Articles | Volume 20
https://doi.org/10.5194/asr-20-49-2023
https://doi.org/10.5194/asr-20-49-2023
06 Jun 2023
 | 06 Jun 2023

Spatial regression of multi-fidelity meteorological observations using a proxy-based measurement error model

Jouke H. S. de Baar, Irene Garcia-Marti, and Gerard van der Schrier

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Latest update: 22 Nov 2024
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Short summary
Combining high-fidelity official meteorological observations with low-fidelity crowd-sourced data in a single climate or weather map is challenging because of the significant bias and noise in the low-fidelity data. In this work, we present a method to treat this bias and noise in a statistical framework. In addition, we show that we can make an additional improvement in the quality of the map when we add high-resolution land use information.