Penta, Bradley: Naval Research Laboratory (Project Lead)
Project Funding:
2013 - 2018
NRA: 2012 NASA: Ecological Forecasting
Funded by NASA
Abstract:
We will develop an Adaptive Ecosystem Climatology (AEC) to provide a flexible, on- line tool for ecoforecasting applications; it will meld observations collected by amateur observers (crowdsourcing), Earth Observation (EO) satellites, archived in-situ data, and output from a state-of-the-art, data assimilative, coupled bio-optical-physical ocean model system. The AEC mitigates the shortcomings of the components and combines their strengths to enhance decision-making activities of our end-user, partner organizations (NOAA, BOEM, EPA).
Analyses of decadal time-series of EO, in-situ, and numerical model simulations provide temporal and spatial relationships (covariances, multivariate correlations) of primary ecosystem components. Using these relationships, we will build a three-dimensional, dynamically balanced, gridded, static climatology for each calendar day of temperature, salinity, sea surface height, currents, nitrate, ammonium, silicate, phosphate, oxygen, zoo- and phyto- plankton, chlorophyll, detritus, and submarine light. Using the static climatology as a background first guess , observations (EO, in-situ, or crowdsourced) from a particular date can be ingested to nudge the climatology toward current conditions, to provide updated, representative fields for that date (adaptive climatology). The resultant AEC fields can then be interpolated, sub-sampled, and averaged to provide inputs, initial and/or boundary conditions for many types of management models. An on-line tool (hosted by NOAA) will facilitate rapid and efficient creation of the desired fields from AEC, and will provide tools for analysis and data visualization, along with estimates of uncertainty levels and model sensitivity. These targeted products will be designed in conjunction with partner organizations.
The Feasibility Study (Stage 1) will focus on the Gulf of Mexico and will explore: 1) the practicability of the on-line system for selecting, updating, and delivering the AEC fields to the end-users, 2) the value of the AEC to the end-user decision-making processes, and 3) the feasibility and methodology of collecting and applying data from amateur observers to the AEC. Stage 2 of the project will extend the AEC to the remaining US coastal waters.
Publications:
Gomes, H. D. R., deRada, S., Goes, J. I., Chai, F. 2016. Examining features of enhanced phytoplankton biomass in the Bay of Bengal using a coupled physical-biological model. Journal of Geophysical Research: Oceans. 121(7), 5112-5133. DOI: 10.1002/2015jc011508
More details may be found in the following project profile(s):
