03 Nov 2021
03 Nov 2021
Status: this preprint is currently under review for the journal TC.

Snow cover prediction in the Italian Central Apennines using weather forecast and snowpack numerical models

Edoardo Raparelli1,2, Paolo Tuccella3,2, Valentina Colaiuda3,2, and Frank Silvio Marzano1,2 Edoardo Raparelli et al.
  • 1Dept. Information Engineering, Electronics and Telecommunications, Sapienza Università di Roma, Italy
  • 2Center of Excellence Telesensing of Environment and Model Prediction of Severe Events (CETEMPS), L’Aquila, Italy
  • 3Dept. Physical and Chemical Sciences, Università degli Studi dell’Aquila, Italy

Abstract. Italy is a territory characterized by complex topography with the Apennines mountain range crossing the entire peninsula with its highest peaks in central Italy. Using the latter as area of interest and the winter season during 2018–2019, the goal of this study is to investigate the ability of snow cover models to reproduce the observed snow height, using forecast weather data as meteorological forcing. We here consider two well-known ground surface and soil models: i) Noah LSM, a single-layer Eulerian model; ii) Alpine3D, a multi-layer Lagrangian model. We adopt the Weather Research and Forecasting (WRF) model to produce the meteorological data to drive both Noah LSM and Alpine3D at regional scale with a spatial resolution of 3 km. While Noah LSM is already online coupled with the WRF model, we develop here a dedicated offline coupling between WRF and Alpine3D LSM. We validate the WRF simulations of surface meteorological variables in central Italy using a dense network of automatic weather stations, obtaining correlation coefficients of 0.84, 0.58, 0.4, 0.77 and 0.66 for air temperature, relative humidity, wind speed, incoming shortwave radiation and daily precipitation, respectively. The performances of both WRF-Noah and WRF-Alpine3D, are evaluated by comparing simulated and measured snow heights, provided by a quality-controlled network of snow stations located in Central Apennines. We find that WRF-Noah and WRF-Alpine3D models present similar correlation coefficients equal to 0.77 and 0.71, respectively, but the WRF-Alpine3D model produces a lower bias (about 2.2 cm) compared to the WRF-Noah model (about −8.0 cm) in the snow height estimation. For the estimation of daily snow height variation WRF-Noah and WRF-Alpine3D present similar results with correlation coefficients of 0.72 and 0.71, respectively, but again WRF-Alpine3D showed a bias lower than WRF-Noah, about 0.09 cm and −0.22 cm respectively. The WRF-Noah model is slightly better than WRF-Alpine3D to reproduce the snow cover area observed with respect to the Moderate Resolution Imaging Spectroradiometer (MODIS) with the Jaccard spatial correlation index of 0.38 and 0.36 (optimal value equal 1), respectively, and Average Symmetric Surface Distance (ASSD) of 2.0 and 2.2 (optimal value equal 0), respectively, even though both models tend to overestimate it. We finally show that snow settlement rate in WRF-Alpine3D is mainly driven by densification, whereas in WRF-Noah there is also an important contribution of snow melting especially at high elevation. As a general conclusion, the snow cover extension and height in central Italy at moderate spatial resolution (3 km) are well reproduced by both WRF-Noah and WRF-Alpine3D, but with the latter exhibiting a lower bias likely due to its multi-layer more sophisticated numerical scheme.

Edoardo Raparelli 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 tc-2021-285', Anonymous Referee #1, 07 Feb 2022
    • AC1: 'Reply on RC1', Edoardo Raparelli, 20 Mar 2022
  • RC2: 'Comment on tc-2021-285', Anonymous Referee #2, 19 Feb 2022
    • AC2: 'Reply on RC2', Edoardo Raparelli, 20 Mar 2022

Edoardo Raparelli et al.

Edoardo Raparelli et al.


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Short summary
We evaluate the skills of a single-layer (Noah) and a multi-layer (Alpine3D) snow cover model, forced with a weather model (WRF), to reproduce snow height and extent over Italian Central Apennines. Noah shows a lower bias compared to Alpine3D in predicting snow height and snow height variation. Nevertheless, Noah shows slightly betters skills in the estimation of the snow cover extent. Furthermore we show that snow settlement is mainly driven by melting in Noah and by compaction in Alpine3D.