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.

Abstract. This paper describes an updated configuration of the regional coupled research system, termed UKC3, developed and evaluated under the UK Environmental Prediction collaboration. This represents a further step towards a vision of simulating the numerous interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land using more integrated regional coupled prediction systems at kilometre-scale resolution. The UKC3 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean surface waves (WAVEWATCH III®), coupled together using OASIS3-MCT libraries. The major update introduced since the UKC2 configuration is an explicit representation of wave–ocean feedbacks through introduction of wave-to-ocean coupling. Ocean model results demonstrate that wave coupling, in particular representing the wave-modified surface drag, has a small but positive improvement on the agreement between simulated sea surface temperatures and in situ observations, relative to simulations without wave feedbacks. Other incremental developments to the coupled modelling capability introduced since the UKC2 configuration are also detailed. Coupled regional prediction systems are of interest for applications across a range of timescales, from hours to decades ahead. The first results from four simulation experiments, each of the order of 1 month in duration, are analysed and discussed in the context of characterizing the potential benefits of coupled prediction on forecast skill. Results across atmosphere, ocean and wave components are shown to be stable over time periods of weeks. The coupled approach shows notable improvements in surface temperature, wave state (in near-coastal regions) and wind speed over the sea, whereas the prediction quality of other quantities shows no significant improvement or degradation relative to the equivalent uncoupled control simulations.

Abstract. This paper describes an updated configuration of the regional coupled research system, termed UKC3, developed and evaluated under the UK Environmental Prediction collaboration. This represents a further step towards a vision of simulating the numerous interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land using more integrated regional coupled prediction systems at km-scale resolution. The UKC3 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean surface waves (WAVEWATCH III), coupled together using OASIS3-MCT libraries. The major update introduced since the UKC2 configuration is an explicit representation of wave processes in the ocean and their feedbacks through wave-to-ocean coupling. Ocean model results demonstrate that wave coupling, in particular representing the wave modified surface drag, has a small but positive improvement on the agreement between simulated sea surface temperatures and in situ observations, relative to simulations without wave feedbacks. Other incremental developments to the coupled modelling capability introduced since the UKC2 configuration are also detailed. Coupled regional prediction systems are of interest for applications across a range of timescales, from hours to decades ahead. The first results of simulations run over extended periods, covering four experiments each of order one month in duration are therefore analysed and discussed in the context of further characterising the potential benefits of coupled prediction on forecast skill, and on the stability of such systems over longer time periods. Results across atmosphere, ocean and wave components are shown to be of at least comparable skill to the equivalent uncoupled control simulations, with notable improvements demonstrated in surface temperature and wave state predictions in some near-coastal regions, and in wind speeds over the sea.

Hydrology is still, and for good reasons, an inexact science (for a recent discussion, see Beven, 2019a), even if evolving hydrological understanding has provided a basis for improved water management for at least the last three millennia. The limitations of that understanding have, however, become much more apparent and important in the last century as the pressures of increasing populations, and the anthropogenic impacts on catchment forcing and responses, have intensified (see Abbott et al., 2019; Montanari et al., 2013; Sivapalan, Savenije, & Blöschl, 2012; Srinivasan et al., 2017; Wagener et al., 2010; Wilby, 2019). At the same time, the sophistication of hydrological analyses and models has been developing rapidly, often driven more by the availability of computational power and geographical data sets than any real increases in understanding of hydrologicalprocesses. This sophistication has created an illusion of real progress, but a case can be made that we are still rather muddling along, limited by the significant uncertainties in hydrological observations, knowledge of catchment characteristics, and related gaps in conceptual understanding, particularly of the subsurface. These knowledge gaps are illustrated by the fact that for many catchments, we cannot close the water balance without significant uncertainty (e.g.,

Operational ocean forecasts are typically produced by modelling systems run using a forced mode approach. The evolution of the ocean state is not directly influenced by surface waves, and the ocean dynamics are driven by an external source of meteorological data which are independent of the ocean state. Model coupling provides one approach to increase the extent to which ocean forecast systems can represent the interactions and feedbacks between ocean, waves, and the atmosphere seen in nature. This paper demonstrates the impact of improving how the effect of waves on the momentum exchange across the ocean-atmosphere interface is represented through ocean-wave coupling on the performance of an operational regional ocean prediction system. This study focuses on the eddy-resolving (1.5 km resolution) Atlantic Margin Model (AMM15) ocean model configuration for the north-west European Shelf (NWS) region.A series of 2-year duration forecast trials of the Copernicus Marine Environment Monitoring Service (CMEMS) north-west European Shelf regional ocean prediction system are analysed. The impact of including ocean-wave feedbacks via dynamic coupling on the simulated ocean is discussed. The main interactions included are the modification of surface stress by wave growth and dissipation, Stokes-Coriolis forcing, and wave-height-dependent ocean surface roughness. Given the relevance to operational forecasting, trials with and without ocean data assimilation are considered.Summary forecast metrics demonstrate that the oceanwave coupled system is a viable evolution for future oper-ational implementation. When results are considered in more depth, wave coupling was found to result in an annual cycle of relatively warmer winter and cooler summer sea surface temperatures for seasonally stratified regions of the NWS. This is driven by enhanced mixing due to waves, and a deepening of the ocean mixed layer during summer. The impact of wave coupling is shown to be reduced within the mixed layer with assimilation of ocean observations. Evaluation of salinity and ocean currents against profile measurements in the German Bight demonstrates improved simulation with wave coupling relative to control simulations. Further, evidence is provided of improvement to simulation of extremes of sea surface height anomalies relative to coastal tide gauges.

Abstract. It is hypothesised that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, requires 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-west 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 6 contrasting case studies of 5-day duration is presented. Results demonstrate that at least comparable performance can be achieved with the UKC2 system to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and peak 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.

ABSTRACT:As the societal impacts of hazardous weather and other environmental pressures grow, the need for integrated predictions that can represent the numerous feedbacks and linkages between sub-systems is greater than ever. This was well illustrated during winter 2013/2014 when a prolonged series of deep Atlantic depressions over a 3 month period resulted in damaging wind storms and exceptional rainfall accumulations. The impact on livelihoods and property from the resulting coastal surge and river and surface flooding was substantial. This study reviews the observational and modelling toolkit available to operational meteorologists during this period, which focusses on precipitation forecasting months, weeks, days and hours ahead of time. The routine availability of high-resolution (km scale) deterministic and ensemble rainfall predictions for short-range weather forecasting as well as weather-resolving seasonal prediction capability represent notable landmarks that have resulted from significant progress in research and development over the past decade. Latest results demonstrated that the suite of global and high-resolution UK numerical weather prediction models provided excellent guidance during this period, supported by high-resolution observations networks, such as weather radar, which proved resilient in difficult conditions. The specific challenges for demonstrating this performance for high-resolution precipitation forecasts are discussed. Despite their good operational performance, there remains a need to further develop the capability and skill of these tools to fully meet user needs and to increase the value that they deliver. These challenges are discussed, notably to accelerate the progress towards understanding the value that might be delivered through more integrated environmental prediction.

The combined hazard of large waves occurring at an extreme high water could increase the risk of coastal flooding. Wave-tide interaction processes are known to modulate the wave climate in regions of strong tidal dynamics, yet this process is typically omitted in flood risk assessments. Here, we investigate the role of tidal dynamics in the nearshore wave climate (i.e. water depths > 10 m), with the hypothesis that larger waves occur during high water, when the risk of flooding is greater, because tidal dynamics alter the wave climate propagating into the coast. A dynamically coupled wave-tide model BCOAWST^was applied to the Irish Sea for a 2-month period (January-February 2014). High water wave heights were simulated to be 20% larger in some regions, compared with an uncoupled approach, with clear implications for coastal hazards. Three model spatial resolutions were applied (1/60°, 1/120°, 1/240°), and, although all models displayed similar validation statistics, differences in the simulated tidal modulation of wave height were found (up to a 10% difference in high water wave height); therefore, sub-kilometre-scale model resolution is necessary to capture tidal flow variability and wave-tide interactions around the coast. Additionally, the effects of predicted mean sea-level rise were investigated (0.44-2.00 m to reflect likely and extreme sea-level rise by the end of the twentyfirst century), showing a 5% increase in high water wave height in some areas. Therefore, some regions may experience a future increase in the combined hazard of large waves occurring at an extreme high water.