Our mission at WeatherXM is to create the largest decentralised weather station network. A significant challenge in this direction is how our weather stations should be distributed around the world.
The challenging part has to do with Earth’s surface, which is not uniform (a good thing in so many other aspects of our life!). Each area has its own meteorological peculiarities, from nearly uniform pieces of land that extend many kilometres, to small islands that include almost everything (for example, coastlines and hills and urban areas) in a few square kilometres, to cities where skyscrapers are next to parks, lakes and sea.
The WeatherXM cell modelling lets us optimally distribute our network’s stations around the world. To get there:
- We created a grid of hexagonal cells (size 7 of H3 grid system) that cover the whole Earth.
- Then we used topographic and urban land use data to identify each cell’s characteristics.
- Based on these characteristics, we broke down each cell into zones, and used them to calculate the number of stations required in each cell (aka “cell capacity”). Examples of such zones are green/urban zones or topographical zones depending on the orientation of a slope or the elevation of an area.
We are making public the paper that describes our research: Designing a Global Weather Station Network based on H3 grid, by Dr. Stavros Keppas, Dr. Haris Balis, Dr John Pagonis (short description, full documentation). This paper highlights the need for a total of 35,990,052 weather stations to address a wide range of scientific and commercial requirements.
We are also open sourcing the algorithm implementation. The WeatherXM/cell-capacity github repo includes all the code, detailed documentation on how to use it, and it’s licensed under the most permissive open source license, the MIT License.
One last thing. It took an Amazon EC6 m6g.2xlarge instance with 8 cores and 32GB RAM, nearly 72 hours to crunch the data. If you don’t want to do it yourself, we have uploaded the result set to IPFS, its a total of 44GBs organized per country.
https://bafybeidagjc2qkgcm7ves6pa3xdn7ol642wtqw5pt2qtj3rq4viyqbjd6q.ipfs.dweb.link
At WeatherXM, we believe that open data and open source software are public goods, important tools to make our world better. Today’s announcement is just first in a series of research and software that we will be giving to the public.
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How to Optimize Weather Station Deployments? Cell Capacity Model, In this video, Stavros Kepas, WeatherXM’s Head of Weather R&D highlights gaps in global weather station coverage. He shares strategies and examples for deploying stations in diverse microclimates, concluding with best practices for climate monitoring.
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Source of this article: weatherxm.com