No longer on schedule, the pattern Is breaking apart: The Loss of Seasonal Synchrony in a Sub-Arctic River System Under Warming Climate

Jalali Shahrood, Abolfazl; Ahrari, Amirhossein; Torabi Haghighi, Ali

doi:10.5194/egusphere-2025-2982

Preprints

https://doi.org/10.5194/egusphere-2025-2982

Preprints

07 Nov 2025

| 07 Nov 2025

Status: this preprint is open for discussion and under review for The Cryosphere (TC).

No longer on schedule, the pattern Is breaking apart: The Loss of Seasonal Synchrony in a Sub-Arctic River System Under Warming Climate

Abolfazl Jalali Shahrood, Amirhossein Ahrari, and Ali Torabi Haghighi

Abstract. Climate warming is altering the timing and synchrony of snow and ice processes across northern river systems, yet long-term shifts in their seasonal dynamics remain insufficiently resolved. Here, we analyze a 57-year daily record (1966–2023) from the River Oulankajoki in northeastern Finland to characterize freeze-up, break-up, snow accumulation and melt, and key atmospheric temperature transition points. Using a process-based detection tool, we identify significant advances in spring-related events, including snow melt, ice break-up, and the seasonal shift from cold to warm temperatures. In contrast, autumn transitions such as freeze-up and snow onset exhibit higher year-to-year variability and no consistent trends. The durations of cold season, ice cover, and snow melt periods have shortened, while warm and open-water seasons have lengthened. Moreover, the temporal gap between atmospheric warming and surface responses has increased in spring but contracted in autumn. These findings suggest not only a shift in seasonal timing but also a growing desynchronization between atmospheric conditions and cryo-hydrological processes, with implications for Arctic river ecology, ice forecasting, and flood risk under continued climate change.

Received: 23 Jun 2025 – Discussion started: 07 Nov 2025

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

Download & links

Abolfazl Jalali Shahrood, Amirhossein Ahrari, and Ali Torabi Haghighi

Status: open (until 07 Jan 2026)

Post a comment Subscribe to comment alert

RC1:
'Comment on egusphere-2025-2982', Anonymous Referee #1, 05 Dec 2025 reply
This manuscript applies the RiTiCE (River Ice Timing Characteristics and Extremes) framework to 57 years (1966–2023) of daily discharge, air temperature, and snow depth data from the River Oulankajoki, a boreal/sub-Arctic river in northeastern Finland. Building on earlier RiTiCE work that focused mainly on break-up, the authors extend the framework to detect six phase change timing (PCT) features (FUD, BUD, SBD, SMD, and two temperature transition points TTP⁻ and TTP⁺) and derive associated seasonal durations (cold and warm seasons, ice cover, open water, snow cover, no-snow period). The authors then analyze long-term trends, correlations among PCT features and seasonal periods, and temporal lags between atmospheric transitions and cryo-hydrological responses. A central qualitative conclusion is the asymmetry between autumn and spring. The order and timing of autumn features (SBD, TTP⁻, FUD) exhibit substantial year-to-year variability, whereas spring features (TTP⁺, BUD, SMD) retain a highly stable sequence. This behavior is interpreted as a loss of seasonal synchrony driven by climate warming.
Although this manuscript falls within the scope of TC and is based on a valuable data set, it requires substantial revision before it can be considered for publication. My main concerns are:
The central narrative relies on the sequence and relative timing of the six PCT markers. A key and potentially confusing result is that in some years FUD occurs earlier than both SBD and TTP⁻. This is counter-intuitive if one understands “freeze-up” as the date when the river is first observed to be completely ice-covered.

The manuscript states in Sect. 2.3 that FUD and BUD are hydrological signatures, distinct from IAHR visual definitions. However, later sections routinely interpret FUD as freeze-up in the physical sense. The paper needs to be more precise and transparent here, especially given the unusual orderings of events.

I suggest adding an explicit clarification such as “FUD is a discharge-based proxy for the onset of the winter low-flow regime, which is typically associated with sustained ice cover in this river, but does not necessarily coincide with the date when the channel is first completely ice-covered in a visual sense.”

In Fig. 7, the authors should explicitly discuss the years when FUD precedes SBD and/or TTP⁻. It would help to show one or two example years (similar to Fig. 6) with T, Q, S and all six PCT markers overlaid, and to guide the reader through how an early FUD can arise physically, for example a very dry autumn, early stabilization of baseflow, delayed continuous snow cover at the nearby terrestrial station, and a late zero-crossing in the cumulative temperature curve.

I think the authors need to acknowledge more explicitly the limitations of the hydrological proxy and to demonstrate that these cases are physically plausible and reasonably rare, for instance X out of 57 years, rather than artefacts of the detection algorithm.

The phrase “loss of seasonal synchrony” is prominent in the title, abstract, and conclusions, but there is no clear quantitative definition of synchrony and no consolidated figure that directly supports this claim. What exactly does "seasonal synchrony" mean here in this study?

The study relies on one air and snow station (Kuusamo Kiutaköngäs, about 500 m from the river gauge) and one discharge gauge to characterise the whole sub-Arctic river system. This is understandable given data availability, but it has direct consequences for the interpretation of the PCT features. SBD and SMD are based on terrestrial snow depth at the weather station rather than snow on the river. Vegetation and wind redistribution can lead to systematic differences between station snow and river ice or river-adjacent snow conditions.

Air temperature is also a single-point measurement, whereas freeze-up, break-up, and hydrological responses integrate the entire upstream basin. I suggest that in Sect. 4, when discuss cases where FUD precedes SBD or TTP⁻, or where snow and ice duration diverge, 他和authors should explicitly mention this spatial representativeness issue as one plausible explanation.

Specific comments:
Line 11: Calling RiTiCE a “process-based detection tool” may be misleading. It is a statistical rule-based method using thresholds on Q, T, and S, not a physical energy-balance or hydrodynamic model.

Line 95: At present the manuscript moves into the Methods in a descriptive way and does not clearly state two or three guiding scientific questions. I suggest adding a short paragraph with explicit research questions, for example “Specifically, we ask how the timings of six key PCT features have changed over 1966–2023, how the duration of cold, warm, ice-covered and snow-covered seasons have been reorganised, and how the lags between atmospheric transitions and surface hydrological and cryospheric responses have evolved.”

Line 104: The water year is defined from 1 October to 30 September. Based on Fig. 4, negative temperatures can already occur in October. For some colder water years this choice might prevent capturing the full evolution of Ct within a water year. It would be helpful to comment on this point. In addition, the figures linked in Appendix A are currently provided in emf or eps format. If possible, providing tif versions would make them easier to view.

Equation 1: the authors define DVD as ΔQ_t = Q_t+1 −Q_t. Mathematically, using Q_t −Q_t−1 would only shift indices by one day, so the stable segment and FUD/BUD would be essentially unchanged. However, from a physical perspective it may be more intuitive to define “change from day t−1 to t” instead of “from t to t+1”.

Equations 5 and 6: authors treat any S_t > 0 as “snow present” in the CSP algorithm. Please state the measurement resolution. This is especially relevant for short early/late snow events and could affect SBD/SMD in marginal years.

Section 2.5: It is not entirely clear why authors do not directly use the more classical and widely used FDD and TDD metrics. A short explanation of why the ZCAT approach is preferred here would be helpful.

Line 225: “The manuscript states that it provides “one of the most comprehensive long-term assessments”. However, authors have already published related work in Water titled “RiTiCE: River Flow Timing Characteristics and Extremes in the Arctic Region”, where the DVD method was developed and applied to 100-year discharge series in sub-Arctic rivers. I suggest softening the current claim to something like “a detailed 57-year assessment for a well-monitored sub-Arctic river”.

Line 228: Please explain why 1966 was chosen as the reference year. For example, is it simply the first year of the record, or was it selected because it is particularly representative?

Figure 9: The figure is not very clear in its current layout and would benefit from being rearranged or redrawn. In addition, important information is missing, such as the Sen slope and the Mann–Kendall p value for each variable.

Reply
Citation: https://doi.org/10.5194/egusphere-2025-2982-RC1

Abolfazl Jalali Shahrood, Amirhossein Ahrari, and Ali Torabi Haghighi

Viewed

Total article views: 217 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
118	78	21	217	15	16

HTML: 118
PDF: 78
XML: 21
Total: 217
BibTeX: 15
EndNote: 16

Views and downloads (calculated since 07 Nov 2025)

Month	HTML	PDF	XML	Total
Nov 2025	85	48	14	147
Dec 2025	33	30	7	70

Cumulative views and downloads (calculated since 07 Nov 2025)

Month	HTML	PDF	XML	Total
Nov 2025	85	48	14	147
Dec 2025	33	30	7	70

Viewed (geographical distribution)

Total article views: 209 (including HTML, PDF, and XML) Thereof 209 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 18 Dec 2025

Short summary

We analyzed 57 years of river, snow, and temperature records from a sub-Arctic watershed in Finland to understand how seasonal freezing and thawing have changed due to climate warming. Our findings show that spring events like snowmelt and ice break-up are happening earlier, while autumn changes remain unpredictable. This loss of seasonal coordination affects river behavior, water resources, and future planning under ongoing climate change.


Total:	0
HTML:	0
PDF:	0
XML:	0