Anderson, Clarissa: University of California San Diego (Project Lead)
Project Funding:
2013 - 2018
NRA: 2012 NASA: Ecological Forecasting
Funded by Other, NASA, Other US Funding: NASA Paula Bontempi
Abstract:
We propose a method for predicting the spatial distribution of harmful algal bloom (HAB) and toxin load likelihoods in the coastal region of the California Current System (CCS) using a unique blend of numerical models, ecological forecast models of target phytoplankton species (Pseudo-nitzschia and its neurotoxin, domoic acid), and satellite ocean color imagery. We propose to generate these forecast products routinely and in a pre-transitional demonstration of operational predictions of toxic blooms for central California using available satellite data (MODISA, VIIRS, Sentinel-3 MERIS). Our approach satisfies the three required program elements of A.36 Ecological Forecasting for Conservation and Ecological Resource Management in that it merges earth system models and satellite observations with ecological forecasting and in situ observations of HABs from several field programs and networked data sources. What we consider to be the most innovative aspect of this proposal is that we can merge satellite data with numerical forecasts of the physical data to statistically reconstruct biogeochemical fields up to three days to then force our existing statistical models for forecasting HAB events. We propose that this is the fastest and most robust method for immediately executing HAB forecasts. We will leverage the distributed databases established by the Central and Northern California Ocean Observing System and Southern California Coastal Ocean Observing System for data management, interface with end-users, and communication with their many regional partners on the value of this effort. A forecasting analysis tool will be developed to transform HAB monitoring and crowdsource data streams to usable information for an adaptive forecasting system that employs both models and citizen scientist observations for constraining prediction certainty. Importantly, this forecasting system and analysis tool will be developed in partnership with the National Oceanic and Atmospheric Administration (NOAA, specifically the National Ocean Service and the National Weather Service (NWS), as a testbed for collaboration toward transitioning research results to an operational center. Transfer to operations will be accomplished by leveraging NOAA expertise and experience transitioning regional ocean models, guided by HAB research, into NWS National Center for Environmental Prediction. This is aligned with NOAA s regional and national transition plans and coordinated efforts that issue operational beach hazard statements with integrated HAB forecasts to alert decision makers and inform managers. Such a capability will allow us to predict large-scale ecosystem changes and the associated impact on HABs that scale well beyond existing, shore-based monitoring programs, making this approach the most cost-effective method for monitoring offshore disturbances that affect both aquaculture facilities and marine mammal populations.
Publications:
Anderson, C. R., Kudela, R. M., Kahru, M., Chao, Y., Rosenfeld, L. K., Bahr, F. L., Anderson, D. M., Norris, T. A. 2016. Initial skill assessment of the California Harmful Algae Risk Mapping (C-HARM) system. Harmful Algae. 59, 1-18. DOI: 10.1016/j.hal.2016.08.006
Kahru, M., Kudela, R. M., Anderson, C. R., Mitchell, B. G. 2015. Optimized Merger of Ocean Chlorophyll Algorithms of MODIS-Aqua and VIIRS. IEEE Geoscience and Remote Sensing Letters. 12(11), 2282-2285. DOI: 10.1109/lgrs.2015.2470250
Kahru, M., Kudela, R., Anderson, C., Manzano-Sarabia, M., Mitchell, B. 2014. Evaluation of Satellite Retrievals of Ocean Chlorophyll-a in the California Current. Remote Sensing. 6(9), 8524-8540. DOI: 10.3390/rs6098524
More details may be found in the following project profile(s):
