Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?

Ocean color data assimilation has been shown to dramatically improve chlorophyll abundances and distributions globally and regionally in the oceans. Chlorophyll is a proxy for phytoplankton biomass (which is explicitly defined in a model), and is related to the inorganic carbon cycle through the int...

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Main Author: Gregg, Watson
Format: Other/Unknown Material
Language:unknown
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/2060/20120008820
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spelling ftnasantrs:oai:casi.ntrs.nasa.gov:20120008820 2023-05-15T14:05:05+02:00 Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon? Gregg, Watson Unclassified, Unlimited, Publicly available January 2012 application/pdf http://hdl.handle.net/2060/20120008820 unknown Document ID: 20120008820 http://hdl.handle.net/2060/20120008820 No Copyright CASI Oceanography GSFC.ABS.6018.2012 2012 ftnasantrs 2019-07-21T06:21:53Z Ocean color data assimilation has been shown to dramatically improve chlorophyll abundances and distributions globally and regionally in the oceans. Chlorophyll is a proxy for phytoplankton biomass (which is explicitly defined in a model), and is related to the inorganic carbon cycle through the interactions of the organic carbon (particulate and dissolved) and through primary production where inorganic carbon is directly taken out of the system. Does ocean color data assimilation, whose effects on estimates of chlorophyll are demonstrable, trickle through the simulated ocean carbon system to produce improved estimates of inorganic carbon? Our emphasis here is dissolved inorganic carbon, pC02, and the air-sea flux. We use a sequential data assimilation method that assimilates chlorophyll directly and indirectly changes nutrient concentrations in a multi-variate approach. The results are decidedly mixed. Dissolved organic carbon estimates from the assimilation model are not meaningfully different from free-run, or unassimilated results, and comparisons with in situ data are similar. pC02 estimates are generally worse after data assimilation, with global estimates diverging 6.4% from in situ data, while free-run estimates are only 4.7% higher. Basin correlations are, however, slightly improved: r increase from 0.78 to 0.79, and slope closer to unity at 0.94 compared to 0.86. In contrast, air-sea flux of C02 is noticeably improved after data assimilation. Global differences decline from -0.635 mol/m2/y (stronger model sink from the atmosphere) to -0.202 mol/m2/y. Basin correlations are slightly improved from r=O.77 to r=0.78, with slope closer to unity (from 0.93 to 0.99). The Equatorial Atlantic appears as a slight sink in the free-run, but is correctly represented as a moderate source in the assimilation model. However, the assimilation model shows the Antarctic to be a source, rather than a modest sink and the North Indian basin is represented incorrectly as a sink rather than the source indicated by the free-run model and data estimates. Other/Unknown Material Antarc* Antarctic NASA Technical Reports Server (NTRS) Antarctic The Antarctic Indian
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Oceanography
spellingShingle Oceanography
Gregg, Watson
Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?
topic_facet Oceanography
description Ocean color data assimilation has been shown to dramatically improve chlorophyll abundances and distributions globally and regionally in the oceans. Chlorophyll is a proxy for phytoplankton biomass (which is explicitly defined in a model), and is related to the inorganic carbon cycle through the interactions of the organic carbon (particulate and dissolved) and through primary production where inorganic carbon is directly taken out of the system. Does ocean color data assimilation, whose effects on estimates of chlorophyll are demonstrable, trickle through the simulated ocean carbon system to produce improved estimates of inorganic carbon? Our emphasis here is dissolved inorganic carbon, pC02, and the air-sea flux. We use a sequential data assimilation method that assimilates chlorophyll directly and indirectly changes nutrient concentrations in a multi-variate approach. The results are decidedly mixed. Dissolved organic carbon estimates from the assimilation model are not meaningfully different from free-run, or unassimilated results, and comparisons with in situ data are similar. pC02 estimates are generally worse after data assimilation, with global estimates diverging 6.4% from in situ data, while free-run estimates are only 4.7% higher. Basin correlations are, however, slightly improved: r increase from 0.78 to 0.79, and slope closer to unity at 0.94 compared to 0.86. In contrast, air-sea flux of C02 is noticeably improved after data assimilation. Global differences decline from -0.635 mol/m2/y (stronger model sink from the atmosphere) to -0.202 mol/m2/y. Basin correlations are slightly improved from r=O.77 to r=0.78, with slope closer to unity (from 0.93 to 0.99). The Equatorial Atlantic appears as a slight sink in the free-run, but is correctly represented as a moderate source in the assimilation model. However, the assimilation model shows the Antarctic to be a source, rather than a modest sink and the North Indian basin is represented incorrectly as a sink rather than the source indicated by the free-run model and data estimates.
format Other/Unknown Material
author Gregg, Watson
author_facet Gregg, Watson
author_sort Gregg, Watson
title Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?
title_short Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?
title_full Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?
title_fullStr Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?
title_full_unstemmed Does Ocean Color Data Assimilation Improve Estimates of Global Ocean Inorganic Carbon?
title_sort does ocean color data assimilation improve estimates of global ocean inorganic carbon?
publishDate 2012
url http://hdl.handle.net/2060/20120008820
op_coverage Unclassified, Unlimited, Publicly available
geographic Antarctic
The Antarctic
Indian
geographic_facet Antarctic
The Antarctic
Indian
genre Antarc*
Antarctic
genre_facet Antarc*
Antarctic
op_source CASI
op_relation Document ID: 20120008820
http://hdl.handle.net/2060/20120008820
op_rights No Copyright
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