{"id":"0107cac2-49a1-4c0b-94ec-a05bfdb2f915","arxiv_id":"2411.09234","paper_version":1,"verdict":"REJECT","confidence":"MODERATE","novelty_score":5.0,"correctness_risk":"high","formal_verification":"none","parameter_count":4,"one_line_summary":"A 122-year case study reports season-dependent links between solar cycle phase and extreme rainfall in Kerala, but the supporting statistics are not significant and the analysis has reproducibility problems.","lead":"This paper compares 122 years of sunspot numbers with Kerala rainfall and reports that extreme winter and pre-monsoon rain tends to occur during the descending phase of the solar cycle, while monsoon and post-monsoon extremes align with the ascending phase. The findings are presented as a first-time result, but the paper's own statistics show the phase counts are not significant and several methodological details are ambiguous.","discovery_kind":"extension","skeptic_critique":{"model":"deepseek-v4-flash","headline":"The paper's own binomial tests give p-values of 0.709–0.927 and call them 'not unusual,' yet the abstract claims phase-dependent impacts; the central association is unsupported by the paper's statistics.","rationale":"The reader's verdict is REJECT, and I agree. My primary concern is not the phase-threshold definition (the reader's stated weakest assumption) but the fact that the paper's own statistical tests directly contradict its headline conclusions. The binomial probabilities reported in Section 3 are all >0.7, meaning the observed phase splits are entirely consistent with random 50/50 occurrence, yet the abstract and conclusions state that descending and ascending phases 'had an impact' and 'notably affected' extreme rainfall. That is an internal inconsistency between evidence and interpretation. The even/odd cycle assertion is even weaker: it is based on eyeballing counts in Tables 1–4 with no test at all. The wrong deficit formula is an additional correctness error that could change the counts. These problems are load-bearing because they target the central claim directly, not a peripheral methodological detail. If the corrected analysis still yields non-significance, the paper's contribution reduces to descriptive correlation and wavelet coherence, which the paper itself notes are ambiguous (phase reversals, no definitive phase information). Therefore the verdict should remain REJECT. The reader partially identified this issue in their rationale but focused their weakest-assumption field on the phase thresholds; hence 'partial' agreement.","tokens_in":15061,"tokens_out":3168,"duration_ms":33371,"concrete_test":"Obtain the seasonal SSN and Kerala rainfall series (SILSO and IMD), reproduce Tables 1–4 with the corrected deficit definition Ri <= mu−sigma, and recompute the direction and counts of excess/deficit years in ascending versus descending phases. Compute two-sided binomial p-values for each season and phase combination under the null p=0.5, and a Fisher exact test on the 2×2 even/odd cycle by season table (e.g., JF/MAM combined vs JJAS/OND combined) for the even/odd asymmetry claim. If all p-values exceed 0.05, the paper's headline conclusions fail even with correct phase classification.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The strongest claim is that solar cycle phase (ascending/descending) and cycle polarity (even/odd) modulate seasonal extreme rainfall over Kerala. The evidence consists of counts of excess and deficit years per phase per season. The paper's own binomial tests give p = 0.895 (JF excess in descending), 0.927 (MAM excess in descending), 0.709 (JJAS excess in ascending), and 0.725 (OND excess in ascending), and it explicitly labels these 'not unusual' and 'not uncommon.' Under a 50/50 null hypothesis, none of these counts is significant, so the observed phase distribution is indistinguishable from chance. The even/odd asymmetry (even cycles more extreme in JF/MAM, odd in JJAS/OND) is asserted without any statistical test; no contingency table, chi-square, or Fisher exact p-value is reported. Furthermore, the deficit-year rule printed in Section 2.2 is Ri <= mu+sigma, which would label high-rainfall years as deficit; if corrected to Ri <= mu−sigma, the deficit lists change, altering all phase counts. Thus the central claim is not supported by the paper's own statistics, independent of any questions about the phase-threshold rule.","agreement_with_reader":"partial"},"referee_report":{"model":"deepseek-v4-flash","summary":"The paper investigates a possible relationship between sunspot number and seasonal rainfall over Kerala, India, using 122 years (1901–2022) of data. It applies Spearman correlation, cross-wavelet transform (XWT), and wavelet coherence (WTC) to seasonally averaged sunspot number and rainfall, and classifies the phases of Solar Cycles 14–24 using thresholds from Sawadogo et al. (2023). The central claims are that the descending phase influenced excess rainfall in winter and pre-monsoon seasons, that the ascending phase influenced monsoon and post-monsoon seasons, and that even solar cycles had more extreme rainfall in winter and pre-monsoon while odd cycles had more in monsoon and post-monsoon. These claims are based on counts of excess and deficit rainfall years per phase, with significance assessed by simple binomial probabilities.","tokens_in":15191,"tokens_out":4574,"duration_ms":48367,"significance":"If the phase–season and even/odd cycle claims were well supported, this would be a notable regional contribution to the sun–climate literature, with potential implications for seasonal predictability of extreme rainfall over Kerala. The paper has strengths: it uses a long homogeneous rainfall dataset, a widely used solar index, and standard wavelet tools, and it reports the binomial probabilities explicitly rather than hiding them. However, the central claims are not supported by the paper's own statistics. The reported binomial probabilities are all consistent with a 50/50 null hypothesis, the even/odd asymmetry is tested with no statistical procedure at all, and the printed deficit-year definition is internally inconsistent. As a result, the paper's main conclusions do not follow from its analysis as written.","major_comments":[{"comment":"The paper's own binomial probabilities are 0.895 for JF excess years in the descending phase, 0.927 for MAM excess years in the descending phase, 0.709 for JJAS excess years in the ascending phase, and 0.725 for OND excess years in the ascending phase; the text explicitly labels these values as 'not unusual' and 'not uncommon.' Under the stated 5/10 null hypothesis, these probabilities provide no evidence that extreme rainfall years occur preferentially in one solar phase. Yet the abstract and Section 4 conclude that the descending phase 'had an impact' and the ascending phase 'notably affected' extreme rainfall. This is an internal contradiction between the paper's own statistical assessment and its central claim.","section":"Section 3.4, Eqs. (1)–(2); Sections 3.5–3.7"},{"comment":"The deficit-year definition is printed as Ri ≤ (μ + σ), which labels high-rainfall years as deficit; the intended rule for a deficit year should be Ri ≤ (μ − σ). Because the deficit-year lists in Sections 3.4–3.7 are generated from this rule, the phase counts and the even/odd asymmetry involving deficit years are not reliable as printed. This is a load-bearing error, not a typo in isolation, since the deficit lists are part of the evidence for the phase and polarity claims.","section":"Section 2.2"},{"comment":"The phase classification inequalities do not partition the solar cycle. The increasing phase is defined as 0.122 × SNmax ≤ SN(t), which includes the maximum phase (SN(t) > 0.73 × SNmax); the maximum phase is therefore also an increasing phase. The decreasing phase is defined as 0.73 × SNmax ≥ SN(t) > SNmin(next cycle), which overlaps with both the minimum phase (SN(t) < 0.122 × SNmax) and the increasing phase. No rule is given for assigning a year to exactly one phase when multiple inequalities are satisfied. Since all phase–season counts depend on this assignment, the ambiguity is central to the paper's claims.","section":"Section 2.2"},{"comment":"The even/odd cycle asymmetry is asserted without any statistical test. The paper states that even cycles have more extreme rainfall occurrences in JF and MAM and that odd cycles have more in JJAS and OND, but it reports no contingency table, chi-square statistic, Fisher exact test, or any other quantification. Given the small counts and the multiple seasons examined, the apparent asymmetry may be entirely consistent with chance; a formal test is required before this claim can be accepted.","section":"Sections 3.4–3.7 and Section 4"},{"comment":"The Spearman correlations and the wavelet analyses are computed on 31-year moving averages. Moving-average smoothing induces strong autocorrelation in the series, so the effective sample size is far smaller than the nominal 122 years, and the reported significance levels (for correlations of −0.37, −0.27, 0.15, and 0.31) are not valid as computed. The XWT and WTC are also applied to the smoothed series, which reduces the effective degrees of freedom for the significance contours. This affects the correlation and wavelet claims reported in the abstract and conclusions.","section":"Sections 3.1–3.2"}],"minor_comments":[{"comment":"The abstract says all correlations were statistically significant, but Section 3.1 describes the JJAS correlation (0.15) as weak and does not claim significance for it.","section":"Section 3.1 and Abstract"},{"comment":"The text uses 'old cycles' where 'odd cycles' is meant; this appears in the JF and MAM season discussions.","section":"Sections 3.4–3.5"},{"comment":"The abbreviation 'TSA' is used for total solar irradiance; the standard abbreviation is TSI.","section":"Section 3.7, final paragraph"},{"comment":"The captions say 'Solar cycles 11-24', but the text and tables cover Solar Cycles 14–24.","section":"Figure captions 5–8"},{"comment":"The reference 'Barde et al. ()' is missing a year and complete bibliographic details, and the DOI in the paper header is a placeholder.","section":"References"},{"comment":"The claim that these findings are 'presented for the first time' is overstated, because the wavelet results in Section 3.2 largely reproduce earlier work by the same group (Thomas and Abraham 2022b; Thomas et al. 2023) cited in the paper itself.","section":"Abstract and Section 4"},{"comment":"The notation 'Ri ≤ (µ + σ), where Ri is the rainfall of that year, i, k ∈ R' is unclear; the role of k is not explained before the sentence 'In this study, k is defined as one.'","section":"Section 2.2"}],"recommendation":"reject","confidential_remarks":"The reader's assessment and the stress-test note align with my own reading: the central phase–season claim is contradicted by the paper's own binomial probabilities, and the deficit-year formula in Section 2.2 is wrong as printed. The even/odd asymmetry is asserted without statistical support. I also note that the paper's novelty claim is weakened by its own citations: the wavelet sections closely track earlier papers by the same group, so the only substantively new contribution is the phase–season analysis, which is not statistically supported. Unless the authors are prepared to reanalyze the data, correct the deficit threshold, and reframe the conclusions as a null result, the paper is not suitable for publication."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"Dear colleague,\n\nThis one is a reject, and the authors' own statistics do most of the work. The new piece is the attempt to connect solar cycle phase and polarity to extreme rainfall seasons in Kerala. That specific breakdown is not in their earlier papers. The data are real and the wavelet tools are standard. But the analysis doesn't hold together: the deficit-year rule printed in Section 2.2 (Ri ≤ μ + σ) labels high-rainfall years as deficit, presumably a typo for μ − σ, but as written it invalidates the deficit lists. The phase thresholds overlap, so a year can fall in multiple phases. And the binomial tests the authors themselves report give p-values between 0.71 and 0.93, which they call 'not unusual'. Those p-values directly contradict the abstract's claim that descending/ascending phases had a significant effect on excess rainfall. The even/odd cycle asymmetry is asserted without any test—no chi-square, no Fisher's exact, just eyeballing. On the wavelet side, they say a 31-year moving average filters out 11- and 22-year periods, then report significant 8–16 year XWT power on those same averaged series; that is an internal contradiction. The correlations on 31-year moving averages ignore autocorrelation, so the reported significances are suspect.\n\nThe one genuinely new idea—season-dependent phase and parity effects—might be worth a careful look, but this paper does not provide the evidence. The phase thresholds come from a different context (annual data applied to seasonal averages) and need clarification. If the deficit-year formula is corrected, the phase counts change and the conclusions likely shift.\n\nBottom line: not a serious referee. The paper needs major rework before the claims are testable. I would not send it to review in its current form; I would tell the authors the statistics do not support their abstract and the method section needs an overhaul. Not worth citing, and not worth bringing to group unless you want a cautionary example of ignoring binomial p-values.","headline":"The paper's own binomial p-values (0.71–0.93) disprove its phase claims, and the flawed deficit-year rule and overlapping phase thresholds make the central result untestable.","tokens_in":15837,"tokens_out":2229,"would_cite":false,"duration_ms":24316,"reading_group":"no","serious_thinker":"no","would_accept_peer_review":false},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"The paper claims that across 122 years of Kerala rainfall, the phase of the solar cycle (plus its even/odd magnetic-polarity alternation) is associated with which seasons produce excess rain, with the descending phase tied to…","keywords":["sunspot number","solar cycle phases","Kerala rainfall","extreme precipitation","cross-wavelet transform","wavelet coherence","even/odd solar cycles","solar-terrestrial climate link"],"falsifier":"Re-derive the phase assignments for Solar Cycles 14–24 using a non-overlapping rule (for example, assign the maximum phase first whenever the sunspot number exceeds 0.73 times the cycle maximum, and assign every other year to ascending or descending relative to the cycle minimum), then re-count excess and deficit years per season and per even/odd cycle parity; if the reported pattern — 10 of 16 winter excess years and 8 of 12 pre-monsoon excess years in the descending phase, and a monsoon/post-monsoon lean toward the ascending phase — does not survive this unambiguous reclassification, the central claim fails.","tokens_in":14707,"feed_emoji":"🌧️","tokens_out":8342,"duration_ms":81345,"temperature":0.7,"pith_summary":"This paper tries to establish that the solar activity cycle leaves a seasonally structured imprint on extreme rainfall over Kerala, India. Using 122 years of sunspot numbers and gridded rainfall, it reports statistically significant rank correlations between 31-year averaged sunspot number and rainfall that switch sign by season, and wavelet analyses showing shared power at 8–12 year and shorter periods. It then classifies each year into solar-cycle phases and finds that excess rainfall in winter and pre-monsoon seasons falls preferentially in the descending phase and in even cycles, while monsoon and post-monsoon excess rainfall falls preferentially in the ascending phase and in odd cycles. If the association is real, the timing of Kerala's extreme rain events carries a solar-activity component that could be anticipated from the phase of the sunspot cycle.","feed_headline":"Solar cycle phase lines up with Kerala's extreme rain seasons","feed_subtitle":"122 years of data tie descending phase to winter and pre-monsoon floods, ascending phase to monsoon.","key_machinery":"The analysis is carried by four objects: the sunspot number time series, seasonally averaged; the Kerala rainfall series split into winter (January–February), pre-monsoon (March–May), monsoon (June–September), and post-monsoon (October–December); a threshold rule that assigns each year to a solar-cycle phase based on the cycle's peak sunspot number (below 0.122 of the peak is minimum, above 0.73 is maximum, with the remaining years assigned to increasing and decreasing phases); and a definition of extreme years as those whose seasonal rainfall lies at least one standard deviation above (excess) or below (deficit) the seasonal mean. The time-frequency machinery is a cross-wavelet transform and wavelet coherence built on a complex wavelet with balanced time–frequency localization, applied to 31-year moving averages, which is what produces the significant 8–12 year common-power and 2–4 and 4–8 year coherence bands.","core_discovery":"The central claim is that seasonal rainfall over Kerala is related to solar activity in a way that is not just a single correlation: the sign of the relationship flips across the year, and the phase of the sunspot cycle selects which season sees excess rain. The authors report significant negative rank correlations between 31-year averaged sunspot number and rainfall in winter and post-monsoon, and positive correlations in pre-monsoon and monsoon. Cross-wavelet analysis shows significant common power at the 8–12 year scale in all seasons, and wavelet coherence shows significant local correlation at 2–4 and 4–8 year scales in all four seasons; longer-period coherence appears in monsoon and post-monsoon. Sorting extreme rainfall years by solar phase, they find 10 of 16 winter excess years and 8 of 12 pre-monsoon excess years occurring during the descending phase, while excess years in monsoon and post-monsoon lean toward the ascending phase. Grouping by cycle parity, extreme events are more frequent in even cycles for winter and pre-monsoon and in odd cycles for monsoon and post-monsoon, which the paper presents as a new result tied to the opposite magnetic polarity of sunspots in alternating cycles.","pith_inferences":["The data stop at Solar Cycle 24 (2022); a clean out-of-sample test would be to predict, from the ascending phase of Cycle 25, that monsoon and post-monsoon excess rain should be more frequent in the coming years and then check the observed extremes.","The reported correlations and coherence bands do not by themselves identify a mechanism; a testable extension is to run a climate model with and without solar-cycle forcing to see whether the same season-dependent sign flips and phase selection emerge.","Because the even/odd asymmetry is presented as tied to sunspot magnetic polarity, a natural extension is to see whether the same seasonal asymmetry appears in other monsoon regions or in long Indian rainfall subdivisions.","The overlapping phase thresholds could slightly mislabel years; re-deriving the counts under an unambiguous phase rule would show whether the central pattern is robust to that choice."],"forward_implications":["If the association holds, Kerala's seasonal extreme-rainfall risk is partially set by where the sunspot cycle stands, giving a long-lead indicator for winter/pre-monsoon versus monsoon/post-monsoon extremes.","The descending phase becomes a risk window for excess rain in winter and pre-monsoon, while the ascending phase is a risk window for monsoon and post-monsoon excess rain.","The even/odd cycle asymmetry implies a 22-year magnetic-polarity (Hale-cycle-like) component in seasonal rainfall extremes, so extremes in a given season may alternate in frequency from one 11-year cycle to the next.","The significant 8–12 year cross-power across all seasons supports a solar-cycle-scale coupling that is seasonally modulated rather than a single all-year response.","The pattern could be folded into seasonal forecasting practice for Kerala, supplementing internal climate drivers such as the monsoon system."],"supporting_citations":[{"why":"Supplies the solar-phase classification thresholds (0.122 and 0.73 of cycle-maximum sunspot number) used to assign each season-year to a phase.","marker":"Sawadogo et al., 2023"},{"why":"Provides the extreme/deficit rainfall year definition (seasonal rainfall at least one standard deviation above or below the mean) used to flag extreme years.","marker":"Azad, 2011"},{"why":"Provides the cross-wavelet transform and wavelet coherence methods and their significance testing used in the time-frequency analysis.","marker":"Grinsted et al., 2004"},{"why":"Supplies the wavelet analysis framework and practical guide underlying the cross-wavelet and coherence computations.","marker":"Torrence & Compo, 1998"},{"why":"Provides the long-period 0.25-degree gridded rainfall data set over India that supplies the Kerala rainfall time series.","marker":"Pai et al., 2014"},{"why":"Earlier seasonal wavelet study of sunspot number and Kerala rainfall whose similar cross-power results are compared and extended.","marker":"Thomas & Abraham, 2022b"},{"why":"Earlier annual wavelet analysis of Kerala rainfall and sunspot number that this work extends to seasons and solar phases.","marker":"Thomas et al., 2023"},{"why":"Prior report of positive solar-activity correlation with spring and southwest-monsoon Indian rainfall used as a comparison point for the sign of correlations.","marker":"Hiremath & Mandi, 2004a"},{"why":"Supplies the binomial-test approach used to roughly evaluate whether phase-conditional counts of extreme years are unusual under randomness.","marker":"Ananthakrishnan & Parthasarathy, 1984"}],"fun_headline_variants":["Sunspot cycle phase predicts which Kerala season floods","Kerala rains shift with solar cycle phase, 122-year record shows","Even and odd solar cycles split Kerala's extreme rain seasons","Solar phase flips Kerala rainfall correlation season by season","Sunspot polarity tied to Kerala extreme rain timing"],"cache_read_input_tokens":3200,"weakest_assumption_plain":"The load-bearing premise is that the phase-classification thresholds of 0.122 and 0.73 of each cycle's peak sunspot number remain valid when applied to seasonally averaged sunspot numbers, and that the overlapping inequalities can be disambiguated so every year falls in exactly one phase.","fun_headline_variants_meta":{"raw":{"variants":["Sunspot cycle phase predicts which Kerala season floods","Kerala rains shift with solar cycle phase, 122-year record shows","Even and odd solar cycles split Kerala's extreme rain seasons","Solar phase flips Kerala rainfall correlation season by season","Sunspot polarity tied to Kerala extreme rain timing"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000511,"raw_usage":{"total_tokens":2566,"prompt_tokens":1109,"completion_tokens":1457,"prompt_tokens_details":{"cached_tokens":384},"prompt_cache_hit_tokens":384,"prompt_cache_miss_tokens":725,"completion_tokens_details":{"reasoning_tokens":1378}},"tokens_in":725,"tokens_out":1457,"duration_ms":11418,"temperature":1.0,"reasoning_tokens":1378,"cache_read_input_tokens":384,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-12T20:53:40.393959+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Re-derive the phase assignments for Solar Cycles 14–24 using a non-overlapping rule (for example, assign the maximum phase first whenever the sunspot number exceeds 0.73 times the cycle maximum, and assign every other year to ascending or descending relative to the cycle minimum), then re-count excess and deficit years per season and per even/odd cycle parity; if the reported pattern — 10 of 16 winter excess years and 8 of 12 pre-monsoon excess years in the descending phase, and a monsoon/post-monsoon lean toward the ascending phase — does not survive this unambiguous reclassification, the central claim fails.","supporting_citations":[{"cited_title":", author Allain Gnabahou , D","cited_arxiv_id":null,"evidence_quote":"Supplies the solar-phase classification thresholds (0.122 and 0.73 of cycle-maximum sunspot number) used to assign each season-year to a phase."},{"cited_title":"( year 2011 )","cited_arxiv_id":null,"evidence_quote":"Provides the extreme/deficit rainfall year definition (seasonal rainfall at least one standard deviation above or below the mean) used to flag extreme years."},{"cited_title":", & author Compo, G","cited_arxiv_id":null,"evidence_quote":"Supplies the wavelet analysis framework and practical guide underlying the cross-wavelet and coherence computations."},{"cited_title":", author Joseph, I","cited_arxiv_id":null,"evidence_quote":"Earlier annual wavelet analysis of Kerala rainfall and sunspot number that this work extends to seasons and solar phases."},{"cited_title":", & author Parthasarathy, B","cited_arxiv_id":null,"evidence_quote":"Supplies the binomial-test approach used to roughly evaluate whether phase-conditional counts of extreme years are unusual under randomness."}],"review_version":1}