over a long period, informing climate models, carbon budgets, and food and forestry studies.

What's measured

CopernicusCLMSNPPNet Primary Productioncarbon fluxglobal10-daily300mPROBA-VSentinel-3OLCI

Coverage & cadence

  • Time span2013-11-01 → ongoing
  • Spatial extent-179.9999999, -59.9985119, 179.9985119, 80.0014881
  • FormatsCOG, NetCDF

What you can do with it

  • Map vegetation, forests and biomass
  • Monitor ecosystem productivity and carbon
  • Support habitat and biodiversity studies
Official description

Defined as the net amount of biomass, or carbon, produced by plants per unit area and time, expressed in gC/m²/day. It is equal to the difference between the Gross Primary Production (GPP), i.e. the total amount of carbon produced through photosynthesis, and the amount of energy used for plant respiration. Every 10-days estimates are available in near real time at global scale in the spatial resolution of about 300 m from January 2014 to the present.

Get the data

copernicus_access.py
# ESA Copernicus Data Space — open STAC API (free account)
from pystac_client import Client

cat = Client.open("https://stac.dataspace.copernicus.eu/v1")
search = cat.search(
    collections=["clms_npp_global_300m_10daily_v2"],   # add _cog or _nc for a format variant
    bbox=(-10, 35, 30, 60),             # your area (W,S,E,N)
    datetime="2024-01-01/2024-12-31",
)
items = list(search.items())            # then read assets with rioxarray / xarray
Browsing the Copernicus STAC is open; downloading bytes needs a free Copernicus Data Space account.