Company
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 delivered by consultancies and enterprise software vendors. We hypothesised that there was a need for affordable, high quality weather insights delivered by a modern software platform.
Vision
Enable society and businesses to adapt to a changing climate.
Mission
To build a reliable, trustworthy and comprehensive source for weather and climate insights by combining high quality climate research and software engineering.
Terms
Attribution
Unless otherwise noted, all content on this website is the property of Weathersight LLC and is protected by United States and international copyright laws. You are welcome to use our content for personal, non-commercial purposes, but we require that you attribute the content to us by including a hyperlink to our website or the specific page from which the content originated. You may not use our content for commercial purposes without our express written consent.
Your email-address
Email-addresses that you have shared with us through our contact page will not be shared with third parties without your explicit consent.
The email-address that you have used to authenticate for API access token(s) will never be shared with third parties.
Data
Historical Data
All historical data used for daily (FULL_DAY), weekly (WEEK), monthly (MONTH), yearly (YEAR) anomalies and timeseries are derived from NOAA GSOD dataset.
The daily maximum temperature (Tmax) and daily minimum temperature(Tmin) are computed across UTC days for all
locations.
For some locations this means that their actual Tmax, Tmin computed according to their definition of
meteorological day will be different.
The anomaly detection though will remain unaffected for all
locations as
UTC days are consistently applied across historical data.
All historical data used for climatlogy comparisons and extremes estimation are derived from NOAA GHCND dataset.
Recent Data
METAR
All recent data interprets METAR data and is made consistent with local timezone meteorological day starting
and
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 DAY are restricted to US administered locations.
SYNOP
For fast turn-around of Tmax, Tmin and precipiation anomalies of global stations, SYNOP reports via ogimet are used. FULL_DAY reports and their anomalies 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.
Forecast Data
A number of sources are being tested for forecast quality and accuracy. They form the basis to calculate FUTURE_DAY anomalies and trends. The forecast dataset is refreshed sub-daily for all locations.Reanalysis Datasets
We have used ERA5 dataset made available by open-meteo.com