Connecting volcanic climate impacts to famine in China using the REACHES database

Warren, Richard

doi:10.5194/egusphere-2026-1228

Preprints

https://doi.org/10.5194/egusphere-2026-1228

Preprints

08 Apr 2026

| 08 Apr 2026

Connecting volcanic climate impacts to famine in China using the REACHES database

Richard Warren

Abstract. Volcanic eruptions have been linked to historical famines in many parts of the world. In China, reduced temperatures following major eruptions can destabilise the hydroclimate and agricultural production, contributing to subsistence crises and even the downfall of dynasties. This study provides the first long term analysis of the specific connection between volcanic activity and famine in eastern China from 1440 to 1900 CE. Using the REACHES historical climate database, it reconstructs indices measuring temperature, drought, flooding, crop failure and famine. Superposed epoch analysis of these indices reveals a recurring, though regionally distinct, association between eruptions and famine. Famine peaks occur in northern China in the year of an eruption, in central China one to three years later – coinciding with delayed drought and crop failure – and in southern China in the first post-eruption year. Correlation analysis indicates statistically significant relationships between volcanic forcing, hydroclimatic extremes, crop failure and famine. Case studies – including a new assessment of the impacts of the 1809 “unknown” eruption – demonstrate how other factors, such as the El Niño Southern Oscillation, non-volcanic climate processes, price volatility, disease and state relief mediate volcanic impacts. Many of these factors form feedback loop than can delay, amplify or counteract volcanic effects. We conclude that while eruptions may not be the primary drivers of famine in China, they significantly increase the risk of drought, flood, harvest failure and subsequent subsistence crises. The findings demonstrate the capacity of major volcanic events to destabilise food systems through coupled climatic and societal pathways.

Received: 11 Mar 2026 – Discussion started: 08 Apr 2026

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Richard Warren

Status: final response (author comments only)

RC1:
'Comment on egusphere-2026-1228', Anonymous Referee #1, 06 Jul 2026
Review of “Connecting volcanic climate impacts to famine in China using the REACHES database”
The manuscript provides a comprehensive analysis of the link between volcanic eruptions and famine in eastern China during 1440–1900 CE using the REACHES data. The author argues that volcanic activity does not necessarily cause famine, although some of their analyses suggest it could increase the likelihood of droughts and floods, thereby increasing associated agricultural and societal risks, including crop failure. Overall, this study is a valuable contribution to understanding volcano–climate–society relationships. However, I recommend clarifying some aspects of methodology and including additional analyses and discussion. I would also like to note that my background is in climate dynamics, so my review of the context and discussion on agricultural and societal impacts may be limited.

Major comments
In Section 2.3, it is mentioned that 23 provinces were categorized into three regions based on “climatology, agriculture, and historically concurrent famines.” Defining regions by climatology and agriculture sounds reasonable, but could the inclusion of historical famines systematically bias the assessment of the link between volcanic climate impacts and famines? Do the results vary widely depending on how these three regions are defined?

The analysis of the impact of volcanic eruptions on climate is based solely on the Drought Index from the REACHES database. However, hydroclimatic paleo records are available for this region (e.g., the Great Eurasian Drought Atlas by Cook et al. 2024). I think it would be beneficial to evaluate whether the REACHES-based Drought Index is consistent with other hydroclimatic reconstructions.

In Lines 161–161, the author mentioned that the summer temperature index is defined as the average of the summer temperature reconstruction from Wang et al. (2024) across each study region, because the reconstruction covers smaller regions than this study. How small was the coverage in Wang et al. (2024) compared to that in this study? I also do not quite understand exactly how the author was able to average across regions when data from some areas are missing.

This manuscript contributes to an analysis of the Unidentified 1809 event as a case study, but for the other three events, the author relies on previous studies. To demonstrate that the methodology employed in this study would yield results consistent with previous studies, I think the author should repeat the analysis used for the 1809 event (e.g., Fig. 6) for the other events.

Minor comments
The introduction could benefit from reorganization. I think adding an explanation of why the author focuses on China and why the period 1440 to 1900 CE is selected would strengthen the context. Additionally, clarifying the type of climate variability described in Lines 49–60 is important, as it is somewhat ambiguous (ENSO is mentioned in the paragraph before but not in Lines 49–60). ENSO and its influence on the climate in China should also be explained in detail in the Introduction, since a decent amount of analysis and discussion is devoted to it in later sections. Furthermore, I recommend adding a paragraph that briefly describes the rest of the manuscript (or the general context of this manuscript) at the end of the Introduction.

The VICES approach is introduced in Section 2.1, but it is still unclear to me how it is incorporated into the actual analyses. Does it only come into play in Table 5 and Figure 7, or is the inclusion of climatic, environmental, and societal indices (i.e., drought, crop failure, and famine indices) in all analyses considered a part of this VICES approach? I think clarifying this would greatly improve the manuscript and highlight the importance of this study.

I do not think you need to refer to figures/tables that include analysis results in the Data and Methodology section. Also, please make sure that the font size in figures is large enough when the manuscript is printed at a standard A4 size (e.g., Fig. 2) and number the figures and tables in the order they are mentioned in the text.

I understand this manuscript is based on the REACHES database, but did the other studies mentioned in the text also use a similar index to the Event Index defined by Eq. (1)? This is my first time reviewing a paper that bases analyses on reports rather than numerical observations, and I am curious how common this approach is and whether the results could be largely influenced by how famine and drought are defined.

The author discusses the link between ENSO and famine in China, but some of the links mentioned precede Lag Year 0 (e.g., Line 211). Are such links commonly considered more than a coincidence in studies on famine or other agricultural/environmental contexts?

Line comments
Line 10: I recommend including a brief description of the REACHES database.
Lines 16–17: What are considered “non-volcanic climate processes” here?
Lines 25–26: What periods exactly are meant by “early Chinese history” and “later periods”? I think it is crucial to state specific periods since later in this paragraph it states “a persistent connection between volcanic activity and famine has not been systematically investigated,” which implies a comprehensive analysis, and it is probably better to make sure those “early” and “later” periods are included in this study’s focus 1440–1900 CE.
Line 30: It may be worth briefly defining the difference between “climatic” and “environmental” pathways. It is clear once you introduce the VICES approach in Section 2.1, but not here yet.
Line 49: Again, I recommend including a brief description of the REACHES database if you are mentioning it before the Data and Methodology section. Is REACHES an abbreviation?
Line 67: Can you clarify what is meant by “perception and meaning” here?
Line 89: I recommend referring to figures and tables in parentheses instead of a dash [e.g., (see Fig. 1) instead of - see Fig. 1].
Line 96: Did you mean Table 1?
Lines 102–103: How were these four eruptions chosen as case studies? What is special about these events? I also want to point out that mentioning these events before explaining how major eruptions were chosen is a little bit confusing.
Line 117: What period is used to define the 95th percentile of SST anomalies? Is it the same as the study period of 1440–1900 CE?
Line 131: What was considered “a sufficiently large number” of reports?
Lines 161–169: I assume the author computed post-eruption anomalies relative to some pre-eruption baseline period to perform Superposed epoch analysis. What was the baseline period used in this study? Also, were volcanic years included in the original data used in the Monte Carlo model test?
Lines 176–181: Are the case study analyses also based on anomalies relative to some reference period, or on absolute index values?
Figure 3: I recommend picking a different color for either the non-volcanic year or Yr 0. Black and grey dots are hard to distinguish, unfortunately.
Figures 4–5: It may be beneficial to include individual events as thinner lines in these Superposed epoch analysis figures.
Table 4: It is just a suggestion, but it may be worth using a heatmap and hatching the insignificant correlations, rather than simply omitting the insignificant coefficient values.
Figure 6: A more detailed explanation would be appreciated in the caption. For instance, what are the top and bottom rows in each panel? It may also be worth putting lag years next to actual years in CE [e.g., 1809 (Lag Year 0)].
Lines 393–394: I would be curious what the results look like if only tropical eruptions are considered. Since there are still 10 events, I think the analysis can be performed reasonably well.
Line 341: How are the volcanic impacts on climate (both summer temperature and drought) discussed here consistent with other previous studies that looked at the last millennium? There seems to be some post-eruption drying in northern China and wetting in southern China, according to Tejedor et al. (2021, PNAS), which studied 1000–1850. Could the lack of hydroclimatic impact in southern China mentioned in Line 370 be due to the selection of events?
Lines 375–389: I enjoyed this paragraph, especially I appreciated the explanation of the different crop types and their sensitivity to climate conditions.
Lines 403–404: The dash and en dash are used inconsistently throughout the text. Please make sure to use a consistent notation!
Citation: https://doi.org/10.5194/egusphere-2026-1228-RC1
RC2: 'Comment on egusphere-2026-1228', Anonymous Referee #2, 21 Jul 2026

This study addresses an important research question: how major volcanic eruptions may be linked to famine through climate-driven impacts on agricultural production. The topic of volcanic impacts on climate has received considerable attention in recent years, leading to a rapidly growing body of literature examining the severe societal consequences after major volcanic eruptions, including dynastic collapse and social turmoil. A common pitfall in this line of research is the lack of socio-environmental data at appropriate spatial and temporal resolutions, which hinders a thorough examination and often leads to an oversimplification of human societal mechanisms. In this context, I do see the scientific value and potential in this manuscript to help bridge these research gaps. By saying so, I also have several major and minor comments regarding conceptual framing, statistical methodology, and data interpretation that I hope to help the author strengthen the scientific rigidity of the manuscript.
Conceptual rationality and causal claims:

The study adopts the VICES framework to guide its conceptual and methodological design. While this framework acknowledges feedback loops, it remains relatively linear and leans heavily on a top-down approach. Although the VICES framework appears practical, the statistical methods employed—namely correlation analysis and Superposed Epoch Analysis (SEA)—can only establish statistical associations or temporal alignments; they cannot demonstrate direct causality. Furthermore, the spatial distribution maps of climatic, environmental, and societal events (Figure 6) before and after the 1809 eruption indicate that events occur in clusters, suggesting a spatial evolution over time. For example, drought began in North China in 1810, intensified in 1811, and eased slightly in 1812; meanwhile, famine took place in 1811 and peaked in 1812. While this spatiotemporal analysis likely suggests a spatial correlation and a lagged effect (with famine peaking one year after drought), it does not provide empirical proof of a direct causal relationship among these events. Therefore, I strongly suggest the author to reframe the terminology used in the study and tone down the causal claims that can better reflect the level of analysis in the research.
Data description:

The abundance of Chinese historical documentary records provides a rich material for studying past climate variability and human responses. Utilizing the REACHES database is a practical approach, and showcasing its utility is valuable for the broader research community. However, because a big portion of readers may be unfamiliar with REACHES database, the manuscript would benefit from a more detailed description of how the records were retrieved in this study, the strength of using the REACHES records, and the potential limitations observed during the research process.
Results and proposed causal framework:

I appreciate the transparency and clarity of the results presented in the study and in the Appendices. For instance, Figure 3 clearly illustrates that a large proportion of volcanic eruption years coincided with extreme climate events, which is really interesting. At the same time, there are many extreme event years without volcanic eruptions. This is both expected and important, as volcanic forcing is only one of the external drivers of climate variability as noted in Figure 7. However, figure 7 requires substantial clarification and refinement. For example, what is the non-volcanic climate variability? Does non-volcanic climate variability only influence flood/drought instead of temperature and other environmental processes? Why and how ENSO leads to reduced temperature but not warming temperature? What does temperature mean here, i.e., land surface temperature? Also, soil moisture/cloud feedback can be affected by volcanic eruptions and non-volcanic climate factors. In other words, this is an ambitious figure, aiming to produce causal pathways that are beyond what has been discovered in this study. Moreover, many arrows in the figure and their directionality are still understudied and some of them remain scientific debate such as ENSO’s influence on East Asian monsoon and so on. Therefore, I strongly suggest the author to reframe the figure and focus on the key findings of this study, rather than attempting an all-encompassing conceptual model.
ENSO interpretation and statistical methods:

I found ENSO part in this study is confusing. First of all, the SEA statistical results in Appendixes are not convincing and the high/low index classifications in Table 3 are difficult to interpret (how do you define high and low?). Then by looking at the El Nino and La Nina years used in this study (Table 2), it is soon clear to me that many El Nino and La Nina years have short time intervals such as the El Nino years in 1606, 1609, and in 1800, 1804, and then in 1828, 1833, and 1839 and so on. This means that when applying an 11-year window for SEA, these events inevitably overlap across preceding and succeeding years (i.e., 1608 is the succeeding year of 1606 event but a preceding year for 1609 event), introducing significant noise and confounding the signal. Therefore, if the author wishes to retain the ENSO analysis, I strongly recommend applying alternative statistical methods, utilizing narrower time windows, or applying appropriate filtering techniques. Moreover, it is important to clarity the purpose of introducing ENSO in this research. For example, if ENSO is treated as an intermediate factor, you may consider analyzing how many volcanic eruptions co-occurred with ENSO events versus non-ENSO years, and compare their relative environmental and social impacts. Overall, a clear identification of the role of ENSO in this study would help sharpen the analysis.
Lagged correlation analysis:

The authors tested lagged correlations between the SAOD volcanic forcing index and various environmental/societal indices, finding none or very weak relationships. This actually adds little value to the main narrative and does not match other results in Figure 5 and 6. I suggest to remove it, otherwise the author has to improve the way of assessment. Lagged correlation is a good approach to assess lagged effect in time however it can also be sensitive depending on the temporal scale (i.e., seasonality) and the parameter in question. By reviewing other figures, I feel the lagged effects for crop failure and famine may associate with severe climate events (i.e., drought) but not volcanic eruption itself. So, there is something for author to reconsider.
Minor comment:

The manuscript presents a writing style easy to understand and follow. However, several typos need to be corrected, and certain sections would benefit from a more formal academic writing style. Below I list a few examples:

Line 17-18, ‘Many of these factors form feedback loop than can delay, amplify or counteract volcanic effects’

Line 262, 'r value indicate at best very weak correlations’

Line 319, ‘breading conditions for locusts’

Line 354, ‘eastern China might partly be due variable hydroclimatic impacts’

Citation: https://doi.org/10.5194/egusphere-2026-1228-RC2

Richard Warren

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Short summary

This study examines whether volcanic eruptions contributed to famine in China between 1440 and 1900. Combining historical records of climate, harvest failure, famine and other social phenomena, it finds that eruptions significantly increased the risk of drought and crop failure, raising the likelihood of food shortages. However, other factors such as El Niño and government relief shaped outcomes. The results show that while eruptions did not directly cause famine, they did make it more likely.


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