Preprints
https://doi.org/10.5194/gmd-2021-92
https://doi.org/10.5194/gmd-2021-92

Submitted as: model description paper 08 Apr 2021

Submitted as: model description paper | 08 Apr 2021

Review status: this preprint is currently under review for the journal GMD.

S3M 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt

Francesco Avanzi1, Simone Gabellani1, Fabio Delogu1, Francesco Silvestro1, Edoardo Cremonese2, Umberto Morra di Cella2,1, Sara Ratto3, and Hervé Stevenin3 Francesco Avanzi et al.
  • 1CIMA Research Foundation, Via Armando Magliotto 2, 17100 Savona, Italy
  • 2Climate Change Unit, Environmental Protection Agency of Aosta Valley, Loc. La Maladière, 48-11020 Saint-Christophe, Italy
  • 3Regione Autonoma Valle d’Aosta, Centro funzionale regionale, Via Promis 2/a, 11100 Aosta, Italy

Abstract. By shifting winter precipitation into summer freshet, the cryosphere supports life across the world. The sensitivity of this shifting mechanism to climate, as well as the role played by the cryosphere in the Earth energy budget, has motivated the development of a broad spectrum of predictive models. Such models rarely combine a high degree of physical realism in both the seasonal snow and glaciers, and generally are not integrated with hydrologic models describing the fate of meltwater through the hydrologic budget. We present S3M v5.1, a spatially explicit and hydrology-oriented cryospheric model that successfully reconstructs seasonal snow and glacier evolution through time and that can be natively coupled with distributed hydrologic models. Model physics include precipitation-phase partitioning, snow and glacier energy and mass balances, snow rheology and hydraulics, and a data-assimilation protocol. Comparatively novel aspects of S3M with respect to the existing literature are an explicit representation of the spatial patterns of snow liquid-water content, an hybrid approach to snowmelt that decouples the radiation- and temperature-driven contributions, the implementation of the ∆h parametrization for distributed ice-thickness change, and the inclusion of a distributed debris-driven melt factor. Focusing on its operational implementation in the Italian north-western Alps, we show that S3M provides robust predictions of the snow and glacier mass balances at multiple scales, thus delivering the necessary information to support real-world hydrologic operations. S3M is well suited for both operational flood forecasting and basic research, including future scenarios of the fate of the cryosphere and water supply in a warming climate. The model is open source, and the paper comprises an user manual as well as resources to prepare input data and set up computational environments and libraries.

Francesco Avanzi et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-92', Anonymous Referee #1, 10 May 2021
    • AC1: 'Reply on RC1', Francesco Avanzi, 15 May 2021
  • RC2: 'Comment on gmd-2021-92', Anonymous Referee #2, 25 Oct 2021

Francesco Avanzi et al.

Model code and software

S3M-model source code Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro https://doi.org/10.5281/zenodo.4663899

Francesco Avanzi et al.

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Short summary
Knowing in real time how much snow and glacier ice is accumulated across the landscape has significant implications for water-resources management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s, but is here being made open source for the first time.