Working with vast amounts of data is not trivial. Working with this amount of data quickly turns into a computer science exercise and it is a pain for any researcher who only need time-series data for a couple of locations. In the case of Open-Meteo with 23 weather variables, more than 20 terabytes had to be downloaded from the CDS.
#Look up past weather full#
Even if you are only interested in a hand full of weather variables like temperature, precipitation and wind, you quickly have to download 1 terabyte or more. I did not find exact numbers, but the data size must exceed 1 petabyte (1024 terabytes). There is one drawback however: ERA5 is huge!
#Look up past weather license#
Register an account, accept the license terms for open-data and with the CDS client Python library, you can start downloading. There are literally hundreds of weather variables available and some of them on 137 atmospheric levels reaching 80 km altitude.ĭata is available since 2019, but since June 2022 the real-time dataset is now available starting from 1959 until now with of delay 5-7 days.īy now, ERA5 is one of the most recognised historical weather datasets and used for many agriculture, energy and insurance applications. It offers global weather data in 30 km resolution and hourly values. ERA5 is available as open-data and you can download it from the Climate Data Store (CDS). A reanalysis still depends on measurement data, but gaps and inconsistencies can be corrected more easily.ĮRA5 is the fifth reanalysis weather dataset from the publicly funded EU Copernicus program and implemented by ECMWF. The principle is:Ĭollect station measurements from the last decadeĬombine them with satellite, radar and airplane observationsĪ reanalysis dataset can therefore provide global and consistent historical weather data bound by physical models. Many researchers faced these issues in the past and started to work on “reanalysis“ weather datasets. You can work around that, by combining data from multiple sources, filling gaps, ensuring consistency and using weather models to bridge larger distances between stations. Quality, accuracy and reliability differs.Įven if you find weather station data for your country, odds are that there are no weather stations close to the location of interest or that the time-series data are incomplete or inconsistent. High quality weather stations measure weather according to WMO standards, others were just recently installed with commodity hardware and measure less reliantly with infrequent maintenance intervals. Other NWS do not even share data on request. Some NWS offer data on open-data servers in CSV or scientific data files. Often, the national weather services (NWS) are a good start as they operate high quality weather measurements stations over decades. With climate change and more extreme weather patterns, many journalists rely on measurements to objectively evaluate whether the current heat spell or drought is a new record high or “just weather”. While working in the academic field, students often face the challenge of getting historical weather data for their research papers to analyse their hypothesis more deeply.
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