High-frequency radar surface current data reveals local and remote drivers of three bays: Chesapeake Bay, Delaware Bay, and New York Bay

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This study expands the previous findings in one bay into three major U.S. East Coast bays: the Chesapeake Bay (CB), the Delaware Bay (DB) and the New York Bay (NB). Monthly surface currents at 2 km resolution near the mouths of these bays were obtained from high-frequency radars (Coastal Ocean Dynamics Application Radar, CODAR) during 2012–2024. The contribution to flow variability from local and remote forcing is evaluated by comparing surface currents with (a) river discharges into each bay, (b) with winds, and (c) with the North Atlantic Oscillation (NAO). The results show that flow variability in the bays is significantly correlated with all three driving factors. The three bays often show similar flow patterns not only of the seasonal cycle, but also during extreme weather events. For example, increased inflow into the bays from the Atlantic Ocean is seen when hurricanes are observed offshore in the fall, and increased outflow from the bays is seen during winter storms. During positive NAO phases, outflow from all three bays increased due to intensified westerly winds, while during negative NAO phases outflow decreased with weakening winds in the region. Increased river discharges over the record length resulted in increased outflows from DB and NB of about 4 cm/s per decade. However, in CB extremely large river discharges into the bay in 2018–2019 resulted in a change in the outflow from a significant upward trend before 2018 to a significant downward trend after 2019. The results demonstrate the complex nature of the outflow from bays since multiple drivers contribute to the observed variability. CODAR Estuarine Circulation Chesapeake Bay Delaware Bay New York Bay Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1 Introduction The motivation for this study comes from results of recent studies of seasonal, interannual and decadal variations in sea level, temperature, and surface currents in the Chesapeake Bay (CB, Ezer 2023a ; Ezer and Updyke 2024 ). These studies suggest potential links between variations in this bay, which is the largest estuary of the U.S., and large-scale variations in the Atlantic Ocean characterized for example by the North Atlantic Oscillations (NAO; Hurrell 1995 ) and the Atlantic Meridional Overturning Circulation (AMOC, Smeed et al. 2014 ; Moat et al. 2023 ). Previous studies of CB also suggested that sea level acceleration in the bay is linked to slowdown of AMOC and the Gulf Stream (Ezer and Corlett 2012 ; Ezer et al. 2013 ). The CB and most of the U.S. East coast are subject to fast sea level rise and increased risk of flooding, including variations in sea level on a wide range of time scales (Ezer and Corlett 2012 ; Ezer and Atkinson 2014 ; Sweet and Park 2014 ; Karegar et al. 2016 ; Valle-Levinson et al. 2017; Boesch et al. 2018 ; Domingues et al. 2018 ; Ezer et al. 2017 ; Ezer 2020b , 2022 , 2023a ). Therefore, numerous studies focused on the potential links between offshore variations in the Atlantic Ocean and coastal sea level along the U.S. Gulf Coast and East Coast (Ezer et al. 2013 ; Ezer and Atkinson 2014 ; Ezer 2015 , 2023; Goddard et al. 2015 ; Little et al. 2019 ; Piecuch et al. 2019 ; Volkov et al. 2019 , 2023 ; Dangendorf et al. 2021 , 2023 ; Park et al. 2022 , 2024 ). However, not much research was done on the impact of remote Atlantic forcing on the circulation pattern in bays and estuaries. If remote forcing is affecting variations in sea level in bays, then these variations should also affect the flow pattern and transport exchange between bays and the open ocean. High-frequency radar data of surface currents near the mouth of the CB indeed suggested some links with the Atlantic Ocean variability (Ezer et al., 2022 ; Ezer and Updyke 2024 ). In recent years Coastal Ocean Dynamics Application Radar (CODAR) high frequency radar (HFR) stations have been installed along long stretches of the U.S. East Coast, providing surface current data near the CB (Atkinson et al. 2009 ; Ezer et al. 2022 ; Ezer and Updyke 2024 ), the Delaware Bay (DB; Muscarella et al. 2011 ), and the New York Bay (Gopalakrishnan and Blumberg 2012 ; note that NB sometimes is referred to as the lower bay of New York Harbor). The existence of these new observations led us to expand the previous study (Ezer and Updyke 2024 ) from the CB to the DB and NB. Classic estuarine circulation is well described in the literature as driven by freshwater river discharge at one end and saltwater intrusion and tidal mixing at the other open end, though circulation can be quite complex and vary from bay to bay due to topography, stratification, and other factors (Valle-Levinson et al. 1998 , 2003 ; Valle-Levinson 2010 ). Also, not many studies address long-term variabilities in bays beyond the tidal and seasonal time scales. By comparing three different bays, separated by ~ 400 km, having different topographies and different river inputs, we try to evaluate what part of the dynamics is locally driven versus potential common forcing from large-scale climate patterns. The study may have important implications for coastal ocean prediction, since remote forcing from the open ocean on the coast is not well understood or predicted. The study is organized as follows. First, the data sources and analysis methods are described in section 2 , then results are presented in section 3 , focusing on correlations between the bays, river discharges, and Atlantic Ocean variability. Finally, summery and conclusions are offered in section 4 . 2 Data sources and analysis methods Monthly surface currents were obtained from HFR data archived at https://cordc.ucsd.edu/projects/hfrnet/ ; data on 2km grid from March 2012 to March 2024 were extracted for the U.S. East Coast from the Scripps Institution of Oceanography National HFR Network data catalog (HFRNet; https://hfrnet-tds.ucsd.edu/thredds/catalog.html ). The data were further extracted for three subregions near the mouth of the three bays of this study (Fig. 1 ). The data represent flow in the upper meter of the water column. To evaluate flow exchange between each bay and the Atlantic Ocean, most of the study involves analysis of zonal flow (U-components of surface currents), where positive values represent outflow from the bay toward the Atlantic Ocean. It is noted that the previous study that focused only on the CB (Ezer and Updyke 2024 ) used our locally maintained HFR observations ( http://www.ccpo.odu.edu/currentmapping/ ; see also Atkinson et al. 2009 and Ezer et al. 2022 ) with slightly different quality control, a different period (2007–2021) and a focus on flow toward the southeast. However, comparison (not shown) between the local institutional data and the public (HFRNet) data used here shows that the two data sets are generally consistent with each other, and differences in trends are due to the period used (more on this later). Monthly river streamflow into the CB, which includes several rivers and streams, was obtained from USGS ( https://www.usgs.gov/media/images/estimated-monthly-mean-streamflow-entering-chesapeake-bay ). For freshwater input to the DB, we used the transport of the Delaware River (near Trenton, NJ), and for the NB we used the transport of the Hudson River (extracted from: https://waterdata.usgs.gov/nwis/uv/?referred_module=sw ). Variations in the Delaware River flow dominate the circulation and water properties of the DB (Sharp et al. 1986 ), and the Hudson River provides most of the discharge water into NB (Li et al 2019 ), so that unlike the CB, a single river discharge is sufficient for these two bays. The units were converted from ft 3 s − 1 as reported by USGS to m 3 s − 1 . Also, because the flow into the CB is much larger than that of the other two bays, in some analysis, streamflow into the CB was divided by a factor of 4 to allow plotting on the same axis. Monthly North Atlantic Oscillation (NAO; Hurrel 1995) Index was obtained from NOAA’s Climate Prediction Center ( https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml ). NAO is related to wind patterns over the Atlantic Ocean that may affect currents along the U.S. East Coast, so wind pattern data from NCEP/NCAR Reanalysis were obtained from NOAA’s Physical Science Laboratory ( https://psl.noaa.gov/data/reanalysis/reanalysis.shtml ). Local wind data were obtained from NOAA stations ( https://tidesandcurrents.noaa.gov/ ); monthly means were calculated from 6-minute data. Statistical analyses of these data include correlations between time series of the same type of data, e.g., transport in river#1 versus river#2, as well as correlations across different sources, e.g., transport of river#1 versus flow in bay#1. Linear trends of each time series were also calculated, but one should keep in mind that 12-year records are too short for assessing long-term climatic trends and decadal variability. As shown later, large anomaly in one or two years can significantly change the trend during this relatively short period. 3 Results 3.1 Surface currents in the three bays: pattern, trend, and correlation The mean surface current pattern over the study period (March 2012 to March 2024) shows some similarity and some differences between the three bays (Fig. 2 ). In all three bays, the strongest outflow is seen in the southern side of the mouth of the bay, but the DB has a distinctly different pattern than the other two bays with a strong southwestward flow in the lower bay. Previous studies of these bays used past observations and models (though none as recent as here, until March 2024), and often focused on tides and short time scales of days to months (e.g., Galperin and Mellor 1990 ; Blumberg et al. 1999 ; Muscarella et al. 2011 ). The general pattern seen here is quite like that of previous studies with models and observations (e.g., see Atkinson et al. 2009 , Ezer et al. 2022 and Ezer and Updyke 2024 for CB, Galperin and Mellor 1990 and Muscarella et al. 2011 for DB, Blumberg et al. 1999 , Gopalakrishnan and Blumberg 2012 and Li et al. 2019 for NB). Since the interest here is the exchange of water between the bay and the Atlantic Ocean, and each bay has slightly different flow pattern near its mouth, we analyzed the zonal component (U-velocity; referred to here as “outflow”) averaged over the regions in Fig. 2 . Note that Ezer and Updyke ( 2024 ) rotated the vectors toward the southeast, but trends and variability seem very similar to the U-velocity since the flow direction near the mouth of CB changes very little in this region (Fig. 2 c). The chosen area extends beyond the mouth of the bay because there is too much missing data in the mouth itself. The monthly time series of outflow are shown in Fig. 3 . The upward trend of increased outflow from NB and DB of about 4 cm/s per decade (Fig. 3 a and Fig. 3 b) is consistent with the increased precipitation and river discharge in the northeastern U.S. (Rice et al. 2017 ). However, the insignificant trend in the CB outflow of -0.7 cm/s per decade (Fig. 3 c) in 2012–2024 seems to contradict the recent results of Ezer and Updyke ( 2024 ) who found in CB increased outflow of 2.2 cm/s per decade in 2007–2021. The data set in the previous study was somewhat different in the period, the area, and the data sources. In the Ezer and Updyke 2024 study, in-house data was used instead of the public data used now. Further analysis of the in-house U-velocity data found that the different period used was the main source of the discrepancy; there was a large increase in outflow from CB of 3.3 cm/s per decade from 2006 to 2016, but this trend reduced by a factor of 10 to insignificant 0.3 cm/s per decade from 2016 to 2021 and further reduced from 2021 to 2024 as seen in Fig. 3 c. Therefore, we conclude that the two data sets are consistent with each other, and changes of trends over time are responsible for the differences. This trend shift will be explained later when river discharge is analyzed. Moreover, decadal variability such as those associated with the North Atlantic Oscillation (NAO; Hurrel 1995) and the Atlantic Meridional Overturning Circulation (AMOC; Moat et al. 2023 ) can affect the bays, as suggested by Ezer and Updyke ( 2024 ), but longer observations than the 12-year data used here, are likely needed to capture these decadal variations. To assess if there is a large-scale common driver for the three bays, correlations between the outflow of the bays are calculated after removing the trends (Fig. 4 ). The results indeed show statistically significant correlations (Table 1), whereas the highest correlation is found between the two northernmost bays, DB and NB (99.999% confidence level), and the lowest correlation (99% confidence level) was found between the two southernmost bays, CB and DB. The multiple rivers and the large watershed of the CB probably makes its variability more complex than if driven by a single major river like DB and NB. While having statistically significant correlation demonstrates relations, it does not indicate the cause of the relation. It is also noted that only about 15% of the variability is explained by this common driver, in fact, there are probably several different drivers of variability in the bays as discussed later. Figure 5 shows the monthly outflow anomaly (detrended time series) of the three bays, indicating several unusual peaks where all the bays have similar anomalies. Negative anomalies that indicate increased inflow into the bay were identified at periods when hurricanes were observed offshore the U.S. East Coast. Studies of these hurricanes show increased coastal sea level, due to storm surge and weakening of the Gulf Stream by the storms (sometimes for weeks after the storm). Therefore, when storms move along the U.S. East Coast, they cause additional transport of water toward the shore and into the bays, and this is consistent with the increased flow toward the bays as seen in the negative peaks in Fig. 5 . More information on the hurricanes indicated in Fig. 5 can be found in recent studies of Hurricane Joaquin in 2015 (Ezer and Atkinson 2017 ), Hurricane Matthew in 2016 (Ezer et al. 2017 , Park et al. 2022 , 2024 ), Hurricane Florence in 2018 (Ezer 2019 ) and Hurricane Dorian in 2019 (Ezer 2020b ). Note that tropical storms and hurricanes occur mostly during the fall, when the seasonal sea level is higher with the so-called “King Tide” (Ezer 2020a ). On the other hand, positive peaks in Fig. 5 , which represent larger than normal outflow from the bays, occur recently (since 2018) mostly in the winter around January. These anomalies may be related to the increase in extreme snow events over the U.S. due to global warming (Chen et al. 2021 ). Close examination of the period of these peaks found that they are indeed associated with winter storms that passed over the northeastern U.S. For example, the largest peak in outflow in the DB occurred in January 2019, during the “Harper” winter snow storm event in middle January 2019 ( https://www.weather.gov/pah/SnowJan19_2019 ). During this period a weak jet stream and an extreme cold wave (called a “Polar Vortex” by the media) were seen. Winter storms named “Jacob” and “Isaiah” in January 2020 coincide with peak outflow in all three bays seen in Fig. 5 . Another big winter storm occurred in January 2022 ( https://www.weather.gov/akq/Jan22-2022Snow ), which again coincides with peak outflows. Storms occur over short time scales of days, and have much larger impact on daily radar data, but they seem to have enough impact to influence the monthly data analyzed here. 3.2 Comparison of surface currents with river discharge Classical estuarine circulation is usually described as driven by freshwater discharge from rivers at one end and tides from the open ocean on the other end (Valle-Levinson 2010 ), so when analyzing monthly data, which removes the daily tides, river discharge should have strong influence on the seasonal and interannual variability of outflow from bays. Figure 6 a shows the monthly river inflows into the bays; these river discharges are highly correlated with each other (R = 0.64–0.85; Table 1). While seasonal variations are dominating the variability, large interannual variations are also seen. Especially large discharge is seen around January 2019, during the winter snowstorm and the extreme cold wave of the northeastern U.S. as discussed before in section 3.1 . The river flow after applying a 24-month Hanning Filter (Fig. 6 b) indicates unusually large stream flow into the CB during 2018–2019 (and to lesser degree in DB). This anomaly in river flows into the CB, results in a change in outflow trend from positive before 2018 to negative after 2019 and explains the apparent discrepancy between the result shown here of a negligible outflow trend for 2012–2024, and the results of Ezer and Updyke ( 2024 ) of upward trend in earlier years. Figure 7 shows the seasonal cycle (monthly mean) of rivers and currents. Maximum spring river flow occurs around April (Fig. 7 a) while maximum bay outflow occurs a month later around May (Fig. 7 b). Another peak of outflow is seen in the fall around November, when the seasonal sea level also peaks (Ezer 2020a , 2023a ), and when river flow starts to increase from the late summer minimum. Figure 8 shows comparisons between outflow velocities and river discharges in the bays; the calculations were done with and without the seasonal cycle, and correlations are all statistically significant at over 95% confidence level (Table 1). The seasonal cycle contributes to the correlations, especially in NB and DB; when the seasonal cycle is removed, correlations are lower there. This is different in CB (lower panels of Fig. 8 ) with higher correlation (R = 0.28 at 99.9% confidence level) without the seasonal cycle. The latter result is due to the large signal in this region during the winter storms of 2019 and 2021 (which is also evident in DB; middle panels of Fig. 8 ). While the CB river discharge includes the combinations of several rivers, additional calculations (not shown) of correlation with individual river discharges show very similar correlations as the combined discharge, which indicates that all those rivers are affected by the same weather pattern and storms passing the region. 3.3 Comparison of currents with winds and NAO As demonstrated in the previous section, outflows from the bays are correlated with river discharges, as expected, but the correlations indicate that river discharge is only responsible for some 10% or less of the monthly outflow variability (somewhat larger percentage is found if lag is considered). Other potential sources of variability include local winds and large-scale atmospheric and oceanic variations over the Atlantic Ocean. Upper ocean currents are generally assumed to be driven by surface winds, i.e., the so-called Ekman Transport (e.g., see recent evaluation of the Ekman Theory by Ezer, 2023b ). Short-term observations by Muscarella et al. ( 2011 ) show for example that surface currents near the mouth of DB were mostly driven by local wind, however, it is not clear if this is also the case for long-term monthly observations. When comparing local NOAA wind stations (monthly values calculated from 6-minute data) with surface currents, results (not shown) found maximum correlation when the angle between the wind and currents is ~ 20–40 degrees (Ekman theory implies that pure wind-driven surface current in non-stratified ocean is expected to be directed 45 degrees to the right of the wind in the northern hemisphere). The maximum correlations between local wind and nearby currents at the three bays are around R = 0.74. These results are in general agreement with the Ekman theory of local wind-driven currents. However, what about large-scale wind pattern influence? Fig. 9 compares the currents in the three bays with the mean zonal wind (U-component) obtained from reanalysis over the entire region (the V-component of the wind is insignificant in the reanalysis over this region). While the correlations are a little lower than correlation with local winds, they are still significant at over 99.99% confidence (R = 0.25, 0.55 and 0.61, for CB, DB and NB, respectively; Table 1). One should keep in mind though that the coarse resolution (~ 2.5 degree) reanalysis represents the large-scale wind patterns over the Atlantic Ocean. Past studies focused on remote influence of the Atlantic Ocean and the Gulf Stream on coastal sea level (Ezer et al. 2013 ; Ezer 2015 , 2023a ; Dangendorf et al. 2021 , 2023 ), but little research is done on remote influence on currents near bays – one exception is the study of Ezer and Updyke ( 2024 ) that shows potential links between surface currents in the CB and the Atlantic Meridional Overturning Circulation (AMOC). The large-scale atmospheric pattern over the North Atlantic can be characterized by the North Atlantic Oscillation (NAO) index (Hurrell 1995 ), whereas positive phase indicates storm track farther north and more wet and stormy weather over the northeastern U.S., while negative phase indicates southern shift in the storm track, dryer weather and fewer storms over the same region. To evaluate the impact of NAO, it is compared with the outflow velocity of the three bays (Fig. 10 and Table 1). The monthly records were filtered by a 6-month Hanning Filter to remove high-frequency noise and focus on interannual to decadal NAO variability. The comparisons show statistically significant positive correlations (99–99.9% confidence) between NAO and outflow velocity - when NAO is positive/negative outflow is generally stronger/weaker. There are however some exceptions, for example during 2018 when NAO was especially high, outflow from CB was also high, but outflows from DB and NB were lower than normal. Such variations are expected since wind can vary significantly with latitude. Two periods of more coherent outflow of the three bays that are consistent with the positive correlation are seen around May 2019 (NAO in a negative phase and all three bays show weak outflow), and January 2020 (NAO in a positive phase and all three bays show larger outflow, especially DB and NB). The wind pattern of these two periods from NCEP/NCAR reanalysis (Fig. 11 ) can explain the change in the observed outflow. In May 2019 (negative NAO) wind pattern shifted southward (Fig. 11 a), so that monthly mean wind speed in the study area was weak (~ 0.5–1.5 m/s), while in January 2020 (positive NAO) stronger westerly winds (~ 3.5 m/s) may have caused the increased outflow seen in the data. The pattern in Fig. 11 is generally consistent with the NAO pattern described above – similar patterns are also seen in other months with significant anomalies. 4 Summary and conclusions This research followed on the footsteps of recent studies of CB that found potential influence from Atlantic Ocean variability on observed sea level in the bay and on surface currents near the mouth of the bay (Ezer 2023a ; Ezer and Updyke 2024 ). Here, we expanded the CB study by analyzing the surface currents obtained by high frequency radars near the mouths of three bays- CB, DB and NB. The goal was to find if statistically significant correlations exist between the flow variabilities of the three bays, and to investigate the sources of these correlations - are they driven by local wind? precipitation? or river runoffs? Are there remote influences on the currents from large-scale Atlantic Ocean variability? or from other sources? The main findings can be summarized as follows. The patterns of surface flow near the mouth of the three bays have similarities in that a strong southeastern flow is seen near the southern side of the mouth. However, the flow in the DB is unique in its strong southwestward flow along most of the entrance to the bay before it turns southeastward. This pattern near the mouth of DB was also found in other studies (see Fig. 9 in Muscarella et al. 2011 ) and is likely driven by the local southwestward winds. Like our study, Muscarella et al ( 2011 ) also used CODAR data, but only for the region outside the DB and for a much shorter time (8 months). Our study found that monthly currents near the mouth of bays generally follow the Ekman theory of wind-driven flow by local wind, but the flow is also affected by several other, local and remote factors. There is a significant, although weak, correlation between the variability of the mean outflow from the three bays, pointing to contribution from common forcing sources. Only 10–15% of the variability can be explained by the common source, pointing to forcing that combines local factors unique for each bay as well as regional factors that affect the entire Mid-Atlantic Bight area. A somewhat surprising result was the linear trend of outflows. Ezer and Updyke ( 2024 ) found significant upward trend in CB during the 2007–2016 period of their analysis that was linked with long-term increased precipitation and river discharges in the region (Rice et al. 2017 ). In this study for the 2012–2024 period there was no significant trend in the CB, while a significant upward trend of about 4 cm/s per decade was found in DB and NB. Decadal and interannual variations might be responsible for the change in trend in the CB. The increased streamflow into the CB before 2018 and decreased streamflow afterward (Fig. 6 b) are due to extreme winter snowstorms in 2018 and 2019 and unusually high river flows during these years. The result is a change in outflow trend from the CB from positive to negative around 2018–2019. The other two bays which are fed by a single river each do not have the shift in outflow as in CB, and thus maintain a positive trend of increased outflow. River discharge flow into each bay is significantly correlated with the outflow of that bay over seasonal and interannual time scales (an expected result). However, only ~ 10% of the monthly outflow variability can be explained by the river discharge alone. Delay response of bays to extreme precipitation and related river discharges were not considered here, but likely result in higher correlations if lags are considered. An interesting finding was that extreme peaks in surface currents that are seen simultaneously in all bays at the same month are often related to extreme weather events. During months in the fall when hurricanes were observed in the western North Atlantic, anomalous large inflows into the bays were recorded, while during winter storms anomalous large outflows were recorded. The impact of hurricanes – i.e., the increased flows toward bays - is consistent with their impact on raising coastal sea level during and after hurricanes (Ezer et al. 2017 ; Ezer 2019 , 2020b ; Park et al. 2022 , 2024 ). The NAO index was found to be significantly correlated with the outflow from the bays, but only about 5–10% of the variability is explained by the NAO. The positive correlation between NAO and outflows suggests that during positive phases of the NAO there is increased outflow from the bays. The wind pattern over the area during positive NAO indeed shows stronger westerly winds (offshore) that is consistent with increased outflow from the bays toward the open ocean. During negative NAO phases the storm track moves southward of the study area, the westerly winds are weaker, and outflows are weaker (i.e., indicating stronger inflow into the bays). This pattern is consistent with studies that show increased sea level and flooding during periods of very negative NAO (Ezer 2015 ; Goddard et al. 2015 ). In summary, the study of surface currents from high-frequency radars shows a complex pattern of velocities near the mouth of three major U.S. East Coast bays. To our knowledge, this is the first study that compares these three bays using this type of data for relatively long period (12 years). The surface currents seem to be driven by multiple sources, local and remote, that include river discharges, tropical storms and hurricanes, winter storms, and changing wind patterns over the Atlantic Ocean associated with large-scale climate variability; each of these drivers contributes a portion of the observed variability, so there is no one dominant factor. While the three bays are separated by some 400 km, have different topographies and sizes, and have input from different watersheds and different rivers, there are similarities in their flow variability that suggest common drivers that may affect a long stretch of the U.S. East Coast and especially the Mid-Atlantic Bight where the bays are situated. The study is important for better understanding coastal dynamics and potential impacts of climate change (including sea level rise) on the highly populated coastal communities and cities along the U.S. East Coast. Declarations The paper is original research that has not been submitted or under consideration for any other publication. Conflict of interest : the authors declare no conflict of interest. Data availability statement : all data are available from the links provided in the paper. Acknowledgments: The research is part of ODU’s Institute for Coastal Adaptation and Resilience (ICAR). The Center for Coastal Physical Oceanography (CCPO) provided office space and computational support. The CODAR maintenance work conducted by T. Updyke was funded by NOAA’s Mid-Atlantic Regional Association Coastal Ocean Observing System (MARACOOS; Award Number: #NA21NOS0120096). Data Availability Statement: The radar surface current data are available from several sources such as https://cordc.ucsd.edu/projects/hfrnet/. Monthly river streamflow data are available from https://waterdata.usgs.gov/nwis/uv/?referred_module=sw. Monthly NAO index data are available from https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml). Wind data are available from NOAA at https://psl.noaa.gov/data/reanalysis/reanalysis.shtml and https://tidesandcurrents.noaa.gov/. References Atkinson LP, Garner T, Blanco J, Paternostro C, Burke P (2009) HFR surface currents observing system in lower Chesapeake Bay and Virginia coast. OCEANS 2009. 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Bay Ocean Dyn 73(1):23–34. https://doi.org/10.1007/s10236-022-01536-6 Ezer T (2023b) Evaluation of the applicability of the Ekman theory for wind-driven ocean currents: a comparison with the Mellor-Yamada turbulent model. Ocean Dyn 73. https://doi.org/10.1007/s10236-023-01570-y Ezer T, Corlett WB (2012) Is sea level rise accelerating in the Chesapeake Bay? A demonstration of a novel new approach for analyzing sea level data. Geophys Res Lett 39(19):L19605. https://doi.org/10.1029/2012GL053435 Ezer T, Atkinson LP (2014) Accelerated flooding along the U.S. East Coast: On the impact of sea-level rise, tides, storms, the Gulf Stream, and the North Atlantic Oscillations. Earths Future 2(8):362–382. https://doi.org/10.1002/2014EF000252 Ezer T, Atkinson LP (2017) On the predictability of high water level along the U.S. East Coast: can the Florida Current measurement be an indicator for flooding caused by remote forcing? Ocean Dyn 67(6):751–766. https://doi.org/10.1007/s10236-017-1057-0 Ezer T, Atkinson LP, Corlett WB, Blanco JL (2013) Gulf Stream's induced sea level rise and variability along the U.S. mid-Atlantic coast. J Geophys Res 118(2):685–697. https://doi.org/10.1002/jgrc.20091 Ezer T, Atkinson LP, Tuleya R (2017) Observations and operational model simulations reveal the impact of Hurricane Matthew (2016) on the Gulf Stream and coastal sea level. Dyn Atmos Oceans 80:124–138. https://doi.org/10.1016/j.dynatmoce.2017.10.006 Ezer T, Henderson-Griswold S, Updyke T (2022) Dynamic observations in the Hampton Roads region: how surface currents at the mouth of Chesapeake Bay may be linked with winds, water level, river discharge and remote forcing from the Gulf Stream. Oceans 2022. IEEE Xplore. https://doi.org/10.1109/OCEANS47191.2022.9977092 Ezer T, Updyke T (2024) On the links between sea level and temperature variations in the Chesapeake Bay and the Atlantic Meridional Overturning Circulation (AMOC). https://doi.org/10.1007/s10236-024-01605-y . Ocean Dyn 74 Galperin B, Mellor GL (1990) A time-dependent, three-dimensional model of the Delaware Bay and River system. Part 2: Three-dimensional flow fields and residual circulation. Est Coast Shelf Sci 31(3):255–281. https://doi.org/10.1016/0272-7714(90)90104-Y Goddard PB, Yin J, Griffies SM, Zhang S (2015) An extreme event of sea-level rise along the Northeast coast of North America in 2009–2010. Nat Commun. https://doi.org/10.1038/ncomms7346 Gopalakrishnan G, Blumberg AF (2012) Assimilation of HF radar-derived surface currents on tidal-timescales. J Oper Oceanogr 5(1):75–87. https://doi.org/10.1080/1755876X.2012.11020133 Hurrell JW (1995) Decadal trends in the North Atlantic oscillation: regional temperatures and precipitation. Science 269:676–679. https://doi.org/10.1126/science.269.5224.676 Karegar MA, Dixon TH, Engelhart SE (2016) Subsidence along the Atlantic Coast of North America: Insights from GPS and late Holocene relative sea level data. Geophys Res Lett 43:3126–3133. https://doi.org/10.1002/2016GL068015 Li Y, Feng H, Zhang H, Sun J, Yuan D, Guo L, Nie J, Du J (2019) Hydrodynamics and water circulation in the New York/New Jersey Harbor: A study from the perspective of water age. J Mar Sys 199. https://doi.org/10.1016/j.jmarsys.2019.103219 Little CM, Hu A, Hughes CW, McCarthy GD, Piecuch CG, Ponte RM, Thomas MD (2019) The Relationship Between U.S. East Coast Sea Level and the Atlantic Meridional Overturning Circulation: A Review. J Geophys Res 124(9):6435–6458. https://doi.org/10.1029/2019JC015152 Moat BI, Smeed DA, Rayner D, Johns WE, Smith R, Volkov D, Baringer MO, Collins J (2023) Atlantic meridional overturning circulation observed by the RAPID-MOCHA-WBTS (RAPID-Meridional Overturning Circulation and Heatflux Array-Western Boundary Time Series) array at 26N from 2004 to 2022 (v2022.1), British Oceanographic Data Centre - Natural Environment Research Council, UK. https://doi.org/10.5285/04c79ece-3186-349a-e063-6c86abc0158c Muscarella PA, Barton NP, Lipphardt BL Jr, Veron DE, Wong KC, Kirwan AD Jr. (2011) Surface currents and winds at the Delaware Bay mouth. Cont Shelf Res 31(12):1282–1293. https://doi.org/10.1016/j.csr.2011.05.003 Park K, Federico I, Di Lorenzo E, Ezer T, Cobb KM, Pinardi N, Coppini G (2022) The contribution of hurricane remote ocean forcing to storm surge along the Southeastern U.S. coast. Coastal Eng 173:104098. https://doi.org/10.1016/j.coastaleng.2022.104098 Park K, Di Lorenzo E, Zhang YJ, Wang H, Ezer T, Ye F (2024) Delayed coastal inundation caused by ocean dynamics post-hurricane Matthew. NPJ Clim Atmos Sci 7:5. https://doi.org/10.1038/s41612-023-00549-2 Piecuch CG, Dangendorf S, Gawarkiewicz GG, Little CM, Ponte RM, Yang J (2019) How is New England coastal sea level related to the Atlantic meridional overturning circulation at 26°N? Geophys Res Lett 46. https://doi.org/10.1029/2019GL083073 Rice KC, Moyer DL, Mills AL (2017) Riverine discharges to Chesapeake Bay: Analysis of long-term (1927–2014) records and implications for future flows in the Chesapeake Bay basin. J Env Mng 204(1):246–254. https://doi.org/10.1016/j.jenvman.2017.08.057 Sharp JH, Cifuentes LA, Coffin RB, Pennock JR, Wong KC (1986) The influence of river variability on the circulation, chemistry, and microbiology of the Delaware Estuary. Estuaries 9:261–269. https://doi.org/10.2307/1352098 Smeed DA, McCarthy GD, Cunningham SA, Frajka-Williams E, Rayner D, Johns WE, Meinen CS, Baringer MO, Moat B, Duchez A, Bryden HL (2014) Observed decline of the Atlantic meridional overturning circulation 2004–2012. Ocean Sci 10:29–38. https://doi.org/10.5194/os-10-29-2014 Sweet W, Park J (2014) From the extreme to the mean: Acceleration and tipping points of coastal inundation from sea level rise. Earths Future 2(12):579–600. https://doi.org/10.1002/2014EF000272 Valle-Levinson A (2010) Definition and classification of estuaries. Contemporary Issues in Estuarine Physics 1–11. Valle-Levinson (Ed), Cambridge Univ. Press, Cambridge, UK. https://doi.org/10.1017/CBO9780511676567.002 Valle-Levinson A, Li C, Royer TC, Atkinson LP (1998) Flow patterns at the Chesapeake Bay entrance. Cont Shelf Res 18(10):1157–1177. https://doi.org/10.1016/S0278-4343(98)00036-3 Valle-Levinson A, Boicourt WC, Roman MR (2003) On the linkages among density, flow, and bathymetry gradients at the entrance to the Chesapeake Bay. Estuaries 26:1437–1449. https://doi.org/10.1007/BF02803652 Volkov DL, Lee S-K, Domingues R, Zhang H, Goes M (2019) Interannual sea level variability along the southeastern seaboard of the United States in relation to the gyre-scale heat divergence in the North Atlantic. Geophys Res Lett. https://doi.org/10.1029/2019GL083596 Volkov D, Zhang K, Johns W, Willis J, Hobbs W, Goes M, Zhang H, Menemenlis D (2023) Atlantic meridional overturning circulation increases flood risk along the United States southeast coast. Nat Comm 14:5095. https://doi.org/10.1038/s41467-023-40848-z Tables Table 1 Summary of correlations between variables (monthly time series, March 2012 to March 2024). U is the zonal surface velocity anomaly (detrended) near the mouth of the 3 bays (CB, DB, NB) and R is the river discharge into each bay. Wind is the near surface U-component from reanalysis (2.5°x2.5° grid point centered near the bays). The comparison with NAO is after a 6-month Hanning Filter. Background colors represent correlations between different variables. All the shown correlations have statistical significance over 95% (P < 0.05). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Dec, 2024 Read the published version in Ocean Dynamics → Version 1 posted Editorial decision: Revision requested 20 Aug, 2024 Reviews received at journal 19 Aug, 2024 Reviewers agreed at journal 05 Aug, 2024 Reviewers invited by journal 02 Aug, 2024 Editor assigned by journal 02 Aug, 2024 Submission checks completed at journal 30 Jul, 2024 First submitted to journal 22 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4783316","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":342678242,"identity":"eca2708e-b998-4182-ab41-224695e06df2","order_by":0,"name":"Tal Ezer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAn0lEQVRIiWNgGAWjYNCCCgbGBiAlQZRiHjB5hmQtjG2kaLFnb3/4uHKejeyGA8wHb/MQZQvPgWTDs9vSjDccYEu2Jk6LRMIxycZthxM3HOAxkyZOi/zD9p+Nc0Ba+L8RqUWCmY2xsQFsCxuRWs6kMUs2HEsznnmYzdhyDjFa2NuPP/zYUGMj23e8+eGNN8RoQQBm0pSPglEwCkbBKMAHAPwsMA4Gft+BAAAAAElFTkSuQmCC","orcid":"","institution":"Old Dominion University","correspondingAuthor":true,"prefix":"","firstName":"Tal","middleName":"","lastName":"Ezer","suffix":""},{"id":342678243,"identity":"7ef8e85e-7066-428b-8ad7-3716a401d21b","order_by":1,"name":"Teresa Updyke","email":"","orcid":"","institution":"Old Dominion University","correspondingAuthor":false,"prefix":"","firstName":"Teresa","middleName":"","lastName":"Updyke","suffix":""}],"badges":[],"createdAt":"2024-07-22 16:32:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4783316/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4783316/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10236-024-01656-1","type":"published","date":"2024-12-26T15:57:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63353845,"identity":"d5e85bd5-2e2b-4f01-a938-fac24350b3d8","added_by":"auto","created_at":"2024-08-27 08:52:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":496268,"visible":true,"origin":"","legend":"\u003cp\u003eA map of the study area and the CODAR 2km data for the three locations: Chesapeake Bay (CB), Delaware Bay (DB) and New York Bay (NB).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/405997bf838016eca79343ff.png"},{"id":63354420,"identity":"6dacff47-7169-45f1-ae1b-0b87f2d5c4aa","added_by":"auto","created_at":"2024-08-27 09:00:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":399760,"visible":true,"origin":"","legend":"\u003cp\u003eMean surface currents (m/s) over the period March 2012-March 2024 near the mouth of the three bays.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/3814e8683396b1e6e7c28257.png"},{"id":63353853,"identity":"469852a1-d9f5-4c54-91d4-da92181587ae","added_by":"auto","created_at":"2024-08-27 08:52:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":311969,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly zonal surface velocity (U-component) averaged over each region of Fig. 2. The mean, standard deviation, and trend (in m/s per year) are indicated, as well as the linear trend line.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/353143f68cdc0ce8c0eb3256.png"},{"id":63353847,"identity":"2dbd262e-f182-4440-8f5a-f651e825a5a4","added_by":"auto","created_at":"2024-08-27 08:52:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":268080,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots and correlations between the detrended flows of the three bays. Statistical significance of the correlations range between 99% (DB vs. CB; Fig.4c) and 99.999% (DB vs. NB).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/a6803dc065526008e89d5c57.png"},{"id":63354417,"identity":"ba7b5948-791e-4b04-b06e-afc0084e4fcb","added_by":"auto","created_at":"2024-08-27 09:00:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":208691,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly time series of the anomaly flow (detrended) in CB (red line), DB (green line) and NB (blue line). Several peaks where similar anomaly is seen in multiple locations are indicated. Negative peaks (larger than normal inflow into the bay) associated with offshore hurricanes are seen in the fall (September-October; see inset boxes), while positive peaks (larger than normal outflow from the bay) associated with winter storms are seen recently in January.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/d7d3a9d88eec6360e68f050e.png"},{"id":63353849,"identity":"d973e071-2ff3-4ca7-86c2-abfa3c688364","added_by":"auto","created_at":"2024-08-27 08:52:02","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":317756,"visible":true,"origin":"","legend":"\u003cp\u003eTransport of rivers and streams into the bays: sum of streamflow into CB (red line; value divided by 4), Delaware River discharge into DB (green line) and Hudson River discharge into NB (blue line). \u003cstrong\u003ea\u003c/strong\u003e Monthly data. \u003cstrong\u003eb\u003c/strong\u003e After applying a 24-month Hanning Filter.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/e2b928aceb46b7b2782470f8.png"},{"id":63353846,"identity":"88030f58-5e75-41c0-b8a2-ee77e4eedd95","added_by":"auto","created_at":"2024-08-27 08:52:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":235002,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly mean seasonal cycle of \u003cstrong\u003ea\u003c/strong\u003e river discharges and \u003cstrong\u003eb\u003c/strong\u003e surface velocity in the three bays.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/ab104773ab55d8f19102a5a1.png"},{"id":63354419,"identity":"7e2e58a4-9f8f-46fd-b581-b43a81027bf6","added_by":"auto","created_at":"2024-08-27 09:00:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":509935,"visible":true,"origin":"","legend":"\u003cp\u003eTime series comparing outflow velocity (blue; left axis) and inflow from rivers (red; right axis). Left panels are for the original monthly data (Fig. 5 and Fig. 6) and right panels are after the seasonal cycle (Fig. 7) was removed; panels from top to bottom are for NB, DB and CB, respectively. Correlations and P-values are also shown (statistical significance of all cases is \u0026gt;95%).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/69b9eec3fff66222d56991cc.png"},{"id":63354421,"identity":"670b030f-c757-4ad5-b89e-7b4ad50454fa","added_by":"auto","created_at":"2024-08-27 09:00:03","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":193959,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly U-component of mean wind over the region from reanalysis data (heavy black line; y-axis on the right) versus the current velocity at the three bays (color lines; y-axis on the left). The correlations for the three bays are indicated.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/7a4fbc52d3f6e9a86d8a0bdd.png"},{"id":63353854,"identity":"82bb6975-7620-4711-86e8-f0582c744839","added_by":"auto","created_at":"2024-08-27 08:52:02","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":194660,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly NAO index (black; heavy line, right axis) versus velocity anomaly in CB (red), DB (green) and NB (blue). High-frequency variability was smoothed with a 6-month Hanning Filter. Correlation coefficients are also listed.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/35d9269050d5f13671cff63c.png"},{"id":63353856,"identity":"e92d5745-a3e5-48a2-83ae-4ebf7421e0f3","added_by":"auto","created_at":"2024-08-27 08:52:02","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":241765,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly mean wind pattern from NCEP/NCAR Reanalysis (speed in color and direction in vectors) during \u003cstrong\u003ea\u003c/strong\u003e May 2019 when NAO was in a negative phase (monthly index of -2.62) and \u003cstrong\u003eb\u003c/strong\u003e January 2020 when NAO was in a positive phase (monthly index of +1.34). The study area is indicated.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/ec59dfdf4466c774ebfe9d37.png"},{"id":72640830,"identity":"427a285b-3813-4fe8-a6d0-c4bbbd9f3efc","added_by":"auto","created_at":"2024-12-30 16:10:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3750635,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4783316/v1/2d7bbe60-d1d8-47d3-b52a-6c5fa6373e43.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High-frequency radar surface current data reveals local and remote drivers of three bays: Chesapeake Bay, Delaware Bay, and New York Bay","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe motivation for this study comes from results of recent studies of seasonal, interannual and decadal variations in sea level, temperature, and surface currents in the Chesapeake Bay (CB, Ezer \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e; Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These studies suggest potential links between variations in this bay, which is the largest estuary of the U.S., and large-scale variations in the Atlantic Ocean characterized for example by the North Atlantic Oscillations (NAO; Hurrell \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) and the Atlantic Meridional Overturning Circulation (AMOC, Smeed et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Moat et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Previous studies of CB also suggested that sea level acceleration in the bay is linked to slowdown of AMOC and the Gulf Stream (Ezer and Corlett \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ezer et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The CB and most of the U.S. East coast are subject to fast sea level rise and increased risk of flooding, including variations in sea level on a wide range of time scales (Ezer and Corlett \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ezer and Atkinson \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sweet and Park \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Karegar et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Valle-Levinson et al. 2017; Boesch et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Domingues et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ezer et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ezer \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). Therefore, numerous studies focused on the potential links between offshore variations in the Atlantic Ocean and coastal sea level along the U.S. Gulf Coast and East Coast (Ezer et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ezer and Atkinson \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ezer \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, 2023; Goddard et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Little et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Piecuch et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Volkov et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Dangendorf et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, not much research was done on the impact of remote Atlantic forcing on the circulation pattern in bays and estuaries.\u003c/p\u003e \u003cp\u003eIf remote forcing is affecting variations in sea level in bays, then these variations should also affect the flow pattern and transport exchange between bays and the open ocean. High-frequency radar data of surface currents near the mouth of the CB indeed suggested some links with the Atlantic Ocean variability (Ezer et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In recent years Coastal Ocean Dynamics Application Radar (CODAR) high frequency radar (HFR) stations have been installed along long stretches of the U.S. East Coast, providing surface current data near the CB (Atkinson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Ezer et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the Delaware Bay (DB; Muscarella et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and the New York Bay (Gopalakrishnan and Blumberg \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; note that NB sometimes is referred to as the lower bay of New York Harbor). The existence of these new observations led us to expand the previous study (Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) from the CB to the DB and NB. Classic estuarine circulation is well described in the literature as driven by freshwater river discharge at one end and saltwater intrusion and tidal mixing at the other open end, though circulation can be quite complex and vary from bay to bay due to topography, stratification, and other factors (Valle-Levinson et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1998\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Valle-Levinson \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Also, not many studies address long-term variabilities in bays beyond the tidal and seasonal time scales. By comparing three different bays, separated by ~\u0026thinsp;400 km, having different topographies and different river inputs, we try to evaluate what part of the dynamics is locally driven versus potential common forcing from large-scale climate patterns. The study may have important implications for coastal ocean prediction, since remote forcing from the open ocean on the coast is not well understood or predicted.\u003c/p\u003e \u003cp\u003eThe study is organized as follows. First, the data sources and analysis methods are described in section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, then results are presented in section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, focusing on correlations between the bays, river discharges, and Atlantic Ocean variability. Finally, summery and conclusions are offered in section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e"},{"header":"2 Data sources and analysis methods","content":"\u003cp\u003eMonthly surface currents were obtained from HFR data archived at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cordc.ucsd.edu/projects/hfrnet/\u003c/span\u003e\u003cspan address=\"https://cordc.ucsd.edu/projects/hfrnet/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; data on 2km grid from March 2012 to March 2024 were extracted for the U.S. East Coast from the Scripps Institution of Oceanography National HFR Network data catalog (HFRNet; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hfrnet-tds.ucsd.edu/thredds/catalog.html\u003c/span\u003e\u003cspan address=\"https://hfrnet-tds.ucsd.edu/thredds/catalog.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The data were further extracted for three subregions near the mouth of the three bays of this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The data represent flow in the upper meter of the water column. To evaluate flow exchange between each bay and the Atlantic Ocean, most of the study involves analysis of zonal flow (U-components of surface currents), where positive values represent outflow from the bay toward the Atlantic Ocean. It is noted that the previous study that focused only on the CB (Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) used our locally maintained HFR observations (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ccpo.odu.edu/currentmapping/\u003c/span\u003e\u003cspan address=\"http://www.ccpo.odu.edu/currentmapping/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; see also Atkinson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e and Ezer et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) with slightly different quality control, a different period (2007\u0026ndash;2021) and a focus on flow toward the southeast. However, comparison (not shown) between the local institutional data and the public (HFRNet) data used here shows that the two data sets are generally consistent with each other, and differences in trends are due to the period used (more on this later).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMonthly river streamflow into the CB, which includes several rivers and streams, was obtained from USGS (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.usgs.gov/media/images/estimated-monthly-mean-streamflow-entering-chesapeake-bay\u003c/span\u003e\u003cspan address=\"https://www.usgs.gov/media/images/estimated-monthly-mean-streamflow-entering-chesapeake-bay\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For freshwater input to the DB, we used the transport of the Delaware River (near Trenton, NJ), and for the NB we used the transport of the Hudson River (extracted from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://waterdata.usgs.gov/nwis/uv/?referred_module=sw\u003c/span\u003e\u003cspan address=\"https://waterdata.usgs.gov/nwis/uv/?referred_module=sw\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Variations in the Delaware River flow dominate the circulation and water properties of the DB (Sharp et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), and the Hudson River provides most of the discharge water into NB (Li et al \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), so that unlike the CB, a single river discharge is sufficient for these two bays. The units were converted from ft\u003csup\u003e3\u003c/sup\u003es\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as reported by USGS to m\u003csup\u003e3\u003c/sup\u003es\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Also, because the flow into the CB is much larger than that of the other two bays, in some analysis, streamflow into the CB was divided by a factor of 4 to allow plotting on the same axis.\u003c/p\u003e \u003cp\u003eMonthly North Atlantic Oscillation (NAO; Hurrel 1995) Index was obtained from NOAA\u0026rsquo;s Climate Prediction Center (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml\u003c/span\u003e\u003cspan address=\"https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). NAO is related to wind patterns over the Atlantic Ocean that may affect currents along the U.S. East Coast, so wind pattern data from NCEP/NCAR Reanalysis were obtained from NOAA\u0026rsquo;s Physical Science Laboratory (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://psl.noaa.gov/data/reanalysis/reanalysis.shtml\u003c/span\u003e\u003cspan address=\"https://psl.noaa.gov/data/reanalysis/reanalysis.shtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Local wind data were obtained from NOAA stations (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tidesandcurrents.noaa.gov/\u003c/span\u003e\u003cspan address=\"https://tidesandcurrents.noaa.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); monthly means were calculated from 6-minute data.\u003c/p\u003e \u003cp\u003eStatistical analyses of these data include correlations between time series of the same type of data, e.g., transport in river#1 versus river#2, as well as correlations across different sources, e.g., transport of river#1 versus flow in bay#1. Linear trends of each time series were also calculated, but one should keep in mind that 12-year records are too short for assessing long-term climatic trends and decadal variability. As shown later, large anomaly in one or two years can significantly change the trend during this relatively short period.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Surface currents in the three bays: pattern, trend, and correlation\u003c/h2\u003e \u003cp\u003eThe mean surface current pattern over the study period (March 2012 to March 2024) shows some similarity and some differences between the three bays (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In all three bays, the strongest outflow is seen in the southern side of the mouth of the bay, but the DB has a distinctly different pattern than the other two bays with a strong southwestward flow in the lower bay. Previous studies of these bays used past observations and models (though none as recent as here, until March 2024), and often focused on tides and short time scales of days to months (e.g., Galperin and Mellor \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Blumberg et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Muscarella et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The general pattern seen here is quite like that of previous studies with models and observations (e.g., see Atkinson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Ezer et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e and Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e for CB, Galperin and Mellor \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1990\u003c/span\u003e and Muscarella et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e for DB, Blumberg et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1999\u003c/span\u003e, Gopalakrishnan and Blumberg \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e and Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e for NB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSince the interest here is the exchange of water between the bay and the Atlantic Ocean, and each bay has slightly different flow pattern near its mouth, we analyzed the zonal component (U-velocity; referred to here as \u0026ldquo;outflow\u0026rdquo;) averaged over the regions in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Note that Ezer and Updyke (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) rotated the vectors toward the southeast, but trends and variability seem very similar to the U-velocity since the flow direction near the mouth of CB changes very little in this region (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). The chosen area extends beyond the mouth of the bay because there is too much missing data in the mouth itself. The monthly time series of outflow are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The upward trend of increased outflow from NB and DB of about 4 cm/s per decade (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb) is consistent with the increased precipitation and river discharge in the northeastern U.S. (Rice et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, the insignificant trend in the CB outflow of -0.7 cm/s per decade (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec) in 2012\u0026ndash;2024 seems to contradict the recent results of Ezer and Updyke (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) who found in CB increased outflow of 2.2 cm/s per decade in 2007\u0026ndash;2021. The data set in the previous study was somewhat different in the period, the area, and the data sources. In the Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e study, in-house data was used instead of the public data used now. Further analysis of the in-house U-velocity data found that the different period used was the main source of the discrepancy; there was a large increase in outflow from CB of 3.3 cm/s per decade from 2006 to 2016, but this trend reduced by a factor of 10 to insignificant 0.3 cm/s per decade from 2016 to 2021 and further reduced from 2021 to 2024 as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec. Therefore, we conclude that the two data sets are consistent with each other, and changes of trends over time are responsible for the differences. This trend shift will be explained later when river discharge is analyzed. Moreover, decadal variability such as those associated with the North Atlantic Oscillation (NAO; Hurrel 1995) and the Atlantic Meridional Overturning Circulation (AMOC; Moat et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) can affect the bays, as suggested by Ezer and Updyke (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), but longer observations than the 12-year data used here, are likely needed to capture these decadal variations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo assess if there is a large-scale common driver for the three bays, correlations between the outflow of the bays are calculated after removing the trends (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results indeed show statistically significant correlations (Table\u0026nbsp;1), whereas the highest correlation is found between the two northernmost bays, DB and NB (99.999% confidence level), and the lowest correlation (99% confidence level) was found between the two southernmost bays, CB and DB. The multiple rivers and the large watershed of the CB probably makes its variability more complex than if driven by a single major river like DB and NB. While having statistically significant correlation demonstrates relations, it does not indicate the cause of the relation. It is also noted that only about 15% of the variability is explained by this common driver, in fact, there are probably several different drivers of variability in the bays as discussed later. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the monthly outflow anomaly (detrended time series) of the three bays, indicating several unusual peaks where all the bays have similar anomalies. Negative anomalies that indicate increased inflow into the bay were identified at periods when hurricanes were observed offshore the U.S. East Coast. Studies of these hurricanes show increased coastal sea level, due to storm surge and weakening of the Gulf Stream by the storms (sometimes for weeks after the storm). Therefore, when storms move along the U.S. East Coast, they cause additional transport of water toward the shore and into the bays, and this is consistent with the increased flow toward the bays as seen in the negative peaks in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. More information on the hurricanes indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e can be found in recent studies of Hurricane Joaquin in 2015 (Ezer and Atkinson \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Hurricane Matthew in 2016 (Ezer et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), Hurricane Florence in 2018 (Ezer \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Hurricane Dorian in 2019 (Ezer \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). Note that tropical storms and hurricanes occur mostly during the fall, when the seasonal sea level is higher with the so-called \u0026ldquo;King Tide\u0026rdquo; (Ezer \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). On the other hand, positive peaks in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, which represent larger than normal outflow from the bays, occur recently (since 2018) mostly in the winter around January. These anomalies may be related to the increase in extreme snow events over the U.S. due to global warming (Chen et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Close examination of the period of these peaks found that they are indeed associated with winter storms that passed over the northeastern U.S. For example, the largest peak in outflow in the DB occurred in January 2019, during the \u0026ldquo;Harper\u0026rdquo; winter snow storm event in middle January 2019 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.weather.gov/pah/SnowJan19_2019\u003c/span\u003e\u003cspan address=\"https://www.weather.gov/pah/SnowJan19_2019\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). During this period a weak jet stream and an extreme cold wave (called a \u0026ldquo;Polar Vortex\u0026rdquo; by the media) were seen. Winter storms named \u0026ldquo;Jacob\u0026rdquo; and \u0026ldquo;Isaiah\u0026rdquo; in January 2020 coincide with peak outflow in all three bays seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Another big winter storm occurred in January 2022 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.weather.gov/akq/Jan22-2022Snow\u003c/span\u003e\u003cspan address=\"https://www.weather.gov/akq/Jan22-2022Snow\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which again coincides with peak outflows. Storms occur over short time scales of days, and have much larger impact on daily radar data, but they seem to have enough impact to influence the monthly data analyzed here.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparison of surface currents with river discharge\u003c/h2\u003e \u003cp\u003eClassical estuarine circulation is usually described as driven by freshwater discharge from rivers at one end and tides from the open ocean on the other end (Valle-Levinson \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), so when analyzing monthly data, which removes the daily tides, river discharge should have strong influence on the seasonal and interannual variability of outflow from bays. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea shows the monthly river inflows into the bays; these river discharges are highly correlated with each other (R\u0026thinsp;=\u0026thinsp;0.64\u0026ndash;0.85; Table\u0026nbsp;1). While seasonal variations are dominating the variability, large interannual variations are also seen. Especially large discharge is seen around January 2019, during the winter snowstorm and the extreme cold wave of the northeastern U.S. as discussed before in section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e. The river flow after applying a 24-month Hanning Filter (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb) indicates unusually large stream flow into the CB during 2018\u0026ndash;2019 (and to lesser degree in DB). This anomaly in river flows into the CB, results in a change in outflow trend from positive before 2018 to negative after 2019 and explains the apparent discrepancy between the result shown here of a negligible outflow trend for 2012\u0026ndash;2024, and the results of Ezer and Updyke (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) of upward trend in earlier years. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows the seasonal cycle (monthly mean) of rivers and currents. Maximum spring river flow occurs around April (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea) while maximum bay outflow occurs a month later around May (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Another peak of outflow is seen in the fall around November, when the seasonal sea level also peaks (Ezer \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e), and when river flow starts to increase from the late summer minimum. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows comparisons between outflow velocities and river discharges in the bays; the calculations were done with and without the seasonal cycle, and correlations are all statistically significant at over 95% confidence level (Table\u0026nbsp;1). The seasonal cycle contributes to the correlations, especially in NB and DB; when the seasonal cycle is removed, correlations are lower there. This is different in CB (lower panels of Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) with higher correlation (R\u0026thinsp;=\u0026thinsp;0.28 at 99.9% confidence level) without the seasonal cycle. The latter result is due to the large signal in this region during the winter storms of 2019 and 2021 (which is also evident in DB; middle panels of Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). While the CB river discharge includes the combinations of several rivers, additional calculations (not shown) of correlation with individual river discharges show very similar correlations as the combined discharge, which indicates that all those rivers are affected by the same weather pattern and storms passing the region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Comparison of currents with winds and NAO\u003c/h2\u003e \u003cp\u003eAs demonstrated in the previous section, outflows from the bays are correlated with river discharges, as expected, but the correlations indicate that river discharge is only responsible for some 10% or less of the monthly outflow variability (somewhat larger percentage is found if lag is considered). Other potential sources of variability include local winds and large-scale atmospheric and oceanic variations over the Atlantic Ocean. Upper ocean currents are generally assumed to be driven by surface winds, i.e., the so-called Ekman Transport (e.g., see recent evaluation of the Ekman Theory by Ezer, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Short-term observations by Muscarella et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) show for example that surface currents near the mouth of DB were mostly driven by local wind, however, it is not clear if this is also the case for long-term monthly observations. When comparing local NOAA wind stations (monthly values calculated from 6-minute data) with surface currents, results (not shown) found maximum correlation when the angle between the wind and currents is ~\u0026thinsp;20\u0026ndash;40 degrees (Ekman theory implies that pure wind-driven surface current in non-stratified ocean is expected to be directed 45 degrees to the right of the wind in the northern hemisphere). The maximum correlations between local wind and nearby currents at the three bays are around R\u0026thinsp;=\u0026thinsp;0.74. These results are in general agreement with the Ekman theory of local wind-driven currents. However, what about large-scale wind pattern influence? Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e compares the currents in the three bays with the mean zonal wind (U-component) obtained from reanalysis over the entire region (the V-component of the wind is insignificant in the reanalysis over this region). While the correlations are a little lower than correlation with local winds, they are still significant at over 99.99% confidence (R\u0026thinsp;=\u0026thinsp;0.25, 0.55 and 0.61, for CB, DB and NB, respectively; Table\u0026nbsp;1). One should keep in mind though that the coarse resolution (~\u0026thinsp;2.5 degree) reanalysis represents the large-scale wind patterns over the Atlantic Ocean.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePast studies focused on remote influence of the Atlantic Ocean and the Gulf Stream on coastal sea level (Ezer et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ezer \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e; Dangendorf et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), but little research is done on remote influence on currents near bays \u0026ndash; one exception is the study of Ezer and Updyke (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) that shows potential links between surface currents in the CB and the Atlantic Meridional Overturning Circulation (AMOC). The large-scale atmospheric pattern over the North Atlantic can be characterized by the North Atlantic Oscillation (NAO) index (Hurrell \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), whereas positive phase indicates storm track farther north and more wet and stormy weather over the northeastern U.S., while negative phase indicates southern shift in the storm track, dryer weather and fewer storms over the same region. To evaluate the impact of NAO, it is compared with the outflow velocity of the three bays (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e and Table\u0026nbsp;1). The monthly records were filtered by a 6-month Hanning Filter to remove high-frequency noise and focus on interannual to decadal NAO variability. The comparisons show statistically significant positive correlations (99\u0026ndash;99.9% confidence) between NAO and outflow velocity - when NAO is positive/negative outflow is generally stronger/weaker. There are however some exceptions, for example during 2018 when NAO was especially high, outflow from CB was also high, but outflows from DB and NB were lower than normal. Such variations are expected since wind can vary significantly with latitude. Two periods of more coherent outflow of the three bays that are consistent with the positive correlation are seen around May 2019 (NAO in a negative phase and all three bays show weak outflow), and January 2020 (NAO in a positive phase and all three bays show larger outflow, especially DB and NB). The wind pattern of these two periods from NCEP/NCAR reanalysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) can explain the change in the observed outflow. In May 2019 (negative NAO) wind pattern shifted southward (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ea), so that monthly mean wind speed in the study area was weak (~\u0026thinsp;0.5\u0026ndash;1.5 m/s), while in January 2020 (positive NAO) stronger westerly winds (~\u0026thinsp;3.5 m/s) may have caused the increased outflow seen in the data. The pattern in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e is generally consistent with the NAO pattern described above \u0026ndash; similar patterns are also seen in other months with significant anomalies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Summary and conclusions","content":"\u003cp\u003eThis research followed on the footsteps of recent studies of CB that found potential influence from Atlantic Ocean variability on observed sea level in the bay and on surface currents near the mouth of the bay (Ezer \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e; Ezer and Updyke \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Here, we expanded the CB study by analyzing the surface currents obtained by high frequency radars near the mouths of three bays- CB, DB and NB. The goal was to find if statistically significant correlations exist between the flow variabilities of the three bays, and to investigate the sources of these correlations - are they driven by local wind? precipitation? or river runoffs? Are there remote influences on the currents from large-scale Atlantic Ocean variability? or from other sources?\u003c/p\u003e \u003cp\u003eThe main findings can be summarized as follows.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe patterns of surface flow near the mouth of the three bays have similarities in that a strong southeastern flow is seen near the southern side of the mouth. However, the flow in the DB is unique in its strong southwestward flow along most of the entrance to the bay before it turns southeastward. This pattern near the mouth of DB was also found in other studies (see Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e in Muscarella et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and is likely driven by the local southwestward winds. Like our study, Muscarella et al (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) also used CODAR data, but only for the region outside the DB and for a much shorter time (8 months). Our study found that monthly currents near the mouth of bays generally follow the Ekman theory of wind-driven flow by local wind, but the flow is also affected by several other, local and remote factors.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is a significant, although weak, correlation between the variability of the mean outflow from the three bays, pointing to contribution from common forcing sources. Only 10\u0026ndash;15% of the variability can be explained by the common source, pointing to forcing that combines local factors unique for each bay as well as regional factors that affect the entire Mid-Atlantic Bight area.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eA somewhat surprising result was the linear trend of outflows. Ezer and Updyke (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found significant upward trend in CB during the 2007\u0026ndash;2016 period of their analysis that was linked with long-term increased precipitation and river discharges in the region (Rice et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this study for the 2012\u0026ndash;2024 period there was no significant trend in the CB, while a significant upward trend of about 4 cm/s per decade was found in DB and NB. Decadal and interannual variations might be responsible for the change in trend in the CB. The increased streamflow into the CB before 2018 and decreased streamflow afterward (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb) are due to extreme winter snowstorms in 2018 and 2019 and unusually high river flows during these years. The result is a change in outflow trend from the CB from positive to negative around 2018\u0026ndash;2019. The other two bays which are fed by a single river each do not have the shift in outflow as in CB, and thus maintain a positive trend of increased outflow.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRiver discharge flow into each bay is significantly correlated with the outflow of that bay over seasonal and interannual time scales (an expected result). However, only\u0026thinsp;~\u0026thinsp;10% of the monthly outflow variability can be explained by the river discharge alone. Delay response of bays to extreme precipitation and related river discharges were not considered here, but likely result in higher correlations if lags are considered.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAn interesting finding was that extreme peaks in surface currents that are seen simultaneously in all bays at the same month are often related to extreme weather events. During months in the fall when hurricanes were observed in the western North Atlantic, anomalous large inflows into the bays were recorded, while during winter storms anomalous large outflows were recorded. The impact of hurricanes \u0026ndash; i.e., the increased flows toward bays - is consistent with their impact on raising coastal sea level during and after hurricanes (Ezer et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ezer \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe NAO index was found to be significantly correlated with the outflow from the bays, but only about 5\u0026ndash;10% of the variability is explained by the NAO. The positive correlation between NAO and outflows suggests that during positive phases of the NAO there is increased outflow from the bays. The wind pattern over the area during positive NAO indeed shows stronger westerly winds (offshore) that is consistent with increased outflow from the bays toward the open ocean. During negative NAO phases the storm track moves southward of the study area, the westerly winds are weaker, and outflows are weaker (i.e., indicating stronger inflow into the bays). This pattern is consistent with studies that show increased sea level and flooding during periods of very negative NAO (Ezer \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Goddard et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eIn summary, the study of surface currents from high-frequency radars shows a complex pattern of velocities near the mouth of three major U.S. East Coast bays. To our knowledge, this is the first study that compares these three bays using this type of data for relatively long period (12 years). The surface currents seem to be driven by multiple sources, local and remote, that include river discharges, tropical storms and hurricanes, winter storms, and changing wind patterns over the Atlantic Ocean associated with large-scale climate variability; each of these drivers contributes a portion of the observed variability, so there is no one dominant factor. While the three bays are separated by some 400 km, have different topographies and sizes, and have input from different watersheds and different rivers, there are similarities in their flow variability that suggest common drivers that may affect a long stretch of the U.S. East Coast and especially the Mid-Atlantic Bight where the bays are situated. The study is important for better understanding coastal dynamics and potential impacts of climate change (including sea level rise) on the highly populated coastal communities and cities along the U.S. East Coast.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n\u003cli\u003eThe paper is original research that has not been submitted or under consideration for any other publication.\u003c/li\u003e\n\u003cli\u003e\u003cu\u003eConflict of interest\u003c/u\u003e: the authors declare no conflict of interest.\u003c/li\u003e\n\u003cli\u003e\u003cu\u003eData availability statement\u003c/u\u003e: all data are available from the links provided in the paper.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The research is part of ODU\u0026rsquo;s Institute for Coastal Adaptation and Resilience (ICAR). The Center for Coastal Physical Oceanography (CCPO) provided office space and computational support. The CODAR maintenance work conducted by T. Updyke was funded by NOAA\u0026rsquo;s Mid-Atlantic Regional Association Coastal Ocean Observing System (MARACOOS; Award Number: #NA21NOS0120096).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The radar surface current data are available from several sources such as https://cordc.ucsd.edu/projects/hfrnet/. Monthly river streamflow data are available from https://waterdata.usgs.gov/nwis/uv/?referred_module=sw. Monthly NAO index data are available from https://www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/nao.shtml). Wind data are available from NOAA at https://psl.noaa.gov/data/reanalysis/reanalysis.shtml and https://tidesandcurrents.noaa.gov/.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAtkinson LP, Garner T, Blanco J, Paternostro C, Burke P (2009) HFR surface currents observing system in lower Chesapeake Bay and Virginia coast. OCEANS 2009. 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Nat Comm 14:5095. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41467-023-40848-z\u003c/span\u003e\u003cspan address=\"10.1038/s41467-023-40848-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e Summary of correlations between variables (monthly time series, March 2012 to March 2024). U is the zonal surface velocity anomaly (detrended) near the mouth of the 3 bays (CB, DB, NB) and R is the river discharge into each bay. Wind is the near surface U-component from reanalysis (2.5°x2.5° grid point centered near the bays). The comparison with NAO is after a 6-month Hanning Filter. Background colors represent correlations between different variables. All the shown correlations have statistical significance over 95% (P \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"672\" 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\" alt=\"image\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"ocean-dynamics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"odyn","sideBox":"Learn more about [Ocean Dynamics](https://link.springer.com/journal/10236)","snPcode":"10236","submissionUrl":"https://submission.springernature.com/new-submission/10236/3","title":"Ocean Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"CODAR, Estuarine Circulation, Chesapeake Bay, Delaware Bay, New York Bay","lastPublishedDoi":"10.21203/rs.3.rs-4783316/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4783316/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA recent study of currents, sea level and temperatures in the Chesapeake Bay found interannual to decadal variability and a significant trend in outflow from the bay toward the Atlantic Ocean, suggesting influence on the dynamics of the bay from both- local river discharges as well as large scale climate variability. This study expands the previous findings in one bay into three major U.S. East Coast bays: the Chesapeake Bay (CB), the Delaware Bay (DB) and the New York Bay (NB). Monthly surface currents at 2 km resolution near the mouths of these bays were obtained from high-frequency radars (Coastal Ocean Dynamics Application Radar, CODAR) during 2012\u0026ndash;2024. The contribution to flow variability from local and remote forcing is evaluated by comparing surface currents with (a) river discharges into each bay, (b) with winds, and (c) with the North Atlantic Oscillation (NAO). The results show that flow variability in the bays is significantly correlated with all three driving factors. The three bays often show similar flow patterns not only of the seasonal cycle, but also during extreme weather events. For example, increased inflow into the bays from the Atlantic Ocean is seen when hurricanes are observed offshore in the fall, and increased outflow from the bays is seen during winter storms. During positive NAO phases, outflow from all three bays increased due to intensified westerly winds, while during negative NAO phases outflow decreased with weakening winds in the region. Increased river discharges over the record length resulted in increased outflows from DB and NB of about 4 cm/s per decade. However, in CB extremely large river discharges into the bay in 2018\u0026ndash;2019 resulted in a change in the outflow from a significant upward trend before 2018 to a significant downward trend after 2019. The results demonstrate the complex nature of the outflow from bays since multiple drivers contribute to the observed variability.\u003c/p\u003e","manuscriptTitle":"High-frequency radar surface current data reveals local and remote drivers of three bays: Chesapeake Bay, Delaware Bay, and New York Bay","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-27 08:51:57","doi":"10.21203/rs.3.rs-4783316/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-20T12:46:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T19:44:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135740753883584316287179392399190584183","date":"2024-08-05T14:57:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-02T21:30:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-02T08:08:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-30T11:24:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Ocean Dynamics","date":"2024-07-22T16:30:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"ocean-dynamics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"odyn","sideBox":"Learn more about [Ocean Dynamics](https://link.springer.com/journal/10236)","snPcode":"10236","submissionUrl":"https://submission.springernature.com/new-submission/10236/3","title":"Ocean Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e6a41c17-1da6-413f-ac9d-b6ace54495ed","owner":[],"postedDate":"August 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-30T16:04:57+00:00","versionOfRecord":{"articleIdentity":"rs-4783316","link":"https://doi.org/10.1007/s10236-024-01656-1","journal":{"identity":"ocean-dynamics","isVorOnly":false,"title":"Ocean Dynamics"},"publishedOn":"2024-12-26 15:57:28","publishedOnDateReadable":"December 26th, 2024"},"versionCreatedAt":"2024-08-27 08:51:57","video":"","vorDoi":"10.1007/s10236-024-01656-1","vorDoiUrl":"https://doi.org/10.1007/s10236-024-01656-1","workflowStages":[]},"version":"v1","identity":"rs-4783316","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4783316","identity":"rs-4783316","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}