An EnKF-based scheme for snow multivariable data assimilation at an Alpine site

Title:

An EnKF-based scheme for snow multivariable data assimilation at an Alpine site

Creator:

Piazzi, Gaia, Campo, Lorenzo, Gabellani, Simone, Castelli, Fabio, Cremonese, Edoardo, di Cella, Umberto Morra, Stevenin, Hervé, and Ratto, Sara Maria

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:73eaf22d-fe94-489f-a3db-88e186321747
uuid:73eaf22d-fe94-489f-a3db-88e186321747
doi:10.2478/johh-2018-0013

Subject:

snow modeling, energy-balance model, data assimilation, and Ensemble Kalman Filter

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The knowledge of snowpack dynamics is of critical importance to several real-time applications especially in mountain basins, such as agricultural production, water resource management, flood prevention, hydropower generation. Since simulations are affected by model biases and forcing data uncertainty, an increasing interest focuses on the assimilation of snow-related observations with the purpose of enhancing predictions on snowpack state. The study aims at investigating the effectiveness of snow multivariable data assimilation (DA) at an Alpine site. The system consists of a snow energy-balance model strengthened by a multivariable DA system. An Ensemble Kalman Filter (EnKF) scheme allows assimilating ground-based and remotely sensed snow observations in order to improve the model simulations. This research aims to investigate and discuss: (1) the limitations and constraints in implementing a multivariate EnKF scheme in the framework of snow modelling, and (2) its performance in consistently updating the snowpack state. The performance of the multivariable DA is shown for the study case of Torgnon station (Aosta Valley, Italy) in the period June 2012 – December 2013. The results of several experiments are discussed with the aim of analyzing system sensitivity to the DA frequency, the ensemble size, and the impact of assimilating different observations.

Language:

Slovak

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Journal of hydrology and hydromechanics | 2019 Volume:67 | Number:1

Harvested from:

CDK

Metadata only:

false