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Anderson, CR, Berdalet E, Kudela RM, Cusack CK, Silke J, O'Rourke E, Dugan D, McCammon M, Newton JA, Moore SK, Paige K, Ruberg S, Morrison JR, Kirkpatrick B, Hubbard K, Morell J.  2019.  Scaling up from regional case studies to a global Harmful Algal Bloom observing system. Frontiers in Marine Science. 6   10.3389/fmars.2019.00250   AbstractWebsite

Harmful algal blooms (HABs) produce local impacts in nearly all freshwater and marine systems. They are a problem that occurs globally requiring an integrated and coordinated scientific understanding, leading to regional responses and solutions. Given that these natural phenomena will never be completely eliminated, an improved scientific understanding of HAB dynamics coupled with monitoring and ocean observations, facilitates new prediction and prevention strategies. Regional efforts are underway worldwide to create state-of-the-art HAB monitoring and forecasting tools, vulnerability assessments, and observing networks. In the United States, these include Alaska, Pacific Northwest, California, Gulf of Mexico, Gulf of Maine, Great Lakes, and the United States Caribbean islands. This paper examines several regional programs in the United States, European Union, and Asia and concludes that there is no one-size-fits-all approach. At the same time, successful programs require strong coordination with stakeholders and institutional sustainability to maintain and reinforce them with new automating technologies, wherever possible, ensuring integration of modeling efforts with multiple regional to national programs. Recommendations for scaling up to a global observing system for HABs can be summarized as follows: (1) advance and improve cost-effective and sustainable HAB forecast systems that address the HAB-risk warning requirements of key end-users at global and regional levels; (2) design programs that leverage and expand regional HAB observing systems to evaluate emerging technologies for Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) in order to support interregional technology comparisons and regional networks of observing capabilities; (3) fill the essential need for sustained, preferably automated, near real-time information from nearshore and offshore sites situated in HAB transport pathways to provide improved, advanced HAB warnings; (4) merge ecological knowledge and models with existing Earth System Modeling Frameworks to enhance end-to-end capabilities in forecasting and scenario-building; (5) provide seasonal to decadal forecasts to allow governments to plan, adapt to a changing marine environment, and ensure coastal industries are supported and sustained in the years ahead; and (6) support implementation of the recent calls for action by the United Nations Decade 2010 Sustainable Development Goals (SDGs) to develop indicators that are relevant to an effective and global HAB early warning system.

Kahru, M, Kudela RM, Anderson CR, Mitchell BG.  2015.  Optimized merger of ocean chlorophyll algorithms of MODIS-Aqua and VIIRS. Ieee Geoscience and Remote Sensing Letters. 12:2282-2285.   10.1109/lgrs.2015.2470250   AbstractWebsite

Standard ocean chlorophyll-a (Chla) products from currently operational satellite sensors Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Visible Infrared Imager Radiometer Suite (VIIRS) underestimate medium and high in situ Chla concentrations and have approximately 9% bias between each other in the California Current. By using the regional optimization approach of Kahru et al., we minimized the differences between satellite estimates and in situ match-ups as well as between estimates of the two satellite sensors and created improved empirical algorithms for both sensors. The regionally optimized Chla estimates from MODIS-Aqua and VIIRS have no bias between each other, have improved retrievals at medium to high in situ Chla, and can be merged to improve temporal frequency and spatial coverage and to extend the merged time series.

Kahru, M, Kudela RM, Anderson CR, Manzano-Sarabia M, Mitchell BG.  2014.  Evaluation of satellite retrievals of ocean chlorophyll-a in the California Current. Remote Sensing. 6:8524-8540.   10.3390/rs6098524   AbstractWebsite

Retrievals of ocean surface chlorophyll-a concentration (Chla) by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS) using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R-2) between 0.79 and 0.88 and a median absolute percent error (MdAPE) between 21% and 27%. However, at in situ Chla > 1 mg m(-3), only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a) maintained reasonable accuracy (R-2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively), while the other sensors had R-2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance.