The Historical Climate KPI (Historical Climate Trend) displays the daily time series of a user-selected climate variable for the study area, showing -- for each day of the chosen period -- mean, maximum, and minimum values. It is an exploratory visualization tool: it produces no A--E quality scores, but provides the complete time series of 24 meteorological variables from 1940 to the present.
The data source is the Open-Meteo ERA5-Land reanalysis, with a spatial resolution of approximately 10 km and daily coverage from 1940 to the present. The chart colors each point in the series based on 1961--1990 reference percentiles, making it immediately visible when values are anomalous relative to the historical climatology.
This KPI is the parent of 26 sub-variable KPIs (e.g., Historical Temperature, Historical Cloud Cover, Historical Precipitation, etc.), each corresponding to a specific state of the variable selector in the same chart.
For each day in the selected period, daily values are extracted from the ERA5-Land reanalysis:
The severity color of each data point is calculated by comparing the value against reference percentiles computed for that variable and location over the 1961--1990 period:
where the percentile intervals cover levels [10, 20, 30, 40, 50, 60, 70, 80, 90, 95, 99] of the 1961--1990 reference distribution. For some variables, the color scale is inverted so that ecologically unfavorable extremes always map to warm tones.
Units vary by variable: degrees C for temperatures, % for humidity and cloud cover, mm for precipitation, m3/m3 for soil moisture, hPa for pressure, km/h for wind, MJ/m2 for radiation, h for sunshine duration.
Data are sourced from the Open-Meteo Historical Weather API (ERA5-Land reanalysis, ECMWF) at approximately 10 km spatial resolution with daily coverage from 1940 to the present.
Line Chart. An interactive daily time series chart showing the evolution of a selectable climate variable over time, with per-point severity coloring and -- for 9 variables -- three separate lines for minimum, mean, and maximum.
Purpose: Answers the question "How have temperature, humidity, wind, soil moisture, and other climate variables evolved at this site over recent years?" Allows identification of anomalies, trends, and seasonal cycles for any of the 24 available variables.
Description: The component is organized with a header showing the title, topic badge, variable dropdown selector, date range selector, and download button. Above the chart, Min / Mean / Max statistics for the displayed period are shown. The chart itself presents:
How it's calculated: Values are extracted from the ERA5-Land reanalysis via the Open-Meteo API. For each day, minimum, mean, and maximum are recorded. Severity coloring is calculated by comparing each value against the variable's percentile intervals derived from the 1961--1990 reference period. The default variable on load is temperature at 2 m above ground.
Note: There is no fixed color legend -- the severity scale varies per variable. In general:
Interpretation example:
If the temperature chart shows red data points in July 2022 with maximums reaching 38 degrees C, those days were anomalously hot compared to the 1961--1990 historical average, indicating a significant heat wave. In autumn, a return to green/yellow points signals a return to climatological norms.
| Source | Provider | Coverage | Resolution | Period |
|---|---|---|---|---|
| Open-Meteo Historical Weather (ERA5-Land) | Open-Meteo / ECMWF | Global | ~10 km spatial, daily | 1940 -- present |
For each requested day, the platform queries the Open-Meteo Historical Weather API, which serves ERA5-Land reanalysis data. The response includes daily minimum, mean, and maximum for the 9 min/max variables, and daily mean (or daily sum for cumulative quantities such as precipitation, snowfall, radiation, and reference evapotranspiration) for the remaining 15 variables.
Severity coloring is computed by comparing each daily value against a set of reference percentile intervals calculated over the 1961--1990 period (WMO standard climatological normal) for that specific variable and geographic location. The percentile levels used are [10, 20, 30, 40, 50, 60, 70, 80, 90, 95, 99]. Each value is mapped to a color from a continuous gradient based on where it falls within these percentile intervals. For variables where high values are ecologically negative (e.g., temperature extremes), warm colors indicate stress; for variables where low values are negative (e.g., precipitation deficit), the color scale is inverted accordingly.
Data is generated on demand in 5-year chunks to avoid API timeouts; the first display may take a few seconds. The display window is configurable up to 5 years back from the current date.