the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 May 2026
Assessing sedimentological proxies for characterizing tropical storm deposits in the Chandipur coastal region of Bay of Bengal, India: A modern analog for paleotempestology
Abstract. Coastal morphodynamics in barrier systems are governed by changes in sediment supply, sea level, and storm events. However, the limited availability of well-characterized modern analogs hinders the interpretation of sediments deposited by tropical storms, particularly in the Bay of Bengal. This study aims to evaluate the sedimentological proxies for identifying overwash deposits in the back-barrier region of Chandipur, India, using integrated granulometric and morphoscopic analyses across five sediment transects. Grain size distributions were modeled into four end-members (EMs) representing aqueous suspension-dominated transport, aqueous suspension with minor saltation, aeolian saltation, and high-energy depositional environment. To address compositional constraints, centered log-ratio (Clr)-transformed EM scores, were analyzed spatially to assess variations in depositional processes. Quartz grain morphoscopy, following the Cailleux classification, was used to assign grains to seven established shape categories, with fractured C-type grains being interpreted as indicative of high-energy mechanical modification. By combining grain size and morphoscopic characteristics, cluster analysis distinguished three sediment groups linked to aqueous, aeolian, and overwash-dominated environments. Microtextural observations further refine transport interpretations, indicating that many grains underwent high-energy collisions typical of marine reworking during storm events. A multi-proxy approach incorporating EM modelling, compositional analysis, grain morphology, and microtextural evidence establishes a reliable framework for differentiating overwash deposits. The results emphasize the value of integrating multiple sedimentological proxies to identify tropical storm signatures, with clear applications in paleotempestology and coastal management initiatives.
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Status: open (until 13 Aug 2026)
- RC1: 'Comment on egusphere-2026-2347', Anonymous Referee #1, 13 Jul 2026 reply
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CC1: 'Comment on egusphere-2026-2347', Marianne Dietz, 03 Aug 2026
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This study characterizes modern storm-overwash deposits in the back-barrier marsh of Chandipur, Bay of Bengal, India, using surface sediment samples collected along five shore-parallel transects in 2018. The authors combine end-member mixing analysis (EMMA) of grain-size distributions, Cailleux-based grain morphoscopy, and SEM microtextural analysis to define four grain-size end-members and three depositional clusters (aqueous, aeolian, and storm/overwash), which they propose as a multi-proxy framework for identifying storm deposits and informing paleotempestological reconstruction and coastal hazard management.
The methodology is intriguing and combines complementary techniques in a way that could meaningfully contribute to paleotempestology. However, the study lacks temporal control, offers no way to distinguish single storm events from cumulative reworking, and relies on grain classification schemes with no demonstrated reproducibility. As a result, the central claim that this proxy can reliably identify and reconstruct storm-surge deposits is not supported by the data presented. The approach shows promise but requires substantial additional development and validation before it can be considered a reliable paleotempestological proxy.
Major Comments
- Proxy applicability overstated. The authors frame this as a tool for paleotempestology but present no evidence bearing on preservation potential, i.e., whether these grain-size/morphoscopic signatures would survive burial or reworking over the timescales relevant to the paleo-record. This is never discussed.
- No mechanism for differentiating stacked or successive events. Although the paper discusses resuspension and reworking, it never addresses how a single overwash event's signature would be distinguished from the cumulative effect of multiple prior events, or how much of the observed pattern reflects post-storm quiescent reworking (e.g., aeolian) rather than the storm itself. This is a core requirement for any proxy intended for paleotempestological use, and it is absent.
- No temporal control. Samples were collected in 2018 in what appears to be a single field campaign (Section 3, lines 116–120), with no indication of sampling relative to a specific storm's timing, nor repeat sampling to track change over time. Section 4.6 lists multiple 2018 storm/depression events (Tropical Storm Daye, Cyclone Titli, and three depressions) without establishing which, if any, produced the sampled deposits, or discussing whether this was a typical or anomalous year for the region. Critically, while individual storms and depressions are named, none of the granulometric, morphoscopic, or microtextural data are tied to a specific one of these events, so even with the storms listed, the paper cannot attribute its "storm cluster" signature to a particular storm or distinguish the contribution of one event from another.
- Poor separation between aeolian and overwash end-members. EM-3 (aeolian, modal 2.8φ) and EM-4 (overwash, modal 2.4φ) have substantially overlapping size ranges — Figure 10 lists EM-3 as 4.0φ–1.6φ and EM-4 as 3.8φ–1.1φ, an overlap spanning roughly 3.8φ–1.6φ. Given this, it's unclear how confidently the two processes can be distinguished by grain size alone, undermining the paper's central diagnostic claim.
- Grain classification relies on subjective visual assessment with no reported reproducibility check. Both the Cailleux morphoscopic categories and the SEM-based microtextural scoring depend on a single analyst's visual judgment, and the qualitative category definitions (e.g., "partially-rounded," matte surface "limited to the most convex parts") leave real room for inconsistent classification. No inter-analyst reliability or repeat-scoring check is reported for either scheme. Since these classifications feed directly into the cluster analysis underlying the paper's central claims, this is a meaningful gap for a paper proposing a new proxy.
- Authors don't fully engage with the existing proxy landscape. The Introduction (lines 42–44) cites Yao et al. (2023) for the documented unreliability of geochemical proxies in some coastal settings, using this as partial motivation for proposing a granulometric/morphoscopic alternative. However, the paper never returns to this point to demonstrate that its own proxy avoids the same pitfalls Yao et al. identified: no comparison, no discussion of what made those geochemical proxies fail, and no argument for why a grain-size/morphoscopic approach would be more robust in the same failure conditions. This is consistent with the authors' general lack of engagement with the broader array of proxies used in paleotempestology, treating the presence or absence of microfossils as though it were the primary alternative to their approach.
- Figures are frequently unclear (see specific examples in minor comments below — Figures 4, 5, and 8 in particular).
Minor comments
- No clear demonstration that "high-energy" grain features (cracked/C-type grains) specifically indicate storm transport as opposed to other high-energy aqueous processes.
- Line 30: "storm surges sediments landward" — strange phrasing; likely missing a verb or should read "storm surge transports sediments landward."
- Line 37–38: Paleotempestology is introduced but its relevance to this specific study's findings/methods is never revisited or discussed.
- Rationale for site selection is missing: Why Bay of Bengal/Chandipur specifically? No discussion of regional tropical meteorology, whether the site is a good sediment repository (vs. continually reworked), or prior overwash studies at this location to justify testing a new proxy here.
- Sampling design not justified: why five shore-parallel transects, why this spacing/resolution, and why surface samples only rather than cores (which would provide the vertical/temporal context this proxy needs)?
- Lines 90–91: "modern analog" claim — unclear, since there's no before/after or repeat sampling around a specific storm event.
- Line 183: "temsological" — appears to be a typo.
- Lines 227–229: Poor sorting in transects 1–2, moderate-to-poor in 3–5 — no interpretation offered as to whether this is normal for the beach or diagnostic of anything; no clear grain-size pattern differentiates the transects.
- Figure 2: Sorting values plotted but not discussed quantitatively.
- Figure 4: Scale bar has no stated units (presumably %); using an identical color ramp for all four EM panels invites direct visual comparison between EMs that may not be valid.
- Figure 5: Confusing; category labels (RM, EM/RM, EL, etc.) would benefit from being tied more explicitly to the grain-shape photos in Figure 6.
- Lines 264–266, 272–273, 275–276: These are interpretive statements (aqueous origin, wind transport, storm-grain resemblance) placed in the Results section rather than Discussion.
- Line 317: SEM microtexture analysis was performed only on Cluster 3 (the "stormy" cluster). No SEM comparison data exist for Clusters 1 and 2, so the microtextural "signature" of storm deposits is never contrasted against non-storm SEM data.
- Figure 8: The y-axis conflates two different ordinal scales — Angularity uses the Powers (1953) 0–5 roundness scale, while Fresh Surface/Percussion Marks/Adhering Particles/Dissolution use a separate 0–5 "proportion of surface occupation" scale — plotted on the same axis without clear distinction.
- Section 4.6: No context on whether 2018 was a typical or unusual storm year for the region.
- Lines 356–362: The text first describes EM-3 transport under "favorable weather conditions" (i.e., normal/background), then invokes strong-wind resuspension for the same fraction, with no way to distinguish the two regimes from the data. This directly undercuts the proxy's usefulness.
- Lines 369–371: Claim that EM-4 transport is "particularly prominent during storm events" is asserted without citation or supporting temporal data.
- Line 381: Figure 10 (which most directly supports the cluster/depositional-environment discussion here) is not cited in this paragraph — only Figure 9 is cited nearby (line 385).
Citation: https://doi.org/10.5194/egusphere-2026-2347-CC1
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- 1
Review of “Assessing sedimentological proxies for characterizing tropical storm deposits in the Chandipur coastal region of Bay of Bengal, India: A modern analog for paleotempestology”
Saha et al presents an investigation on the sedimentological characteristics of tropical storm deposits in the Chandipur coasta region by using grain-size distribution, end-member modeling analysis, SEM grain-morphoscopic and microtextural analysis inspired in Mycielska and Woronko (1998), and multivariate statistics. The topic is very relevant to the fields of paleotempestology and coastal hazard assessment because of the studies on forecasting tropical storms and sea level rise deposits remain limited. The authors present a dataset over 5 transects along the Barrier bar located in the Bay of Bengal; for this specific case samples were extracted at ~10 cm from the surface. The manuscript also employs a multi-proxy approach that might have a potential value. However; several aspects of the study require clarification and strengthening before the discussion and conclusions can be fully supported. One of my main concerns goes to the evidence linking the different sediment populations that were identified to the different types of deposits. In the case of the overwash deposition (cluster 3), it is largely inferential and it is difficult to conclude something from Figure 11. Finally, the current manuscript lacks direct validation that the samples obtained were generated by specific documented storm events.
Major-comments:
One of the main conclusions of the manuscript is that EM4 and the associated morphoscopic cluster (NU and C grains) respresent storm-overwash deposits (Fig. 10). Nevertheless, this interpretation seems to be based on grain-size characteristics and the presence of fractured grains, which can be a good assumption, but other high-energy coastal processes are not excluded. In addition, the presence of this distribution over most of the transects is not well discussed.
The manuscript states that surface sediments were collected in 2018 from the upper ~10 cm of sediment. A 10 cm thick surface sample may integrate multiple depositional events occurring over months or years. Consequently, it is difficult to directly associate the observed sediment characteristics with specific storms such as Daye or Titli. The authors should discuss the temporal resolution of the sampling strategy and the extent to which the sampled material can realistically be attributed to individual storm events.
The manuscript repeatedly interprets fractured grains as indicators of storm activity due to high-energy collisions and other factors. While previous studies have reported similar observations, fractured quartz grains can originate from multiple processes including sediment recycling, beach swash processes, mechanical weathering, and fluvial transport. The authors should better justify why fractured grains in this setting specifically indicate storm overwash rather than generic high-energy transport.
The assignment of EM1–EM4 to distinct transport modes (suspension, suspension with saltation, aeolian transport, and overwash transport) appears largely conceptual. No independent hydrodynamic measurements or transport modelling are shown to validate these interpretations. The authors should explain more clearly how each end-member was linked to a specific transport process and discuss uncertainties associated with these assignments.
The PCA and cluster analysis identify three groups interpreted as aqueous, aeolian, and overwash deposits (Fig. 10). However, the observed clustering may simply reflect spatial gradients across the barrier-marsh system. The authors should demonstrate that the clusters represent distinct depositional processes rather than a continuum of environmental conditions.
SEM analysis is presented as an important component of the study, yet the interpretation remains largely qualitative. The manuscript would benefit from more detailed presentation of representative SEM images and clearer explanation of how specific microtextures distinguish storm transport from normal marine reworking. From Figs. 6, 12 and 13, it is hard to see the difference between shine and mate particles.
Several studies have described sedimentological characteristics of known storm deposits from other regions. A more detailed comparison between the Chandipur deposits and established modern overwash analogs would strengthen the interpretation.
Minor comments:
From line 87-91: this paragraph has to be more specific. Here the authors can relate the grain characteristics (size, shape, etc) to the storm derived sediments.
Line 118-119: explain why the samples were only at 10cm from the surface
Line 127-129: explain better why the authors used a solution of (NaPO3)6
Line 155: Why the samples were sieved only for the grain morphoscopic and microstructural study? This comes back to the grain size distribution. It should be well explained. The reader can get confused.
Line 172-178: There is too much explanation on the SEM details, instead, the authors should focus more on the characterization of rounded/angular shine/mate surfaces. This process seems that was very random.
From section 3.3 on: authors called EM as the end-member method, but sometimes, I got confused with the other nomenclature (shape/brightness), what about the authors renamed as EMMA as stated in section 3.1
Section 3.4: This section should be enhanced, this is the one that leads the discussion and conclusions. See major comments.
Line 229: Authors say that only CL3 to CL5 have moderate to poor sorting, but I see that all the transects have this distribution (Fig.2)
Figure 4 and 5 should have a label of the colormaps, what the colors represent?
Figure 10: In my opinion, this is the most important figure in the manuscript; however the last column should be enhanced, it is difficult to distinguish the aqueous, aeolian, and overwash transport.
Figure 12 and 13: The images should be zoomed in to see the real differences of the patterns described. For me, it is difficult to differentiate CF, AP, and VS.