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ABSTRACT Drought is the primary driver of wildfires in humid regions, and the main drought drivers for wildfire occurrence and spread vary across different humid climatic areas. This study

explores the suitability of different drought descriptions for wildfires under various humid temperate climates in Japan. Based on wildfire data from 1995 to 2012, statistical and

correlation analyses were conducted to examine the performance of effective humidity (EH) and soil moisture (SM) as indicators of atmospheric and soil drought. EH is used for nationwide

wildfire and drought warnings in Japan. The results show that EH is significantly influenced by seasonal and regional factors, with its ability to assess drought for wildfire varying

accordingly, whereas SM demonstrates a more consistent ability to assess drought across different seasons and regions. Correlation analysis revealed that atmospheric drought better explains

the drought conditions for wildfire ignition in 11 prefectures, mainly concentrated in the northern regions along the Sea of Japan. In contrast, the correlation coefficients for SM were

higher in 33 prefectures, particularly along the Pacific coast, indicating that soil drought better explains the drought conditions for burned areas in these prefectures. SIMILAR CONTENT

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access 05 July 2023 Keywords Wildfire characteristics; Soil drought; Atmospheric drought; Humid temperate climate; Japan INTRODUCTION The impacts of wildfires are varied, encompassing

impacts on biodiversity, ecosystem distribution, atmospheric chemistry, and loss of life. The species composition and community structure are influenced by the number of recurrent fires,

with a high fire frequency potentially inhibiting vegetation regeneration1. Frequent wildfires may result in soil degradation and changes in soil salinity2. Wildfires are major producers of

atmospheric trace gases and aerosols, which may have a significant influence on the atmosphere’s radiative balance and pose substantial health hazards3. Moreover, wildfires also result in

economic losses and casualties4. Research suggests that wildfire risks in humid areas are likely to increase, with future climate change potentially exacerbating losses in these regions5,6.

Due to the increase in warm and dry weather caused by climate change, South Korea experienced an unexpected large-scale wildfire in March 2022, burning 22,477 hectares7. This resulted in the

production of large amounts of ultrafine aerosols and an increase in air pollution levels by more than 20 times compared to pre-fire levels. In recent years, multiple wildfire incidents

have occurred in Liangshan Prefecture, Sichuan Province, China. The wildfires in 2019 resulted in 31 deaths, while in 2020, the wildfires burned an area of over 3,000 hectares, causing 19

fatalities8. Therefore, evaluating suitable drought descriptions for humid temperate regions will help to better assess wildfire risk in those areas. Wildfires are complex phenomena

influenced by factors such as climate, weather, topography, vegetation characteristics, and human activities9,10,11. The occurrence of wildfires requires dry fuel and an ignition source.

Human activities and lightning strikes are significant sources of ignition for wildfires. Different types of vegetation exhibit distinct burning characteristics. For instance, shrublands and

grasslands in Mediterranean regions are more prone to wildfires12. Climatic and weather conditions indirectly affect the spread of wildfires by reducing fuel moisture and thus providing

more fuel for wildfires, while strong winds directly affect the rate and direction of fire spread. Topographic factors indirectly affect fire spread by influencing fuel moisture and

distribution, including elevation, slope, and aspect, especially in mountainous areas or areas with complex terrain. Therefore, even within the same region, the main factors affecting the

occurrence and burned area of wildfires may differ. Wildfires in California are more likely to occur under high temperature and high vapor pressure deficit13, but the combination of hot,

dry, and windy weather and dry soil conditions strongly correlates with large wildfire activities14. In Japan, research on wildfires is relatively limited, primarily focusing on prefecture-

or city-level analyses15,16, but the main drought drivers affecting the frequency of wildfires and burned areas across different climatic regions in Japan are not known. On the other hand,

the driving factors of wildfires vary in different climatic regions. In the humid areas of the Inner Mongolia Autonomous Region, China, high annual rainfall results in a higher fuel moisture

content, while high temperatures mainly cause a reduction in fuel moisture in the region, which is considered the leading factor for wildfires17. The specific humidity, vapor pressure, and

Normalized Difference Vegetation Index (NDVI) are the primary driving factors of wildfires in Pakistan18. High temperatures, strong surface winds, and low relative humidity significantly

influence wildfire behavior in Mediterranean climatic regions, including California, southern Europe, Africa, and southern Australia9,19,20. The frequency of wildfires in Siberian larch

forests is strongly correlated with incoming solar radiation21. Japan has a humid climate, which extends from north to south and is influenced by monsoons and ocean currents, leading to

various hydrological conditions. Specifically, the regions along the Sea of Japan are generally humid during winter, especially in the northern areas with abundant snowfall, while summers

are comparatively drier. In contrast, the regions along the Pacific experience relatively dry conditions in winter with lower precipitation levels, while summer is humid and rainy.

Presently, the assessment of nationwide drought and wildfire alerts in Japan is based solely on effective humidity and wind speed. However, considering the link between soil drought and

wildfires (Fig. 1), the mechanisms driving drought wildfire in various climatic regions of Japan and the appropriate assessment of drought remain unclear. Fuel resources are abundant and

spatially continuous in humid temperate areas, but the combustibility of fuel is low. In these areas, wildfires are often driven by drought, as drought reduces fuel moisture, affecting fuel

combustibility and thus controlling wildfire activity22. In the Tohoku region of Japan, as a result of low winter rainfall and strong winds, wildfires occurred simultaneously in three

prefectures on the same day in May 2017. The burned area of the wildfire in Kamaishi city, Iwate Prefecture, was larger than the total burned area in Japan in 201623. Therefore,

understanding the mechanisms of fuel moisture content (FMC) variation helps clarify the interrelationship between drought and wildfires in Japan. This study defines atmospheric drought and

soil drought based on the hydrological processes that affect fuel moisture content (Fig. 1). When the vapor pressure on the fuel surface differs from the vapor pressure in the surrounding

air, vapor exchange occurs. High temperatures and low humidity can reduce fuel moisture content by enhancing vapor exchange. A study24 reported that short-term (1–2 weeks) periods of

unusually high temperatures and low atmospheric humidity can lead to rapid fuel drying. Accordingly, the reduction in fuel moisture due to enhanced vapor exchange is defined as atmospheric

drought. Studies have shown that water can be transported from the soil layer to the duff layer by capillary action and evaporation, thereby influencing the fuel moisture content25,26. In

contrast, low soil moisture inhibits capillary action and evaporation, resulting in the drying of surface fuels. The moisture content of dead woody fuel in the Sierra Nevada Mountains is

notably influenced by soil moisture, and the incorporation of soil moisture information can also enhance the spatial heterogeneity of the probability of ignition26. Furthermore, the memory

of soil moisture is closely related to land‒atmosphere feedback processes. Several studies have indicated a correlation between decreased soil moisture and increased wildfire risk, which may

be associated with reduced snowfall and earlier snowmelt27,28. Consequently, drought caused by a reduction in fuel moisture due to soil moisture is defined as soil drought. Wildfires in

humid areas are generally small in Japan, the average area burned by each wildfire from 1995 to 2020 was approximately 0.52 ha29. Remote sensing is an effective tool for wildfire

identification and characterization in a variety of ecosystems, and it is capable of providing wildfire information in areas where wildfire data are lacking17,30. However, it is still

difficult to provide a more accurate wildfire dataset for humid areas using remote sensing technology due to the limitations of remote sensing image quality and spatial/temporal resolution.

Research has shown that wildfires in the Tohoku region of Japan typically do not constitute crown fires, and it is challenging to determine their occurrence and burned area using satellite

data31. Japan produces detailed wildfire reports, which record detailed information on each wildfire since 1995, including the basic burned area, date and time of initiation, and ignition

and firefighting sources. Therefore, this study conducted wildfire analysis in different climatic regions of Japan based on wildfire reports. This research selected the effective humidity

(EH) and soil moisture (SM) from a land surface model as indicators of atmospheric and soil drought. Effective Humidity is calculated based on relative humidity, which represents the ratio

of the actual water vapor content in the air to the maximum water vapor content at a given temperature. EH indirectly reflects the moisture status of the atmosphere. Moreover, EH serves as a

crucial indicator in Japan’s nationwide fire alerts. Despite the country’s diverse and humid climate, EH is extensively utilized in fire weather reports across various prefectures to

evaluate and warn of fire risks. This widespread application underscores EH’s practical utility in assessing both drought and fire risk in Japan. Soil moisture information has significant

potential for understanding, assessing, and predicting wildfire risks. For example, a week before the Camp Fire in California, NASA’s SMAP satellite observations revealed abnormally low soil

moisture levels in northern California32. In the Australian fire danger rating system, the Keetch–Byram Drought Index (KBDI) is utilized to assess the fire risk in dry eucalyptus forests.

The KBDI measures the moisture deficit in organic and mineral soil layers by estimating the net effect of precipitation and evapotranspiration, but it does not account for factors such as

wind speed, radiation, vegetation, and soil properties. Process-based models simulate soil moisture by accounting for complex hydrological processes, including climate, topography, and

vegetation effects, while also overcoming the limitations of insufficient historical in situ and satellite measurements of soil moisture. Consequently, this study conducted a statistical

analysis of wildfire incidence rates in different prefectures of Japan within varying EH and SM threshold ranges. Due to climate and vegetation variations across regions, wildfires exhibit

distinct temporal characteristics in Japan: wildfires mainly occur in spring. In this research, the fire season was defined based on the number of wildfires. Then, an assessment of suitable

drought descriptions for different prefectures was conducted by evaluating the correlation between wildfire (occurrence/burned area) and drought indices (SM/EH) during the wildfire season.

This study aimed to (1) elucidate the seasonal and spatial characteristics of the interrelationships between soil drought/atmospheric drought and the occurrence of wildfires, (2) evaluate

the ability of effective humidity to explain drought (for which a fire warning system for Japanese fire alarms was used), (3) and assess the primary drought-driven type influencing the

wildfire frequency and burned area in different regions of Japan during the wildfire season. In summary, this study provides new insights into wildfire risk assessment in Japan while also

serving as a reference for exploring the drought-driven factors of wildfires in humid temperate climatic regions. RESULTS STATISTICAL ANALYSIS OF WILDFIRE OCCURRENCE BASED ON EH AND SM

THRESHOLDS The incidence of wildfires within different EH and SM thresholds was calculated for different seasons in each prefecture in Japan. The seasons are defined as follows: spring

corresponds to the months of March, April, and May; summer corresponds to June, July, and August; autumn corresponds to September, October, and November; and winter corresponds to December,

January, and February. The results indicated that EH conditions for wildfire occurrence exhibited distinct seasonal variations across prefectures. Some prefectures had relatively small

differences in EH conditions for wildfire occurrence, such as Hokkaido (PC1) and Niigata (PC15) (Fig. 2a, b). In this study, \(\:{T}_{EH}^{80}/{T}_{SM}^{80}\) is defined as the EH/SM

threshold at which 80% of the fires occur within a season in the prefecture. In addition, \(\:{{D}_{EH}^{80}/D}_{SM}^{80}\) is defined as the proportion of days within a given season where

the EH/SM falls below the defined threshold. Most wildfires in Hokkaido occurred at EH values of 70–80%, with \(\:{T}_{EH}^{80}\:\)being less than 74% in spring, 82% in summer, 77% in fall,

and 80% in winter. The \(\:{T}_{EH}^{80}\) in Niigata Prefecture was 68% in spring, 76% in summer, 74% in fall, and 76% in winter. In contrast, in some prefectures, there was a large

variation in the EH conditions under which wildfires occurred in different seasons, such as in Chiba (PC12) and Shizuoka Prefectures (PC22) (Fig. 2c, d). In Chiba and Shizuoka Prefectures,

most of the wildfires occurred at EH values below 60% in winter, 60–70% in spring, and 70–80% in summer and fall. Compared with the results for EH, the seasonal variations in the wildfire

incidence rate within the different SM thresholds were relatively small (Fig. 2e, f, g, h). In Hokkaido and the Niigata and Shizuoka Prefectures, wildfires were mostly concentrated within an

SM of 0.7–0.8, regardless of season. In Chiba Prefecture, the frequency of wildfires was greater at SM values less than 0.7. To assess the spatial characteristics of seasonal variations in

Japan, the EH and SM thresholds were calculated for 80% of the wildfire incidence in each prefecture for each season. In addition, the proportion of days below the corresponding EH threshold

and SM threshold were calculated for each season (Fig. 3 and Fig. 4). There were significant spatial differences in winter \(\:{T}_{EH}^{80}\), with higher \(\:{T}_{EH}^{80}\) in the

northern part of Japan, mainly along the Sea of Japan. In the Tohoku and Chugoku regions along the Sea of Japan, \(\:{D}_{EH}^{80}\) was mostly less than 0.4, and the results indicated that

even though the majority of the wildfires occurred under high EH conditions, they still occurred during the relatively low EH period of the season. However, in other areas, especially in

fire-prone areas (Hiroshima (PC34), Okayama (PC33), and Hyogo Prefectures (PC28)), high \(\:{T}_{EH}^{80}\) and high \(\:{D}_{EH}^{80}\) suggest that EH had less influence on wildfire

occurrence in these areas during the winter. In spring, \(\:{T}_{EH}^{80}\) was relatively high in northern Japan. However, in Hokkaido and the Tohoku and Chugoku regions along the Sea of

Japan, despite the relatively high \(\:{T}_{EH}^{80}\), it corresponded to a lower EH period of the spring, with \(\:{D}_{EH}^{80}\) around 0.4. Across all prefectures of Japan,

\(\:{T}_{EH}^{80}\) was higher in the summer and fall. However, during the summer, although most prefectures experienced wildfires under high EH conditions, the majority of these wildfires

still occurred during periods when EH was relatively low, with \(\:{D}_{EH}^{80}\) generally below 0.5. Figure 4 shows that although the seasonal differences in \(\:{T}_{SM}^{80}\) were

relatively small, there were still significant spatial differences. In winter, a higher \(\:{T}_{SM}^{80}\) in northern Japan indicated that most wildfires occurred under high SM conditions,

especially in the coastal region of the Sea of Japan. In the Tohoku and Chubu regions along the Sea of Japan, \(\:{D}_{SM}^{80}\) was greater than 0.7, which indicated that SM did not

affect wildfire occurrence in these regions. In contrast, in the southern region of Japan (including Hiroshima, Okayama, and Hyogo Prefectures), the \(\:{T}_{SM}^{80}\) values were lower,

and the \(\:{D}_{SM}^{80}\) values were also lower. The spatial distribution of \(\:{T}_{SM}^{80}\) in fall is similar to that in winter, with a higher \(\:{T}_{SM}^{80}\) in the northern

part of the prefecture; however, most prefectures in Japan had a smaller \(\:{D}_{SM}^{80}\). The spatial distribution of \(\:{T}_{SM}^{80}\) was similar in spring and summer, with higher

\(\:{T}_{SM}^{80}\) values in the Chubu region, the western part of the Tohoku region, the southern part of the Kinki region, and the northern part of the Kyushu region. However,

\(\:{D}_{SM}^{80}\) was small in all prefectures, ranging from 0.27 to 0.54 in spring and 0.22 to 0.62 in summer, and less than 0.4 in most prefectures, suggesting that most of the wildfires

occurred in the relatively low SM period of spring and summer, including in the northern part of Hokkaido and the coastal region of the Sea of Japan. Figure 5 shows the frequency

distributions of \(\:{T}_{EH}^{80}\) and \(\:{T}_{SM}^{80}\) for all prefectures of Japan in each season, along with \(\:{D}_{EH}^{80}\) and \(\:{D}_{SM}^{80}\). Figure 5 (a) shows that

\(\:{T}_{EH}^{80}\) was concentrated in a range of 60–70% in the spring and 70–80% in the fall and mostly exceeded 75% in the summer. However, dispersed \(\:{T}_{EH}^{80}\) values in winter

indicate significant regional differences. As shown in Fig. 5 (b), \(\:{T}_{SM}^{80}\) throughout the year was concentrated between 0.7 and 0.75. The results in Fig. 5 (c) show that in

spring and summer, \(\:{D}_{EH}^{80}\) was relatively low, mainly in a range of 0.3–0.5, indicating that the majority of wildfires occurred during relatively low SM periods. In contrast,

during the winter and fall, the \(\:{D}_{EH}^{80}\) was relatively high, mainly between 0.5 and 0.7. Figure 5 (d) shows that in all seasons except winter, most prefectures had a lower

\(\:{D}_{SM}^{80}\), suggesting that most wildfires occurred during periods of soil drought in these seasons. In summer, the \(\:{D}_{SM}^{80}\) values were mainly concentrated in a range of

0.2–0.4 in all prefectures, whereas they were in a range of 0.3–0.5 in spring and fall and in a range of 0.5–0.6 in winter. SPATIAL PATTERNS OF THE WILDFIRE-DROUGHT INDEX (DI) CORRELATIONS

DURING THE WILDFIRE SEASON Wildfires in Japan exhibit significant seasonal impacts, and to explore the main drought drivers of wildfires in different regions, we subsequently focused on the

wildfire season. We first computed the annual EH and SM distributions for each day during the wildfire season in every prefecture (Fig. 6), with different colors representing different

regions of Japan. As shown in Fig. 6(a), the EH values during the wildfire season in the southern parts of the Kanto and Chubu regions were relatively low, mostly below 60%. In contrast, the

EH values during the wildfire season in Hokkaido, Tohoku, along the coast of the Sea of Japan in the Chubu region, and in Okinawa were greater than 70%. According to the SM results (Fig.

6b), prefectures with exceptionally low soil moisture were mainly located in the southern part of the Chugoku region and the northern part of the Shikoku region, mostly below 0.7. The soil

moisture in the prefectures along the coast of the Sea of Japan in the Tohoku and Chubu regions was relatively high. Additionally, most prefectures in the Kanto region exhibited low soil

moisture, typically around 0.7. To evaluate the suitability of drought descriptions, this analysis utilized Pearson correlation to examine the relationships between wildfire and drought

indices (SM and EH). Since the SM obtained from the SiBUC is hourly and EH is a daily index, the monthly drought index is derived by averaging the lowest 20% values of SM and EH within each

month, serving as a representative measure of drought intensity for that month. Given that the majority of burned areas were small and that the raw data distribution was nonnormal, the

logarithm of the monthly total burned area (BA) was used in this study. Additionally, months with a total BA of 0 were excluded from the calculations. Figure 7 shows the Pearson correlation

coefficient between the monthly total number of wildfires (NO)/the logarithm of the monthly total burned area and drought indices for each prefecture in Japan. The white color in Fig. 7

indicates that the corresponding EH/SM results for the prefecture had a significance level greater than 0.05, while other colors indicate results with a significance level less than 0.05.

The Pearson correlation coefficient measures the degree of correlation (linear correlation) between two variables, and its value is between − 1 and 1. A larger absolute value indicates a

stronger correlation between two variables. A notably strong correlation with EH was observed in the northern region of Japan, particularly along the coast of the Sea of Japan. The

correlation coefficient ranged from 0.5 to 0.75 in the Hokkaido and Tohoku regions. Conversely, a strong correlation with SM was identified along the Pacific coast Fig. 7 (b), with

correlation coefficients exceeding 0.65 in fire-prone prefectures such as Chiba, Fukushima, Hyogo, Hiroshima, and Okayama. A comparison of the correlation coefficients between SM and EH for

each prefecture is shown in Fig. 7 (c), where green indicates a stronger correlation between SM and the number of wildfires and red indicates a stronger correlation between EH and the number

of wildfires. Among the 11 prefectures, EH exhibited a greater correlation with NO, which was primarily concentrated in the northern regions along the coast of the Sea of Japan, while in

the remaining 36 prefectures, SM demonstrated a stronger correlation with NO. The EH results showed a linear correlation with the burned areas in 32 prefectures, with correlation

coefficients ranging from 0.28 to 0.68 (Fig. 7d). Strong correlations were mainly observed in the Hokkaido region and the Tohoku region. In comparison, the SM results revealed correlations

with burned areas across 39 prefectures, with correlation coefficients ranging from 0.28 to 0.67 (Fig. 7e). Regions with higher correlations were predominantly concentrated on the Pacific

coast, where the burned area was also large. A comparison of the SM and EH results (Fig. 7f) revealed that EH had a stronger correlation with the burned areas in 12 prefectures, while SM had

a stronger correlation with the burned areas in the remaining 33 prefectures. Particularly in the Hokkaido region and the northern part of Japan along the Sea of Japan, EH exhibited

stronger correlations with both the number of wildfires and the burned area than SM. However, both the number of wildfires and the burned area were smaller in this region. DISCUSSION This

study defined atmospheric drought and soil drought based on hydrological fuel moisture changes. Using EH and SM as indicators of atmospheric and soil drought, respectively, we analyzed the

temporal and spatial characteristics of their relationships with wildfires. Furthermore, the suitability of drought descriptions under various humid climatic regions in Japan was evaluated.

The main results of the study are summarized as follows: * Through an analysis of \(\:{T}_{EH}^{80}\) and \(\:{T}_{SM}^{80}\) in all prefectures in all seasons (Fig. 3 and Fig. 4), this

study revealed that the ability of EH to assess drought was significantly influenced by both seasonality and regional variation, whereas the assessment ability of SM was less affected by

these factors. Each prefecture in Japan uses different EH thresholds for wildfire warnings, but these thresholds are all below 65%. However, the results of this study indicate that these

thresholds are only applicable in certain seasons within certain prefectures. For example, in Hokkaido and Niigata, wildfires almost never occur when EH is below 65%, whereas in Chiba

Prefecture, most wildfires occur when EH is below 65% in spring and winter, but in summer and autumn, most wildfires occur when EH is above 65%. The results indicated that the EH had a

relatively strong ability to assess drought in Japan during the spring, especially in the Tohoku and Chugoku regions along the Sea of Japan, where \(\:{T}_{EH}^{80}\) was relatively low, and

\(\:{D}_{EH}^{80}\) was also approximately 0.4. Spring was the driest season in Japan with the most wildfires. Spring wildfires in Japan have been found to be related to insolation33,

increased spring insolation and water vapor exchange, resulting in a decrease in fuel moisture. On the other hand, at the regional scale, precipitation is an important meteorological forcing

affecting variations in soil moisture content34. In spring, reduced rainfall and increased temperatures across various regions led to a decrease in soil moisture, thereby inhibiting the

replenishment from soil moisture to fuel moisture and enhancing fuel combustibility. Consequently, SM was also able to better reflect drought conditions during the spring season. During the

summer and fall, wildfires also occurred more often during periods of soil drought, although SM thresholds increased in some prefectures. Northern Japan experiences cold and wet conditions

in winter, particularly in the Tohoku and Chugoku regions along the Sea of Japan, where heavy snowfall is common. The snow cover and increased precipitation help maintain high soil moisture

levels, making it challenging for SM to indicate drought conditions, with a high \(\:{D}_{SM}^{80}\) mostly exceeding 0.7. * The results of the correlation analysis between EH/SM and the

number of wildfires in the wildfire season show that EH can better explain the drought conditions for wildfire ignition in 11 prefectures, which are mainly concentrated in the northern area

along the coast of the Sea of Japan (Fig. 7). Wildfire activity is sensitive to spring snowmelt35,36,37. In Hokkaido and the northern area on the coast of the Sea of Japan, the land surface

is extensively covered with snow during winter. Snowmelt serves as a crucial water source during spring. Both the snowmelt and lower temperatures are important factors in delaying the onset

of the wildfire season in these regions. Figure 8 presents the monthly variations in effective humidity and soil moisture for Akita (PC5), Toyama (PC16), Kochi (PC39), and Chiba (PC12)

Prefectures, which are representative of regions with later and earlier wildfire seasons, respectively. The left panel illustrates the monthly trends in effective humidity across these four

prefectures, while the right panel depicts the corresponding variations in soil moisture. In regions with later wildfire seasons, such as Akita and Toyama, both soil moisture and effective

humidity remain relatively high during the spring, likely influenced by increased moisture from spring snowmelt. These elevated moisture levels may delay fuel drying, thereby postponing the

onset of the wildfire season. Conversely, in regions with earlier wildfire seasons, such as Kochi and Chiba, the absence of significant snow accumulation during the warmer winter months

results in lower soil moisture and effective humidity during the spring. In the northern areas along the Sea of Japan, soil moisture increases after snowmelt38, resulting in relatively high

soil moisture at the beginning of the wildfire season. Despite a decline in soil moisture during drought periods, it remains at relatively high levels. Consequently, wildfires are more

likely to occur when effective humidity decreases to drier conditions. In other regions, especially along the Pacific coast, SM better explains the drought conditions for the ignition of

wildfires. Low rainfall during winter leads to dry surface soil before the wildfire season, and the subsequent decrease in SM during the wildfire season further significantly increases the

combustibility of fuel. * The results of the correlation analysis between EH, SM and burned area in the wildfire season were similar to the results for NO. The correlation coefficient of SM

was greater in 33 prefectures, indicating that SM better explained the drought conditions for burned areas in these prefectures. Substantial antecedent rainfall promotes SM and plant growth,

generating abundant fuel, while low rainfall during the wildfire season dries out fuel, leading to an increase in the frequency of large-scale fires39,40. In the northern region of Kyushu,

abundant rainfall during the rainy season likely results in the accumulation of fuel. During the wildfire season, low EH significantly reduces the FMC, thereby leading to larger-scale

burning. On the other hand, in the southern Chugoku region and the northern Shikoku region, the annual rainfall is noticeably lower than the national average. While the rainy season promotes

fuel accumulation, the overall decrease in rainfall leads to the early onset of soil drought. Consequently, during the wildfire season, significantly reduced soil moisture greatly increases

the availability and combustibility of fuel, thereby facilitating the spread of wildfires. Although Japan’s wildfire alert system relies only on EH and wind for wildfire predictions, the

results indicate that EH is significantly influenced by both seasonal and regional factors, which affects its ability to assess drought conditions for wildfires. In contrast, SM demonstrates

a more consistent ability to assess drought across different seasons and regions. This study contributes to a better understanding of the mechanisms underlying wildfire occurrence and

development in Japan, thereby supporting the formulation of effective wildfire management strategies. Additionally, this study can provide valuable insights for assessing drought in humid

regions in the future. Nevertheless, this study is subject to certain limitations. Although studies have shown that the number and burned area of wildfires in various regions of Japan are

closely related to atmospheric/soil drought, we only examined EH for atmospheric drought. However, factors such as strong winds and high radiation also significantly affect the availability

of fuel. Studies have found that wind was the major driver of the 2020 megafires in the North American Pacific Northwest41. The frequency of wildfires in Siberian larch forests was strongly

correlated with incoming solar radiation21. Additionally, human activities also play a significant role in wildfire activities, primarily affecting wildfire activity through increased

ignition, fire management, and land cover42,43. The occurrence of wildfires in Alaska is related to the distance from human habitation areas, with the probability of wildfires decreasing as

the distance from roads increases44. Wildfire risk at the wildland–urban interface (WUI) continues to increase as human settlements expand into fire-prone areas (forested areas)45. Most

wildfires in Japan are caused by human activities; therefore, future research that comprehensively considers both human factors and climatic impacts on wildfires will help in predicting and

managing wildfires. Most of the fuel ignited during wildfires in Japan consists of dead plant material29. The fuel moisture of dead fuel can respond to short-term (hours to days) dry

atmospheric conditions46,47, but this study is based on monthly scale analysis and cannot effectively capture short-term changes in fuel moisture content. Additionally, topography, climate,

and vegetation influence the spatial distribution patterns of fuels7,48,49. Therefore, future work should include detailed fuel moisture content analysis and comprehensively consider the

impact of the temporal and spatial distribution patterns of fuel on wildfires. MATERIALS AND METHODOLOGY STUDY AREA Japan was selected as the targeted area of this study (Fig. 9), where PC

represents the prefecture code shown in the figure below. Japan has 37.8 million hectares of land and 25.5 million hectares of forest, and approximately two-thirds (66%) of the land area in

Japan is forest. Most of Japan falls within the temperate climate zone and experiences four distinct seasons, with notable variations between summer and winter. In Hokkaido, winters are

characterized by a prolonged and cold climate, while summers are cool, notably without a rainy season. The average annual temperature in Japan is approximately 15 °C. Okinawa Prefecture

boasts the highest average temperature, reaching approximately 23 °C, while Hokkaido experiences the lowest average temperature, at approximately 9 °C. Climatic disparities are influenced

not only by latitude but also by the presence of mountains in the central part of the Japanese archipelago, resulting in significant variations between the Pacific Ocean and Sea of Japan

coasts. On the Pacific coast, summers are hot, and winters are relatively dry. On the Sea of Japan coast, winters are humid with substantial snowfall, especially in the western Tohoku and

northern Chubu regions, while summers tend to be dry and hot. Southern Chugoku, northern Shikoku, western Kinki, and northern Kyushu, which are sheltered by the Shikoku Mountains in summer

and the Chugoku Mountains in winter, exhibit a stable and warm climate with low annual rainfall. In the Kyushu and Okinawa regions, summers are hot, winters are mild, and annual rainfall is

high, particularly during the summer rainy season and typhoon season. WILDFIRE IN JAPAN The fire reports in Japan, documenting detailed surveys of all fires since 1995, are consolidated and

managed by the Fire and Disaster Management Agency (FDMA). This dataset contains detailed information about each wildfire, such as fire location, burned area, cause of ignition, and date and

time of initiation. A total of 45,070 wildfires occurred in Japan during 1995–2012, with a total burned area of 241.06 km2. This study focused on all of Japan as the study area, and Fig. 10

shows the temporal–spatial characteristics of wildfires in Japan from 1995 to 2012. The number and burned area of wildfires in Japan showed a declining trend. The number of wildfires in

2012 was approximately 40% of that in 1995, while the burned area was only approximately 20% of the 1995 level (Fig. 10a). Figure 10 (b) illustrates the total number of wildfires and burned

area per month in Japan, and Fig. 10 (c, d, e) shows the spatial characteristics of wildfires in each prefecture from 1995 to 2012. Based on the average value in 2015–2019, Japan experienced

more than 1200 wildfires annually, with a yearly burned area exceeding 700 hectares. Both the number and burned area of wildfires in Japan had similar seasonal variations, with wildfires

predominantly occurring during the spring and the period from winter to the rainy season. During these times, there was also a significant extent of burned area. Figure 10(c, d) shows the

spatial variations in the number and burned area of wildfires across different prefectures. Regions with a higher incidence of wildfires and a more substantial burned area were predominantly

located along the Pacific coast, particularly in the southern part of the Chugoku region. On average, more than 100 incidents occurred annually, with burned areas exceeding 60 hectares. The

Chugoku region experiences less annual rainfall and is below the national average50. The eastern regions of Kanto and Tohoku experienced a greater frequency of wildfires, but these

incidents tended to result in smaller burned areas. In contrast, the northern part of the Kyushu and Hokkaido regions exhibited larger burned areas despite a lower incidence of wildfires.

Figure 10(e) shows the starting date of the wildfire season in 47 prefectures. Due to the seasonal characteristics of wildfires in Japan, the fire season was defined in this study as the

period comprising 90 consecutive days with the greatest number of wildfires29. The wildfire season in the northern region starts later than that in the southern region, and the most recent

place where the wildfire season starts is Hokkaido, which is around late March. Snowmelt provides water in spring and summer, while heavy snowfall in the northern Chubu region and western

Tohoku region is crucial for delaying the wildfire season. EFFECTIVE HUMIDITY Low humidity makes fuel drier and flammable. In Japan, effective humidity, minimum humidity and wind speed are

used as fire warning criteria. Previous studies have indicated that effective humidity could be utilized as a predictive factor for wildfires in Japan16. The effective humidity accounts for

the history of humidity over previous days. It is an index showing the degree of dryness of wood. It is given by the following equation: $$\:{H}_{e}=(1-r)({H}_{0}+r{H}_{1}+{r}^{2}{H}_{2})$$

(1) where \(\:{H}_{e}\) is the effective humidity and \(\:{H}_{0}\), \(\:{H}_{1}\), and \(\:{H}_{2}\) are the relative humidities within 3 days. _r_ is generally set to 0.7. The relative

humidity was calculated using the air temperature and dew point temperature from Dynamical Regional Downscaling Using the JRA-55 Reanalysis dataset (DSJRA-55) at a 0.5°×0.5° resolution from

1995 to 201251. SOIL MOISTURE FROM THE LAND SURFACE MODEL The soil moisture from the simple biosphere including urban canopy (SiBUC) model was used in this study52. The SiBUC is based on

physical processes, and it has three layers of soil considering the effects of deep-water supply and root transpiration. Furthermore, SiBUC adopts a single-layer snow model, allowing for the

consideration of snowmelt in the water supply conditions during spring. The surface soil moisture simulated by SiBUC demonstrated good accuracy compared to the validated measured surface

soil moisture53. In this study, we focused on the soil moisture content of the first layer, as it directly influences the moisture content and combustion of dead fuel. Soil moisture analysis

by SiBUC could be an indicator of the dry condition of the soil in the Tohoku region of Japan54. The unsaturated permeability of the soil is calculated according to the saturation of each

soil layer. When it is converted into volumetric water content, the accuracy of soil parameters such as porosity has a great influence; therefore, the saturation rate is directly used for

evaluation. The analysis using the SiBUC model was performed at 5 km and 1-hour resolutions in Japan from 1995 to 2012. The land-use data were created based on the digital national land

information of Japan, with forest classification conducted using the GLCC55. Additionally, the vegetation index and soil conditions were determined using ECOCLIMAP-II data56. The

precipitation data were obtained from the Asian Precipitation Highly Resolved Observational Data_Japan (APHRO_JP)57,58, while other forcing data, such as temperature, downward shortwave

radiation, downward longwave radiation, and wind velocity, were sourced from the DSJRA-55 dataset. DATA AVAILABILITY The wildfire data that support the findings of this study are available

from the Fire and Disaster Management Agency (Japan) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly

available. The authors do not have permission to share the wildfire data. Other datasets utilized to perform this study are freely available on the internet. For further information, please

contact the corresponding author. The specific data sources are as follows: DSJRA-55 dataset: https://jra.kishou.go.jp/DSJRA-55/index_en.html. APHRO_JP:

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ADS  Google Scholar  Download references AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan Chenling

Sun, Yoshiya Touge & Kenji Tanaka * China Institute of Water Resources and Hydropower Research, Beijing, 100038, China Ke Shi Authors * Chenling Sun View author publications You can

also search for this author inPubMed Google Scholar * Yoshiya Touge View author publications You can also search for this author inPubMed Google Scholar * Ke Shi View author publications You

can also search for this author inPubMed Google Scholar * Kenji Tanaka View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS All authors

contributed to the study’s conception and design. C.S. conceptualized the study, performed the data analysis, and wrote the original draft. Y.T. contributed to the conceptualization,

methodology, data collection, and reviewed and edited the manuscript. K.S. was responsible for the methodology, and reviewed and edited the manuscript. K.T. provided supervision and

contributed to the methodology. All authors reviewed the manuscript. CORRESPONDING AUTHOR Correspondence to Yoshiya Touge. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no

competing interests. ACKNOWLEDGEMENTS This work was conducted by Theme 4 of the Advanced Studies of Climate Change Projection (SENTAN Program) Grant Number JPMXD0722678534, Grant-in-Aid for

Scientific Research (A), 2024–2027 (24H00336; Yoshiya Touge), and Grant-in-Aid for Scientific Research (B), 2020–2023 (20H02248; Yoshiya Touge) supported by the Ministry of Education,

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suitability of drought descriptions for wildfires under various humid temperate climates in Japan. _Sci Rep_ 14, 23759 (2024). https://doi.org/10.1038/s41598-024-75563-2 Download citation *

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