Data Assimilation

doi:10.1007/978-3-540-74703-1

Cited by 137 publications

(20 citation statements)

References 24 publications

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“…Model updating methods are used for integrating the real-time observations within mathematical models and thus to correct model input, states, parameters, or outputs to reduce model uncertainty (Lahoz et al, 2010;Liu et al, 2012;Refsgaard, 1997;WMO, 1992). In this study, states updating and output correction methods are used to improve flow estimation.…”

Section: Model Updatingmentioning

confidence: 99%

Integrating Qualitative Flow Observations in a Lumped Hydrologic Routing Model

Mazzoleni

Amaranto²,

Solomatine

2019

Water Resources Research

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This study aims at proposing novel approaches for integrating qualitative flow observations in a lumped hydrologic routing model and assessing their usefulness for improving flood estimation. Routing is based on a three‐parameter Muskingum model used to propagate streamflow in five different rivers in the United States. Qualitative flow observations, synthetically generated from observed flow, are converted into fuzzy observations using flow characteristic for defining fuzzy classes. A model states updating method and a model output correction technique are implemented. An innovative application of Interacting Multiple Models, which use was previously demonstrated on tracking in ballistic missile applications, is proposed as state updating method, together with the traditional Kalman filter. The output corrector approach is based on the fuzzy error corrector, which was previously used for robots navigation. This study demonstrates the usefulness of integrating qualitative flow observations for improving flood estimation. In particular, state updating methods outperform the output correction approach in terms of average improvement of model performances, while the latter is found to be less sensitive to biased observations and to the definition of fuzzy sets used to represent qualitative observations.

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Section: Model Updatingmentioning

confidence: 99%

Integrating Qualitative Flow Observations in a Lumped Hydrologic Routing Model

Mazzoleni

Amaranto²,

Solomatine

2019

Water Resources Research

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“…The calculated model data of meteorological characteristics are available for free on various portals. The largest of them are global data assimilation systems [3,4], such as the GDAS (Global Data Assimilation System [https://www.ncdc.noaa.gov]), LDAS (Land Data Assimilation System). There are the regional products.…”

Section: Introductionmentioning

confidence: 99%

Opportunities of short-term weather forecasts data in the environmental monitoring of the Kazakhstan

et al. 2020

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This paper considers the possibilities of assimilation of FEWS NET (Famine early Warning System Network) products in natural resource monitoring of the territory of Kazakhstan in the cold period. With an area of 2.7 million km2, Kazakhstan is located in the center of Eurasia in the arid zone, and snow is one of the most important water sources in the first half of the vegetation season. The products “Snow Depth”, “Temperature” and “Precipitation” developed for Central Asia are based on model meteorological data, including short-term weather forecasts. This information, presented in the form of regular matrices, has several advantages in efficiency and spatial detailing over direct ground (remote) measurements of meteorological parameters. The use of FEWS NET products for the environmental monitoring of the entire territory of Kazakhstan or its separate parts is of benefit for assessing the current situation on snow reserves, weather regimes and prospects for spring snowmelt.

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“…These are observations and models. Such methods were most widely used in meteorology and oceanography, where observations are assimilated into numerical models in order to obtain boundary or initial conditions (or other model parameters) for further modeling and forecast [1][2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Variational Data Assimilation in the Mathematical Model of the Black Sea Dynamics

Agoshkov¹,

Shutyaev²,

Parmuzin³

et al. 2019

PhO

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In order to simulate the sea hydrothermodynamics, the problem of variational assimilation of the sea surface temperature data is solved. The data assimilation permits to adjust the numerical model calculations to the measurement data obtained in the environment under study. Methods and Results. The mathematical model of hydrothermodynamics of the Black and Azov seas, developed at the Institute of Numerical Mathematics of RAS and written in the sigma coordinate system, is considered. The distinctive feature of the model consists in applying the splitting method to physical processes and spatial coordinates that can significantly simplify the variational data assimilation algorithm. The problem of variational assimilation of the sea surface temperature data is formulated. A cost functional has been introduced; it includes the control function-heat flux at the sea upper boundary and satellite observations of the sea surface temperature. The necessary condition for the functional minimum is reformulated through the optimality system including the direct and adjoint problems, and the control condition. Using the variational assimilation of the satellite-derived observations, the algorithm for solving the stated problem was developed. It takes into account the observational errors' covariance matrix calculated based on the statistical characteristics of the sea surface temperature observational data. The algorithm implies a sequential solution of the optimality system in the iterative process with the specially selected iterative parameter. The results of numerical solution of this problem are represented by the example of the Black and Azov seas. Conslusion. The results of numerical modeling with the observational data assimilation and without it are compared; efficiency of the observational data assimilation procedures is shown. Influence of the sea surface temperature assimilation upon the other system parameters is investigated. It is shown that when assimilating the sea surface temperature, only temperature in the upper layers is affected, whereas, provided that the depth is sufficient, the profile in the lower layers remains practically unchanged. The impact on the other system parameters is either minimal or not manifested at all.

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Data Assimilation

Abstract: Publication information

Cited by 137 publications

References 24 publications

Integrating Qualitative Flow Observations in a Lumped Hydrologic Routing Model

Integrating Qualitative Flow Observations in a Lumped Hydrologic Routing Model

Opportunities of short-term weather forecasts data in the environmental monitoring of the Kazakhstan

Variational Data Assimilation in the Mathematical Model of the Black Sea Dynamics

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