Impact of water mass dynamical and property variability on the inflow of a semi-enclosed sea

Beutel, Becca; Allen, Susan E.; Xiong, Jilian; Maldonado, Maite

doi:https://doi.org/10.5194/egusphere-2025-3179

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https://doi.org/10.5194/egusphere-2025-3179

Preprints

07 Aug 2025

| 07 Aug 2025

Impact of water mass dynamical and property variability on the inflow of a semi-enclosed sea

Becca Beutel, Susan E. Allen, Jilian Xiong, and Maite Maldonado

Abstract. The biogeochemistry of the Salish Sea is strongly connected to its Pacific Ocean inflow through Juan de Fuca Strait (JdF), which varies seasonally and interannually in both volume and property flux. Long-term trends in warming, acidification, and deoxygenation are a concern in the region, and inflow variability influences the flux of tracers potentially contributing to these threats in the Salish Sea. Using ten years (2014–2023, inclusive) of Lagrangian particle tracking from JdF, we quantified the contributions of distinct Pacific water masses to interannual variability in JdF inflow and its biogeochemical properties. We decompose variability in salinity, temperature, dissolved oxygen, nitrate, and carbonate system tracers into components arising from changes in water mass transport (dynamical variability) and changes in source properties (property variability). Observations in the region provide insight into water mass processes not resolved by the model, including denitrification and trace metal supply. Deep water masses dominate total inflow volume and drive variability in nitrate flux through changes in transport. Shallow water masses, particularly south shelf water, exhibit greater interannual variability and disproportionately affect temperature, oxygen, and [TA–DIC], driving change through both dynamical and property variability. This study highlights the combined roles of circulation and source water properties in shaping biogeochemical variability in a semi-enclosed sea, and how these roles differ between biogeochemical tracers. It provides a framework for attributing flux changes to specific source waters and physical and biogeochemical drivers, with implications for forecasting coastal ocean change under future climate scenarios.

Received: 03 Jul 2025 – Discussion started: 07 Aug 2025

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Becca Beutel, Susan E. Allen, Jilian Xiong, and Maite Maldonado

Status: final response (author comments only)

RC1:
'Comment on egusphere-2025-3179', Anonymous Referee #1, 18 Aug 2025

In this manuscripts, the authors present a detailed analysis of the role of changes in advection and source water properties in driving variability in water properties within the Salish Sea. Their analysis is based on Lagrangian experiments performed from outputs of an ocean model, and informed by observational data. The authors present interesting results whereby the processes governing variability differ across tracers, and discuss the implications for future changes. The manuscript is convincing, well-structured and well-written. I believe it will be ready for publication following minor revisions.
General comments
1.1 The authors currently present the results primarily in terms of years and seasons. I suggest that the authors also provide some of the results in terms of density or depth, since we can expect different water masses to contribute differently to different depth-levels. This perspective could for instance help to assess local impacts, since different areas/depths of the Salish Sea are probably fed by specific density-levels. For example, the authors could provide figures similar to Fig. 3a and 7 but plotted against density. These discussion of these results could be linked to densities presented at L260 onward.
1.2 Related to this point, it would be informative to show whether the density of water entering the JdF line varies interannually and seasonally, and show how this variability relates to changes in upwelling/downwelling or shifts in water source properties.
2. I invite the authors to clarify how observational data was used in this study, and how the inter-annual variations in the source water properties were computed. If I understand correctly, these inter-annual variations were derived from the model, but this should be stated explicitly in the method section, along with details on the procedure of how they were calculated (e.g. temporal averaging, selection of grid cells, etc.). Stating clearly how the observations will be used in section 3.3 should help alleviate the ambiguity.

In addition, I find it unclear what observations were used to produce Fig. 5., i.e. if the averaging was performed on data close to the source lines or within regions, and if so how the spatial variability within those regions was considered. One can expect water properties to differ substantially from the westernmost point to the easternmost dark-blue point on the subpanel of Fig. 1.
3.1 I have a concern regarding terminology. The authors refer to the different sources as “water masses” (e.g. L290). However, those sources are defined based on the properties at fixed lines, rather than by distinct water masses with coherent properties. The authors discuss the similarity between some of the source waters at L290-295. I recommend revising the terminology throughout the manuscript to “water sources” instead of “water masses”.
3.2 Related to this, I suggest that the authors comment on the similarity of source waters noted at L290-295 and discuss the meaning and implication of this similarity.
4. While the manuscript presents a separation into the upwelling vs downwelling season, the analysis stemming from this separation could be further developed. An attribution of the drivers per season, similar to what is presented in Fig. 7, would help discuss the impact of varying length of the upwelling and downwelling season (Fig. 2) on water properties.
Specific comments
This is really only a suggestion, but I found the title not very engaging, and would suggest finding a more engaging title. Maybe putting forward the variability in water properties, with something like “Water property variability in a semi-enclosed sea dominated by dynamics, modulated by properties”.
Throughout the manuscript, best practice would be to provide the most recent citation first when referring to multiple papers.
L64-66: I suggest supporting this statement with a reference or with a figure.
L81: For uniformity, I suggest including the range of values for oxygen as well.
L118: I believe we should read “Resolution gradually decreases” and not “increases”.
L169: Providing an histogram of the time it takes for particles to cross the different boundaries would help convince the reader that 100 days is sufficient, in addition to providing useful information about the dynamics of the region. Such a figure could go in the supplementary material.
In addition, how does the advection time compares with the duration of upwelling and downwelling events, and should a delay between the source water property definition and measurement at JdF be considered.
L171: Given the chaotic nature of particle trajectories, which will look different for different experiments due to numerical error, how will using three separate runs per analysis affect the results? For example, one specific parcel might not provide exactly the same oxygen concentration at its source location if the experiment was run multiple times, and could in this case lead to associate oxygen and nitrate concentrations from different sources. Running multiple experiments for the same tracer would allow to diagnose the uncertainty associated with this method. I suggest presenting the results from such tests.
L176: Please provide the proportion of tidally-pumped parcels.

In addition, are there parcels moving inland from the initialization line, and what is their proportion? These would not be the same as lost particles between the initialization line and sources lines, but could rather come from recirculation or surface currents? I understand that the current method, whereby parcels are saved when they reach a line, might not allow to answer this question, but tests with a smaller number of particles could.
L191-195: Since this can be seen in the figures and tables and does not affect the method, I suggest removing.
L210-212: When reading the first time, it is not very clear how this classification will be used. I suggest more explicitly stating that these are the definitions used for the source water masses. Moreover, please specify the maximum depth along the north boundary, to confirm that all waters sourced there can be defined as shallow waters.
Figure S3: Panels a-o do not highlight a clear separation. I suggest focusing on the S-property plots.
Fig. 1 :

a. In the subpanel, I suggest using a paler color for the 2000 m, since it can be confused with the coast for people not used to looking at this region.

b. I believe the initialization line is red, not brown.
L221: “grey bars in Fig. 2b, Bakun...”
Eq. 2: I would like to invite the authors to clarify Eq. 2. If we think of fields P and J as being separable into a mean and a yearly anomaly term (P = Pbase + Pyear), we would have four terms, including a crossed PbaseJbase term.
L254: Fig. 3a does not show the looped parcels. The authors should point to Fig. S6 or add the looped particles to Fig. 3.
L260: What is the full density range of the water at JdF? Having an idea of the vertical structure of the section would help visualizing what dynamics we are looking at.
Fig. 3: I suggest adding the percentages on Fig. 3a if possible, to relate the result more easily with those of Fig. 7.
Fig. 4: I suggest showing the total volume flux. Visualizing the seasonal variability of the total volume flux would help seeing how the different source waters contribute to the total variability.
Fig. 5: This is really just a suggestion, but, since the objective of this figure is to compare the water properties of different water sources, I suggest inverting the axis of the figure (hence show different water sources in x and variables in y) to ease the comparison.
L335: For 2018, it appears that property variability plays a larger role for all properties, not only TA-DIC. Maybe this is worth discussing.
Fig. 6: I suggest adding the standard deviation on the seasonal means on the right panels, to provide information on how the intra-seasonal variability compared with the separation between seasons.
L440: Near the surface, N* can be affected not only by denitrification, but also by nitrogen deposition (e.g. https://doi.org/10.5194/bg-5-1199-2008) and mixing. I suggest that the authors consider whether and how this could affect their interpretation of the N* results.
L500-504: I suggest to move this to method section, to clarify how the data was used and how the water source properties were defined.
L507: I suggest to mention this earlier, in section 3.2.

Citation: https://doi.org/10.5194/egusphere-2025-3179-RC1
- AC2: 'Reply on RC1', Becca Beutel, 30 Sep 2025
  
  We are grateful to Reviewer 1 for their thoughtful and detailed comments on this manuscript. Overall our takeaways from their review is that (1) the paper conclusions and relevance would be enhanced by analysing the results with respect to the density of inflow, (2) the use of observational data and how exactly it contributes to the conclusions is currently unclear, and (3) seasonal differences in the drivers of variability are relevant to interannual variability and should be discussed. We detail our plan to address these comments below, but in short plan to do so by (1) adding a series of density-based analysis, plots, and discussion to the main text and supplement, (2) expanding the description of the use of observations and how they were delineated into water sources, and (3) including more information and analysis on water masses and drivers during upwelling and downwelling. We are confident that these revisions, along with the other proposed changes below, will improve the quality of the manuscript, and are optimistic that they will satisfy the concerns raised by Reviewer 1.
  General comment 1.1- Including the density perspective
  Thank you for this suggestion, we agree that this perspective will enhance the relevance of the results to the interior of the Salish Sea. In the next draft we will include an attribution analysis (similar to Fig. 7) plotted against density ranges. Preliminary analyses show that the CUC and offshore deep water contribute to variability in higher density ranges, south shelf and offshore surface water in lower density ranges, and north shelf water in all density ranges. These results will be placed in the context of JdF inflow by also including a Hovmöller diagram of monthly climatology of density with depth at the initialisation cross-section, and histograms of parcel densities from each of the water sources at the beginning and end of their trajectories.
  General comment 1.2 – Interannual variability in the density of JdF inflow
  The variability in the density of water entering JdF and the drivers of this density variability were found to match very closely with that of salinity – since density is primarily driven by salinity in the region this correlation did not come as a surprise. With this in mind, it was decided that including a variability analysis of both tracers in the main text would be redundant. This choice will be stated explicitly in the text and figures of density variability and the drivers of it will be included in the supplement.
  The seasonal variability in the density of JdF inflow was studied in Beutel & Allen (2024). During periods of upwelling, inflow originates primarily from the north shelf, offshore deep, and CUC water. During periods of downwelling, inflow originates primarily from the south shelf and south brackish water. This change in seasonal source waters was accompanied by a large difference in the density of water entering JdF on seasonal scales, with the inflow being significantly more dense during periods of upwelling. Inflow to the Salish Sea also is much more likely to reach the inner basins during upwelling, as intermittent winds during downwelling often change the direction of flow in JdF. The seasonal source water and density differences from Beutel & Allen (2024) will be added to the regional description and results when discussing seasonal differences in JdF inflow.
  General comment 2 – Clarifying the use of observational data
  Any interannual variability or driver calculations discussed in the text were computed using results from model simulations as will be stated clearly in the methods section to reduce the ambiguity on the role of observations in this study. Additionally, more information will be added to the methods section on what processing went into the simulation output to calculate interannual variation.
  It should be noted that, where sufficient observations are available, observed properties paired with simulated transports could be used to determine the drivers of variability in tracers not included in the model. This calculation was not feasible in this study but is a topic of future interest. This potential for future work will be included in the text.
  With regards to the selection of observations to represent each of the water sources we agree that the offshore observations used cover too broad a region. We will be using a new cutoff of 1000 km from the shore, according to the definition of the California Current’s spatial range in Hickey (1979), as opposed to the longitudinal cutoff in the current draft. Preliminary analysis shows that while this new cutoff substantially reduces the number of observations in the two offshore water sources, that their mean properties do not change significantly. We will also clarify in the text that the observations used to define source water properties include all those shown in Fig. 1 and are divided according to the criteria in Table 1.
  During this review process we were introduced to an additional source of trace metal data. Specifically, this new source includes observations in the north shelf source water, which we believe will enhance the discussion of trace metal transport into the Salish Sea. This addition of trace metal data will entail adding trace metal boxes for north shelf water in Fig. 5, updating table A1 and A2 to reflect the data, altering the trace metal discussion (section 5.1.5) slightly, and including new authors on the manuscript who were responsible for collecting and making this data available (Jay T. Cullen and Tia Anderlini).
  General comment 3.1 – Use of the term "water mass"
  We will change the wording throughout the paper from “water mass(es)” to “water source(s)” or “source water(s).”
  General comment 3.2 – Similarity of source waters
  We were surprised by the similarity of the deep source waters in this region and believe that is may relate to the shallow depth cutoff (500 m) used in the observational data. We will explore this similarity further, including checking if this similarity is persistent if the data is split into smaller latitudinal bands and if observations in the two sources vary similarly in time and space. We will include a brief discussion of the results of this exploration, including the potential reasons for the similarity and effect that it has on the results of this paper.
  General comment 4 – Upwelling and downwelling analysis
  The precursor to this paper, Beutel & Allen (2024), goes into detail on the seasonal differences in water sources and their physical properties to the Salish Sea. Reference to the seasonal results of this paper will be stated more explicitly in the text. What Beutel & Allen (2024) does not include is an analysis of the drivers of variability. Figures showing the drivers of interannual biogeochemical variability on seasonal scales will be included in the supplement and referenced in text, and the implications of these seasonal differences will be discussed.
  Specific comments
  Title (…found the title not very engaging…)
  The title will be changed to the suggested.
  In-text citations (…best practice would be to provide the most recent citation first…)
  In-text citations will be done in reverse chronological order when referencing multiple sources.
  L64-66 (I suggest supporting this statement with a reference or with a figure.)
  Beutel & Allen (2024) will be added to support the statement on the relationship between upwelling and downwelling to interannual variability; Checkley & Barth (2009) will be added to support the statement on the extent of the CCS.
  L81 (For uniformity, I suggest including the range of values for oxygen as well.)
  A typical range of oxygen concentrations for both the PSUW and PEW will be added.
  L118 (I believe we should read “Resolution gradually decreases” and not “increases”.)
  Will fix typo.
  L169 (…histogram of the time it takes for particles to cross…)
  Histograms of particle crossing times from each source water will be added to the supplement and referenced in text to support the use of a 100 days crossing time. It will also be clarified in the text that the particle crossing time of 100 days was originally chosen based on the findings in Beutel & Allen (2024). It will also be noted that the small number of lost parcels (~1%) demonstrates that 100 days us sufficient for the grand majority of parcels to complete their trajectory.
  L169 continued (…how does the advection time compares with the duration of upwelling and downwelling events…)
  A consideration of the advection time of the water parcels and how they compare between source water and seasons will be added to the text, with reference to the timing histograms added to the supplement. As the focus of this paper is on interannual variability, and the property definitions provided are multi-year averages, it is not believed that a delay is required. However, a note on the impact of slowly moving parcels on seasonal definitions will be added to the limitations discussion.
  L171 (Given the chaotic nature of particle trajectories,… how will using three separate runs per analysis affect the results?...)
  The exclusion of subgrid-scale mixing in Ariane removes this chaotic nature, such that experiments are completely repeatable/reproduceable. The text will be clarified.
  L176 (Please provide the proportion of tidally-pumped parcels.)
  The percentage of total transport that is tidally-pumped is 72%; this value will be added to the text.
  L176 continued (…parcels moving inland from the initialization line…)
  It will been clarified in the text that parcels are only seeded where the direction of transport is towards the analysis domain. Recirculating particles are captured in “loop” flow, while parcels that are in theory pushed back and forth over the initialisation section due to tides (in practice these are seeded, return to the initialisation section within one or two tidal cycles, and are re-seeded) are captured in “tidally-pumped” flow and removed.
  L191-195 (…suggest removing.)
  This information will be removed.
  L210-212 (…it is not very clear how this classification will be used…)
  That the classification will be used to divide observations into water sources will be explicitly stated in the text.
  L210-212 continued (…specify the maximum depth along the north boundary, to confirm that all waters sourced there can be defined as shallow waters…)
  While the northern boundary does extend to the ~2000 m isobath 96% of water originating from the northern slope originates from depths shallower than 150 m, and 99% from depths shallower than 200 m. As such, while the northern boundary is not purely shallow, the parcels originating from it can be described as so. This intricacy will be clarified in the text.
  Figure S3 (Panels a-o do not highlight a clear separation…)
  The box plots are intended to highlight that very little change in the mean and interquartile range of the source water properties occurs due to the ±0.2 g/kg change in salinity boundary. Looking at the S-property plots alone may incorrectly suggest a larger impact due to the proximity of the CUC versus south shelf division to the high density core of parcels. This interpretation will be emphasized in the text and added to the caption of figure S3.
  Fig. 1 : a. (…paler color for the 2000 m…)
  The colouring for the bathymetric contours and the coast will be switched, with the coast in black and the bathymetry in grey.
  
  Fig. 1 : b. (I believe the initialization line is red, not brown.)
  The colour of the initialization line will be changed to green to increase contrast.
  L221 (“grey bars in Fig. 2b, Bakun...”)
  This sentence will be reworded as suggested.
  Eq. 2 (…clarify Eq. 2. …we would have four terms, including a crossed PbaseJbase term.)
  As Pbase and Jbase are constant terms they are zero when considering changes (Eq.2). For clarity, a step-by-step of this calculation will be added to the supplement (S4) and referenced in the text.
  L254 (... The authors should point to Fig. S6 or add the looped particles to Fig. 3.)
  The text will point to Fig. 4b as a reference for the inflow contribution of loop water and its seasonal variation.
  L260 (…full density range of the water at JdF?...)
  A Hovmöller diagram of the climatological mean monthly density with depth at the initialisation boundary in JdF will be added to the text, see the reply to general comment 1.1.
  Fig. 3 (I suggest adding the percentages on Fig. 3a if possible…)
  Percentage contributions will be added to the bars of Fig. 3a.
  Fig. 4 (I suggest showing the total volume flux…)
  Fig. 4a, currently another visualisation of the range in number of upwelling and downwelling days that does not directly add to the paper, will be replaced with the total volume flux.
  Fig. 5 (… I suggest inverting the axis of the figure…)
  Unfortunately, given the large number of tracers being compared, Fig. 5 becomes too busy or too long to fit on one page when the axis is inverted.
  L335 (For 2018, it appears that property variability plays a larger role for all properties…)
  In the ten years studied, the volume transport in 2018 is not extreme in any way – it has an “average” total transport and percentage transport from each water mass. While the mean NO₃, [TA-DIC], and DO values in 2018 are also not the most extreme highs or lows in the ten years studied, they are relatively close to said extremes. The combination of these two factors makes 2018 stand out in terms of property driven variability in NO₃, [TA-DIC], and DO. The fact that 2018 stands out, despite not being a particularly extreme year, is in itself interesting. A short discussion on the occasional disconnect between years with extreme properties and those with larger property driven variability will be added to improve the clarity of how to interpret the attribution results.
  Fig. 6 (I suggest adding the standard deviation on the seasonal means on the right panels…)
  The markers representing upwelling and downwelling means in the right panels will be changed to orange (upwelling) and blue (downwelling) box and whisker plots to show the range of values experienced in those periods in each of the water sources.
  L440 (…N* can be affected not only by denitrification, but also by nitrogen deposition … and mixing.)
  Text addressing N* as a measure of denitrification will be added as follows: “It should be noted that deviations from the Redfield ratio (and thus N*) can occur due to processes outside of denitrification, such as atmospheric deposition of nitrogen rich material, differing rates of nitrogen and phosphorus uptake or remineralisation, and nitrogen fixation (Landolfi et al., 2008). It is possible that the negative N* found in the shallow water masses is due to the preferential remineralisation of total organic phosphorus or the preferential uptake of NO₃ in the surface layer, as opposed to strong denitrification at the shelf bottom.”
  L500-504 (I suggest to move this to method section, to clarify how the data was used and how the water source properties were defined.)
  This information will be moved to the methods and removed from limitations.
  L507 (I suggest to mention this earlier, in section 3.2.)
  The potential slowing of parcels due to the lack of subgrid-scale mixing will be stated explicitly in the methods.
  
  Citation: https://doi.org/10.5194/egusphere-2025-3179-AC2
RC2:
'Comment on egusphere-2025-3179', Anonymous Referee #2, 03 Sep 2025

Beutel et al. present a practical approach to disentangle the effects of variable volume imports from effects of variable import properties on the variability of biogeochemical properties in the Salish Sea – a marginal sea of the Pacific Ocean. By backtracing water parcels in a coupled ocean-circulation biogeochemical model biogeochemical variability in the Sea could be traced back to imported contributions of distinct Pacific water masses.
The manuscript is well structured and clearly written. It is of interest to a wide audience (beyond those interested in the Salish Sea) also because it showcases how causes of variablity in estuary systems may be explored by combining observations with coupled ocean-circulation biogeochemical models (I especially liked Figure 7). Since this is a relevant question in many other coastal regions potentially affected by climate change the paper has both high scientific and societal relevance. I suggest, however, minor revision.
My suggestion is to clarify / elaborate on how the obervations support conclusions. I think this could strengthen the manuscrip because the combination of simulated trajectories with observed concentrations may raise some questions. For example:
Ln. 367 in the discussion “ … Combining observed water mass properties with model results can help reveal drivers of variability in biogeochemical tracers not explicitly represented in the model ….“
and
Ln. 531 in the conclusion “… Water mass contributions to JdF inflow, and the modelled and observed biogeochemical properties of these water masses, highlight the diverse drivers of interannual variability in tracer flux. …”
raise the questions: why are observed water mass properties needed? Is it because the model’s water mass properties are inaccurate? If so, does this imply that the model physics are biased? And if that is the case, can we trust the backtracking?
Further, Lagrangian Backtracking is a very common technique. It has been used extensively in the past to analyze water mass composition / origins of water masses. Maybe cite some exemplary (most pioneering or most sensational ...) papers of this field.
Ln. 8: “… Observations in the region provide insight into water mass processes not resolved by the model, including denitrification and …“ is confusing because, at this stage, it is unclear what model is referred to.

Citation: https://doi.org/10.5194/egusphere-2025-3179-RC2
- AC1:
  'Reply on RC2', Becca Beutel, 30 Sep 2025
  We are grateful to Reviewer 2 for their kind words and thoughtful comments on this manuscript. Our main takeaway from their review is that it is unclear how the observational data was used and exactly how it contributes to the conclusions. We detail our plan to address these comments below, but in short plan to do so by significantly expanding the description of the use of observations in the methods section, and expanding on how they contribute to the conclusions in the discussion. We are confident that these revisions along with the other proposed changes below will improve the quality of the manuscript, and are optimistic that they will satisfy the concerns raised by Reviewer 2.
  General comment - How the observations support the conclusions
  Observations were used in this study to extend the discussion of the drivers of biogeochemical variability beyond tracers available in the model, not to replace those in the model output. Model evaluations separated by source, as well as those previously reported in Xiong et al. (2024), suggest that salinity, temperature, DO, NO₃, TA, and DIC fields are sufficiently close to measurements to support their use in this study. The attribution of drivers was only done using model output, the aim of looking at observations of the modelled and un-modelled tracers is to identify where some un-modelled tracers may behave like modelled ones. For example, in the case of nutrients, NO₃ and DIP varied similarly between water masses whereas DSi did not. This comparison of observations allowed for a discussion of the factors that are likely important to DIP and DSi despite neither of them being modelled. This use of observations will be outlined explicitly in the methods of the next draft. Where the combination of observations and modelled properties is mentioned later in the text, such as the two lines in the discussion and conclusions that Reviewer 2 highlighted, the process for how exactly these methods were combined will be explained clearly.
  During this review process we were introduced to an additional source of trace metal data. Specifically, this new source includes observations in the north shelf source water, which we believe will enhance the discussion of trace metal transport into the Salish Sea. This addition of trace metal data will entail adding trace metal boxes for north shelf water in Fig. 5, updating table A1 and A2 to reflect the data, altering the trace metal discussion (section 5.1.5) slightly, and including new authors on the manuscript who were responsible for collecting and making this data available (Jay T. Cullen and Tia Anderlini).
  Specific Comments
  Lagrangian Backtracking
  References to papers that use Lagrangian backtracking to quantify water sources will be added to the description of Lagrangian tracking in the methods. This exemplary reference will include the following:
  Brasseale, E. and MacCready, P (2025),Seasonal Wind Stress Direction Influences Source and Properties of Inflow to the Salish Sea and Columbia River Estuary, Journal of Geophysical Research: Oceans, 130, doi: 10.1029/2024JC022024.
  
  Chouksey, M., A. Griesel, C. Eden, and R. Steinfeldt (2022), Transit Time Distributions and Ventilation Pathways Using CFCs and Lagrangian Backtracking in the South Atlantic of an Eddying Ocean Model. Journal of Physical Oceanography, 52, 1531–1548, doi:10.1175/JPO-D-21-0070.1.
  
  deBoisséson, E., V. Thierry, H. Mercier, G. Caniaux, and D. Desbruyères (2012), Origin, formation and variability of the Subpolar Mode Water located over the Reykjanes Ridge, Journal of Geophysical Research: Oceans, 117, C12005, doi:10.1029/2011JC007519.
  
  Ln. 8 (“…water mass processes not resolved by the model, …” is confusing because, at this stage, it is unclear what model is referred to.)
  This sentence will be reworded to make it clear what model this statement refers to.
  
  Citation: https://doi.org/10.5194/egusphere-2025-3179-AC1

Becca Beutel, Susan E. Allen, Jilian Xiong, and Maite Maldonado

Supplement

https://doi.org/10.5194/egusphere-2025-3179-supplement

Interactive computing environment

Analysis files for Beutel et al. (2025) - Impact of water mass dynamical and property variability on the inflow of a semi-enclosed sea Becca Beutel https://github.com/rbeutel/PI_BIOGEO_PAPER

Becca Beutel, Susan E. Allen, Jilian Xiong, and Maite Maldonado

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Short summary

This study examines how variability in Pacific source waters influences the biogeochemistry of the Salish Sea. Using model simulations and observations, we traced the origins and properties of inflowing water and quantified the roles of circulation and property variability in shaping fluxes of oxygen, nutrients, and carbonate system tracers. These findings highlight key drivers of interannual change and their relevance under a changing climate.


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