scholarly journals Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA

2014 ◽  
Vol 6 (2) ◽  
pp. 1007-1025 ◽  
Author(s):  
John Ryan ◽  
Curtiss Davis ◽  
Nicholas Tufillaro ◽  
Raphael Kudela ◽  
Bo-Cai Gao
Keyword(s):  
Coastal Ocean ◽  
Monterey Bay ◽  
Phytoplankton Ecology

scholarly journals Correction: Ryan, J., et al. Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA. Remote Sens. 2014, 6, 1007–1025

2015 ◽  
Vol 7 (10) ◽  
pp. 13364-13366
Author(s):  
Marcos Montes ◽  
John Ryan ◽  
Curtiss Davis ◽  
Nicholas Tufillaro ◽  
Raphael Kudela
Keyword(s):  
Coastal Ocean ◽  
Monterey Bay ◽  
Phytoplankton Ecology

scholarly journals Coastal Ocean Physics and Red Tides: An Example from Monterey Bay, California

Oceanography ◽  
2005 ◽  
Vol 18 (2) ◽  
pp. 246-255 ◽  
Author(s):  
John Ryan ◽  
Heidi Dierssen ◽  
Raphael Kudela ◽  
Christopher Scholin ◽  
Kenneth Johnson ◽  
...  
Keyword(s):  
Coastal Ocean ◽  
Monterey Bay ◽  
Red Tides ◽  
Ocean Physics

A 4DVAR System for the Navy Coastal Ocean Model. Part I: System Description and Assimilation of Synthetic Observations in Monterey Bay*

2014 ◽  
Vol 142 (6) ◽  
pp. 2085-2107 ◽  
Author(s):  
Hans Ngodock ◽  
Matthew Carrier
Keyword(s):  
Initial Conditions ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Descent Method ◽  
Forecast Errors ◽  
Gradient Descent Method ◽  
Monterey Bay ◽  
Coastal Ocean Model ◽  
Weak Constraints ◽  
Assimilation System

Abstract A 4D variational data assimilation system was developed for assimilating ocean observations with the Navy Coastal Ocean Model. It is described in this paper, along with initial assimilation experiments in Monterey Bay using synthetic observations. The assimilation system is tested in a series of twin data experiments to assess its ability to fit assimilated and independent observations by controlling the initial conditions and/or the external forcing while assimilating surface and/or subsurface observations. In all strong and weak constraint experiments, the minimization of the cost function is done with both the gradient descent method (in the control space) and the representer method (observation space). The accuracy of the forecasts following the analysis and the relevance of the retrieved forcing correction in the case of weak constraints are evaluated. It is shown that the assimilation system generally fits the assimilated and nonassimilated observations well in all experiments, yielding lower forecast errors.

scholarly journals A 4DVAR System for the Navy Coastal Ocean Model. Part II: Strong and Weak Constraint Assimilation Experiments with Real Observations in Monterey Bay*

2014 ◽  
Vol 142 (6) ◽  
pp. 2108-2117 ◽  
Author(s):  
Hans Ngodock ◽  
Matthew Carrier
Keyword(s):  
Data Assimilation ◽  
Model Simulation ◽  
Full Range ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Sea Surface ◽  
Real Surface ◽  
Monterey Bay ◽  
Strong Constraint ◽  
Coastal Ocean Model

Abstract A four-dimensional variational data assimilation (4DVAR) system was recently developed for the Navy Coastal Ocean Model (NCOM). The system was tested in the first part of this study using synthetic surface and subsurface data. Here, a full range of real surface and subsurface data is considered following encouraging results from the preliminary test. The data include sea surface temperature and sea surface height from satellite, as well as subsurface observations from gliders deployed during the second Autonomous Ocean Sampling Network field experiment in California’s Monterey Bay. Data assimilation is carried out with strong and weak constraints, and results are compared against independent observations. This study clearly shows that the 4DVAR approach improves the free-running model simulation and that the weak constraint experiment has lower analysis errors than does the strong constraint version.

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