Simulation of snow accumulation and melting in the Kama river basin using data from global prognostic models

• Published in: Ice and Snow
• Main Authors: S. Pyankov V., A. Shikhov N., P. Mikhaylyukova G., С. Пьянков В., А. Шихов Н., П. Михайлюков Г.
• Other Authors: The study was funded by RFBR grant № 17-05-01001-a. The authors are grateful to the team of the Center for collective usage of highperformance computing resources of the Perm State University for assistance in obtaining and processing atmospheric models data, and also thank the team of the Laboratory of advanced numerical methods in atmospheric models of the Hydro-meteorological Center of Russia and M.A. Tolstykh personally for the providing of the PL-AV atmospheric model data., Исследование выполнено при поддержке РФФИ, проект № 17-05-01001-а. Авторы выражают благодарность сотрудникам Центра коллективного пользования высокопроизводительными вычислительными ресурсами (ЦКП ВВР) Пермского государственного национального исследовательского университета за помощь в получении и обработке данных моделей прогноза погоды, а также сотрудникам лаборатории перспективных численных методов в моделях атмосферы Гидрометцентра России и лично М.А. Толстых за предоставленные данные модели ПЛ-АВ.
• Format: Article in Journal/Newspaper
• Language: Russian
• Published: IGRAS 2019
• Subjects: GIS-technologies; global atmospheric models; Kama river basin; snow accumulation; snow water equivalent; sublimation and melting; бассейн р. Кама; ГИС-технологии; глобальные модели прогноза погоды; запас воды в снежном покрове; испарение и таяние снега; снегонакопление; Canada; Kama; The Cryosphere
• Online Access: https://ice-snow.igras.ru/jour/article/view/647; https://doi.org/10.15356/2076-6734-2019-4-423

Currently, the improvement of numerical models of weather forecasting allows using them for hydrological problems, including calculations of snow water equivalent (SWE) or snow storage. In this paper, we discuss the applicability of daily precipitation forecasts for three global atmospheric models: GFS (USA), GEM (Canada) and PL-AV (Russia) for calculating snow storage (SWE) in the Kama river basin for the cold season of 2017–2018. As the main components of the balance of snow storages the following parameters were taken into account: precipitation (with regard for the phase); snow melting during thaws; evaporation from the surface of the snow cover; interception of solid precipitation by forest vegetation. The calculation of snow accumulation and melting was based on empirical methods and performed with the GIS technologies. The degree-day factor was used to calculate snowmelt intensity, and snow sublimation was estimated by P.P. Kuz’min formula. The accuracy of numerical precipitation forecasts was estimated by comparing the results with the data of 101 weather stations. Materials of 40 field and 27 forest snow-measuring routes were taken into account to assess the reliability of the calculation of snow storages (SWE). During the snowmelt period, the part of the snow-covered area of the basin was also calculated using satellite images of Terra/Aqua MODIS on the basis of the NDFSI index. The most important result is that under conditions of 2017/18 the mean square error of calculating the maximum snow storage by the GFS, GEM and PL-AB models was less than 25% of its measured values. It is difficult to determine which model provides the maximum accuracy of the snow storage calculation since each one has individual limitations. According to the PL-AV model, the mean square error of snow storage calculation was minimal, but there was a significant underestimation of snow accumulation in the mountainous part of the basin. According to the GEM model, snow storages were overestimated by 10–25%. When calculating with ...