Designing a Global Weather Station Network

Designing a weather station network is a demanding, multi-objective optimisation problem and usually constrained to local geographies. In this study, the authors deviate from typical approaches that focus the design of weather station networks on a small or country-wide area and present a method that is applicable on a global scale.

Prior art suggests that weather networks should exhibit high density, often at 1-3km or finer resolution, especially when deployed over complex topographies and urban landscapes. High station density is usually required to support research on urban micrometeorology, agricultural applications and to capture intricate meteorological mesoscale phenomena such as convective precipitation and sea breeze. High density is also required due to the persistence of temperature inversions at near-surface layers is significantly influenced by topography, leading to prolonged periods of temperature inversion.

In this novel approach, the authors suggest the design of a global weather network distributed over millions of hexagons covering the entire world. The number of weather stations per hexagon is determined by the topology (e.g. maximum elevation difference, aspects, water formations, etc.) and the land use (urban coverage, green areas, etc.) of the covered area.

The method is materialized via an open-source software tool (available on GitHub) which utilizes freely available elevation data (Copernicus DEM) and land use data (OpenStreetMap) and is capable of preparing the global weather station network in reasonable computation time (~24 hours on a 16-core CPU).

Finally, the authors present their findings, discuss the effect of various hexagon sizes and suggest that the design of a global weather station network is viable and computationally feasible.