Abstract 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.
Abstract The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends “ urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities .” Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.
Abstract 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 useful to partition ocean wave spectra for the classification of wind sea and swell and for detecting
weaknesses in models or measuring systems. In this study various partitioning scheme have been investigated and their effectiveness, robustness and feasibility for use in automated systems taken into consideration. The partitioning scheme used by Hasselmann et al. (1996) appears to be the most useful for fully automated
processes and therefore the performance of the partitioning method has been analyzed by comparisons of
spectra from the Wavewatch III model, the Swan model and from HF radar. This comparison suggests that specific processes are needed to manage the effect of noise and sensitivity on the partitioning method when looking at the different spectra. The research has focused on the Celtic sea region for the 2003 to 2005 period when the Pisces radar system was operational. In addition a Directional Waverider buoy was deployed in the area and the buoy’s reconstructed spectra have also been considered.
In sub-Saharan Africa, storm surge zones are concentrated in four nations including Nigeria where half of the region's surge zones resulting from sea level rise and violent storms originate. This comes in an era in which Africa's coastline population will be at risk from sea level rise and coastal flooding over the coming decades. With much of Nigeria's urban population and economic activity located along the low-lying coastline, including the Niger Delta and portions of Lagos in the South west. Risk exposures will increase with population growth in these areas. Considering that significant levels of the country's CO2 and CH4 (carbon dioxide and methane) emissions come from the Southern region, the projected impacts of rising sea levels from warming temperature threatens several Southern states such as Lagos and others. Given the economic potentials of the coast, highlighting extreme climate patterns in the zone spatially, offers ideal opportunity for mitigation. While very little has been done to capture these concerns, the dangers from sea level rise, flood hazards and coastal erosion in the region has been exacerbated by different elements like human activities, greenhouse gas emissions and natural forces. Seeing the connections between sea level rise threats and many factors, there is a need for a mix scale model using GIS (Geographic Information Systems) and descriptive statistics in order to enhance coastal environmental management strategies. Accordingly, this project focuses on a regional assessment of climate change hazards in Southern Nigeria with emphasis on the issues, trends, factors, impacts and efforts. In applying the mix scale tools, results show that the region is facing challenges with changes in climate parameters (land use, (GHG) Green House Gas emissions, precipitation patterns, sea level rise, flooding and rising temperature) due to pressures from socio-economic and physical factors. GIS mapping of the trends also pinpointed the exposures in the major ecozones, vulnerability of surging population centers, the risks to oil and gas infrastructure in low lying areas and the intensity of rainfall and flood hazards. To remedy the situation, the study proffered suggestions ranging from the need for effective policy, growth management measures, installation of early warning systems to more use of GIS and the design of a regional climate information system to protect the study area.
Abstract 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 the sub‐polar gyre is de‐stabilized. With the addition of the thermohaline forcing the deficiencies of the salinity field associated with the wind‐driven solution are largely corrected, whilst the solution retains a reasonable representation of the climatological temperature field. Temperature and salinity anomaly fields relative to the Levitus climatology, calculated from the Met. Office Forecasting Ocean Assimilation Model, are shown to be qualitatively similar to the anomaly fields derviedfrom the model discussed in this paper. This result serves to underline the message that the combination of wind and surface buoyancy forcing are essential when modelling the large‐scale temperature and salinity fields using the thermocline equations. Résumé [Traduit par la rédaction] Les auteurs proposent de nouvelles solutions aux équations linérarisées de la thermocline en régime stable pour un océan semi‐infini à profondeur constante. Ces solutions satisfont aux flux thermique ethalin établis à la base de la couche d'Ekman, à la surface de l'océan. Pour le résoudre, les auteurs décomposent le problème en modes verticaux. Ils expriment d'abord la solution en termes de la dérivée de la densité inconnue à la surface et déterminent ensuite cette dérivée au moyen de l'intégrale résultant de l'application de conditions limites thermohalines à la surface. Les auteurs examinent ainsi les solutions dans lesquelles n ‘interviennent que la tension du vent ou la tension du vent et le forçage thermohalin. Dans les solutions où intervient le vent, on remarque un champ de température présentant bon nombre de conditions réalistes comme la présence des plus grands gradients méridionaux dans le tourbillon sub‐polaire et l'étalement latitudinal des isothermes vers la limite est. Le champ de salinité créé par le vent augmente quand on approche des pôles, contrairement à ce qu ‘on observe avec le champ de salinité annuel moyen. Le tourbillon subtropical est plus stable tandis qu ‘il y a déstabilisation du tourbillon sub‐polaire. Les lacunes du champ de salinité associées à la solution ne tenant compte que de la tension du vent sont largement comblées dès qu'on tient compte du forçage thermohalin, et la nouvelle solution aboutit constamment à une représentation raisonnable du champ de température climatologique. Les champs d'anomalies de salinité et de température par rapport à la climatologie Levitus obtenus au moyen du modèle de prévision des conditions océaniques du Met. Office sont qualitativement similaires aux champs d'anomalies dérivés du modèle que décrivent les auteurs. On en conclut qu ‘il faut absolument tenir compte de la tension du vent et de la poussée hydrostatique à la surface quand on modélise des champs de température et de salinité à grande échelle avec les équations de la thermocline. Notes Corresponding author's e‐mail: ahines@meto.gov.uk
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