Research priorities in support of ocean monitoring and forecasting at the Met Office

Siddorn, John; Good, Simon; Harris, Christopher M.; Lewis, Huw; Maksymczuk, Jan; Martin, Matthew J.; Saulter, Andrew

doi:10.5194/os-12-217-2016

Cited by 14 publications

(13 citation statements)

References 73 publications

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“…5, boundary data are provided from the archived 12 km resolution NATL12 operational ocean model configuration (e.g. Siddorn et al, 2016), and the initial conditions are taken from a 1-year run of the UKO2 configuration initialized from the 2014 AMM15 hindcast on 1 January 2015. For initial development, climatological river discharge data are applied as freshwater forcing (Graham et al, 2017).…”

Section: Uko2 Initialization and Forcingmentioning

confidence: 99%

The UKC2 regional coupled environmental prediction system

et al. 2018

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Abstract. It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere-land-ocean-wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed.

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Section: Uko2 Initialization and Forcingmentioning

confidence: 99%

The UKC2 regional coupled environmental prediction system

et al. 2018

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“…The advances in coastal ocean forecasting were recently reviewed by Kourafalou et al (2015b). A review of ocean monitoring and forecasting activities in both the open and coastal oceans was presented by Siddorn et al (2016). The new challenges and trends in this field were recently reviewed by She et al (2016).…”

Section: Introductionmentioning

confidence: 99%

Ocean forecasting for the German Bight: from regional to coastal scales

Stanev¹,

Schulz‐Stellenfleth²,

Staneva³

et al. 2016

Ocean Sci.

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Abstract. This paper describes recent developments based on advances in coastal ocean forecasting in the fields of numerical modeling, data assimilation, and observational array design, exemplified by the Coastal Observing System for the North and Arctic Seas (COSYNA). The region of interest is the North and Baltic seas, and most of the coastal examples are for the German Bight. Several pre-operational applications are presented to demonstrate the outcome of using the best available science in coastal ocean predictions. The applications address the nonlinear behavior of the coastal ocean, which for the studied region is manifested by the tidal distortion and generation of shallow-water tides. Led by the motivation to maximize the benefits of the observations, this study focuses on the integration of observations and modeling using advanced statistical methods. Coastal and regional ocean forecasting systems do not operate in isolation but are linked, either weakly by using forcing data or interactively using two-way nesting or unstructured-grid models. Therefore, the problems of downscaling and upscaling are addressed, along with a discussion of the potential influence of the information from coastal observatories or coastal forecasting systems on the regional models. One example of coupling coarse-resolution regional models with a fineresolution model interface in the area of straits connecting the North and Baltic seas using a two-way nesting method is presented. Illustrations from the assimilation of remote sensing, in situ and high-frequency (HF) radar data, the prediction of wind waves and storm surges, and possible applications to search and rescue operations are also presented. Concepts for seamless approaches to link coastal and regional forecasting systems are exemplified by the application of an unstructured-grid model for the Ems Estuary.

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“…For WAVE standalone simulations, a constant WL was applied at the open sea boundary, at the level of HWL during the selected event, to eliminate the effect of tidal currents on H s and variability in WL. Time‐ and space‐varying wave conditions (H s , wave direction, mean period, and directional spread) from the Met Office WAVEWATCH III hindcast (Saulter et al, ; Siddorn et al, ; Met Office, ) were used at five equidistant points along the open sea boundary (see Figure a) and were linearly interpolated along the boundary to force the model at 15‐min intervals. A time‐ and space‐varying wind and atmospheric pressure field forced the model domain at hourly intervals, using data originating from the Met Office global unified model (Walters et al, ) and extracted from the Extended Area Continental Shelf Model CS3X (Williams & Horsburgh, ; NOCL, ).…”

Section: Methodsmentioning

confidence: 99%

“…The open sea boundary to the west was forced with a time varying, spatially uniform water level at a 15-min interval using observation data from Ilfracombe tide gauge (NTSLF, 2018 Siddorn et al, 2016;Met Office, 2019) were used at five equidistant points along the open sea boundary (see Figure 1a) and were linearly interpolated along the boundary to force the model at 15-min intervals. A time-and space-varying wind and atmospheric pressure field forced the model domain at hourly intervals, using data originating from the Met Office global unified model (Walters et al, 2014) and extracted from the Extended Area Continental Shelf Model CS3X (Williams & Horsburgh, 2013;NOCL, 2019).…”

Section: Delft3d Hindcast Of Select Historic Eventsmentioning

confidence: 99%

Quantification of the Uncertainty in Coastal Storm Hazard Predictions Due to Wave‐Current Interaction and Wind Forcing

Lyddon

Brown

Leonardi

et al. 2019

Geophysical Research Letters

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Coastal flood warning and design of coastal protection schemes rely on accurate estimations of water level and waves during hurricanes and violent storms. These estimations frequently use numerical models, which, for computational reasons, neglect the interaction between the hydrodynamic and wave fields. Here, we show that neglecting such interactions, or local effects of atmospheric forcing, causes large uncertainties, which could have financial and operational consequences because flood warnings are potentially missed or protection schemes underdesigned. Using the Severn Estuary, SW England, we show that exclusion of locally generated winds underestimates high water significant wave height by up to 90.1%, high water level by 1.5%, and hazard proxy (water level + 1/2 significant wave height) by 9.1%. The uncertainty in water level and waves is quantified using a system to model tide-surge-wave conditions, Delft3D-FLOW-WAVE in a series of eight model simulations for four historic storm events.Plain Language Summary Coastal zones worldwide are subject to combined effects of astronomical tides, meteorological storms surges, waves, and wind during storms and hurricanes, which can lead to flooding, property damage, and casualties. Coastal communities and critical infrastructure rely on accurate water level and wave forecasts to mitigate these combined hazards. Forecasts utilize hydrodynamic numerical models, which need to accurately represent these hazards and how they interact with, and feedback to, each other. This study uses a model, Delft3D-FLOW-WAVE, to calculate how tides and waves from four historic storm events combine to contribute to water level, wave height, and hazard proxy (water level + 1/2 wave height) in the Severn Estuary, southwest England. Additional simulations are run to show how local winds can further contribute to the hazard. Results show that including locally generating winds in simulations of water level, wave height, and hazard proxy is most important for accurate representation of physical processes that contribute to coastal hazards. Excluding locally generated winds from numerical model predictions could mean that flood alerts, warnings, and evacuation orders are missed, or coastal protection schemes are underdesigned, potentially leading to more flooding.

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Research priorities in support of ocean monitoring and forecasting at the Met Office

Cited by 14 publications

References 73 publications

The UKC2 regional coupled environmental prediction system

The UKC2 regional coupled environmental prediction system

Ocean forecasting for the German Bight: from regional to coastal scales

Quantification of the Uncertainty in Coastal Storm Hazard Predictions Due to Wave‐Current Interaction and Wind Forcing

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