Improved local UK weather data freely available, Met Office Crowd-grid released via the CEDA Archive

We are pleased to announce that a new dataset from the Met Office: Crowd-Grid is now available in the CEDA Archive. 

Crowd-Grid is an innovative new prototype dataset that includes quality-controlled public observations to provide enhanced local-level detail to a 1km x 1km grid of the UK’s weather.

It adds crowdsourced observations from the Met Office Weather Observation Website (WOW), to give a more detailed view of the temperatures people experience, including in built-up areas. It also draws on datasets such as the MIDAS Open  (historical weather station data), and is designed to supplement the HadUK-Grid data  (gridded climate variables), both of which are also curated for wider access via the CEDA Archive. 

The crowd-grid data consists of two parts:

• Minimum and maximum daily temperatures that differs from and complements the “standard” gridded dataset, HadUK-Grid, the Met Office’s official climate record.
• A set of Recent Heat Packs  that provide information about the temperatures experienced recently in each local authority area.

Crowd-Grid aims to support the UK’s adaptation to our current climate and in anticipation of the changes in climate to come. By leveraging quality-controlled public observations, Crowd-Grid improves our understanding of the local detail in heatwaves and cold spells, and how it varies across urban and rural areas. This improved understanding can then inform decisions aimed at reducing the impact on the UK population of future heatwave events.

More information on Crowd-Grid is available via the Met Office’s “Adding local insight: How public observations could enhance weather station data”  article.

The dataset publication work was completed as part of CEDA’s work with the Met Office Hadley Centre Climate Programme. We have provided guidance on preparing the data for wider, long-term re-use and services to ensure that they remain Findable, Accessible, Interoperable, and Re-useable for a wide range of users alongside many other complementary datasets.