Challenges associated with modeling low-oxygen waters in Chesapeake Bay : a multiple model comparison

dc.contributor.author Irby, Isaac D.
dc.contributor.author Friedrichs, Marjorie A. M.
dc.contributor.author Friedrichs, Carl T.
dc.contributor.author Bever, Aaron J.
dc.contributor.author Hood, Raleigh R.
dc.contributor.author Lanerolle, Lyon W. J.
dc.contributor.author Li, Ming
dc.contributor.author Linker, Lewis
dc.contributor.author Scully, Malcolm E.
dc.contributor.author Sellner, Kevin G.
dc.contributor.author Shen, Jian
dc.contributor.author Testa, Jeremy M.
dc.contributor.author Wang, Hao
dc.contributor.author Wang, Ping
dc.contributor.author Xia, Meng
dc.date.accessioned 2016-07-07T18:15:29Z
dc.date.available 2016-07-07T18:15:29Z
dc.date.issued 2016-04-06
dc.description © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 13 (2016): 2011-2028, doi:10.5194/bg-13-2011-2016. en_US
dc.description.abstract As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient. en_US
dc.description.sponsorship This work was supported by the NOAA IOOS program as part of the Coastal Ocean Modeling Testbed. en_US
dc.identifier.citation Biogeosciences 13 (2016): 2011-2028 en_US
dc.identifier.doi 10.5194/bg-13-2011-2016
dc.identifier.uri https://hdl.handle.net/1912/8092
dc.language.iso en_US en_US
dc.publisher Copernicus Publications on behalf of the European Geosciences Union en_US
dc.relation.uri https://doi.org/10.5194/bg-13-2011-2016
dc.rights Attribution 3.0 Unported *
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.title Challenges associated with modeling low-oxygen waters in Chesapeake Bay : a multiple model comparison en_US
dc.type Article en_US
dspace.entity.type Publication
relation.isAuthorOfPublication 0b665fcc-025c-4b03-aae9-d61bbeb030c9
relation.isAuthorOfPublication fefae04f-e294-4d9e-a2f6-ec9f9bee66b5
relation.isAuthorOfPublication 14cbcfcf-d98b-4ca4-9a04-88dfa1509c34
relation.isAuthorOfPublication 75c2e2d9-caa1-4bcf-8189-cc8b4dda4c62
relation.isAuthorOfPublication 6833b499-9c3f-4be8-ad6d-11c6ad3418fd
relation.isAuthorOfPublication 607d009b-e6ad-4cd9-bc90-b57a19a2d3fc
relation.isAuthorOfPublication 0817160d-0a6c-49f0-a0fe-fcdf1c806df6
relation.isAuthorOfPublication dc8156cd-87bd-442a-a821-c0099159029c
relation.isAuthorOfPublication 74659585-c98b-462f-a9ce-3fbb3ef590ec
relation.isAuthorOfPublication 5c06d5cd-edd0-4217-94ac-5cd775e632a4
relation.isAuthorOfPublication a7f66f63-c523-4c1b-a3ea-ed9e626d52c8
relation.isAuthorOfPublication 302c1ee4-e4a6-4acd-8298-b44060f56384
relation.isAuthorOfPublication bd47523b-db97-46f5-b370-ea87342e7fc4
relation.isAuthorOfPublication 77ff4f74-c286-46d6-a772-b5ae824cf513
relation.isAuthorOfPublication e8d029a5-7914-4267-bff9-53906f09661f
relation.isAuthorOfPublication.latestForDiscovery 0b665fcc-025c-4b03-aae9-d61bbeb030c9
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
bg-13-2011-2016.pdf
Size:
3.42 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.89 KB
Format:
Item-specific license agreed upon to submission
Description: