Assessing the scientific basis and regional applicability of a Chinese agrometeorological proverb in a warming climate

Chinese Agrometeorological Proverbs represent a valuable repository of traditional knowledge supporting agricultural practices; however, their scientific validity and regional applicability under climate change remain insufficiently examined. This study evaluates the proverb “The heat of Dog Days on double Beginning of Spring of the Lunar Years” using daily meteorological data from 699 stations across China (1966–2019). We compared temperature trends between Double-Beginning of Spring Lunar Years (BSLY) and Normal Years (NY) from the Beginning of Spring to Minor Heat to identify periods of “Rapid Warming” (RW), and assessed the intensity of “Dog Days Heat” (DDH) using the Temperature-Humidity Index (THI). The results reveal spatially varying consistency with the RW characteristic: southern China and the middle-lower Yellow River basin showed the strongest agreement, meeting the RW criterion within both 31 and 46 days after the Beginning of Spring. During the Dog Days period, BSLY exhibited significantly higher heat intensity in southern regions, with spatial variations influenced by topography and local climate conditions. This research confirms the scientific basis of the proverb and demonstrates that its applicability extends beyond its region of origin. The findings provide practical insights for integrating traditional knowledge into climate-resilient agricultural planning, supporting adaptive strategies under changing climatic conditions.

1 Introduction

Chinese Agrometeorological Proverbs represent a traditional knowledge system developed within the framework of the Twenty-Four Solar Terms, which are themselves based on the lunisolar calendar traditionally used in China. This calendar integrates the cycles of the moon and the sun, and its 24 solar terms were established to reflect annual cyclical climate changes, serving as a unique timeline guiding agricultural activities and daily life. These solar terms provide the fundamental temporal framework for the formation and application of Agrometeorological Proverbs. The proverbs essentially encapsulate empirical observations about the relationships between these solar terms, weather patterns, and phenological phases, forming a condensed body of practical knowledge for agricultural production. Formed through long-term observation of weather and phenological changes combined with agricultural practices. These proverbs embody the empirical wisdom essential for agricultural production and crop management (Chen, 2016). Their origins can be traced back to oracle bone inscriptions from the Shang Dynasty (c. 1,300–1,046 BC), which already contained records of climate-related proverbs (Mu and Ali, 2023). Later, these sayings were systematically compiled and developed in ancient agricultural texts such as of the Western Han Dynasty (202 BC-8 AD) and “Qi Min Yao Shu” of the Northern Wei Dynasty (386–534 AD) (Jia, 2024). Throughout China’s long agricultural history, these proverbs have been refined through repeated practice and ultimately evolved into a knowledge system possessing both cultural and scientific significance. Proverbs from different regions reflect varied climatic characteristics—for instance, “No more snow after Pure Brightness, but often a small amount of snow; no frost after Grain Rain, but there may be some frost” in North China and “No snow after Pure Brightness, no frost after Grain Rain” in the middle and lower reaches of the Yangtze River—and often guide farming activities based on phenological phenomena. However, the scientific validity of these proverbs under modern climate change remains subject to systematic verification. In this context, temperature-related proverbs deserve particular attention. For example, “The heat of Dog Days on double Beginning of Spring of the Lunar Years” suggests that in years with BSLY markers in the lunar calendar, an earlier and more rapid spring warming occurs, which may lead to higher temperatures during the Dog Days. However, the meteorological mechanisms underlying this association have not yet been rigorously validated.

As the foundation of Agrometeorological Proverbs, the twenty-four solar terms were inscribed on the Representative List of the Intangible Cultural Heritage of Humanity by the United Nations Educational, Scientific and Cultural Organization (UNESCO) on 30 November 2016, in accordance with Article 16 of the Convention. The twenty-four solar terms can be traced back to the observations and summaries made by ancient Chinese agricultural societies of natural phenomena. From early astronomical observations to the refinement of astronomy and calendrical systems during the Zhou Dynasty (1046 BC-256BC), terms like Beginning of Spring, Beginning of Summer, Beginning of Autumn, and Beginning of Winter were applied to people’s daily life and agricultural production activities, to the Qin and Han dynasties (221 BC-220 AD) formed a more complete Twenty-four solar terms, clearly taking one cycle of the Earth’s rotation around the Sun as a cycle, that is, the Sun from the zero degree of the ecliptic longitude, along the ecliptic longitude every 15° run as a solar term (Xu and Wang, 2018). The twenty-four solar terms start from the Beginning of Spring and end with the Major Cold, which reflects the climate changes in different temporal periods of the year in detail, for example, Beginning of Spring, Beginning of Summer, Beginning of Autumn, and Beginning of Winter represent the beginning of the four seasons, and Awakening of Insects, Pure Brightness, Grain Buds, and Grain in Ear not only represent climate changes, which also reflects the phenological phenomenon of crops. In addition to the main twenty-four solar terms, there exist other important secondary solar terms, like Dog Days, which are used to define in detail the hottest time of the year (Xu, 2024). Traditional meteorological culture, including the twenty-four solar terms and agrometeorological proverbs, not only had far-reaching influences in the history of Chinese civilization, but also occupies an important position in the history of world civilization and is receiving more attention from researchers.

In recent years, increasing climate variability has drawn widespread attention to agricultural meteorological proverbs due to their potential in modern adaptation strategies. The inclusion of the “Twenty-Four Solar Terms” in the UNESCO Intangible Cultural Heritage List in 2016 has further stimulated research in this field. Frequent extreme climate events—such as the record-breaking heatwaves across multiple countries and spatially compound heat events in 2023 (Zhang W. et al., 2024) —pose severe threats to global food security. These challenges have prompted the scientific community to re-evaluate the predictive and practical value of traditional agricultural weather proverbs. In this domain, international research methodologies have gradually shifted from early descriptive analysis toward more scientific and empirical approaches. Studies globally can be broadly categorized into two main themes: (i) examining the correlation between proverbs and climatic factors, and (ii) assessing the accuracy of proverbs under climate change. For instance, Kanno et al. (2013) illustrated the relationship between proverbs, local climate and global climate elements like ENSO (El Niño and Southern Oscillation) by comparing proverbs from the Sinazongwe District of Zambia’s Southern Province with modern meteorological records; meanwhile, Garteizgogeascoa et al. (2020) studied local perceptions of climate change through proverbs, taking the Sierra Nevada region of Spain as an example, and the results showed both consistency and inconsistency between people’s perceptions of the proverbs’ accuracy and the information available from science-based assessments of the impacts of climate change in the region. Notably, Matczak et al. (2020) used meteorological data to statistically analyze temperature-related proverbs in Poland, and in their studies were found that proverbs’ accuracy inversely correlates with chronology (decreased with time), and their values increase in the direction of the east and north of the station site. In contrast, domestic research specifically focused on temperature-predicting proverbs remains relatively limited, with existing work predominantly centered on the solar terms themselves. Qian et al. (2012) indicated that there is a general tendency to advance the four climatic solar terms reflecting phenological phenomena within China, and many agricultural proverbs and experiences related to solar terms may become no longer appropriate; Ji et al. (2015) found a significant increase in (mean, maximum and minimum) temperatures in the spring-type seasons in their study of the twenty-four solar terms in the middle and lower reaches of the Yellow River, and in the winter-type seasons, only the minimum temperatures increased significantly. Despite these findings, there remains a notable research gap in the systematic validation of temperature-predicting proverbs—particularly those based on astronomical or phenological indicators for predicting thermal conditions. As a result, the scientific validity and regional applicability of these traditional proverbs under modern climate conditions remain open to critical questioning. There is an urgent need to move beyond macro-level comparative research paradigms and conduct targeted verification of the climate predictive functions embedded in the proverbs—such as the relationship between “Double Beginning of Spring” and the intensity of summer heat—to provide a scientific basis for sustainable agricultural adaptation measures.

This study selects the widely circulated Agricultural Meteorological Proverb “The heat of Dog Days on double Beginning of Spring of the Lunar Years”, which has a deep historical background in the farming civilization of the Jiangsu, Zhejiang, and Shanghai regions. The proverb originates from the empirical observation of the occurrence of double “Beginning of Spring” periods in a lunar year, reflecting the idea that warm air arrives early, the temperature increases rapidly, and heat accumulates quickly, leading to abnormally high temperatures during the Dog Days. In order to explore the Scientificity of the proverb and clarify its regional applicability, thus providing reliable scientific guidance for more accurate climate change predictions in agricultural production, this study focuses on the characteristics of “Rapid Warming” (RW) and “Dog Days Heat” (DDH) in double Beginning of Spring of the Lunar Years (BSLY). The research utilizes comprehensive data collected from 699 meteorological stations between 1966 and 2019 to conduct an in-depth analysis.

2 Area and data

2.1 Study area

China, as the third-largest country in the world by land area, is located in the eastern part of Asia, on the western edge of the Pacific Ocean. Its unique geographical position, along with its complex terrain and diverse underlying surfaces (Zheng et al., 2013), results in a rich and varied natural geography. The country encompasses a wide range of landforms, including vast plateaus, plains, mountains, hills, and basins, contributing to the diversity of its physical environment. China’s terrain is high in the west and low in the east, mainly showing a stepped distribution, from the Tibetan Plateau on the first step (average elevation above 4000 m) in the west to the basins and plateaus on the second step (average elevation of 1,000–2000 m) in the center and the plains, hills, and low mountains on the third step (average elevation below 500 m) in the east, with obvious terrain steps and complex topography (Figure 1). Meanwhile, many mountains in China are trending east-west and northeast-southwest, many of which play an important role and are often the dividing line between different topographic and climatic regions. The existence and differences of various topographical features make the combination of natural resources such as soil, moisture, and heat diverse.

Figure 1

Figure 1. Study area and distribution of weather stations (no station data for Taiwan).

China’s vast territory extends approximately 73°E to 135°E in longitude and 18°N to 53°N in latitude. This expansive coverage, combined with significant variations in continental-maritime distances, mountain orientations, and topographic elevations, creates exceptionally complex climate patterns with highly diversified climatic resources. Looking at the type of climate, the eastern part is a monsoon zone (which includes temperate monsoon, subtropical monsoon and tropical monsoon climates), the northwestern part has a temperate continental zone, and the Tibetan Plateau is an alpine zone. Divided by temperature zones, there are the tropical, subtropical, warm temperate, middle temperate, cold temperate, and Qinghai-Tibet Plateau zones. In terms of humid and arid areas, there are humid, semi-humid, semi-arid and arid areas. Where different wet and dry areas may belong to the same temperature zone; different temperature zones may belong to the same wet and dry area. Thus within the same climate type, there are differences in heat and dryness and humidity. The variability conferred by various elements of nature, human activities, and climate change always influences the climatic characteristics of different regions of China.

2.2 Study data

2.2.1 Meteorological data

The meteorological data used in this study were obtained from the China Surface Climate Data Daily Dataset (V3.0), covering observational records from 1966 to 2019. The dataset is accessible through the China Meteorological Administration’s Data Sharing Service Platform (URL: http://data.cma.cn). This dataset includes daily observational data from 699 weather stations across China, covering the period from 1951 to the present. Key elements recorded in the dataset include station-level atmospheric pressure (0.1 hPa), air temperature (0.1 °C), relative humidity (1%), precipitation (0.1 mm), evaporation (0.1 mm), wind direction and speed (0.1 m/s), sunshine duration (0.1 h), and ground surface temperature at 0 cm (0.1 °C). The temperature and relative humidity data are derived from the average of four daily observations taken at 02:00, 08:00, 14:00, and 20:00.

The dataset employs a rigorous three-tiered quality control system (“Station-Provincial-National”) to ensure data accuracy and completeness. Compared to earlier released surface meteorological datasets, this version demonstrated significantly improved data quality, with an effective data rate exceeding 99% for most meteorological elements and accuracy rates approaching 100%. These characteristics make it a highly reliable source for studying long-term climate changes and regional meteorological patterns. Moreover, the dataset’s extensive spatial coverage and long temporal span offer well-preserved historical meteorological records, providing robust support for analyses of climatic variations across different regions and periods. These features render it an invaluable resource for research in fields such as agriculture, climatology, and ecology.

The data mainly involved in the paper are temperature, relative humidity, and precipitation. Due to objective reasons such as instrument failure and environmental factors, there are some stations with missing data, so to ensure data integrity and continuity, processing and screening are required before calculation and analysis. In case of missing data for a particular day from the continuous observations of the temporal period used in this paper, the average of the previous day and the next day is used instead to supplement them; linear interpolation using the values of the same date elements from neighboring stations when the continuous observations of the temporal period used are missing data for multiple days. If the interpolation rate is greater than 0.5% in the site data, the site is deleted. To meet the actual research needed, and eliminate the problems such as insufficient stations or regional errors brought by the division according to different administrative districts, therefore, this paper divides the area according to municipal administrative boundaries, and the distribution of its specific weather station locations are displayed in Figure 1.

2.2.2 Calendar data

Agrometeorological Proverbs, major solar terms, e.g., Wakening of Insects, Major Heat, as well as minor solar terms like the Dog Days, are frequently mentioned (Chen et al., 2022). To facilitate this study, it was necessary to compile and analyze the dates of these solar terms. The calendar data used in this research were sourced from the “Chinese Almanac Network” (https://www.rili.com.cn). The Twenty-Four Solar Terms are defined based on the sun’s position along the ecliptic, reflecting the annual changes caused by Earth’s revolution. Consequently, their dates on the Gregorian calendar are generally fixed, but slight annual variations of 2–3 days may occur. To enable cross-year comparisons, representative dates were assigned to each solar term (Ji et al., 2015). Specifically, if the date varied by 2 days across years, the last day was chosen as the representative date. For variations spanning 3 days, the middle date was selected (see Table 1). Due to the cumulative effects of Earth’s orbital motion, some years witness the phenomenon of double Beginning of Spring, commonly referred to as “double Beginning of Spring of the Lunar Years”. Other years are classified as “normal years” (see Table 2). Furthermore, differences between leap years and common years were addressed. Following the method of Qian et al. (2011), leap year data were adjusted by removing February 29. The value for February 28 was then replaced by the average of February 28 and February 29 to maintain continuity. This approach eliminates potential discrepancies caused by leap years while ensuring that the time series for each year has a uniform length, facilitating more robust data processing and analysis. Through these standardization methods, the solar term dates and yearly time series were harmonized, providing a solid foundation for investigating the scientific validity, regional applicability, and meteorological principles underlying agricultural proverbs.

Table 1

Table 1. The time periods of the twenty-four solar terms over the years and their selected reference dates.

Table 2

Table 2. Type of year and length of Dog Days.

The Dog Days, a minor solar term, represents the hottest and most humid, sultry period of the year. It is divided into the early, middle, and late phases, with the dates determined by the alignment of the Twenty-Four Solar Terms and the traditional Chinese Heavenly Stems (number:10) and Earthly Branches (number:12). The annual Dog Days begin with the Summer Solstice, one of the Twenty-Four Solar Terms in the traditional Chinese calendar. According to the ancient Chinese method of recording time using the heavenly stems and earthly branches, the Dog Days officially starts on the third Geng day following the Summer Solstice. This marks the onset of the first phase, known as Initial Fu. Each Geng day occurs 10 days apart, with the Initial Fu and Final Fu phases each lasting 10 days. However, the specific date of the third Geng day following the Summer Solstice varies annually, leading to differences in the duration of the Middle Fu phase, which can last either 10 or 20 days. Additionally, due to the annual variation in the timing of the Summer Solstice, the start date of the Dog Days differs across years. In summary, the start and duration of the Dog Days vary each year (Table 2), though the period generally falls between July and August (Xu, 2024). Due to the variability of the Dog Days, the study does not assign fixed representative dates for each phase of the Dog Days.

3 Methods

3.1 Least-square fitting

Due to the complexity and variability of climate factors in daily weather changes, temperature fluctuations are often large and difficult to predict. As a result, directly comparing and analyzing temperature data can be challenging, often leading to a lack of clear and direct comparisons between data points (see Figure 2). To address this issue, the article employs the least squares polynomial method (Gao et al., 2021) to fit a curve, highlighting the “RW” characteristic and illustrating the warming trend. Least squares polynomial fitting is a mathematical method designed to find the best approximation of a set of discrete data points by fitting a function. Geometrically, the method seeks a curve that minimizes the sum of squared distances between the data points and the fitted curve, aiming to reflect the basic trend or most closely approximate the variation pattern of the data. Since the fitting function is a polynomial, this method is referred to as polynomial fitting.

Figure 2

Figure 2. Comparison chart of raw temperature data.

This study uses statistical data to obtain two time series of daily average temperatures over multiple years, representing the BSLY and NY, for the period from the Beginning of Spring to the Minor Heat (time period before Dog Days), with a duration of 155 days. Through multiple comparative analyses of the fitting results, it was found that a 5 best polynomial provided the best fit for the warming trend under study, with a correlation coefficient (R²) of approximately 0.90, as confirmed by significance testing. Although the R² value slightly fluctuates for polynomial degrees higher than 5, the marginal benefit of the fitting results gradually diminishes. Therefore, a 5 polynomial fitting is chosen in this study (Figure 3).

Figure 3

Figure 3. Comparison of different degree fitting of polynomial (Note: degree of polynomial, (A) 3, (B) 4, (C) 5, (D) 6).

It is important to note that due to significant differences in climate conditions, topography, and other factors across different regions of China, the warming trends exhibit considerable variation. Therefore, in analyzing the warming trends, this study establishes the following criteria for the cases where the warming rate in BSLY exceeds that in NY (Equation 1).

$\left(d_{\left[\left(k_s/k_n\right)>1\right]}/d\right)\times 100\%>65\%(1)$

In Equation 1, $d_{\left[\left(k_s/k_n\right)>1\right]}$ represents the number of days within a specific period during which the warming rate of BSLY exceeds that of NY, d denotes the total number of days in that period, k_s is the warming rate of BSLY, k_n is the warming rate of NY. This parameter allows for a quantitative comparison of the differences in temperature increase rates and their duration across different types of years.

3.2 Temperature-humidity index

Given the lack of modern precision measuring instruments in ancient times, the “heat” described in the proverb “The heat of Dog Days on double Beginning of Spring of the Lunar Years” primarily refers to the human perception of temperature, rather than just the air temperature values. Perceived temperature is influenced not only by temperature but also by factors such as humidity. Studies indicate that when the temperature falls within a comfortable range for the human body, changes in humidity have little effect on comfort levels. However, when the temperature exceeds or falls below the comfort zone, higher humidity levels can significantly impact the human body, causing discomfort, such as a feeling of stuffiness or chilliness (Ren, 2017). This effect is particularly evident under extreme weather conditions. For example, in the desert regions of northwest China, daytime temperatures can be extremely high, with dry air, while nighttime temperatures rapidly drop, creating significant diurnal temperature variation. In such cases, the changes in both humidity and temperature lead to a marked shift in perceived temperature, resulting in varying sensations of “heat”.

Considering these factors, this study provides a more scientific analysis of the “DDH” characteristic by incorporating the Temperature-Humidity Index (THI) (Zhang C. et al., 2024). The THI integrates the daily maximum temperature, daily minimum temperature, and relative humidity to assess the temperature-humidity conditions and reflect human comfort levels. The concept of the THI was first introduced by Thom as the Discomfort Index (DI) (Thom, 1959), which was later widely adopted by the U.S. National Weather Service to evaluate summer comfort and work hours. The THI is not only applicable in the U.S., but can also be used in regions with latitudes similar to that of the U.S. (Giles et al., 1990), and it has been extensively applied in climate studies in China (Wang and Shen, 1998; Li et al., 2005; Wu et al., 2007). The THI provides a more accurate reflection of human thermal sensation, especially during hot summer months, where it is more sensitive to climatic variations.

This study analyzes the differences in the THI between BSLY and NY during the period from the beginning of spring to the Minor Heat, just prior to the Dag Days period. Specifically, the THI is used to measure the “Degree of Heat” characteristic of “DDH” in different years. By calculating the THI difference between BSLY and NY at various weather stations, this study further evaluates the variations in “Degree of Heat” between the two types of years (Formula 2, 3). The study also proposes a classification standard based on the THI for assessing the “Degree of Heat” and lists the corresponding criteria (Table 3), which quantitatively describe the “DDH” characteristics for different year types. In the context of intensifying global climate change, understanding and quantifying the impact of temperature and humidity changes on human comfort in different regions will be crucial for formulating more effective climate adaptation policies and mitigation strategies.

$THI=K^{-1}{\displaystyle \sum _{i=1}^K}{t}_i-0.55\left(1-K^{-1}{\displaystyle \sum _{i=1}^K}{x}_i\right)\left(K^{-1}{\displaystyle \sum _{i=1}^K}{t}_i-14.5\right)(2)$

$D_j={THI}_j^s-{THI}_j^n(3)$

Table 3

Table 3. Dog days “Degree of Heat” of compliance criteria.

Where, THI represents the Temperature-Humidity Index, t_i denotes the temperature on the ith day (unit: °C), x_i denotes the relative humidity on the ith day (unit: 1%), with i = 1,2 … , K, where K is the study period. D_j represents the difference in THI between two types of years. ${THI}_j^s$ refers to the daily maximum or minimum temperature-based Temperature-Humidity Index for BSLY; ${THI}_j^n$ refers to the daily maximum or minimum temperature-based THI for NY; j = h, l, where h represents the daily maximum temperature, l represents the daily minimum temperature.

4 Results and analysis

4.1 “Rapid warming” characteristic

This study presents four possible scenarios (Table 4) for the data fitting results based on the classification criteria, comparing the “RW” characteristic observed in the Beginning of Spring to Minor Heat period (time period before Dog Days) in BSLY years with the normal years. Combined with the proverb “The heat of Dog Days on double Beginning of Spring of the Lunar Years” compliance with the regional situation map (Figure 4) shows the geographic areas that meet and don't meet the characteristic of “RW”, it can be seen that there is faster warming of BSLY than NY in most of the regions nationwide from 1966 to 2019, and the area of compliance accounted for 60.6% of China’s area, where the warming temporal periods all occurred before the Spring Equinox, manifesting as different warming amplitude, durations, and temporal periods, and the main reason for the difference situation is the difference in the climate type and geographical topography to which they belong. The “RW” characteristic is divided as follows.

1. As shown in Figure 4, the regions exhibiting a pronounced “RW” characteristic are primarily located in southern China and the middle and lower reaches of the Yellow River, which together account for 35.8% of China’s total land area. In these regions, during the periods from the Beginning of Spring to the Awakening of Insects (as shown in Figure 5A) and from the Beginning of Spring to the Spring Equinox (as shown in Figure 5B), the number of days where the warming rate of the BSLY exceeds that of NY accounts for more than 65% of the total days. This indicates that in these regions, the temperature rise in spring is faster, particularly due to the influx of warm, moist air from the ocean, which causes rapid warming (as shown in Figure 5A, e-m, days 1–14). Notably, at the Rain Water solar term (the 15th day after the Beginning of Spring, as shown in Figure 5: (A), m), vegetation begins to sprout. As the ancients observed, “The east wind thaws the ice, melting and turning it into water, which then becomes rain, hence the name Rain Water.” This natural phenomenon reflects the climate characteristics of spring: with the input of warm air, the weather gradually warms, ice and snow melt, and precipitation increases, the warming speed during the Grain Rain solar term slows down. Scientifically, this phenomenon is closely related to the interaction between oceanic and continental air masses. During the Grain Rain period, the warm, moist air mass from the ocean becomes more active and engages in frequent and intense confrontations with the cold air masses from the continent. This interaction between the air masses not only causes fluctuations in temperature but also creates a boundary, or frontal zone, where the cold and warm air masses meet. This frontal zone leads to an increase in precipitation and a temporary drop in temperatures (Liang et al., 2023) (as shown in Figure 5: (A), m-n, days 15–22), as the competing air masses exert their influence on the region’s weather patterns.

Table 4

Table 4. Warming result division.

Figure 4

Figure 4. Regional conformity types for “The heat of Dog Days on double Beginning of Spring of the Lunar Years” proverb.

Figure 5

Figure 5. Temperature trend map of regions with strong conformity to the warming pattern (Note: Taking Huzhou, Zhejiang Province, as an example). (e, m, n, f) denote specific time points as defined in the text. (A) Beginning of Spring - Awakening of Insects. (B) Beginning of Spring - Spring Equinox.

However, as the Awakening of Insects solar term begins, marking the first phenological period of the Twenty-Four Solar Terms, most regions experience the “season suitable for cultivation.” At this stage, precipitation decreases compared to the Rain Water solar term, and temperatures enter a second round of accelerated warming (as shown in Figure 5: (A): n-f period, days 22–31, (B): n-f period, days 22–45). Two periods that meet the criteria are observed in this region, the cause of this phenomenon can be attributed to the influence of the monsoon system (Chen et al., 2022). The summer monsoon is primarily composed of the southeast monsoon from the Atlantic and the southwest monsoon from the Indian Ocean, which first make landfall in the region in early spring. Compared to other areas, the monsoon arrives earlier and stays longer in this region. As a result, in BSLY, especially during the spring, the rapid arrival of warm and moist air and its prolonged influence lead to a faster rise in temperature and a longer duration of the warming process. Therefore, during BSLY, this region experiences a faster and longer period of temperature increase compared to other areas.

2. In Figure 4, the regions with “RW” characteristic in moderate degree mainly include Xinjiang, Gansu, and western Inner Mongolia, accounting for 21.6% of China’s area. In BSLY, the proportion of days when the slope of the warming curve exceeds that of NY is greater than 65%, and this occurs only during the period from the Beginning of Spring - Awakening of Insects. (Figure 6). This region has a temperate continental climate, which is far from the ocean and controlled by continental air masses all year round, resulting in hot summers with little precipitation and low winter temperatures due to Siberian High (Ding, 1990; Zhu et al., 2019; Huang et al., 2024). This region is located in the middle of the Asian and European continent, in early spring, part of the North Atlantic Current (Kuang et al., 2009) from the west coast of the continent will reach here across the flat European continent, increasing temperatures (Figure 6, e-m points, 1–12 days), yet the warming period is still influenced by the Siberian High (Li et al., 2024), which decreases temperatures (Figure 6, m-n points, 12–18 days). However, with the weakening of the Siberian High (Li et al., 2024) in early spring and the blockage of cold currents by topography such as the northwest-southeast trending Altai Mountains, the region experiences a slight, short-term temperature increase during the Beginning of Spring to Awakening of Insects period in BSLY.

3. In Figure 4, the regions with weak conformity of the “RW” characteristic mainly include Beijing, Tianjin, Liaoning, etc., accounting for 3.2% of China’s area. In BSLY, the period from the Beginning of Spring - Spring Equinox is the only time frame during which the proportion of days when the slope of the warming curve exceeds that of normal years is greater than 65% (Figure 7B). The region belongs to temperate monsoon climate, simultaneous rain and heat, influenced by the marine southeast monsoon, sufficient precipitation, but relative to the southern region in early spring is still influenced by cold currents from high latitudes Siberia (Huang et al., 2024), under the combined influence of the two air currents, the warming in the Rain Water stage is relatively slow (Figure 7A: m-n points, 14–25 days, (B): m-n points, 14–25 days), the warming takes a long time, the warming amplitude is slighter relative to regions with moderate and strong compliance (Figure 7A: m-f, 14–31 days). The warming trend becomes apparent only when considering the entire Beginning of Spring to Vernal Equinox period.

4. Figure 4 indicates certain regions that do not meet the 65% classification standard (as shown in Figure 8) for the “RW” characteristic. These deviations are likely influenced by local topography and climatic conditions. The affected areas primarily include Heilongjiang, Jilin, eastern Inner Mongolia, the Qinghai-Tibet Plateau, and southern Yunnan, collectively covering 32.4% of China’s total area. Among them, in Jilin, Heilongjiang, eastern Inner Mongol, etc., the influence of the Siberian High (Huang et al., 2024) from the high-latitude in winter, cold and dry, while summer is affected by the southeast monsoon, high temperature and rain. Compared to other regions, the higher latitude of this area results in persistent influence from cold northwesterly monsoons originating from high-latitude regions after the Beginning of Spring. Simultaneously, the northeast-southwest-oriented Changbai Mountains block the warm and moist southeast airflow from the ocean, delaying its arrival in this region. These factors collectively contribute to minimal differences in temperature rise between the two types of years following the Beginning of Spring. These factors result in minimal differences in temperature increase between the two types of years after the Beginning of Spring. In addition, the Qinghai-Tibet Plateau (Danzeng et al., 2024), including Tibet and most of Qinghai, falls within a high-altitude cold region. Due to the high elevation, warm-moist air currents from the ocean have difficulty ascending, resulting in no significant warming trend during the early stages compared to other regions. The southern Yunnan region, located in a low-latitude tropical valley (Wang et al., 2024), is characterized by a lack of winter and relatively stable temperature variations. As a result, there is little difference between years, and the “RW” characteristic in BSLY is not as pronounced compared to normal year.

Figure 6

Figure 6. Temperature trend map of regions with moderate conformity to the warming pattern (Note: Taking Altai, Xinjiang Uyghur Autonomous Region as an example).

Figure 7

Figure 7. Temperature trend map of regions with weak conformity to the warming pattern (Case Study: Shenyang, Liaoning). (m, n, f) denote specific time points as defined in the text. (A) Beginning of Spring - Awakening of Insects. (B) Beginning of Spring - Spring Equinox.

Figure 8

Figure 8. Temperature trend map of regions not conforming to the warming pattern (Case Study: Harbin, Heilongjiang).

4.2 “Dog Days Heat” characteristic

This article categorizes the differences in the “Degree of Heat” during the Dog Days period between BSLY and NY from 1966 to 2019 according to the degree of conformity with the characteristics of “DDH,” dividing them into three categories (as shown in Figure 4). In the figure, the regions showing a strong degree of conformity to the “DDH” characteristic represent areas in “BSLY” that experience more intense “DDH” heat compared to “NY”. These areas are primarily located in China’s subtropical monsoon zone (Wang Liping et al., 2021) (one of the five major climatic regions), which is basically in the southern part of China’s geographical division, accounting for 67.2% of the southern region. These regions are influenced by the warm and moist airflows brought by the Pacific subtropical high, resulting in high summer temperatures and frequent rainfall. In July, the average temperature is approximately 28 °C, with certain areas surpassing 29 °C. Additionally, during July and August, the region is under the influence of the subtropical high pressure, resulting in frequent sunny days, long hours of sunshine, and a higher frequency of high temperatures. The research by Kong (2019) also indicates that the number of sauna days (characterized by prolonged high temperatures and “extended standby” conditions) in China shows a clear spatial differentiation, with higher values in the southeast and lower values in the northwest, and minimal differences across different decades. This phenomenon reveals the spatial imbalance in regional climate change in China, as well as the significant impact of regional climatic factors on the frequency and intensity of sauna days. In addition, the study by Xia et al. (2011) on the climate zoning of the Dog Days also points out that the Dog Days and Quasi-Dog Days areas are located south of 40°N in China, primarily influenced by the summer monsoon. These regions are relatively more aligned with the climatic conditions required by the second part of the traditional saying about summer “heat,” making the subtropical areas in southern China particularly suitable for these conditions.

To comprehensively explore the factors behind the “DDH” in BSLY compared to NY in southern regions, and taking into account that rainfall can impact on temperature and relative humidity to a certain degree, the study analyzes and contrasts rainfall data during Dog Days time period for both types of years from 1966 to 2019 within the region. The results indicate that the rainfall during the Dog Days period in NY is generally higher than in BSLY. However, a detailed comparison across decades reveals that in the 1980s, the Dog Days period rainfall in BSLY exceeded that of NY (Figure 9). Specifically, the average rainfall during this period in BSLY was 219.5 mm, compared to 189 mm in NY. The anomalously high rainfall in BSLY during the 1980s may be attributed to the EI Niño phenomenon in 1982 (Gu et al., 2018; Wang Yini et al., 2021). The relatively low temperature will result from more precipitation in short periods. Additionally, the long-term average relative humidity during Dog Days period from 1966 to 2019 shows minimal differences between the two types of years in southern China (78.5% in NY and 78.4% in BSLY). Thus, the Temperature-Humidity Index suggests that rainfall may play a key role in amplifying the “DDH” during BSLY compared to NY across much of the southern region.

Figure 9

Figure 9. A comparison of rainfall during Dog Days across different decades in southern regions. (Note: The decade includes 10 years: Example 1970–1979, and so on. includes 1966–1969.)

In Figure 4, regions with weak conformity to the “DDH” characteristic (covering 11% of the southern region) and those that do not conform (covering 12% of the southern region) are collectively identified as areas that don't satisfy the “DDH” characteristic. Compared to areas where climatic conditions don't meet the characteristics of “DDH,” both areas with weaker and stronger conformity to these characteristics are located in the southern region. However, due to the influence of topography and terrain (Zheng et al., 2013), these areas in some cases do not fully exhibit the characteristics of “DDH.” Among the areas with weak conformity mainly consist of two non-conforming parts: one includes regions influenced by mountain ranges, such as Jiangxi and Fujian, which are affected by the Wuyi Mountain range; Hunan and Hubei, influenced by the Xuefeng and Wushan mountain ranges; Ningguo City in Anhui Province, where the Tianmu Mountain exists in the southeast and the Huangshan Mountain range in the west; and Yangjiang City in Guangdong Province, which has the Tianlu Mountain in the northeast and the Yunwu Mountain in the northwest and is surrounded by mountains and water. The regions that do not exhibit the characteristics of “DDH” may be influenced by mountains, whose orientations are mostly northeast-southwest. This topography often blocks warm and moist airflows from the ocean, limiting the flow of air and the distribution of rainfall. In mountainous areas, rainfall patterns are usually significantly influenced by the terrain. Generally, mountains receive more rainfall than flatlands, and the windward slopes receive more rainfall than the leeward slopes (Liu et al., 2017). For example, Huangshan and Tunxi in Anhui Province are close to each other, but the average annual precipitation in Huangshan is 633 mm more than Tunxi (2387 mm in Huangshan and 1754 mm in Tunxi), which results in a year-round lower temperature in Huangshan compared to the surrounding area. Secondly, the area affected (Zheng et al., 2013) by the type of terrain, in the Guangxi Zhuang Autonomous Region’s Laibin City, Baise City, Jiangxi Province’s Jingdezhen City, etc., the topography of the area is mostly surrounded by high, middle low basin shape, and relatively little precipitation due to the closed topography, surrounded by high mountains, the oceanic warm and humid airflow is difficult to enter.

5 Discussions

Based on the analysis results of the two parts of the proverb in the article, it was found that conforming regions of the proverbs used in the article are overwhelmingly located in the southern region of the geographical zoning of China (Figure 4). These regions account for 15.9% of China’s total area and 67.2% of the southern region. And the article selected “The heat of Dog Days on double Beginning of Spring of the Lunar Years” proverb is mainly spread in the Jiangsu, Zhejiang, and Shanghai area, Jiangsu, Zhejiang, and Shanghai area belong to the southern region, in the subtropical monsoon area (Wang Liping et al., 2021), rain and heat at the same time, the four seasons are distinct. The southern region has been the land of plenty since ancient times, the granary of Jiangnan, and farming civilization using the solar terms was relatively prosperous. This paper analyzes the meteorological knowledge behind the proverbs based on 54 years of meteorological data in China, and finds that the proverbs circulated in Jiangsu, Zhejiang, and Shanghai regions are consistent with the corresponding science, moreover, the analysis process of the proverbs shows that in the southern Yunnan river valley region, there is no winter all year round and the climate change is not significant, while in Jiangsu, Zhejiang and Shanghai regions, the four seasons are distinct, and the climate of the two regions has obvious differences, so in the verification result, the southern Yunnan river valley region does not conform to the proverb “The heat of Dog Days on double Beginning of Spring of the Lunar Years”, and also shows that the applicability of the proverbs has regional characteristics. Therefore, based on various research findings, it can be concluded that the majority of the southern region of China, along with its climatic conditions, relatively meets the meteorological requirements outlined in the proverb. The analysis of the “The heat of Dog Days on double Beginning of Spring of the Lunar Years” proverb in this article reveals that China’s vast territory is characterized by diverse climates across different regions. The proverb circulating in different places may only apply to areas with the same climate type, as well as the differences in topography and terrain may also have some influence to it, thus the proverb has certain regional and limitations.

This study examines the two characteristics of the proverb (The heat of Dog Days on double Beginning of Spring of the Lunar Years) “RW” and “DDH” to verify the scientific validity and regional applicability of the proverb. The study found that the regional classification of the proverb “RW” and “DDH” characteristics showed that the regions that conformed to them basically belonged to the southern region of China (Figure 4). Among them, the characteristic of the proverb that BSLY “RW” than NY has different results in different regions, depending on the degree of conformity, there is a difference between the warming period being within 31 days after the Beginning of Spring or within 46 days, and the difference may be due to the different climate types and geographical topography to which the different regions belong. In addition, in the characteristic of the proverb “DDH”, BSLY is stronger than NY in terms of “Degree of Heat”, which is mainly located in the southern region, covering 67.2% of the southern region. This is because the subtropical monsoon zone in southern China, in contrast to other regions, aligns with the climatic conditions necessary for the “DDH” characteristic as described in the proverb. Additionally, the proverb “RW” characteristic of the study found that in most of the regions in the early warming period, there will be a certain degree of cooling after the warming of the Beginning of Spring, which is often referred to as “late spring coldness” (Figure 5, 15–22 days), in which BSLY temperature fitting curve shows more obvious, NY temperature fitting curve shows not obvious relatively stable, and the cause of this cooling phenomenon or fluctuation phenomenon needs to be further explored. In a study of “DDH” characteristic of the proverb, it was also found that with global warming, the annual maximum temperature in most areas of China in recent decades began to occur during Minor Heat (Kong et al., 2021). In the latest Intergovernmental Panel on Climate Change (IPCC) sixth Report (IPCC, 2021), it is pointed out that the global average surface temperature has risen by 1 °C compared to pre-industrial levels. According to projections for the average temperature change over the next 20 years, global temperatures are likely to rise to or exceed 1.5 °C. The intensifying global warming directly affects the climate system, with a key manifestation being the increased frequency of extreme heat events (Zhou and Zhai, 2023). So the maximum temperature in the future may show an in advance phenomenon. Therefore, under the climate change, what kind of reasonable adjustment needs to be made to the agrometeorological proverbs in the future, how to combine them with modern science and technology by referring to the ancient experience, and how to modify and supplement them with the time, so that they can continue to be useful in modern agricultural production, also need to be further studied.

The findings of this study offer distinct scientific and practical contributions. On a scientific level, the research establishes a data-driven framework to quantitatively validate Traditional Ecological Knowledge. By successfully linking the lunar calendar phenomenon of Double Beginning of Spring to measurable thermal characteristics (Rapid Warming and Dog Days Heat), the study provides empirical evidence that moves beyond anecdotal accounts. This analytical approach can be applied as a template to systematically assess the validity of other agrometeorological proverbs worldwide. From a practical standpoint, the results underscore the particular value of the lunar calendar and its associated proverbs for agricultural communities in developing regions with limited access to modern climate data. In the absence of high-resolution meteorological monitoring and advanced forecasting, these culturally rooted sayings function as an accessible, cost-free, and intuitively understood tool for planning farming activities. The demonstrated connection between the lunar calendar and seasonal climate dynamics in southern China suggests that it can offer reliable guidance for critical decisions, such as optimal sowing and harvest times. This inherent connection to local environmental cycles presents a key advantage over the purely astronomical solar calendar, especially in resource-limited settings.

Several considerations emerging from this work highlight productive pathways for future inquiry. First, our validation concentrated mainly on thermal and humidity variables. Expanding the analytical scope to include factors like extreme rainfall, solar radiation, and wind dynamics would yield a more integrated perspective on the agroclimatic intelligence contained in proverbs. Second, while our regional analysis confirms broad climatic correlations, the practical effectiveness of these proverbs depends on local context. Subsequent research should prioritize fine-scale, participatory studies with farmers to document how these sayings are actively used in management choices and to measure their impact on productivity and resilience. Finally, the accelerating pace of climate change introduces uncertainty into the stability of the historical relationships underpinning these proverbs. As baseline climate patterns evolve, the predictive power of traditional knowledge may require recalibration. A promising direction, therefore, is to create adaptive frameworks that merge the heuristic value of proverbs with contemporary climate data and forecasting tools, thus refining this cultural heritage for modern risk management applications.

6 Conclusion

This study, leveraging decadal meteorological datasets (1966–2019) on temperature, relative humidity, and rainfall, employs polynomial fitting and the Temperature-Humidity Index (THI) to decode the scientific basis of the agrometeorological proverb “Hot Dog Days in Lunar Years with Double Beginning of Spring”. Comparative climate modeling yields three key insights.

6.1 Proverbial model applicability and climate-resilient agriculture

The proverbial model demonstrated significant consistency with its traditional circulation zone (Jiangsu-Zhejiang-Shanghai) and extends to 15.9% of China’s territory (67.2% of southern regions), highlighting its adaptive capacity under climate change. Analysis of the “RW” phenomenon reveals that BSLY exhibit 23.5% more pronounced spring warming trends than NY, with RW zones covering 60.6% of China. Warming periods (31–46 days post-Beginning of Spring, all preceding the Spring Equinox) exhibit spatiotemporal dynamics: southern China and the middle-lower Yellow River show intense warming, while Xinjiang/Inner Mongolia demonstrate moderate responses. For DDH, 67.2% of southern China’s subtropical monsoon zones—characterized by synchronous temperature-rainfall increases—validate the proverb’s climatic predictability, underscoring its utility as a low-cost climate risk indicator for agroecosystems.

6.2 Integrating traditional knowledge into adaptive agricultural strategies

Scientific validation confirms that the empirical rules embedded in the proverbs largely align with region-specific atmospheric thermal-humidity coupling mechanisms. As adaptive tools rooted in millennial agricultural practices, Chinese Agrometeorological Proverbs require iterative scientific refinement under global warming. This study proposes a “time-adaptive, location-specific” framework for upgrading traditional models, enabling their integration into climate-smart practices. Such integration of ancient wisdom with modern climate science enhances their utility in guiding agrifood systems, reducing climate risks, and optimizing resource utilization.

6.3 Localized knowledge as complementary solutions for resilient agrifood systems

While proverbial models exhibit climate-zone specificity, their role in community-level adaptation is indispensable. As culturally embedded knowledge systems, they offer cost-effective risk mitigation for smallholder farmers—particularly in data-scarce regions where high-tech climate services are inaccessible. This study highlights the need to recognize traditional models as complementary to modern agronomy, advocating their inclusion in multi-tiered adaptation strategies. Such integration fosters resilient agrifood systems in developing regions, providing a scalable pathway toward sustainable agricultural transformation.

Data availability statement

Publicly available datasets were analyzed in this study. This data can be found here: URL: http://data.cma.cn, China Surface Climate Data Daily Dataset (V3.0).

Author contributions

SC: Conceptualization, Methodology, Writing – original draft. YH: Data curation, Validation, Investigation, Writing – review and editing. CS: Formal Analysis, Investigation, Software, Writing – review and editing. BS: Data curation, Formal analysis, Funding acquisition, Writing – review and editing. YS: Funding acquisition, Supervision, Writing – review and editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by National Key Research and Development Program of China [No. 2020YFA0608501], Key Project of Jiangsu Aviation Technical College [No. JATC250103], National Key Research and Development Program of China (2024YFE0214000) and Zhenjiang Science & Technology Program (Grant No. NY2024020).

Acknowledgments

I sincerely thank my supervisor, YS, for her expert guidance and unwavering support, which were vital to this research. I also extend my deepest gratitude to my team, funders, and family. Their collaboration, funding, and encouragement made this study possible.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

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AppendixGlossary of technical terms