Preprints
https://doi.org/10.5194/egusphere-2026-2456
https://doi.org/10.5194/egusphere-2026-2456
11 Jun 2026
 | 11 Jun 2026
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

The Arctic Weather Satellite, introducing a new wavelength range for ice hydrometeor retrievals

Peter McEvoy, Eleanor May, and Patrick Eriksson

Abstract. The first cloud property retrievals based on operational sub-millimetre measurements are presented, making use of the channels between 89 and 325 GHz of the Arctic Weather Satellite (AWS). The main quantities of the dataset are frozen water path (FWP) and the associated mass-weighted mean altitudes and particle sizes. In this first version, results are restricted to latitudes between 60° S and 60° N. The retrievals are based on detailed simulations of instrument observations. The actual inversion is made by a quantile regression neural network, and case-specific uncertainty estimates are provided.

Retrievals performed on simulations suggest that retrieved FWP values are essentially unbiased across a wide dynamic range, from 10 kg m-2 down to 40 g m-2. The associated mass-weighted mean altitude is also essentially unbiased for the entire relevant range of 2 km to 12 km. The particle size estimates, however, show a slight bias for sizes other than 400 μm. Comparisons with other datasets provide strong indications that these results also extend to retrievals from real observations; for example, local and zonal means match those of existing radar/lidar-based retrieval products.

The accuracy in FWP should be unprecedented among estimates based on passive satellite data, thanks to the new sensitivity afforded by sub-millimetre channels. The dataset complements cloud radar observations by providing a significantly broader spatial coverage. There is also potential to create a climate-relevant dataset, as the retrievals are directly applicable to the EPS-Sterna constellation, continuing the AWS observations up to 2045.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Peter McEvoy, Eleanor May, and Patrick Eriksson

Status: open (until 17 Jul 2026)

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Peter McEvoy, Eleanor May, and Patrick Eriksson

Data sets

CHIP-AWS v1.0.0 2025 archive: Atmospheric ice mass properties Peter McEvoy, Eleanor May, and Patrick Eriksson https://researchdata.se/en/catalogue/dataset/2026-135/1?previewToken=859edaac-fe43-4f42-b1ad-f86a0d4dc4a2

Peter McEvoy, Eleanor May, and Patrick Eriksson
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Latest update: 11 Jun 2026
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Short summary
Clouds containing ice play an important role in Earth's climate, yet measuring them from space remains challenging. Using a new weather satellite, we developed a method to measure the amount of atmospheric ice across the globe. Computer simulations are used to train a neural network, making all assumptions explicit. It matches the accuracy of specialised radar instruments, but covers a much larger area. With upcoming satellites, observations can continue until 2045, for long-term monitoring.
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