The deep-sea environment into which oil company operations are gradually extending is generally poorly understood with surveys regularly discovering new habitats and communities of animals previously unknown to science. By establishing long term monitoring of the deep sea physical environment and biological activity in that environment it should be possible to compensate to a large degree for previous lack of knowledge. The DELOS system comprises two environmental monitoring platforms situated in the Atlantic Ocean at 1400m depth in block 18 off Angola: - one in the far field (16km form sea floor infrastructure); and one in the near field (within 50metres of a sea floor well). Each platform comprises two parts: - the sea floor docking station that is deployed on the sea floor at the start of the monitoring program and remains for the 25 year project duration; and a number of observatory modules that are designed to perform specific environmental monitoring functions. One of each observatory module will be available to each platform. Once deployed each observatory module will have enough battery and storage capacity for autonomous operation for at least 6 months. Towards the end of the 6 month deployment period each platform will require ROV intervention to recover observatory modules to the surface for service, calibration and data offload. During this service period no monitoring will be possible at the sea floor however, long periods of monitoring will be possible (months), interrupted by short service periods (days). The DELOS represents a stepping stone towards a long term cabled observatory. Returning instrumentation to the surface each 6 months overcomes the problems of instrument calibration, bio fouling, and failure. The DELOS was installed off west Africa in January 2009.

The South African Environmental Observation Network (SAEON) aims to provide a comprehensive, sustained, co-ordinated and responsive South African Earth observation network that delivers long-term reliable data for scientific research and informs decision making for a knowledge society and improved quality of life. SAEON addresses the environmental observation and information needs of future generations, reaching far and wide, nationally, regionally and globally, and its success as a platform for environmental observations depends on delivery of reliable environmental data and products for science, policy and management. Education-Outreach, based on environmental sciences, has a specific focus on science educators, learners and research students. The marine offshore node of SAEON aims to fill the gaps in long-term ocean monitoring, helping to understand the impact of climate change on oceans and their resources surrounding South Africa, as well as improving our knowledge of the oceans’ influence on climate change. It is vital that we better understand these oceans as they have been shown to play a major role in the weather and climate patterns over southern Africa. Thus the impact of climate change through factors such as increases in temperature and sea level rise, which are already evident, are likely to have devastating effects on the lives of millions of impoverished people.

As the impacts of global change become manifest in every component of the Earth System, the need for producing personalized, pre-emptive, and predictive environmental information for Joe, the plumber, is upon us. A regional Earth System model is the only realistic way to combine climate predictions and climate change projections to generate end-to-end Earth System predictions for water, energy, food, human health, transportation, and so on including decision support tools and policy inputs. Such a regoinal Earth System model has been developed as a prototype for the Chesapeake Bay by downscaling seasonal to interannual predictions and IPCC projections to generate routine forecasts of temperature, winds, pollutants, pathogens, currents, watershed, fisheries, harmful algal blooms, including the impact of land use change scenarios on the health of the Bay for an integrated assessment. A decision support tool allows the users to change crop types, smart growth options, urban development, etc. to assess the consequences in terms of nutrient and sediment loadings, streamflow changes, deadzones, fisheries, HABs, waterquality, etc. The challenge is to validate, provide uncertainties, optimize model parameters, and compute skills of these forecasts and this can only be accomplished by a continuous feedback to observational networks via coupled and interdisciplinary observational system simulation experiments. SOme preliminary experiments with a localized ensemble transform Kalman filter are discussed in the context of physical-biogeochemical data assimilation for the Bay. The importance of designing and optimizing observational networks for Earth System prediction can not be overstated.

The United States Integrated Ocean Observing System (US IOOS) is designed to fill global, national, and regional scale needs for ocean data to serve societal benefit in seven areas: public health risk, living marine resources, ecosystem health, coastal hazards, climate change, maritime operations, and national security. Notably, most of these issues vary geographically on a regional basis, in terms of issues and risks as well as in forcing functions. As part of the coastal effort, IOOS has adopted the use of Regional Associations, based on large geographic units. The US is divided into 11 Regional Associations (RAs). Each RA is responsible for connecting with regional stakeholder groups, designing a process to assess user needs, and then crafting a Regional Coastal Ocean Observing System (RCOOS) that is responsive to those needs. A strong component of the RCOOS is the integration of observing assets, data management and communication, modeling and products, and education/outreach. The Northwest Association of Networked Ocean Observing Systems (NANOOS) is the US IOOS RA for the states of Washington, Oregon, and N. California. Established since 2003, this RA has developed a governance system, an assessment of regional needs, and a coalition to build the RCOOS and deliver its products. Focusing on fisheries, maritime operations, coastal hazards, and ecosystem impacts including hypoxia and HABs, NANOOS has developed ocean data products to inform specific user groups, as diverse as tuna fisherman, recreational boaters, state resource managers, and public health officials. An important part in the process is communication and focus on high quality data and science in order to deliver accurate products of use. I will present some case examples and factors for success.

The maritime zone is a highly dynamic region where hydrodynamic and morphodynamic processes may change on a wide range of spatial and temporal scales. Information regarding the variations of the littoral environment is critical for a large range of military and civilian missions. Standard in situ surveying can provide this information but are typically very challenging because they require people and extended periods of time. Moreover, they may not be possible in denied areas. For these reasons, remote sensing of the shore is highly desirable. Satellites are an attractive solution but, for the nearshore-zone they typically have problems related to limited resolution, a complete lack of temporal sampling on dynamical time scales and access limitations. Motivated by this fact, our idea consists in the utilization of alternative platforms (aircraft). The data presented here have been acquired during a cruise conducted by NURC and collaborating institutions. This experiment (BP09 – Battlespace Preparation 2009) address specific problems associated with remote sensing (RS) of denied areas, specifically to improve the quality of the optical properties derived from RS in marine coastal environments. The main objective is to assist in the calibration and validation of large-scale ocean color sensors (MODIS, 1 km), medium scale sensors (MERIS, 300m), and small scale sensors (GeoEye and hyperspectral aircraft over-flights, 1-2 m). During this trial aerial and in situ sensors were used and integrated to provide combined measurements allowing the characterization of the nearshore both in spatial and spectral dimensions (see the attached fig with the aircraft, satellite and in situ stations). In particular, we present a feasibility study which examined the application of a distributed sensor system package to perform ocean observations for maritime missions. The system incorporates several platforms: aerial vehicle, satellites as well as in situ sensors. To analyze the platform integration and their data reliability for oceanographic purposes, a field exercise were performed to build sensor integration, performance evaluation and process refinement. Once these technical aspects were assessed and errors minimized, image geo-rectification and processing were performed. To integrate the satellite measurements, the aircraft images were rectified and geo-referenced to within 1-2 m accuracy generating images that surpass spatial and spectral resolution available from the satellites. To prove the system utilization for oceanographic scope the available optical in situ measurements were integrated with the remote sensing images. The main goal of the project was the development of a novel technique for creating high spatial/spectral resolution surf zone imagery from the available data (satellite, airplane and in situ). In particular, the project objectives were: _to test the logistics and operational use of the OGS aircraft and hyperspectral sensor (Imaging Spectrometer -Aisa EAGLE); _to review the aircraft geolocation capabilities based on internal metadata and to refine the metadata using an high-spatial resolution RS (GeoEye satellite, 0.55 m in the panchromatic channel); _to provide methodologies to perform the atmospheric corrections and provide performance evaluation matrices using the available coincident in situ optical measurements. _to compare variability between instrument calibrations and measurement protocols to compute uncertainties in retrieving in situ radiometric values and how these uncertainties are propagated in RS imagery, thus affecting geophysical parameter derived products. _to determine the intra/inter-pixel variability in optical and physical properties and how this affects the merging of low/medium/high spatial and spectral resolution of RS data for improving spectral and spatial resolution. During our project several methodologies and algorithms have been developed and implemented. In these pages we would like to emphasis the aircraft data that provided an innovation contribution to the development of optical information and assessments as well as coastal forecasting. Aircraft data were radiometrically and georectified using an inertial navigation system mounted onboard the aircraft, final aircraft to satellite (GeoEye) image co-registration has been also applied. After georectification, the atmospheric correction was performed using standard methodologies also with the help of the high-resolution satellite acquisition and the in situ available coincident data. In particular the Research System Incorporated (RSI) ENVI software package was used to perform dark subtraction, thermal infrared correction and to integrate the aerosol characterization information available from the in situ sensors (using FLAASH). Once the path atmosphere and noise were removed, the resultant imagery was converted from radiance values to reflectance and was compared with the in situ coincident available measurements.

Marine ecosystem interactions are critical to climatic variability (both in terms of their climatic driving functions, as well as their being impacted by variability in climate). Yet research is lacking in many areas linking marine ecosystems and climate change. Monitoring is fragmented and unsustainable thereby preventing scientists and policy-makers from making informed decisions on ecosystem-based management and on adaptive reaction to climate change. Various discussion documents related to the IPPC reports focus heavily on the need for adaptation to climate change, on developing a framework for action, particularly at the national level, and on matching financial and technical support (primarily focusing on technologies for adaptation). Little attention, however, has been given to the need for monitoring and measurement mechanisms at the regional and local level that can A. provide accurate indications of specific changes related to climate change at the ecosystem level whilst B. identifying the scale and distribution of expected impacts, and C. translating these into reliable predictions and policy guidelines which countries can act upon so as to adapt and mitigate/avert the negative impacts. There is a strong general agreement on the necessity for assistance to be targeted at the more vulnerable countries to take appropriate adaptation measures, but there is a missing link in terms of how to identify, at the regional and national level, what such measures would need to address and at what scale, in relation to the predicted and actual measurable inputs. Yet this must have inevitable and significant implications in terms of prioritisation of actions and targeting of available funding. Although there is much discussion about mitigation and adaptation, there has been little focus on continuous and sustainable monitoring of changes in many of the world’s more vulnerable areas, the data and information from which are essential in justifying management and governance actions, and to provide credibility for policy decisions. The conclusion of this scenario is an urgent need to develop focused early warning and continuous long-term monitoring networks, particularly in relation to critically vulnerable ecosystems and communities. These need to be sustainable and sufficiently credible in their data and information outputs to be able to drive reliable predictive mechanisms for adaptive management and governance. The Large Marine Ecosystems of the world are seen to be directly related to major global physical phenomena with a particularly close linkage to climate in terms of ocean-atmosphere interactions Specific indicators need to be selected that will act as early warnings of ecosystem variability and climate change at a global, regional and local level.