Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

Advances in statistical methodologies for mid-long term simulation of oil spills in the sea

RESUMEN: Con esta tesis se pretenden aportar nuevas metodologías para mejorar las herramientas disponibles actualmente para la lucha contra la contaminación marina por derrames de hidrocarburos. Por un lado, se propone una metodología para predecir de forma probabilística derrames en el medio-largo plazo. La parte más innovadora de esta metodología consiste en la simulación estadística, mediante modelos de regresión logística, de aquellas variables ambientales que afectan la evolución de un derrame en el mar. El modelado basado en regresión logística es aplicado en el golfo de México y en el Golfo de Vizcaya. En este segundo caso, los patrones ambientales obtenidos son empleados, posteriormente, para la predicción en el medio-largo plazo de derrames. Los resultados obtenidos en cada caso, demuestran el potencial de las técnicas propuestas. Por otro lado, se propone otra metodología enfocada al análisis de peligrosidad asociada a derrames profundos, basada en la extracción de patrones ambientales espacio-temporales. Esta metodología ha sido aplicada en el Mar del Norte y los resultados obtenidos comparados con metodologías tradicionales de estudio de peligrosidad, evidenciando las capacidades de la metodología propuesta, habiendo reducido enormemente los costes computacionales respecto a las técnicas tradicionales. Se ha demostrado como las metodologías propuestas en esta tesis pueden mejorar y ampliar los beneficios de las herramientas existentes para la lucha contra la contaminación marina.ABSTRACT: The aim of this thesis is the improvement of existing tools for the fight against oil spill marine pollution. On the one side, we developed a methodology for the probabilistic forecast of oil spills at the mid-long term. The core of the methodology is the statistical simulation of oil spill met-ocean forcings, using a logistic regression model. Logistic regression modeling of met-ocean patterns is applied in the Gulf of Mexico and in the Bay of Biscay. In the second case, mid-long term prediction of oil spill is achieved considering the statistically simulated met-ocean conditions. On the other hand, we proposed a methodology for deep oil spill hazard assessment, based on the selection of spatio-temporal met-ocean patterns. This methodology was applied in the North Sea, and the obtained results were compared with the ones achieved with a traditional hazard estimation technique, highlighting the benefit of the proposed method. The methodologies presented in this thesis have shown their ability and the benefits they could bring to the tools for the fight against marine pollution

Development of a new urban climate model based on the model PALM – Project overview, planned work, and first achievements

In this article we outline the model development planned within the joint project Model-based city planning and application in climate change (MOSAIK). The MOSAIK project is funded by the German Federal Ministry of Education and Research (BMBF) within the framework Urban Climate Under Change ([UC]2) since 2016. The aim of MOSAIK is to develop a highly-efficient, modern, and high-resolution urban climate model that allows to be applied for building-resolving simulations of large cities such as Berlin (Germany). The new urban climate model will be based on the well-established large-eddy simulation code PALM, which already has numerous features related to this goal, such as an option for prescribing Cartesian obstacles. In this article we will outline those components that will be added or modified in the framework of MOSAIK. Moreover, we will discuss the everlasting issue of acquisition of suitable geographical information as input data and the underlying requirements from the model’s perspective

OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD

Maritime shipping and natural resource development in the Arctic are projected to increase as sea ice coverage decreases, resulting in a greater probability of more and larger oil spills. The increasing risk of Arctic spills emphasizes the need to identify the state-of-the-art oil trajectory and sea ice models and the potential for their integration. The Oil Spill Modeling for Improved Response to Arctic Maritime Spills: The Path Forward (AMSM) project, funded by the Arctic Domain Awareness Center (ADAC), provides a structured approach to gather expert advice to address U.S. Coast Guard (USCG) Federal On-Scene Coordinator (FOSC) core needs for decision-making. The National Oceanic & Atmospheric Administration (NOAA) Office of Response & Restoration (OR&R) provides scientific support to the USCG FOSC during oil spill response. As part of this scientific support, NOAA OR&R supplies decision support models that predict the fate (including chemical and physical weathering) and transport of spilled oil. Oil spill modeling in the Arctic faces many unique challenges including limited availability of environmental data (e.g., currents, wind, ice characteristics) at fine spatial and temporal resolution to feed models. Despite these challenges, OR&R’s modeling products must provide adequate spill trajectory predictions, so that response efforts minimize economic, cultural and environmental impacts, including those to species, habitats and food supplies. The AMSM project addressed the unique needs and challenges associated with Arctic spill response by: (1) identifying state-of-the-art oil spill and sea ice models, (2) recommending new components and algorithms for oil and ice interactions, (3) proposing methods for improving communication of model output uncertainty, and (4) developing methods for coordinating oil and ice modeling efforts

Progress in operational modeling in support of oil spill response

Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies