the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Aug 2026
A cold-season temperature reconstruction for central Japan since 259 CE from a two-millennia Kiso Chamaecyparis ring-width chronology
Abstract. We present an annually dated reconstruction of previous November–April (pNov–Apr) temperature in central Japan from an expanded, provenance-aware Kiso Chamaecyparis ring-width chronology. The numerical chronology spans more than two millennia, but formal climatic interpretation is conservatively limited to 259 CE onward because replication and common-signal strength are lower and less continuous earlier. The primary model relates current-year ring-width index to a regional Chubu rural/background temperature anomaly series incorporating eight stations over 1912–2023 (n = 112), yielding r = 0.416, adjusted R2 = 0.165, and RMSE = 0.789 °C. In seven annual split-period tests predefined in the frozen workflow, reduction of error (RE) and coefficient of efficiency (CEff) are positive in six. RE and CEff are also positive in all four formally evaluable G21 high-pass splits. No centered G21 or G51 low-pass split is formally evaluable under the leakage-safe boundary and effective-sample-size criteria; the smoothed curves are therefore used as persistence summaries rather than as independently verified low-frequency reconstructions. Synthetic tests recover an imposed 51-year signal with median r = 0.972, gain slope = 0.909, and zero median phase lag. Rule-based screening identifies two sustained G21-tail candidates: 1999–2015 CE is retained with conditional support of 1.000 and adequate interval-specific SSS, whereas 1458–1473 CE is not retained because its support is 0.744, below the 0.800 threshold. Spatial correlations and comparisons with documentary snowfall, sea-surface temperature, and circulation indices support a regional winter-climate interpretation but are not independent validation or attribution. The reconstruction provides directly tested annual and sub-21-year information together with a cautiously interpretable view of multidecadal persistence since 259 CE.
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Status: open (until 02 Oct 2026)
- RC1: 'Comment on egusphere-2026-4506', Anonymous Referee #1, 13 Sep 2026 reply
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RC2: 'Comment on egusphere-2026-4506', Anonymous Referee #2, 15 Sep 2026
reply
General comments
This study attempts to reconstruct previous November–April (pNov–Apr) temperature over nearly two millennia in central Japan using TRW proxy. The topic is interesting and valuable. I also appreciate the authors’ careful treatment of reconstruction skill, frequency dependence, signal retention, and uncertainty. The manuscript is transparent about what the statistical tests can and cannot support.
My main concern is whether the current evidence is sufficient to support that the full chronology since 259 CE can be used to do a reliable pNov–Apr temperature reconstruction. The calibration and verification results show that the chronology contains some cold-season temperature information during the instrumental period, but these tests cover only about the last century. It is not clear whether the TRW–temperature relationship remained stable over the preceding ~1700 years. This issue is particularly important because the long chronology combines material from different sites, source histories, and, to some extent, species, whereas the calibration is based on the modern part of the chronology. And also the adjusted R² is only 0.165, which is rather low for a TRW-based temperature reconstruction.
Therefore, I think the main issue is not the rigor of the tests themselves, but whether the available tests are sufficient to support applying the modern TRW–temperature relationship to the full pre-instrumental period. I encourage the authors to address this point more directly and, where possible, provide additional tests of the stability of the chronology and its climate response. If this cannot be tested with the available data, the interpretation of the pre-instrumental reconstruction may need to be further narrowed.
Specific comments
- The statistical relationship between TRW and pNov–Apr temperature is clear, but the biological basis of this relationship remains unclear. The statement that “the defensible inference is statistical” is reasonable, but a better discussion of the possible mechanism would strengthen the reconstruction. I suggest examining the monthly response of TRW to winter temperature, precipitation, drought as well as growing-season temperature, precipitation, soil moisture, and drought et al. This could help clarify whether the winter signal is direct or partly related to other climate variables or carry-over effects. Possible links through snowpack, soil temperature, frost, cambial reactivation, or stored resources could also be discussed.
- Stability of the TRW–temperature relationship is the main concern for the long reconstruction. The current calibration and verification tests show skill during the instrumental period, but they do not tell us whether the same relationship existed throughout the pre-instrumental period. Could the authors examine this using other stationarity tests? It would also be useful to compare the climate response of earlier and later parts of the chronology where replication is sufficient. If the pre-instrumental relationship cannot be tested directly, I suggest making a clearer distinction between the period with tested reconstruction skill and the much longer period for which the chronology is interpreted as a climate record.
- The chronology combines living trees, archaeological wood, historical timbers, and buried wood from different locations. The living chronology also contains a small Sawara component. This raises questions about whether the climate signal in the earlier chronology is comparable to that in the modern calibration material. I suggest examining correlations among chronologies from different sites and, where possible, between species during their overlapping periods. A sensitivity test excluding the Sawara samples would also be useful if the sample size allows. These analyses could help show whether the long chronology has a common regional signal similar to that used for the instrumental calibration.
- The comparisons with documentary snowfall, SST, and circulation indices could provide useful supporting evidence, especially for the pre-instrumental period. I suggest showing these comparisons more clearly, preferably with figures, and discussing what they add to the reconstruction. At the same time, it would be useful to keep a clear distinction between agreement with independent climate records and true independent validation of the reconstruction.
- Please define how the effective sample size is calculated and explain the choice of neff ≥ 8. Since this criterion determines whether the low-frequency verification can be evaluated, its basis should be stated clearly in the Methods.
- The predefined split periods are a strength of the study, but the choice of E25, L25, E45, L45, E56, and L56 could be explained more clearly. If the data allow, testing a few additional split configurations would help assess how sensitive the RE and CE results are to the choice of calibration and verification periods. For example, E25 and L25 for the period 1974-2023.
- The synthetic input–recovery tests are important for interpreting the reconstruction results. Their design and evaluation should be described in the Methods rather than only in the Results.
Technical corrections
- Please define G21 and G51 before their first use.
- The sentence “A long chronology is therefore not, by itself, a reliable climate reconstruction...” is not necessary to present, and could be removed.
- The paragraph beginning “Ring width and stable isotopes need not respond...” is also not necessary, and can be removed.
- Some text in the legend of Fig. 3c appears to be cut off; please check.
- I suggest to show the statistical significance levels in Fig. 5.
Overall, I appreciate the authors’ careful and transparent approach to reconstruction testing. My main concern is the gap between the period in which reconstruction skill is directly tested and the much longer period over which the reconstruction is interpreted. The current results provide evidence for a cold-season temperature signal during the instrumental period, but it remains unclear how well this relationship applies to the earlier chronology, given its changing sources, sites, and species. I therefore encourage the authors to either add analyses that address the stability of the proxy–climate relationship and chronology composition, or further qualify the interpretation of the pre-instrumental record. In particular, the manuscript would benefit from a clear distinction between what is directly supported by the instrumental-period tests and what is inferred from the extended chronology.
Citation: https://doi.org/10.5194/egusphere-2026-4506-RC2
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- 1
In this manuscript, the authors present a two-millennia cold-season temperature reconstruction for central Japan based on an extensive Kiso Chamaecyparis tree-ring width chronology. Combining wood from diverse sources and addressing the urban heat island (UHI) effect through careful target selection are strong methodological points. While the manuscript is well presented and results can provide valuable insights into the cold-season temperatures in central Japan, I has a few concerns regarding the methods, results, and interpretation.
Specific concerns are detailed below:
The primary calibration model yields an adjusted R2 of 0.165 (r = 0.416) for the period 1912–2023. While the cross-validation statistics (RE and CEff) are positive and validate the model’s predictive skill, an explained variance of ~16.5% is relatively low for a temperature reconstruction, implying that over 80% of the variance in the tree-ring chronology is driven by unexplained factors. The authors should expand the discussion on what might be driving this high proportion of unexplained variance and clearly state the implications on interpreting the amplitude of historical temperature anomalies.
In Section 2.1 (Lines 89-91), the authors state that 22 out of 338 living-tree series are Chamaecyparis pisifera (Sawara), which were combined with Chamaecyparis obtusa (Hinoki). The authors acknowledge that “species-specific climate responses were not estimated and this remains a limitation”. If the ratio of these two species changes significantly over the two-millennia chronology, it could introduce non-stationarity into the climate response. The authors should provide a stronger justification for why mixing them does not impact the long-term climatic signal.
The selection of the previous November–April target is well justified statistically. However, the biological discussion in Section 4.1 (Lines 274-279) is somewhat brief. Given that cambial activity in this region typically occurs in the warmer months, the authors should explicitly discuss the ecophysiological mechanisms through which cold-season temperature strongly impact the subsequent ring width in Kiso Chamaecyparis (e.g., specific references to winter desiccation, snowmelt infiltration, or root freezing).
In Section 3.6 and Table 3, the rule-based screening identifies the 1999–2015 CE interval as a sustained upper-tail feature. Because this period falls entirely within the modern instrumental era, its value as a paleoclimatic finding is limited. The authors should further clarify the utility of highlighting this interval, is it primarily to demonstrate that the proxy successfully captures the modern warming trend, or does it serve another purpose?
In Section 4.4 (Lines 343-344), the authors state that detrending reduces the mean station correlation from 0.496 to 0.305, indicating that shared slower variations (likely the modern warming trend) contribute significantly to the raw spatial footprint shown in Figure 5. To prove that the proxy truly captures a coherent regional climate signal at the interannual scale, rather than a global warming trend, the authors should provide a supplementary figure showing the detrended spatial correlation map.
In Sections 4.5 and 4.6, the manuscript discusses the reconstruction’s complementarity with documentary snowfall records and the central-Japan isotope hydroclimate record (Nakatsuka et al., 2020). However, this comparison is entirely textual. Given the paleoclimate context of central Japan, adding a time-series figure that visually compares this new cold-season temperature reconstruction with the documentary and isotope records (for the overlapping periods) would substantially elevate the paper’s impact and make the discussion much more convincing.
Minor comments:
Line 164: The phrasing “Center-year-within-interval assignment” is hard to read. Consider rephrasing (e.g., “Assigning the center year within an interval...”).
Line 350: Typo. “downstream central- Japan” should be “downstream central Japan”.
Line 415-416: The text mentions “documents the complete Table 3 v5.3 candidate”. The “v5.3” appears to be an internal versioning artifact. Please remove or correct it.
Lines 473-475: In the reference list for Bunn et al. (2025) regarding the dplR package, there is a typo at the end of the citation: last accessed: July 29, 2026, 2025. The presence of two years (“2026, 2025”) appears to be an artifact from citation management software. Please correct this.
Figure 3: In Figure 3(c), the text above the bars (specifically “primary 0.127” and “4/4 positive” for the G21 HP category) are partially clipped by the top border of the plot frame. Additionally, the label “carry-over 0.049” overlaps with the bars, making it difficult to read. Please adjust the formatting.