Challenges associated with modeling low-oxygen waters in Chesapeake Bay : a multiple model comparison Irby, Isaac D. Friedrichs, Marjorie A. M. Friedrichs, Carl T. Bever, Aaron J. Hood, Raleigh R. Lanerolle, Lyon W. J. Li, Ming Linker, Lewis Scully, Malcolm E. Sellner, Kevin G. Shen, Jian Testa, Jeremy M. Wang, Hao Wang, Ping Xia, Meng 2016-07-07T18:15:29Z 2016-07-07T18:15:29Z 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.language.iso en_US en_US
dc.publisher Copernicus Publications on behalf of the European Geosciences Union en_US
dc.rights Attribution 3.0 Unported *
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
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