Global CO2 growth signals (growth rate, acceleration, records)
Monthly global CO2 accumulation signals from NOAA Global Monitoring Laboratory measurements (1974 ->): the de-seasonalized global monthly mean with 3-month momentum, year-on-year change, 30-month change volatility, 3-sigma anomaly flags, naive-drift forecasts, the annual growth rate (ppm/yr and %), growth acceleration, a rolling 10-year trend slope, record-high flags and an acceleration flag. The pace-of-accumulation lens on the carbon cycle — levels always rise, so the growth rate is the signal. Companion to us-carbon-accountability-signals (company emissions) and us-climate-signals (city temperatures). Rows normalized to country_code WLD (World). Raw data: NOAA Global Monitoring Laboratory.
Quality
Attribution
NOAA Global Monitoring Laboratory; signals by Frontier Data Hub
Schema
| Column | Type | Description |
|---|---|---|
| date | string | First day of the observation month (NOAA GML co2_mm_gl.txt year/month fields). |
| country | string | |
| country_code | string | |
| series_id | string | CO2_GML: global monthly mean atmospheric CO2 from the NOAA GML cooperative air-sampling network (co2_mm_gl.txt). |
| series_label | string | Global monthly mean atmospheric CO2, de-seasonalized, in parts per million (NOAA GML). |
| value | float | De-seasonalized global monthly mean CO2 mole fraction in dry air, parts per million (NOAA GML co2_mm_gl.txt column 5). |
| momentum_3m | float | |
| yoy_change | float | |
| volatility_30d | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| growth_yoy | float | |
| growth_rate_yoy_pct | float | |
| growth_acceleration | float | |
| trend_slope_10y | float | |
| record_high_flag | integer | |
| accel_flag | integer |
Sample rows
| date | country | country_code | series_id | series_label | value | momentum_3m | yoy_change | volatility_30d | anomaly_flag | forecast_1m | growth_yoy | growth_rate_yoy_pct | growth_acceleration | trend_slope_10y | record_high_flag | accel_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1979-01-01 | World | WLD | CO2_GML | Global monthly mean atmospheric CO2, de-seasonalized (NOAA GML, ppm) | 0.1 | — | — | — | 0 | — | — | — | — | — | 0 | 0 |
| 1979-02-01 | World | WLD | CO2_GML | Global monthly mean atmospheric CO2, de-seasonalized (NOAA GML, ppm) | 0.09 | — | — | — | 0 | — | — | — | — | — | 0 | 0 |
| 1979-03-01 | World | WLD | CO2_GML | Global monthly mean atmospheric CO2, de-seasonalized (NOAA GML, ppm) | 0.1 | — | — | — | 0 | — | — | — | — | — | 1 | 0 |
| 1979-04-01 | World | WLD | CO2_GML | Global monthly mean atmospheric CO2, de-seasonalized (NOAA GML, ppm) | 0.11 | 0.009999999999999995 | — | — | 0 | — | — | — | — | — | 1 | 0 |
| 1979-05-01 | World | WLD | CO2_GML | Global monthly mean atmospheric CO2, de-seasonalized (NOAA GML, ppm) | 0.04 | -0.049999999999999996 | — | — | 0 | — | — | — | — | — | 0 | 0 |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/co2_growth_signals/global_co2_growth_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/co2_growth_signals/global_co2_growth_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/co2_growth_signals/global_co2_growth_signals
Tip: fetch /llms.txt for the full machine-readable catalog.