How to reduce sampling errors in spaceborne cloud radar-based snowfall estimates

Scarsi, Filippo Emilio; Battaglia, Alessandro; Maahn, Maximilian; Lhermitte, Stef

doi:https://doi.org/10.5194/tc-19-4875-2025

Articles | Volume 19, issue 10

https://doi.org/10.5194/tc-19-4875-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-19-4875-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 10

Research article

|

22 Oct 2025

Research article |

| 22 Oct 2025

How to reduce sampling errors in spaceborne cloud radar-based snowfall estimates

Filippo Emilio Scarsi, Alessandro Battaglia, Maximilian Maahn, and Stef Lhermitte

Data sets

ERA5 hourly data on single levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.adbb2d47

ERA5 hourly data on pressure levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.bd0915c6

Short summary

Snowfall measurements at high latitudes are crucial for estimating ice sheet mass balance. Spaceborne radar and radiometer missions help estimate snowfall but face uncertainties. This work evaluates uncertainties in snowfall estimates from a fixed near-nadir radar (CloudSat-like) and a conically scanning radar (WIVERN-like), showing that a WIVERN-like radar will provide better estimates than a CloudSat-like radar at smaller spatial and temporal scales.