Mann–Kendall two-sided p < 0.10. The reported rate is the Theil–Sen slope.
| Variable | Finding |
|---|
A change is called detected when the Mann–Kendall test finds the trend unlikely to have arisen by chance against a background of internal variability:
Mann–Kendall two-sided p < 0.10. The reported rate is the Theil–Sen slope.
The test runs on whatever window you select, so narrowing the window changes both the slope and the verdict.
Each combination is tested on its own and the verdict describes only the series on screen. GHCN and Berkeley Earth can reach different verdicts for the same variable; switch between them to see it.
Significance is not the same as importance. Each chart also draws the 66% and 90% historical range bands so the fitted change can be compared with ordinary year-to-year spread by eye — a trend can clear p < 0.10 while remaining small against that spread. Bear in mind too that a linear trend is a poor summary of a series whose largest feature is a single decade; for CONUS the 1930s dominate.
Every metric runs through one implementation (scripts/metrics.py) for all four
dataset and region combinations, so a difference between two panels is a difference in the
data rather than in the arithmetic. A site is a station for GHCN and a land grid point for
Berkeley Earth.
This is a static page. Every value is precomputed and loaded from
dashboard-series.js; there is no server, no database, and no network request
at view time. The statistics, charts and downloads all run in your browser.
Rebuild with python scripts/build_dashboard_data.py. The CONUS GHCN series come
from the parent project's own checkpoints and reproduce
data/heat_wave_index_raw_adj_wtd.csv and
data/annual_hottest_daily_high_raw_adj_wtd.csv exactly; the Berkeley CONUS Heat
Wave Index reproduces data/heat_wave_index_berkeley.csv exactly. Tests assert
all three.