Earth Indicators

Live climate indicators in plain words, at earthindicators.org.

Each page shows one of Earth's vital signs, updated automatically from the agencies that measure it:

Page	Data
Global air temperature	Copernicus ERA5
Sea surface temperature	NOAA OISST
Coral reef heat stress, on the sea surface page	NOAA Coral Reef Watch
El Niño (Niño 3.4)	NOAA OISST
Hurricane season energy (ACE), on the El Niño page	NOAA NCEI IBTrACS
Pacific Decadal Oscillation	NOAA NCEI
Solar cycle (sunspots)	WDC-SILSO, Royal Observatory of Belgium
Ocean heat content	NOAA NCEI
Sea level	NASA
Sea ice extent	NSIDC Sea Ice Index
Land ice (Greenland, Antarctica)	NASA JPL GRACE/GRACE-FO
Glaciers	WGMS via Copernicus Climate Data Store
Sea ice volume	Copernicus Marine (Mercator GLORYS12; CryoSat-2 + SMOS)
Northern Hemisphere snow cover, on the sea ice page	NOAA snow cover record (Rutgers Global Snow Lab)
Wildfires (CO₂ from fires)	Copernicus / JRC Global Wildfire Information System
CO₂ (Mauna Loa)	NOAA Global Monitoring Laboratory
Methane	NOAA Global Monitoring Laboratory
Earth's energy imbalance	NASA CERES
Water cycle (water vapor in the air)	Copernicus ERA5
World temperature, four more records (air page)	NASA GISTEMP, NOAAGlobalTemp, HadCRUT5, Berkeley Earth
Land and ocean carbon sinks, on the slow signals page	Global Carbon Budget

Common claims, answered: short answers to the claims people run into most, using live numbers from the data pages. Every answer has its own link.

How it works

• Plain HTML, CSS and JavaScript. No build step; GitHub Pages serves the files as they are.
• GitHub Actions workflows (.github/workflows/) download fresh data from each agency on a schedule and commit it to data/.
• indicators.js calculates every live number shown outside the charts, so the front page, the claims page and the "In short" boxes always agree.

Where the numbers come from

How the numbers are made gives, for every chart, the exact dataset and version (with DOI), the files downloaded, the processing steps, the code and the checks.

The files in data/ are of two kinds:

• Agency files, unchanged: CO₂ and methane (NOAA GML), ocean heat content (h22-*.dat, NOAA NCEI), sea level (NASA-SSH, NOAA LSA), sea ice extent (NSIDC Sea Ice Index v4), PDO (NOAA NCEI), sunspot numbers (WDC-SILSO), Greenland and Antarctica ice mass (grace_*.txt, NASA JPL). Derived numbers (trends, running means, growth rates) are calculated in the browser by each page's own script.
• Series calculated here from gridded agency data:
  • scripts/build_nino34.py: El Niño and sea surface temperature, area-weighted averages of NOAA OISST v2.1 (*_daily_sst.csv, oisst2.1_*_sst_day.json).
  • scripts/build_era5.py and build_era5_regions.py: air temperature from Copernicus ERA5 (era5_*). In era5_t2_global_daily.csv the source column marks each day as Copernicus's published value (c3s, final, or c3s-prelim, from Copernicus's live series, about 2 days behind real time) or calculated here (cds, only if the live series can't be read).
  • scripts/build_glaciers.py: world glacier mass change per year (glaciers_global.csv), added up from the WGMS/Copernicus grid.
  • scripts/build_seaice_volume.py: sea ice volume for both poles from Copernicus Marine thickness and concentration grids, model (seaice_volume_glorys.csv) and satellite (seaice_volume_cs2smos.csv).
  • scripts/build_ace.py: hurricane season energy (ACE) for the North Atlantic and Northeast Pacific, added up from every 6-hourly storm position in NOAA IBTrACS (ace_daily.csv, one row per storm per day).
  • scripts/build_era5_tcwv.py: global water vapor in the air (total column water vapor), monthly since 1940, from Copernicus ERA5 monthly averages (era5_tcwv_monthly.csv).
  • scripts/build_snow.py: Northern Hemisphere snow-covered land per week from NOAA's snow cover record (snow_nh_weekly.csv); identical to Rutgers' published tables.
  • scripts/build_coral.py: daily count of coral reef regions at each bleaching alert level, from NOAA Coral Reef Watch's ~210 virtual stations (coral_alert_daily.csv, coral_baa.csv).
  • scripts/build_fires.py: weekly CO₂ from fires per region from the GWIS API (fires_weekly.csv; GWIS's values, saved as published).
  • scripts/build_temp_records.py: four monthly world temperature records as published ().

Calculated series are checked against independently published ones; the results are saved as data/nino34_check.txt, data/era5_seam_check.txt and data/era5_overlap_check.txt and shown on the methods page.