We form a new ‘blended’ data set of sea level anomaly (SLA) fields by combining gridded daily fields derived from altimeter data with coastal tide gauge data. Within approximately 55–70 km of the coast, the altimeter data are discarded and replaced by a linear interpolation between the tide gauge and remaining offshore altimeter data. To create a common reference height for altimeter and tide gauge data, a 20-year mean is subtracted from each time series (from each tide gauge and altimeter grid point) before combining the data sets to form a blended mean sea level anomaly (SLA) data set. Daily mean fields are produced for the 22-year period 1 January 1993–31 December 2014. The primary validation compares geostrophic velocities calculated from the height fields and velocities measured at four moorings covering the north-south range of the new data set. The blended data set improves the alongshore (meridional) component of the currents, indicating an improvement in the cross-shelf gradient of the mean SLA data set.

Global air-sea CO2 fluxes are commonly determined using the CO2 partial pressure difference between surface water and air (ΔpCO2), and wind speed. Numerical interpolation techniques and coarse grid spacing, typically of the order of 4°, used when estimating the global fluxes smooth out small-scale variability in wind and pCO2 fields. There is significant variability on smaller scales in these fields. In particular, wind speed is strongly affected by sea surface temperature (SST) on oceanic mesoscales. Here we provide an estimate of the impact of this small-scale variability on global CO2 fluxes utilizing a highresolution wind product, and estimates of surface water CO2 changes in response to small-scale changes in SST. The results show that, on a global scale, the annual air-sea CO2 fluxes for 1° smoothed fields is 2 to 4% greater than for 10° smoothed SST and winds fields. This suggests that, while the coarser resolution fields used in climatologies miss much of the small-to-regional scale variability in fluxes, they adequately present global and basin-scale flux estimates.

The mission of NANOOS is to coordinate and support the development, implementation, and operations of a regional coastal ocean observing system (RCOOS) for the Pacific Northwest region, as part of the U.S. IOOS. A key objective for NANOOS is to provide data and user-defined products to a diverse group of stakeholders in a timely fashion, and at spatial and temporal scales appropriate for their needs. To this end, NANOOS developed the NANOOS Visualization System (NVS), which aggregates, displays and serves meteorological and oceanographic data, derived from buoys, gliders, tide gauges, HF Radar, meteorological stations and satellites, as well as model forecast information in such a way that it presents end users with a rich, informative and user friendly experience. First released in November 2009, NVS has already undergone several significant updates. While its original focus and continued strength is on near-real-time (NRT) observations from stationary platforms (buoys, coastal stations, etc.), it has evolved to include other types of observations as well as forecast information. NVS integrates data from a wide diversity of providers across the region, ranging from county agencies, private industry and regional partnerships, to core IOOS federal programs, and state agencies and academic groups that are principal partners in NANOOS' Data Management and Communication (DMAC) efforts. Regional and national feedback confirms that NVS has been well received by ocean observing and stakeholder communities alike. This paper discusses, in detail, NVS 2.0, which was released in August 2010. In particular, we provide an in depth look at the database schema, metadata, data harvesting, and component communication. In addition, we discuss the NVS data management and communication approach in the context of the IOOS DMAC interoperability and standards-based efforts, highlighting the strengths and weaknesses of application-focused vs. strong-interoperability-focused approaches. Le- - ssons learned both from technical and project management perspectives are also presented. Lastly, we discuss future plans for NVS. Anticipated improvements include automating asset metadata discovery and processing using IOOS standard protocols, and a NANOOS implementation of ERDDAP that will support NVS by replacing multiple, data-source-specific data harvesters with more generic and easier-to-maintain NERDDAP harvesters; and by enabling customized data subsetting and download capabilities that will be accessible through the NVS user interface.

The Northwest Association of Networked Ocean Observing Systems (NANOOS) is one of eleven Regional Associations of the US Integrated Ocean Observing System (IOOS). NANOOS serves the Pacific Northwest from the US/Canada border to Cape Mendocino on the northern California coast. Its mission is to coordinate and support the development, implementation, and operations of a regional coastal ocean observing system (RCOOS) for the Pacific Northwest region, as part of IOOS. A key objective for NANOOS is to provide data and user-defined products regarding the coast, estuaries and ocean to a diverse group of end users in a timely fashion, and at spatial and temporal scales appropriate for their needs. To this end, NANOOS is developing a web mapping portal, the NANOOS Visualization System (NVS), that aggregates, displays and serves near real-time coastal, estuarine, oceanographic and meteorological data, derived from buoys, gliders, tide gauges, HF Radar, meteorological stations, satellites and shore based coastal stations, as well as model forecast information in such a way that it presents end users with a rich, informative and meaningful experience. NVS makes use of a variety of services, including the Google Maps service and a data translation and visualization service known as ERDDAP (Environmental Research Division's Data Access Program), compliant Open Geospatial Consortium (OGC) web standards such as the Sensor Observation Service (SOS), Web Map Service (WMS), and Keyhole Markup Language (KML), as well as the Open-source Project for a Network Data Access Protocol (OPeNDAP) as served and cataloged by the NANOOS THREDDS (Thematic Realtime Environmental Distributed Data Services) Data Server (TDS). These heterogeneous data streams are transformed on-the-fly to other formats or representations, which NVS makes available to the end user via a Google Maps interface. We will describe in detail the NVS development process and will demonstrate the ability of NVS to serve as a portal for one-stop access to near real-time regional data and forecast products, including NOAA's first seven "core variables" (ocean currents, temperature, salinity, water level, waves, chlorophyll and surface winds), by describing the data flows from NANOOS funded coastal and ocean observing and forecasting assets as well as Federal assets. In addition, we will describe future development plans that include greater functionality, iteratively improving NVS based on feedback received at planned training workshops and from identified stakeholders, and updating NVS to be compliant with future IOOS and OGC standards.

Wind stress variability over the Benguela upwelling system is considered using 16 months (01 August 1999 to 29 November 2000) of satellite‐derived QuikSCAT wind data. Variability is investigated using a type of artificial neural network, the self‐organizing map (SOM), and a wavelet analysis. The SOM and wavelet analysis are applied to an extracted data set to find that the system may be divided into six discrete wind regimes. The wavelet power spectra for these wind regions span a range of frequencies from 4 to 64 days, with each region appearing to contain distinct periodicities. To the north, 10°–23.5°S, the majority of the power occurs during austral winter, with a 4–16 day periodicity. Further investigation of National Centers for Environmental Prediction reanalysis outgoing longwave radiation data indicates that the winter intensification of wind stress off the Angolan coast is linked with convective activity over equatorial West Africa. The summer activity appears to be linked with the intensification of the Angolan heat low. Convective activity over the Congo basin appears to impact upon wind stress variability, off the Angolan coast, throughout the year. Farther south, 24°–35°S, the majority of the power occurs in the summer. Here a bimodal distribution occurs, with peaks of 4–12 and 25–50 days. The southernmost regions appear to be forced at higher frequencies by both midlatitude cyclones (austral winter) and mesoscale coastal lows (austral summer). At lower frequencies, eastward propagating periodic wind events that originate over eastern South America appear to be important to the forcing of wind stress over the southern Benguela.