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Extreme weather events have become a dominant feature of the narrative surrounding changes in global climate with large impacts on ecosystem stability, functioning and resilience; however, understanding of their risk of co‐occurrence at the regional scale is lacking. Based on the UK Met Office’s long‐term temperature and rainfall records, we present the first evidence demonstrating significant increases in the magnitude, direction of change and spatial co‐localisation of extreme weather events since 1961. Combining this new understanding with land‐use data sets allowed us to assess the likely consequences on future agricultural production and conservation priority areas. All land‐uses are impacted by the increasing risk of at least one extreme event and conservation areas were identified as the hotspots of risk for the co‐occurrence of multiple event types. Our findings provide a basis to regionally guide land‐use optimisation, land management practices and regulatory actions preserving ecosystem services against multiple climate threats.

The Research Software Engineer Knowledge IntegrationLandscape Review was written by the ExCALIBUR Programme Community. It documents the concept of the Research Software Engineer (RSE) and their role in many of todays computational science projects.The reviewprovides a comprehensive review of the skills required by Research Software Engineersin HPC and their future training needs

The last few decades have seen a range of advances in climate science and consequential policy initiatives at both national and international levels. These advances have been built on the back of progress in modelling and in part been enabled by the global data sharing initiative - the Earth System Grid Federation (ESGF) - which has underpinned recent phases of the World Climate Research Programme's Coupled Model Intercomparison Projects. The ESGF itself consists of data nodes deployed by individual modelling centres and a backbone of software development and services delivered by a few core institutions. Within Europe, along with some shared development of model components, these core ESGF software development and services are coordinated by the European Network on Earth System Modelling (ENES) and supported by the H2020 IS-ENES Phase 3 research infrastructure project. We provide an historical overview on advances in policy-relevant science, such as the Intergovernmental Panel for Climate Change (IPCC), that have been enabled by long-term underpinning development and funding of the ENES and ESGF infrastructure. We illustrate the recent shift of research funding from physical science objectives alone towards funding services to society (and the necessary underpinning research). We stress the potential dangers of underfunding research infrastructures that need to be simultaneously flexible and reliable enough to serve both ongoing basic research and the growing societal objectives, as emphasised by the development of climate services such as Copernicus Climate Change Service. We conclude by presenting some steps towards sustaining such research infrastructure in the context of the ENES and the possible futures of climate science.

A new coupled data assimilation (DA) system developed with the aim of improving the initialization of coupled forecasts for various time ranges from short range out to seasonal is introduced. The implementation here is based on a “weakly” coupled data assimilation approach whereby the coupled model is used to provide background information for separate ocean–sea ice and atmosphere–land analyses. The increments generated from these separate analyses are then added back into the coupled model. This is different from the existing Met Office system for initializing coupled forecasts, which uses ocean and atmosphere analyses that have been generated independently using the FOAM ocean data assimilation system and NWP atmosphere assimilation systems, respectively. A set of trials has been run to investigate the impact of the weakly coupled data assimilation on the analysis, and on the coupled forecast skill out to 5–10 days. The analyses and forecasts have been assessed by comparing them to observations and by examining differences in the model fields. Encouragingly for this new system, both ocean and atmospheric assessments show the analyses and coupled forecasts produced using coupled DA to be very similar to those produced using separate ocean–atmosphere data assimilation. This work has the benefit of highlighting some aspects on which to focus to improve the coupled DA results. In particular, improving the modeling and data assimilation of the diurnal SST variation and the river runoff should be examined.

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. Fil: Lewis, Huw W.. Exeter Met Office; Reino Unido Fil: Manuel Castillo Sanchez, Juan. Exeter Met Office; Reino Unido Fil: Graham, Jennifer. Exeter Met Office; Reino Unido Fil: Saulter, Andrew. Exeter Met Office; Reino Unido Fil: Bornemann, Jorge. Exeter Met Office; Reino Unido Fil: Arnold, Alex. Exeter Met Office; Reino Unido Fil: Fallmann, Joachim. Exeter Met Office; Reino Unido Fil: Harris, Chris. Exeter Met Office; Reino Unido Fil: Pearson, David. Exeter Met Office; Reino Unido Fil: Ramsdale, Steven. Exeter Met Office; Reino Unido Fil: Martínez De La Torre, Alberto. Centre For Ecology & Hydrology; Reino Unido Fil: Bricheno, Lucy. National Oceanography Centre; Reino Unido Fil: Blyth, Eleanor. Centre For Ecology & Hydrology; Reino Unido Fil: Bell, Victoria A.. Centre For Ecology & Hydrology; Reino Unido Fil: Davies, Helen. Centre For Ecology & Hydrology; Reino Unido Fil: Marthews, Toby R.. Centre For Ecology & Hydrology; Reino Unido Fil: O'Neill, Clare. Exeter Met Office; Reino Unido Fil: Rumbold, Heather. Exeter Met Office; Reino Unido Fil: O'Dea, Enda. Exeter Met Office; Reino Unido Fil: Brereton, Ashley. National Oceanography Centre; Reino Unido Fil: Guihou, Karen. National Oceanography Centre; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Hines, Adrian. Exeter Met Office; Reino Unido Fil: Butenschon, Momme. Plymouth Marine Laboratory; Reino Unido Fil: Dadson, Simon J.. University of Oxford; Reino Unido Fil: Palmer, Tamzin. Exeter Met Office; Reino Unido Fil: Holt, Jason. National Oceanography Centre; Reino Unido Fil: Reynard, Nick. Centre For Ecology & Hydrology; Reino Unido Fil: Best, Martin. Exeter Met Office; Reino Unido Fil: Edwards, John. Exeter Met Office; Reino Unido Fil: Siddorn, John. Exeter Met Office; Reino Unido

In this study the assimilation of HF radar data into a high resolution, coastal Wavewatch III model is investigated. An optimal interpolation scheme is used to assimilate the data and the design of a background error covariance matrix which reflects the local conditions and difficulties associated with a coastal domain is discussed. Two assimilation schemes are trialled; a scheme which assimilates mean parameters from the HF radar data and a scheme which assimilates partitioned spectral HF radar data. This study demonstrates the feasibility of assimilating partitioned wave data into a coastal domain. The results show that the assimilation schemes provide satisfactory improvements to significant wave heights but more mixed results for mean periods. The best improvements are seen during a stormy period with turning winds. During this period the model is deficient at capturing the change in wave directions and the peak in the waveheights, while the high sea state ensures good quality HF radar data for assimilation. The study also suggests that there are both physical and practical advantages to assimilating partitioned wave data compared to assimilating mean parameters for the whole spectrum.

Hardman-Mountford, N. J., Moore, G., Bakker, D. C. E., Watson, A. J., Schuster, U., Barciela, R., Hines, A., Moncoiffé, G., Brown, J., Dye, S., Blackford, J., Somerfield, P. J., Holt, J., Hydes, D. J., and Aiken, J. 2008. An operational monitoring system to provide indicators of CO2-related variables in the ocean. – ICES Journal of Marine Science, 65: 1498–1503. Demand by governments and scientists is increasing for indicators of CO2-related variables for the ocean. We describe a recent project, CARBON-OPS, during which a “supply chain” was developed for automated measurement of pCO2 in the surface of the ocean, data processing, and its use in providing information for research and policy development. Data are gathered by new pCO2 measurement systems on five UK research ships in the Southern Ocean, Atlantic Ocean, and northwestern European shelf seas. These send data in near-real-time, via satellite communication systems, to the British Oceanographic Data Centre, where they are automatically processed, quality controlled, and archived. The data are then delivered to the UK Met Office and others for use in testing predictions from operational ocean models. These models will generate indicator products and assist government through the Marine Climate Change Impact Partnership, a partnership of scientists, government, its agencies, and NGOs, by providing information on ocean CO2 uptake, changes in ocean pH, and potential impacts on global climate and marine ecosystems.

The World Meteorological Organization (WMO) in conjunction with IMO and UNESCO have established a framework for a global Marine Pollution Emergency Response Support System (MPERSS). National Meteorological Services are traditionally called upon to provide a range of meteorological and oceanographic data and services to support operations in response to various marine pollution emergencies, normally working closely with national response agencies when incidents occur in territorial or international waters. To ensure that similar services are available in developing countries and international waters WMO in 1994 established MPERSS. This system has been designed to provide a coherent, internationally coordinated approach to the provision of meteorological and oceanographic services worldwide to marine pollution incidents no matter where and when they happen. Today, the quality and breadth of data products expected by marine industries has expanded considerably and the challenge is to ensure that they provide value to the present and future generation of maritime applications. Operational met-ocean services rely on complex and expensive data collection and real time synthesis systems that must interact in real time across international boundaries. The IOC/WMO Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) has been created to facilitate the development and application of globally distributed marine meteorological and oceanographic services and their supporting observational, data management and capacity building programmes. A close dialog between those people pioneering the development of the next generation of maritime service infrastructures and those using their output in maritime applications is essential to ensure value for money and maximum impact across all maritime operational services.

A detailed description of the data assimilation scheme used in the Forecasting Ocean Assimilation Model (FOAM) operational ocean forecasting system is presented. The theoretical basis for the scheme is an improved version of the analysis correction scheme, which includes information from previously assimilated data. The scheme requires the a priori specification of error covariance information for the background model field and the observations. The way in which these error covariances have been estimated is described and some examples are given. The FOAM system assimilates sea surface temperature, sea-level anomaly, temperature profile, salinity profile and sea-ice concentration data. Aspects of the scheme that are specific to each of these observation types are described. Two sets of experiments demonstrating the impact of the data assimilation are presented. The first set are in an idealized identical-twin setting, using the ° -resolution North Atlantic FOAM configuration in which the state of the true ocean is assumed to be known. These experiments show that the analyses and forecasts are improved by assimilating the altimeter sea-level-anomaly data. The second set of experiments comprise data impact studies in a realistic hindcast setting. These experiments show a positive impact on the analyses from the Argo temperature- and salinity-profile data. Copyright © 2007 Royal Meteorological Society

Attempts to estimate the state of the ocean usually involve one of two approaches: either an assimilation of data (typically altimetric surface height) is performed or an inversion is carried out according to some minimization scheme. The former case normally retains some version of the time-dependent equations of motion; the latter is usually steady. Data sources are frequently not ideal for either approach, usually being spatially and temporally confined (e.g., from an oceanographic cruise). This raises particular difficulties for inversions, whose physics seldom includes much beyond the geostrophic balance. In this paper the authors examine an approach midway between the two, examining several questions. (i) What is the impact of data assimilated continuously to a steady state on regions outside the data sources? (ii) Can remote data improve the long-term mean of a model whose natural response is not close to climatology? (iii) Can an eddy-free model assimilate data containing eddies? The auth...

In this paper, new steady‐state solutions of the linearized thermocline equations satisfying prescribed fluxes of heat and salt at the base of the surface Ekman layer, are presented for a semi‐infinite ocean of constant depth. A decomposition into vertical modes is used to solve the problem. The solution is first determined in terms of a derivative of the unknown density at the surface and this derivative is then determined from an integral equation arising from applying the surface thermohaline boundary conditions. Solutions forced by wind stress alone, and by wind stress and thermohaline forcing are considered. The wind‐driven solution exhibits a temperature field with many realistic features, such as largest meridional gradients in the sub‐polar gyre, and the latitudinal spreading of isotherms towards the eastern boundary. The wind‐driven salinity field increases towards the poles, contrary to the observed annual mean salinity field. The stability of the sub‐tropical gyre is enhanced, whilst t...

An operational system to forecast the state of the global ocean a few days ahead has been implemented at the UK Met. Office (UKMO). The system, known as the Forecasting Ocean Assimilation Model (FOAM), consists of a 1°×1° resolution numerical ocean model driven by surface fluxes from the UKMO numerical weather prediction (NWP) suite and a modified successive correction data assimilation scheme for thermal observations. The assimilation scheme is assessed here in a series of 1-year integrations by comparison with ‘independent’ thermal profile observations and climatology. Assimilating temperature observations significantly reduces model errors in the upper ocean and results in temperature analyses that on average are closer to independent observations than climatology. The specific results depend on location and depth. The extent to which the data assimilation scheme is able to compensate for uncertainties in the surface forcing fluxes is also assessed by comparing integrations forced with climatological and NWP fluxes. Assimilating data is able to compensate for uncertainties in the surface heat forcing fluxes and significantly reduces the impact from uncertainties in the surface wind stress.

Analytical and numerical models are presented for linear quasigeostrophic buoyancy-driven flow forced bya time periodic pulsating point mass source in a continuously stratified, incompressible β-plane ocean withconstant Brunt–Vaisala frequency. The source represents the seasonal introduction of dense water into the abyssalocean and is located on a linear sloping bottom of arbitrary orientation. The ocean domain is horizontallyunbounded and of infinite depth. Rayleigh friction is incorporated into the horizontal momentum equations andappears at order Rossby number in the quasigeostrophic expansions. In the density equation the influence ofRayleigh friction and Laplacian friction are each considered in turn. Analytical solutions are obtained in the case of 1) a midlatitude β plane with no bottom slope and 2) an fplane with a bottom slope. In both of these problems the fluid is initially at rest and the mass source is switchedon and maintained. A three-dimensional radiating field of baroclinic Rossb...

The turbulent mixing in thin ocean surface boundary layers (OSBL), which occupy the upper 100 m or so of the ocean, control the exchange of heat and trace gases between the atmosphere and ocean. Here we show that current parameterizations of this turbulent mixing lead to systematic and substantial errors in the depth of the OSBL in global climate models, which then leads to biases in sea surface temperature. One reason, we argue, is that current parameterizations are missing key surface-wave processes that force Langmuir turbulence that deepens the OSBL more rapidly than steady wind forcing. Scaling arguments are presented to identify two dimensionless parameters that measure the importance of wave forcing against wind forcing, and against buoyancy forcing. A global perspective on the occurrence of wave-forced turbulence is developed using re-analysis data to compute these parameters globally. The diagnostic study developed here suggests that turbulent energy available for mixing the OSBL is under-estimated without forcing by surface waves. Wave-forcing and hence Langmuir turbulence could be important over wide areas of the ocean and in all seasons in the Southern Ocean. We conclude that surface-wave-forced Langmuir turbulence is an important process in the OSBL that requires parameterization. Citation: Belcher, S. E., et al. (2012), A global perspective on Langmuir turbulence in the ocean surface boundary layer, Geophys. Res. Lett., 39, L18605, doi: 10.1029/2012GL052932.

[1] A sea ice concentration and motion assimilation scheme has been developed using the Met Office Forecasting Ocean Assimilation Model (FOAM). FOAM has been upgraded to include a more realistic sea ice rheology and a sea ice thickness distribution. The sea ice data assimilation scheme uses Special Sensor Microwave Imager (SSMI) and QuikSCAT satellite observations to provide ice concentration and motion. A number of 1-year test integrations have been undertaken, and the resulting sea ice analysis has been examined in detail. The assimilation is able to significantly reduce the model sea ice concentration error and is able to address the model biases. Owing to the faster response times of the elastic-viscous-plastic (EVP) sea ice rheology in the model compared to the viscous-plastic used in previous studies, a novel approach to sea ice motion assimilation using increments to the ice stress has been developed. The sea ice motion assimilation scheme is able to reduce the model sea ice velocity errors by approximately 50% when compared to independent data. Ice velocity assimilation was found to have little impact on the ice concentration, and ice concentration assimilation is found to have little impact on ice velocities. This implies that ice concentrations are primarily thermodynamically controlled and ice velocities are primarily dynamically driven. During the summer, model biases and poor-quality observations impair the performance of the assimilation.

We present a detailed technical description of the present FOAM system and discuss some representative examples of the scientific investigations we undertake to track-down problems within the system and to understand the importance (“impact”) of the various inputs to it. We also provide an historical perspective on the development of the system and the changing demands for it, and describe the way in which we are adapting to meet these demands.