@article {lobert_categorization_2023,
	title = {Categorization of High-Wind Events and Their Contribution to the Seasonal Breakdown of Stratification on the Southern New England Shelf},
	journal = {Journal of Geophysical Research - Oceans},
	year = {2023},
	note = {Publisher: American Geophysical Union (AGU)},
	month = {jun},
	pages = {e2022JC019625},
	abstract = {High-wind events predominantly cause the rapid breakdown of seasonal stratification on the continental shelf by the end of October. In particular the timing of events leads to considerable interannual variability in the stratification breakdown with a standard deviation of 15 days. Although previous studies have shown how coastal stratification depends on local wind-forcing characteristics, the locally observed ocean forcing has not yet been linked to regional atmospheric weather patterns that determine the local wind characteristics. Establishing such a connection is a necessary first step toward examining how an altered atmospheric forcing due to climate change affects coastal ocean conditions. Here, we propose a categorization scheme for high-wind events that links atmospheric forcing patterns with changes in stratification. We apply the scheme to the Southern New England shelf utilizing observations from the Ocean Observatories Initiative Coastal Pioneer Array (2015{\textendash}2022). Impactful wind forcing patterns occur predominantly during early fall, have strong downwelling-favorable winds, and are primarily of two types: (a) Cyclonic storms that propagate south of the continental shelf causing anticyclonically rotating winds, and (b) persistent large-scale high-pressure systems over East Canada causing steady north-easterly winds. These patterns are associated with opposite temperature and salinity contributions to destratification, implying differences in the dominant processes driving ocean mixing based on a high-wind pattern{\textquoteright}s overall strength and wind direction steadiness. The high-wind event categorization scheme allows a transition from solely focusing on local wind forcing to considering realistic atmospheric weather patterns when investigating their impact on stratification in the coastal ocean.},
	keywords = {13 Climate Action, continental shelf, destratification, OOI Coastal Pioneer, storm categorization, stratification breakdown, synoptic meteorology},
	issn = {2169-9275},
	doi = {10.1029/2022jc019625},
	author = {Lobert, L and Gawarkiewicz, G and Plueddemann, A}
}
@article {lima_predicting_2023,
	title = {Predicting Carbonate Chemistry on the Northwest Atlantic Shelf using Neural Networks},
	journal = {Journal of Geophysical Research Biogeosciences},
	volume = {128},
	year = {2023},
	note = {Publisher: American Geophysical Union (AGU)},
	pages = {e2023JG007536},
	abstract = {The Northwest Atlantic Shelf (NAS) region has experienced accelerated warming, heatwaves, and is susceptible to ocean acidification, yet also suffers from a paucity of carbonate chemistry observations, particularly at depth. We address this critical data gap by developing three different neural network models to predict dissolved inorganic carbon (DIC) and total alkalinity (TA) in the NAS region from more readily available hydrographic and satellite data. The models predicted DIC with r2 between 0.913{\textendash}0.963 and root mean square errors (RMSE) between 15.4{\textendash}23.7 (μmol kg-1) and TA with r2 between 0.986{\textendash}0.983 and RMSE between 9.0{\textendash}10.4 (μmol kg-1) on an unseen test data set that was not used in training the models. Cross-validation analysis revealed that all models were insensitive to the choice of training data and had good generalization performance on unseen data. Uncertainty in DIC and TA were low (coefficients of variation 0.1\%{\textendash}1\%). Compared with other predictive models of carbonate system variables in this region, a larger and more diverse data set with full seasonal coverage and a more sophisticated model architecture resulted in a robust predictive model with higher accuracy and precision across all seasons. We used one of the models to generate a reconstructed seasonal distribution of carbonate chemistry fields based on DIC and TA predictions that shows a clear seasonal progression and large spatial gradients consistent with observations. The distinct models will allow for a range of applications based on the predictor variables available and will be useful to understand and address ocean sustainability challenges.},
	keywords = {13 Climate Action, carbonate chemistry, Machine learning, neural network, Northwest Atlantic, ocean acidification},
	issn = {2169-8953},
	doi = {10.1029/2023jg007536},
	author = {Lima, ID and Wang, ZA and Cameron, LP and Grabowski, JH and Rheuban, JE}
}
@article {269,
	title = {Arrival of New Great Salinity Anomaly Weakens Convection in the Irminger Sea},
	journal = {Geophysical Research Letters},
	volume = {49},
	year = {2022},
	month = {2022/06/09/},
	pages = {e2022GL098857},
	abstract = {The Subpolar North Atlantic is prone to recurrent extreme freshening events called Great Salinity Anomalies (GSAs). Here, we combine hydrographic ocean analyses and moored observations to document the arrival, spreading, and impacts of the most recent GSA in the Irminger Sea. This GSA is associated with a rapid freshening of the upper Irminger Sea between 2015 and 2020, culminating in annually averaged salinities as low as the freshest years of the 1990s and possibly since 1960. Upon the GSA propagation into the Irminger Sea over the Reykjanes Ridge, the boundary currents rapidly advected its signal around the basin within months while fresher waters slowly spread and accumulated into the interior. The anomalies in the interior freshened waters produced by deep convection during the 2017{\textendash}2018 winter and actively contributed to the suppression of deep convection in the following two winters.},
	keywords = {13 Climate Action},
	isbn = {0094-8276},
	doi = {10.1029/2022GL098857},
	author = {Bil{\'o}, T.C. and Straneo, F. and Holte, J. and Le Bras, I. A.-A.}
}
@article {le_bras_slantwise_2022,
	title = {Slantwise Convection in the Irminger Sea},
	journal = {Journal of Geophysical Research: Oceans},
	volume = {127},
	number = {10},
	year = {2022},
	note = {_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022JC019071},
	pages = {e2022JC019071},
	abstract = {The subpolar North Atlantic is a site of significant carbon dioxide, oxygen, and heat exchange with the atmosphere. This exchange, which regulates transient climate change and prevents large-scale hypoxia throughout the North Atlantic, is thought to be mediated by vertical mixing in the ocean{\textquoteright}s surface mixed layer. Here we present observational evidence that waters deeper than the conventionally defined mixed layer are affected directly by atmospheric forcing in this region. When northerly winds blow along the Irminger Sea{\textquoteright}s western boundary current, the Ekman response pushes denser water over lighter water, potentially triggering slantwise convection. We estimate that this down-front wind forcing is four times stronger than air{\textendash}sea heat flux buoyancy forcing and can mix waters to several times the conventionally defined mixed layer depth. Slantwise convection is not included in most large-scale ocean models, which likely limits their ability to accurately represent subpolar water mass transformations and deep ocean ventilation.},
	keywords = {13 Climate Action},
	issn = {2169-9291},
	doi = {10.1029/2022JC019071},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2022JC019071},
	author = {Le Bras, I. A.-A. and Callies, J. and Straneo, F. and Bil{\'o}, T. C. and Holte, J. and Johnson, H. L.}
}
