We founded Weathersight to improve the utility of a large number of publicly available weather and climate datasets. As we explain in our blog, climate reports that analyzed these datasets were inadequate for informing people of regional changes to weather patterns on a continuous basis. For businesses, site specific analysis of current or future weather patterns remain expensive and are provided by consultancies and enterprise software vendors. We hypothesized that there was a need for affordable, high quality weather insights delivered by a modern software platform.
Enable society and businesses to adapt to a changing climate by providing relevant and timely insights of weather patterns.
To facilitate data-driven communication on climate change by offering reliable and comprehensive information about weather patterns across the globe.
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All recent data interprets METAR data and is made consistent with local timezone meteorological day starting
ending 0000 hrs.
The DAY anomalies use this data to compare against the corresponding week's historical distribution. The Tmax, Tmin are estimates based on hourly or half-hourly readings from the stations and preciptiation totals are sums of readings.
Precipitation data is missing from Global METAR data. So, rainfall and snowfall anomalies of type DAY are restricted to US administered locations.
For fast turn-around of Tmax, Tmin and precipiation anomalies of global stations, SYNOP reports via ogimet are used. Anomalies of type FULL_DAY intend to reflect true Tmax, Tmin and 24hr precipitation totals. These are available within few hours of end of day and are eventually reconciled with NOAA GSOD dataset, usually after 2-7 days.
We have used ERA5 dataset made available by open-meteo.com to cover gaps in observed precipiation and temperature data in several metropolitan areas. Since it is a separate dataset, analyses derived from it can be viewed by altering SourceType available with most offerings.
Climate Projections We have usesd downscaled CMIP6 datasets made available by open-meteo.com to understand estimated climate across various metropolitan areas through 2050. Since it is a separate dataset, analyses derived from it can be viewed by altering SourceType available with most offerings.
Most metrics (see below) for most analyses are defined for the UTC day. The exception are for analyses of type DAY , where metrics are defined for local day starting at and ending before 0000 hrs. Since the definitions are consistent across time periods, anomaly computations are unaffected. However, some absolute measures of counts (e.g. number of days where Tmax breached a threshold) might be different from those obtained by using country specific definitions of a meteorological day (e.g. 0830 to 0830 IST).
|Maximum Temperature (Tmax)
|Highest temperature observed in a 24hr period
|Maximum Temperature (Tmin)
|Lowest temperature observed in a 24hr period
|Average Temperature (Tavg)
|Mean of hourly observations in a 24hr period if good coverage is available , otherwise an estimate (Tmax+Tmin)/2
|Average Dewpoint (ADPT)
|Mean of hourly observations if good coverage is available , otherwise undefined
|Max Wet Bulb Temp (WBULB)
|Highest wet bulb temperature observed in a 24hr period from hourly observations
|Max Dew Point Depression (DPD)
|Highest dew point depression in a 24hr period from hourly observations
|Daily Rain Accumulation (RAIN)
|Accumulated rainfall over a 24hr period
|Hourly Rain Accumulation (RAINH)
|Accumulated rainfall over a 1hr period.
|Daily Snow Accumulation (SNOW)
|Water equivalent of snow over a 24hr period
|Average Wind Speed (AWND)
|Mean of wind speeds observed in a 24hr period if good coverage is available , otherwise undefined
|Maximum Wind Speed (WSF5)
|Highest wind observed in a 24hr period
|Fastest 5-second wind speed
|Peak Wind Gust (WSFG)
|Peak wind gust speed in a 24hr period