Adjoint free four-dimensional variational data assimilation for a storm surge model of the German North Sea

Zheng, Xiaolong; Mayerle, Roberto; Xing, Qianguo; Jaramillo, José Manuel Fernández

doi:10.1007/s10236-016-0962-y

Cited by 6 publications

(6 citation statements)

References 39 publications

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“…Moreover, there are many locations subject to severe storm surges and/or seiche oscillations, where the forecast suffers from errors in surface and lateral boundary conditions and from errors in initial state. Even considering places without seiches, the impact of data assimilation in storm surge forecasting can still be positive although shorter lasting, as in the North Sea (Verlaan et al ; Zijl et al ; Zheng et al ) or on the US East Coast (Peng and Xie, ).…”

Section: Discussionmentioning

confidence: 99%

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Bajo

Međugorac

Umgiesser

et al. 2019

Quart J Royal Meteoro Soc

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In this research we present a modelling study of storm surges influenced by pre‐existing seiches in the Adriatic Sea. The natural oscillation modes – seiches – of the Adriatic Sea can be easily excited by wind, due to the particular marine bathymetry and coastal orography. Moreover, such oscillations can interact with newer wind‐induced storm surges or with other sea‐level components. This paper first considers modelling issues in the seiche reproduction, using a simplified approach, and then analyses the reproduction with the model of two extreme storm surge events, influenced by pre‐existing seiches. In order to investigate the impact of assimilating sea level data, these events are simulated without and with a data assimilation system, based on an Ensemble Kalman Filter. Results show that, while the formulation of the bottom shear stress does not influence the seiche period, the seiche decay time is correctly estimated with a hybrid linear‐quadratic formulation. We found also that non‐linear interactions of bottom currents, caused by different sea level components, can modify the decay time. However, the two events are poorly reproduced by the model, even with a correct modelling set‐up, because of wind deficiencies. Therefore we considered the issue and found that the assimilation of tide‐gauge residual sea level has a strong positive impact, lasting several days, despite the errors in the atmospheric forcing. This is mainly due to the persistence of the seiche oscillations in the Adriatic Sea.

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Section: Discussionmentioning

confidence: 99%

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Bajo

Međugorac

Umgiesser

et al. 2019

Quart J Royal Meteoro Soc

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“…But the development and maintenance of adjoint equations is very tough, making the implementation of 4Dvar difficult. Zheng et al (2016) proposed an adjoint-free 4Dvar. Twin experiments shows that this method improves model parameters effectively.…”

Section: Adjoint-free 4dvarmentioning

confidence: 99%

“…The key step of the adjoint-free 4Dvar is running a model ensemble, and then the tangent linear equations of the primitive model can be obtained explicitly instead of its numerical form. For detailed derivation and validation of the method, readers are referred to Zheng et al (2016).…”

Section: Adjoint-free 4dvarmentioning

confidence: 99%

Study of the wind drag coefficient during the storm Xaver in the German Bight using data assimilation

Zheng

Mayerle²,

Wang

et al. 2018

Dynamics of Atmospheres and Oceans

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Wind stress is the most important driving force for storm surge in coastal waters. Currently, the parameterization of wind stress is still not well developed and is the most uncertain parameters for storm surge models. In this paper, a storm surge model for the German Bight is developed using the model Delft3D. The data assimilation method, adjoint-free 4Dvar, which is relatively easier to be implemented than the adjoint method, is used to assimilate measured water level data into Delft3D. The storm surge prediction is more accurate when we adjusted the drag coefficient using the adjoint free data assimilation method, than in a companion forward model. The drag coefficient is consistent with results from previous studies. The wind drag coefficient is also calculated using results of a wave model. It has been found that the relation between the drag coefficient and wind speed is approximately linear in the deep water. But in the shallow water, wind drag coefficient shows larger variability due to the wave shoaling effect. The linear relation adjusted by data assimilation agrees well with that derived from a wave-related formula. It is also found that wave-related parameterization scheme is necessary for shallow waters.

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“…Combining surface observations with vertical profile data of temperature and salinity can lead to improved representation of mesoscale eddies in the region. Zheng et al (2016) presented an interesting modification of the 4DVAR data assimilation scheme in which the linear tangent equation is approximated by introducing perturbations to the parameters to be estimated and then running the ensemble models as in the ensemble Kalman filter method (Evensen 1994;Xu et al 2013;Xu and Oey 2014). In this way the adjoint equation is not required.…”

mentioning

confidence: 99%

“…The subjects of papers in this Topical Collection include one on process study of the gravity current (Berntsen et al 2016), three on data assimilations (Margvelashvili et al 2016;Peng et al 2016;Zheng et al 2016), two on basin-scale modeling and observational data analyses (Ezer 2016;Quan et al 2016), two on coastal processes (Liu and Chua 2016;Zhu et al 2016), and two on sediment resuspension and tranport (Qiao et al 2016;Yang et al 2016). Berntsen et al (2016) conducted a high-resolution model experiment using a non-hydrostatic model to simulate plume down a canyon under rotation.…”

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confidence: 99%

Editorial—the 7th International Workshop on Modeling the Ocean (IWMO 2015)

et al. 2017

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IWMO 2015 was held in the pristine campus of the Australian National University, Canberra, Australia, from June 1-5, 2015. Despite the negative Coriolis spin that many of us from the northern half of the globe experienced for the first time, we were positively impressed by the vastness and beauty of Australia and the kindness and friendliness of its people. Late fall in Canberra displayed spectacular starry nights and brisk sunny days. The workshop was attended by more than 80 participants from 16 countries around the globe. Seventy papers including both oral and posters were presented, covering a very broad range of topics on observations and models: climate variability, basin circulation and coastal oceanography, air-sea interaction, sea-ice dynamics, sediment transport, tropical cyclones, biogeochemical-physical coupling, boundary currents, sea level rise, extreme events, ocean prediction, and others. As in the past years, many of the participants were students and young scientists-all presented very high-quality research, and three were selected to receive the Outstanding Young Scientist Awards (OYSA). In order that some of us may have a chance to also receive some recognition for our hard work, new this year were three Best Presentation Prizes (BPP), given to any presenters deemed qualified by the audience to receive the honors. Also, new this year were special lunch-time sessions when young and more senior scientists exchanged ideas on a wide range topics.The 10 papers in this Topical Collection were selected from a total of 20 originally submitted papers after they underwent the usual process of reviews and revisions. There were at least 2 reviewers for each paper. The reviews were solicited from both the workshop attendees and the scientific community at large.

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Adjoint free four-dimensional variational data assimilation for a storm surge model of the German North Sea

Cited by 6 publications

References 39 publications

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Storm surge and seiche modelling in the Adriatic Sea and the impact of data assimilation

Study of the wind drag coefficient during the storm Xaver in the German Bight using data assimilation

Editorial—the 7th International Workshop on Modeling the Ocean (IWMO 2015)

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