The NASA Ocean Biogeochemical Model (NOBM) data portals in Giovanni have now added data from a new model run, extending the length of the data set available to users, and also adding new data products which may be of considerable interest to the oceanographic community.
The NOBM chlorophyll data assimilation uses SeaWiFS chlorophyll a concentration data. The new NOBM data set has been extended to cover the entire period of full-time SeaWiFS operation, from January 1998 to December 2007. Both the NOBM Daily data portal and the NOBM Monthly data portal have data for this entire period.
The new NOBM data are of Version R2012.3. Dr. Cecile Rousseaux has been working over the past year with model author Watson W. Gregg to update the model, increase the accuracy of several parameterizations, and provide the data to the NASA GES DISC for inclusion in Giovanni. The figure at right demonstrates the use of Giovanni with NOBM monthly data.
Dr. Rousseaux provided the following description of the new aspects of the NOBM data:
“In the R2012.3 version we now include two new variables: ice and dissolved iron. The variable called 'ice' represents the distribution of sea ice cover. In the model, all biological processes are assumed to cease in the presence of sea ice. The variables chlorophytes, diatoms, coccolithophores, cyanobacteria and total chlorophyll have been normalized to the fraction of ice (data=data(100-ice/100)).
“The R2012.3 version of the NOBM uses a multi-variate assimilation methodology where imbalances derived from the assimilation of satellite chlorophyll are corrected using a mechanistic approach involving the nutrient-to-chlorophyll ratios embedded in the model (Rousseaux & Gregg, 2012). The assimilation of chlorophyll values, by their very nature, changes the balance between the chlorophyll-containing phytoplankton and the nutrients needed to support them. Most of the time this imbalance is small, and is corrected by the interaction of the physics and biology in the model. However, sometimes this imbalance can be important, especially in regions where the chlorophyll assimilation is a persistent adjustment to a persistent model bias.
“This situation is observed in the South Pacific where the model produces higher chlorophyll than the satellite observes, and there is also a high concentration of nitrate in the deep waters. The assimilation of chlorophyll reduces the concentrations, resulting in reduced nitrate uptake, and leading to excessive nitrate arising from deep water to the surface layer (Figure 1). In a multi-variate assimilation methodology, these imbalances derived from the assimilation of satellite chlorophyll are corrected using a mechanistic approach involving the nutrient-to-chlorophyll ratios embedded in the model. The difference between the chlorophyll assimilation results and the prior chlorophyll produced by the model (the analysis increments) are used to adjust the nutrient concentrations. The multi-variate assimilation is applied to silica and dissolved iron, as well as nitrate.”
Figure 1. Comparison of the free run, multivariate, and univariate approaches for chlorophyll and nutrients in the South Pacific Ocean. Time series of annual averages of (a) Chlorophyll, (b) Nitrate, (c) Silicate, and (d) Dissolved Iron.
Authors: Cecile Rousseaux and James Acker. Editing by Bill Teng, editing and Web formatting by James Acker.
The GES DISC is a NASA earth science data center, part of the NASA Earth Science Data and Information System (ESDIS) Project.
NOBM research and development is performed as an activity in the Goddard Modeling and Assimilation Office (GMAO). NOBM is funded by the NASA Earth Observing System and the Modeling, Analysis, and Prediction (MAP) Program.