Research of opportunities of combined use of the runoff formation ECOMAG model and mesoscale atmosphere circulation COSMO-Ru model (on the example of floods on the Sukhona River at the Velikiy Ustyug)

Churiulin, Evgenii; Krylenko, Inna; Frolova, Natalia

doi:10.1088/1755-1315/263/1/012057

Cited by 3 publications

(5 citation statements)

References 2 publications

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“…Especially important for the development of this method is the good correspondence of the hydrographs modeled according to the data from meteorological stations and the COSMO-Ru NWP system. The Nash Sutcliffe efficiency coefficient for streamflow -Ru data on snow accumulation period was absent) was 0.44 when calculated on the basis of the data from the COSMO-Ru NWP system, and 0.62 when calculated using the in-situ data from meteorological stations [4]. In this investigation, a series of experiments has been performed.…”

Section: Applying Nwp System Cosmo-ru and Snow Cover Model Snowe For mentioning

confidence: 95%

“…The Sukhona river joins the Yug river near the town of Veliky Ustyug, forming the Northern Dvina [1]. The results of calculating snow cover characteristics were obtained using the COSMO-Ru NWP system [2] and the snow cover model SnoWE [3,4]. In turn, hydrological modelling of spring floods was calculated using the runoff formation model ECOMAG [5,6].…”

Section: Applying Nwp System Cosmo-ru and Snow Cover Model Snowe For mentioning

confidence: 99%

“…They range from the models obtaining the initial meteorological data (global and mesoscale atmospheric circulation models) to the models of runoff formation which allow to calculate the water inflow into the river network and the flow conditions in specific sections of the river. The articles [4,7] contain more detailed information about: a) synthesizing method of hydrometeorological models; b) the COSMO-Ru NWP system, the SnoWE and the ECOMAG models; c) the information about verification and calibration of these models; d) the first results of modelling spring floods characteristics based on synthesizing method.…”

Section: Applying Nwp System Cosmo-ru and Snow Cover Model Snowe For mentioning

confidence: 99%

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Numerical experiments in calculating snow water equivalent and estimating their impact on the formation of spring floods

et al. 2020

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Seasonal snow cover has a significant impact on forming spring floods. Sparse snow course-measuring network does not meet the requirements of modern tasks related to the technologies of numerical weather prediction (NWP) systems and runoff formation models. Moreover, insufficient volume of hydrometeorological data creates a need to improve spring floods forecasting methods by means of available modern hydrometeorological information related to snow cover. To work out an efficient solution to the issue of initial snow data preparation we need a complex approach including the use of data from satellite, atmospheric models, physical-mathematical models of snow cover and insitu information. This approach will provide modern NWP and hydrological models with reliable initial data on snow cover (snow water equivalent – SWE, snow density – SD). The main purpose of our investigation is related to approbation of satellite data and development of snow cover calculation methods for NWP and hydrological models. Numerous SWE and SD experiments have been performed in order to achieve this aim. A regional snow data assimilation system for COSMORu was implemented during the research. Moreover, a new method of hydrological modelling of spring floods based on ECOMAG model with initial information from COSMO-Ru, SnoWE and in-situ data has been proposed and tested.

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Section: Applying Nwp System Cosmo-ru and Snow Cover Model Snowe For mentioning

confidence: 95%

Section: Applying Nwp System Cosmo-ru and Snow Cover Model Snowe For mentioning

confidence: 99%

Section: Applying Nwp System Cosmo-ru and Snow Cover Model Snowe For mentioning

confidence: 99%

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Numerical experiments in calculating snow water equivalent and estimating their impact on the formation of spring floods

et al. 2020

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“…In Russia, the Hydro-Meteorological Centre (HMC) jointly with the international consortium COSMO developed the technology called 'SnoWE' to simulate snow accumulation and melting over the entire territory of the country [1,[7][8]. In the SnoWE model is used a combination of short-term forecasts from the NWP model COSMO-Ru and in-situ observations on the weather stations.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, two independent numerical experiments on snow accumulation and snowmelt modelling were carried out in the Kama river basin for the cold season 2018/19. As a result, we obtained the outputs of the SnoWE snowpack model [1,8] and simulation based on the ICON model [12]. In this paper, we performed an inter comparison of such two datasets and estimated their accuracy based on field measurements data.…”

Section: Introductionmentioning

confidence: 99%

Comparison of snow water equivalent estimates calculated by SnoWE and ICON models on the example of the Kama river basin

Shikhov

Churiulin

2020

E3S Web Conf.

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More recently, snow accumulation and snowmelt models for their calculations are forced to apply data from numerical weather prediction (NWP) models. This approach allows improvement the accuracy of calculating snow water equivalent (SWE) values especially in remote and mountain regions. In this study, we compared the numerical results of SWE calculations performed by two independent models. The first one is the SnoWE model and the second one is the ICON NWP model. During the period from November 2018 to May 2019, the simulation results of SWE compared with in-situ data from 64 snow surveys, which are located in the Kama river basin. We found that both models (SnoWE and ICON) allow getting satisfactory estimates of the maximum values of SWE (the accuracy of data is sufficient for their practical using). The root mean square error was equal 14-18% from the average measured SWE. Moreover, we got reliable maximum values of SWE for forested areas. At the same time, both models underestimate SWE values during spring snowmelt season. Probably, this underestimation is due to the shortcomings of the models and a sparse snow course-measuring network.

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Modeling Ice-Jam Floods in the Frameworks of an Intelligent System for River Monitoring

et al. 2020

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Research of opportunities of combined use of the runoff formation ECOMAG model and mesoscale atmosphere circulation COSMO-Ru model (on the example of floods on the Sukhona River at the Velikiy Ustyug)

Cited by 3 publications

References 2 publications

Numerical experiments in calculating snow water equivalent and estimating their impact on the formation of spring floods

Numerical experiments in calculating snow water equivalent and estimating their impact on the formation of spring floods

Comparison of snow water equivalent estimates calculated by SnoWE and ICON models on the example of the Kama river basin

Modeling Ice-Jam Floods in the Frameworks of an Intelligent System for River Monitoring

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