The UKC2 regional coupled environmental prediction system

Lewis, Huw; Sanchez, Juan Manuel Castillo; Graham, Jennifer; Saulter, Andrew; Bornemann, Jorge; Fallmann, Joachim; Harris, C.J.; Pearson, D. Graham; Ramsdale, Steven; Torre, Alberto Martínez-de la; Bricheno, Lucy; Blyth, Eleanor; Bell, V. A.; Davies, Helen; Marthews, Toby R.; O’Neill, Clare; Rumbold, Heather; O’Dea, Enda; Brereton, Ashley; Guihou, Karen; Hines, A.; Butenschön, Momme; Dadson, Simon; Palmer, Tamzin; Holt, J. D.; Reynard, Nick; Best, Martin; Edwards, John M.; Siddorn, John

doi:10.5194/gmd-2017-110

Cited by 8 publications

(36 citation statements)

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“…A detailed description of the model hydrological methods is given in Best et al (2011), and a thorough description of the hydrological processes in JULES from the water reaching the land 5 surface as precipitation is given in Blyth et al (2017). Here, we focus on the runoff production process and its parameter variability.…”

Section: The Jules Lsmmentioning

confidence: 99%

“…Schellekens et al, 2017;Blyth et al, 2017) and study land-atmosphere interactions and impacts (Betts, 2007;Harrison et al, 2008 al., 2013). JULES is described by Best et al, (2011; energy and water fluxes) and Clark et al, (2011;carbon fluxes and vegetation dynamics).…”

Section: The Jules Lsmmentioning

confidence: 99%

“…From the precipitated water that arrives at the surface after vegetation interception at each model time step, JULES first determines the infiltration excess component of surface runoff from the soil hydraulic characteristics (Best et al, 2011;Blyth et al, 2017).…”

Section: Runoff Generation and River Routing Schemes In Julesmentioning

confidence: 99%

“…RFM is a kinematic wave equation scheme that incorporates scale dependent parameters and has been recently introduced into JULES (Lewis et al, 2017).…”

Section: Runoff Generation and River Routing Schemes In Julesmentioning

confidence: 99%

“…Improving the representation of runoff 20 generation in models of the land surface which are coupled to the atmosphere, can improve meteorological forecasts as well as hydrological predictions. For the UK, a fully coupled (land, atmosphere, ocean) environmental prediction system is being built (Lewis et al, 2017). The land surface component of this coupled system is the Joint UK Land Environment Simulator (JULES) model.…”

Section: Introductionmentioning

confidence: 99%

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Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

Torre

Blyth

Weedon

2018

Preprint

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Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. Using river flow observations from gauge stations, we study the capability of the Joint UK Land Environment Simulator (JULES) LSM to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at the 1 km 2 spatial resolution. A series of tests, carried out to identify where the model results are 10 sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface 15 runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.

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Section: The Jules Lsmmentioning

confidence: 99%

Section: The Jules Lsmmentioning

confidence: 99%

Section: Runoff Generation and River Routing Schemes In Julesmentioning

confidence: 99%

“…RFM is a kinematic wave equation scheme that incorporates scale dependent parameters and has been recently introduced into JULES (Lewis et al, 2017).…”

Section: Runoff Generation and River Routing Schemes In Julesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

Torre

Blyth

Weedon

2018

Preprint

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The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling

Gentile

Gray

Lewis

2021

Quart J Royal Meteoro Soc

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The benefits of dynamical atmosphere-ocean-wave coupling in probabilistic weather forecasts generated using convective-scale ensemble prediction systems are to date unknown. We investigate the respective impacts of atmosphere-ocean-wave coupling, and initial condition (IC), lateral boundary condition (LBC), and stochastic physics perturbations within a convective-scale ensemble coupled system for an extratropical cyclone case study. Towards this aim, we developed the first 18-member, 2.2 km grid spacing ensemble regional coupled system (Ensemble-RCS) with domain covering the British Isles and surrounding seas. Ensemble-RCS coupled and uncoupled simulations of cyclone Ciara (February 2020) were performed. Adding stochastic perturbations to the model physics parametrizations enhances the ensemble spread of the uncoupled atmosphere-only ensemble driven by IC and LBC perturbations, while slightly reducing (by up to 0.5 m⋅s −1 ) the median of the ensemble 95th percentile 10-m wind speeds from its value of about 24 m⋅s −1 at peak time. A substantial proportion of this impact is attributable to Charnock parameter perturbations alone. By coupling the atmosphere-only ensemble, with stochastic physics, to the ocean, the ensemble median and spread is mainly unaffected. However, additional coupling to waves reduces the median wind speed by 1 m⋅s −1 , which leads to reductions of up to 70% in strong wind strike probability, and halving of the spatial coverage of high values (>50%) of this probability. Finally, we demonstrate the usefulness of two metrics originally developed for precipitation verification -the neighbourhood-based Fraction Skill Score (FSS) and the object-based Structure, Amplitude, Location (SAL) -for examining the spread in convective-scale ensemble forecasts. It is concluded that coupling has a consistent impact across the ensemble members. Remarkably, the impact of coupling to waves is found to be comparable in size to that of adding IC, LBC andThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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The Impact of Atmosphere–Ocean–Wave Coupling on the Near-Surface Wind Speed in Forecasts of Extratropical Cyclones

Gentile

Gray

Barlow

et al. 2021

Boundary-Layer Meteorol

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Accurate modelling of air–sea surface exchanges is crucial for reliable extreme surface wind-speed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 m s$$^{-1}$$ - 1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 m s$$^{-1}$$ - 1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 m s$$^{-1}$$ - 1 , due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 m s$$^{-1}$$ - 1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

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The UKC2 regional coupled environmental prediction system

Cited by 8 publications

References 0 publications

Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

The sensitivity of probabilistic convective‐scale forecasts of an extratropical cyclone to atmosphere–ocean–wave coupling

The Impact of Atmosphere–Ocean–Wave Coupling on the Near-Surface Wind Speed in Forecasts of Extratropical Cyclones

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