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Abstract Sauna weather with high temperature, high humidity and long standby time has become one of the main meteorological hazards faced by urban residents. Based on the daily maximum temperature and relative humidity datasets of 545 meteorological observation stations in China from 1961 to 2017, the spatialtemporal evolution characteristics of sauna days with different intensities in China were studied from three aspects: climatic state, trend and fluctuation characteristics, using the standard of sauna days defined by the Central Meteorological Observatory of China Meteorological Administration. The results showed that: firstly, the spatial pattern of sauna days with different intensities in China was high in southeast China and low in northwest China from 1961 to 2017, and the spatial pattern of sauna days with the same intensity in different research periods had little difference, which was in good agreement with the spatial pattern of sauna days with corresponding intensities in the whole research period. With the increase of intensity, the sauna days in China decreases gradually. Secondly, the trend of sauna days with different intensities in China was bounded by Hu Huanyong Line from 1961 to 2017, showing a pattern of increasing or decreasing mosaic in the southeast China and mainly decreasing trend, while the spatial differentiation pattern in the northwest China changed little. The trend of sauna days with different intensities in China increased significantly in 1991-2017 compared with 1961-1990. Thirdly, the fluctuation of sauna days with different intensities in China was bounded by Hu Huanyong Line, showing a spatial pattern of large fluctuations in the southeast China and small fluctuations in the northwest China. And the fluctuation of sauna days and heavy sauna days showed obvious threeblock distribution characteristics. The fluctuation characteristics of sauna days with different intensities in China from 1961 to 1990 and 1991 to 2017 were in good agreement with the whole research period. The fluctuation difference before and after 1990 mainly concentrated in the vicinity of Hu Huanyong Line and its southeast area, and the fluctuation differences increased mainly, indicating that the variation of sauna days with different intensities in the southeast China increased from 1991 to 2017.
Key words Sauna weather; High temperature and heat waves; Spatial pattern; Interdecadal variation; Climate change; Regional differentiation Received: May 23, 2019Accepted: August 21, 2019
Supported by China Postdoctoral Science Foundation (2019T120114; 2019M650756); National Natural Science Foundation of China (41801064); Central Asia Atmospheric Science Research Fund (CAAS201804).
Feng KONG (1986-), male, P. R. China, assistant professor, PhD, devoted to research about climate change and natural disaster.
*Corresponding author. Email: kongfeng0824@foxmail.com.
In recent years, with global warming and heat island effect caused by the rapid urbanization of countries all over the world, especially in developing countries, the frequency of hot weather in the world is increasing［1-3］. Hightemperature heat wave events occur frequently and have gradually become a serious meteorological disaster［4-6］. Such disasters will not only affect industrial and agricultural production, but also cause water supply and power supply shortages. It will also directly harm peoples health and seriously affect peoples living conditions and quality of life［7-11］.
The Intergovernmental Panel on Climate Change (IPCC) indicates in its fifth assessment report of global temperature that the average global temperature in 2003-2012 increased by 0.78 ℃ compared with 1850-1900［1］. The assessment results in A Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) indicate that by 2081-2100, in most low latitudes such as subSaharan Africa and northern and central South America, days with a daily maximum temperature above 30 ℃ per year will exceed 110 d［2］. According to numerical simulation results, the main factors affecting global warming are solar activity, volcanic activity, human activities and airsea interaction. Human activities affect global climate change mainly through the emission of greenhouse gases such as carbon dioxide, methane and nitrous oxide［1-2］. In the context of global warming, extreme weather and climate events have occurred and will continue to occur and change［12-14］. Observations since 1950 indicate that areas with increased extremelyhigh temperature events and heat wave events may be more than those with decreased extremelyhigh temperature events and heat wave events［1］. Although many extreme weather events continue to be the result of natural climate change, the worlds highest temperature rising continuously might be due to human activities［2］. Estimates of the future show that on a global scale, extreme heat events will increase, extreme cold events will decrease, and heat wave duration, frequency and intensity in most land areas are likely to increase［2］. Through the analysis of the observatory data in 217 urban areas around the world, it is found that the frequency of urban heat wave disasters has increased significantly in recent years, and the frequency of cold wave occurrence has decreased significantly［1］; the highest temperature in many places has broken records, and has even reached 51 ℃ in India; and the number of days of extreme hot weather in most urban areas has also increased significantly［15］. Compared with other extreme weather events, hightemperature heat wave events have received less attention overall［16］. The increase in intensity and frequency of extremelyhigh temperature weather will cause great changes in the stability and distribution of worlds food production. Extremelyhigh temperature weather will lead to crop yield reduction and even 100% reduction, and poultry livestock will suffer from heatstroke. The impact of extremelyhigh temperature on human health will be more common and serious, and some diseases that currently occur mainly in the tropics (such as malaria) may spread to the midlatitudes with climate warming［17-20］. Thousands of people die from extreme heat wave every year. In 1980-2008, an average of 3 100 people died in extreme high temperature weather every year, and more than 159 000 people were affected. In 1995, Chicago suffered severe heat waves, causing at least 700 deaths; in January-February 2009, 374 people died in heat waves in Melbourne, Australia; in 2003, Europes hightemperature heat waves caused more than 70 000 deaths; and in 2010, largescale heat waves in Russia at high latitudes also killed more than 55 730 people［21-22］.
Affected by the subtropical high, Chinas middle and lower reaches of the Yangtze River are also vulnerable to hightemperature heat waves［15］. In the past 30 years, many places in China have experienced cool summers. For example, Beijing, Shanghai, Guangzhou, Nanjing, Wuhan, Chongqing and other cities have suffered severe heat waves many times, and thousands of people died in heat waves［18-19］. In the summer of 2003, rare hightemperature weather occurred in the south of the Yangtze River and South China, and in some places, the high temperature over 35 ℃ even lasted for about 40 d. The heat wave event in 2013 was also very serious. The highest temperature in 18 cities in Zhejiang Province exceeded 40 ℃, and even reached 44.1 ℃ in the severest area［18］. Although with the improvement of living conditions, people generally use air conditioner, electric fans and other cooling tools, but the inevitable outdoor activities will still cause a large number of heatrelated diseases and death. Meanwhile, the use of air conditioners and other equipment puts higher demands on the power supply system under high temperature conditions. In addition, high temperature also causes the consumption of all kinds of water for production and living to increase significantly, which brings great pressure to the urban water supply department［17］. There is no unified definition and standard for current diagnosis of hightemperature heat wave events, and the diagnosis starts from daily maximum temperature mostly, rarely taking humidity into consideration. Human body temperature is not only related to daily maximum temperature, but also closely related to relative humidity and wind speed［9］. The high temperature weather with high relative humidity has an obviously higher effect on human health than the case with low humidity in the same region. Therefore, in this study, the spatialtemporal evolution characteristics of sauna days with different intensities in China from 1961 to 2017 were diagnosed and analyzed according to daily maximum temperature and relative humidity data, using the standard of sauna days defined by the Central Meteorological Observatory of China Meteorological Administration. The study is of great significance for understanding hightemperature heat wave weather and can help to understand the climate risks of extreme weather in the context of climate change.
Data and Methods
Data source
The daily maximum temperature and daily mean relative humidity data for the period 1961-2017 used in this study were from the "Daily Data Set of Basic Meteorological Elements in Chinas National Surface Weather Stations (V3.0)" provided by the Central Meteorological Observatory of China Meteorological Administration. The data set is qualitycontrolled, and it has a data availability rate generally above 99% and a data accuracy rate close to 100%. Based on the data, according to the existing research results［12］, the paper further controlled the quality of the data: the annual missing or wrong data size should be less than 0.5% of the total annual data; and total missing or wrong data should be less than 0.5% of the total data. The stations that did not meet the above conditions were excluded, if there were missing data in a station that satisfied the conditions, the values of the adjacent station or the mean of the years before and after it were used to fill the blank. Eventually, 545 stations were obtained. The weather stations of this paper do not include Hong Kong, Macao and Taiwan.
Computing method
According to the forecasting standard of "sauna weather" by the Central Meteorological Observatory of China Meteorological Administration, when the daily maximum temperature is equal to or higher than 32 ℃ and the daily mean relative humidity is equal to or higher than 80%, it is called "sauna day". When the daily maximum temperature is equal to or higher than 32 ℃ and the daily mean relative humidity is equal to or higher than 85%, it is called "heavy sauna day".When the daily maximum temperature is equal to or higher than 32 ℃ and the daily mean relative humidity is equal to or higher than 90%, it is called "extreme sauna day". According to the above definition, firstly, this paper analyzed the spatial differentiation characteristics of the total number of sauna days with different intensities in China from 1961 to 2017, namely the distribution characteristics of climate state, and also analyzed the spatial differentiation characteristics of sauna days with different intensities in different ages. In this study, 1961-1980, 1971-1980, 1981-1990, 1991-2000, 2001-2010 and 2011-2017 were referred as the 1960, 1970, 1980, 1990, 2000 and 2010 ages, respectively. Secondly, for the three research periods of 1961-2017, 1961-1990 and 1991-2017, the onedimensional linear trend method was applied to calculate the variation trend of sauna days with different intensities in China. At last, the coefficient of variation was used to characterize the fluctuation characteristics of sauna days with different intensities in different periods. The detailed calculation method is reported in literature［12］. Results and Analysis
Spatial differentiation characteristics of sauna days with different intensities in climate state
From the climate state characteristics, the number of sauna days with different intensities in China from 1961 to 2017 was roughly bounded by the line from central Shandong to central Yunnan, that is, the 800 mm precipitation line, showing a spatial pattern of high in southeast China dand low in northwest China (Fig. 1). Sauna days, heavy sauna days and extreme sauna days in the northwestern region of the line were mostly fewer than 300 (Fig. 1a), 100 (Fig. 1b) and 15 d (Fig. 1c), respectively, while sauna days, heavy sauna days and extreme sauna days in the southeast region of the line were all more than 1 200, 400 and 60 d, respectively. With the increase in the intensity of sauna days, the number of sauna days in climate state in China decreased. From the perspective of different ages, the spatial differentiation characteristics of sauna days with different intensities in China were not much different from those of the sauna days with corresponding intensities in the whole research period (Fig. 2, Fig. 3, Fig. 4). Chinas summer maximum temperature is higher than 32 ℃ in many areas, but the relative humidity is quite different between the east and west and the north and south［19］. In summary, the differentiation patterns of sauna days with different intensities in climate state in China are mainly determined by relative humidity.
Feng KONG. Spatialtemporal Differentiation of Sauna Days with Different Intensities in China from 1961 to 2017
Spatial differentiation characteristics of variation trend of sauna days with different intensities
From the trend of change, the trend of sauna days with different intensities in China from 1961 to 2017 was roughly bounded by the line from Heihe, Heilongjiang Province to Tengchong, Yunnan Province, namely the Hu Huanyong Line. The trend in the west of the line was not significant, while in the east of the line, except the northeast region, there was a pattern of increasing or decreasing mosaic and mainly decreasing trend. The areas where sauna days with different intensities showed an increasing trend were scattered in areas with big topographic relief along rivers and hills (Fig. 5).
After 1990, China entered the stage of rapid urbanization. In order to diagnose the variation characteristics of sauna days with different intensities in China around 1990, we diagnosed the trend of sauna days with different intensities in two periods, and further subtracted the trend of sauna days with different intensities in China in the period of 1961-1990 from that of sauna days with corresponding intensities in the period of 1991-2017 (Fig. 6). From the perspective of the variation trend of sauna days, the variation trend of sauna days in China was not significant in the west of the Hu Huanyong Line in 1961-1990, while in the east of this line, there was a clear differentiation trend of increasing in the south and decreasing in the north, which was roughly bounded by the line from the estuary of the Yangtze River to the western part of Guangxi (Fig. 6a). From 1991 to 2017, the sauna days in China was bounded by the Hu Huanyong Line, showing a pattern of increasing or decreasing mosaic, and compared with 1961-1990, the number of stations with increasing sauna days increased and exhibited a decentralized pattern (Fig. 6b). The trend characteristics of the two time periods showed that compared with 1961-1990, the sauna days in 1991-2017 increased in the area east of the Hu Huanyong Line. The variation trend of sauna days in the Beijing-Tianjin-Hebei region was significantly higher in 1991-2017 than in 1961-1990. The sauna days in the south of the Beijing-Tianjin-Hebei region showed a pattern of increasing or decreasing mosaic (Fig. 6c).
From the trend of heavy sauna days, the number of heavy sauna days in China in the east of the Hu Huanyong line was mainly on the increase from 1961 to 1990. Specifically, the Beijing-Tianjin-Hebei region showed a significant decreasing trend, while the middle and lower reaches of the Yangtze River had a significant increasing trend (Fig. 7a). The area south of the Yangtze River showed a significant spatial differentiation pattern of increasing in the east and increasing or decreasing mosaic in the west, and the western areas exhibited a spatial differentiation pattern dominated by increasing in the south and decreasing in the north. From 1991 to 2017, the stations with increasing heavy sauna days in the east of the Hu Huanyong Line began to expand northward, and the stations showing an increasing trend in the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta regions were clearly clustered (Fig. 7b). The trend characteristics of heavy sauna days in the two periods showed that compared with 1961-1990, the number of stations with increasing heavy sauna days in China in the east of the Hu Huanyong Line increased significantly from 1991 to 2017 overall. In particular, the trend of the number of heavy sauna days in the Bohai Rim region including the Beijing-Tianjin-Hebei region increased significantly (Fig. 7c); and other areas to the east of the Hu Huanyong Line showed a pattern of increasing or decreasing mosaic, and the trend had a subregional differentiation characteristic of a significant increase in the number of days and decreased aggregation.
From the trend of extreme sauna days, the extreme sauna days in China in the east of the Hu Huanyong Line from 1961 to 1990 showed a distribution pattern of increasing or decreasing mosaic, and mainly decreasing trend, especially in the Beijing-Tianjin-Hebei region (Fig. 8a).From 1991 to 2017, extreme sauna days in China increased significantly in the east of the Hu Huanyong Line, especially in the area south of the Huanghuai River Basin (Fig. 8b). The difference in the trend of extreme sauna days between the two periods showed that compared with 1961-1990, the extreme sauna day in China increased significantly in the east of the Hu Huanyong Line from 1997 to 2017, especially in the Beijing-Tianjin-Hebei region, Yangtze-Huaihe River Basin and northern South China (Fig. 8c). In summary, the variation trends of sauna days with different intensities in different time periods in China were bounded by the Hu Huanyong Line. Specifically, the trend of increasing or decreasing in the west of the line was small, and had little difference in different time periods; and in the east of the line, with the development of the rapid urbanization process in 1991-2017, the heat island effect was intensified. The number of stations showing increasing trends of sauna days with different intensities increased significantly, especially in the areas where urban agglomerations were distributed. Spatial differentiation characteristics of fluctuations of sauna days with different intensities
From the perspective of the fluctuation characteristic, the fluctuation characteristics of sauna days with different intensities in China had different differentiation patterns from 1961 to 2017. Specifically, the fluctuation of sauna days was the largest in the northeast region and ecotone between agriculture and animal husbandry with a vulnerable climate, followed by the southeast region, and smallest in the northwest region (Fig. 9a). The spatial differentiation pattern of heavy sauna days had a great consistency with sauna days, and it is worth noting that the stations with large fluctuations in the number of heavy sauna days in the northeast region decreased sharply (Fig. 9b). Compared with the fluctuation characteristics of sauna days, the fluctuation characteristic of heavy sauna days in the southeast region increased generally. The number of extreme sauna days was bounded by the Hu Huanyong Line, showing a spatial differentiation pattern of large fluctuations in the southeast and small fluctuations in the northwest (Fig. 9c).This was mainly due to the large differences in extreme sauna days in the southeast region, while the weather in the northwest region failed to reach the definition of extreme sauna days due to the relatively low relative humidity. In summary, with the increase in the intensity of sauna days, the fluctuation of sauna days in southeastern China had gradually increased, indicating that the risk of hightemperature heat wave changes in the southeast region was increasing.
Further, we compared the fluctuation characteristics and spatial differences of sauna days with different intensities in China before and after 1990, that is, the fluctuation characteristics of the sauna days with different intensities from 1991 to 2017 in China was subtracted by the fluctuation characteristics of sauna days with corresponding intensities from 1961 to 1990 in China. The results are shown in Fig. 10-Fig. 12. From the difference in the fluctuation of sauna days between different time periods, the fluctuation patterns of sauna days in 1961-1990 and 1991-2017 in China were similar (Fig. 10a; Fig. 10b), which were in good agreement with the whole study period (Fig. 9a). The fluctuation characteristics of sauna days in the two periods further indicated that the fluctuations in the country were not much different overall (Fig. 10c), and only the fluctuations in the northeast region showed a pattern of increasing or decreasing mosaic. From the fluctuation difference of heavy sauna days between different time periods, the spatial pattern of the fluctuation characteristics in heavy sauna days from 1961 to 1990 in China was similar to that from 1991 to 2017 (Fig. 11a; Fig. 11b), and both were in good agreement with the whole research period (Fig. 9b). The difference characteristics of the fluctuation of heavy sauna days between the two time periods exhibited that the difference in the fluctuation of heavy sauna days was larger in the ecotone between agriculture and animal husbandry and its vicinity before and after 1900 (Fig. 11c), and was mainly positive, indicating the fluctuation characteristics of the region in 1991-2017 were mainly based on increase. It is suggested that the climate change and urbanization process will increase the variation of heavy sauna days in the region where the climate is fragile.
From the difference in the fluctuation of extreme sauna days, the spatial differentiation patterns of extreme sauna days in 1961-1990 and 1991-2017 in China were similar (Fig. 12a; Fig. 12b), which were in good agreement with the whole study period (Fig. 9c). The fluctuation characteristics of extreme sauna days in the two periods indicated that the fluctuations in the east of the Hu Huanyong Line were quite different, showing a pattern of increasing and decreasing mosaic, and the differences were mainly positive, indicating the fluctuation in extreme sauna days increased in most areas east of the Hu Huanyong Line from 1991 to 2017.
Conclusions and Discussion
Conclusions
In terms of climate state, sauna days with different intensities in China from 1961 to 2017 showed a spatial differentiation pattern of high in the southeast China and low in the northwest China. With the increase of the intensity, the sauna days in southeastern China gradually decreased. In different ages, the spatial differentiation characteristics of sauna days with different intensities in China were in good agreement with the spatial differentiation patterns of sauna days with corresponding intensities in 1961-2017, indicating that sauna days with different intensities had little difference with ages.
In the perspective of variation trend, sauna days with different intensities in China from 1961 to 2017 were bounded by the Hu Huanyong Line. The trend in the west of the line was small, while the eastern region of the line showed a pattern of increasing or decreasing mosaic, and mainly a decreasing trend. The comparison before and after 1990 showed that the sauna days with different intensities in China increased significantly with the rapid development of urbanization from 1991 to 2017. However, the trends of sauna days with different intensities in China from 1961 to 1990 and 1991-2017 had their own subregional characteristics, which were mainly reflected in the different degrees of change in the regions where the increasing and decreasing trends were concentrated. In the fluctuation characteristics, the fluctuations of sauna days with different intensities in China was bounded by the Hu Huanyong Line, showing a spatial pattern of large fluctuations in the southeast China and small fluctuations in the northwest China. And the fluctuations of sauna days and heavy sauna days showed obvious threeblock distribution characteristics, that is, the fluctuation was large in the ecotone between agriculture and animal husbandry and its vicinity, followed by the southeast region, and the smallest in the northwest region. However, there was no such phenomenon in the fluctuation characteristic of extreme sauna days, which showed a southeastnorthwest twoblock differentiation characteristic. The differences in the fluctuations of sauna days with different intensities in China before and after 1990 showed that the fluctuation characteristics of sauna days with different intensities in China in 1961-1990 and 1991-2017 were similar to those in 1961-2017 overall, and the regions with large differences were mainly distributed in the boundary line and its east.
Discussion and prospect
Discussion of the definition of sauna days
The term "sauna days" appeared in the situation of frequent hightemperature heat waves in recent years. Based on the definition of sauna days given by the Central Meteorological Observatory of China Meteorological Administration, this paper analyzed the spatial evolution characteristics of sauna days with different intensities in China. However, it is worth noting that due to the large latitude span in the north and south of China, there is a large difference in relative humidity between the north and the south. Therefore, it is urgent to use the relative standard of sauna days to diagnose the regional spatialtemporal variation characteristics of sauna days. Regional sauna day forecasting standards should be developed through a comparison of sauna days defined by various thresholds.
Quantitative determination of the impacts of climate change and urbanization on sauna days
With rapid urbanization and climate change, it has significantly influenced the number of sauna days in urban areas. So what role does urbanization and climate change play in the increase in sauna days? Which one plays a leading role? This is one of the issues that need urgent attention.Quantitatively determining the impact of natural climate change and human activities characterized by urbanization on the changes in sauna days is not only helpful in understanding the changes in extreme weather and climate events in the context of climate change, but also in understanding the influence depth and breadth of human activities in the process of climate change. Study on the impact of extreme hightemperature heat waves on health risks
The hightemperature heat waves characterized by the number of sauna days directly affect by human health, especially for the public engaged in outdoor work. At present, with the increasing urban population and the aging population in China, the increase in sauna days is bound to have a significant impact on the safe operation and sustainable development of cities. Therefore, it is urgent to quantitatively evaluate the possible impact of extremelyhightemperature heat waves on different populations based on the regional disaster system theory, from the stability of hazard inducing environments, the risk of disasterinducing factors and the vulnerability of hazardaffected bodies, which not only helps to prevent the risks of heatstroke and thermoplegia in different populations, but also helps to understand in depth the ways, processes and mechanisms of the impact of extreme weather and climate events on socioeconomic situation in the context of climate change.
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Key words Sauna weather; High temperature and heat waves; Spatial pattern; Interdecadal variation; Climate change; Regional differentiation Received: May 23, 2019Accepted: August 21, 2019
Supported by China Postdoctoral Science Foundation (2019T120114; 2019M650756); National Natural Science Foundation of China (41801064); Central Asia Atmospheric Science Research Fund (CAAS201804).
Feng KONG (1986-), male, P. R. China, assistant professor, PhD, devoted to research about climate change and natural disaster.
*Corresponding author. Email: kongfeng0824@foxmail.com.
In recent years, with global warming and heat island effect caused by the rapid urbanization of countries all over the world, especially in developing countries, the frequency of hot weather in the world is increasing［1-3］. Hightemperature heat wave events occur frequently and have gradually become a serious meteorological disaster［4-6］. Such disasters will not only affect industrial and agricultural production, but also cause water supply and power supply shortages. It will also directly harm peoples health and seriously affect peoples living conditions and quality of life［7-11］.
The Intergovernmental Panel on Climate Change (IPCC) indicates in its fifth assessment report of global temperature that the average global temperature in 2003-2012 increased by 0.78 ℃ compared with 1850-1900［1］. The assessment results in A Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) indicate that by 2081-2100, in most low latitudes such as subSaharan Africa and northern and central South America, days with a daily maximum temperature above 30 ℃ per year will exceed 110 d［2］. According to numerical simulation results, the main factors affecting global warming are solar activity, volcanic activity, human activities and airsea interaction. Human activities affect global climate change mainly through the emission of greenhouse gases such as carbon dioxide, methane and nitrous oxide［1-2］. In the context of global warming, extreme weather and climate events have occurred and will continue to occur and change［12-14］. Observations since 1950 indicate that areas with increased extremelyhigh temperature events and heat wave events may be more than those with decreased extremelyhigh temperature events and heat wave events［1］. Although many extreme weather events continue to be the result of natural climate change, the worlds highest temperature rising continuously might be due to human activities［2］. Estimates of the future show that on a global scale, extreme heat events will increase, extreme cold events will decrease, and heat wave duration, frequency and intensity in most land areas are likely to increase［2］. Through the analysis of the observatory data in 217 urban areas around the world, it is found that the frequency of urban heat wave disasters has increased significantly in recent years, and the frequency of cold wave occurrence has decreased significantly［1］; the highest temperature in many places has broken records, and has even reached 51 ℃ in India; and the number of days of extreme hot weather in most urban areas has also increased significantly［15］. Compared with other extreme weather events, hightemperature heat wave events have received less attention overall［16］. The increase in intensity and frequency of extremelyhigh temperature weather will cause great changes in the stability and distribution of worlds food production. Extremelyhigh temperature weather will lead to crop yield reduction and even 100% reduction, and poultry livestock will suffer from heatstroke. The impact of extremelyhigh temperature on human health will be more common and serious, and some diseases that currently occur mainly in the tropics (such as malaria) may spread to the midlatitudes with climate warming［17-20］. Thousands of people die from extreme heat wave every year. In 1980-2008, an average of 3 100 people died in extreme high temperature weather every year, and more than 159 000 people were affected. In 1995, Chicago suffered severe heat waves, causing at least 700 deaths; in January-February 2009, 374 people died in heat waves in Melbourne, Australia; in 2003, Europes hightemperature heat waves caused more than 70 000 deaths; and in 2010, largescale heat waves in Russia at high latitudes also killed more than 55 730 people［21-22］.
Affected by the subtropical high, Chinas middle and lower reaches of the Yangtze River are also vulnerable to hightemperature heat waves［15］. In the past 30 years, many places in China have experienced cool summers. For example, Beijing, Shanghai, Guangzhou, Nanjing, Wuhan, Chongqing and other cities have suffered severe heat waves many times, and thousands of people died in heat waves［18-19］. In the summer of 2003, rare hightemperature weather occurred in the south of the Yangtze River and South China, and in some places, the high temperature over 35 ℃ even lasted for about 40 d. The heat wave event in 2013 was also very serious. The highest temperature in 18 cities in Zhejiang Province exceeded 40 ℃, and even reached 44.1 ℃ in the severest area［18］. Although with the improvement of living conditions, people generally use air conditioner, electric fans and other cooling tools, but the inevitable outdoor activities will still cause a large number of heatrelated diseases and death. Meanwhile, the use of air conditioners and other equipment puts higher demands on the power supply system under high temperature conditions. In addition, high temperature also causes the consumption of all kinds of water for production and living to increase significantly, which brings great pressure to the urban water supply department［17］. There is no unified definition and standard for current diagnosis of hightemperature heat wave events, and the diagnosis starts from daily maximum temperature mostly, rarely taking humidity into consideration. Human body temperature is not only related to daily maximum temperature, but also closely related to relative humidity and wind speed［9］. The high temperature weather with high relative humidity has an obviously higher effect on human health than the case with low humidity in the same region. Therefore, in this study, the spatialtemporal evolution characteristics of sauna days with different intensities in China from 1961 to 2017 were diagnosed and analyzed according to daily maximum temperature and relative humidity data, using the standard of sauna days defined by the Central Meteorological Observatory of China Meteorological Administration. The study is of great significance for understanding hightemperature heat wave weather and can help to understand the climate risks of extreme weather in the context of climate change.
Data and Methods
Data source
The daily maximum temperature and daily mean relative humidity data for the period 1961-2017 used in this study were from the "Daily Data Set of Basic Meteorological Elements in Chinas National Surface Weather Stations (V3.0)" provided by the Central Meteorological Observatory of China Meteorological Administration. The data set is qualitycontrolled, and it has a data availability rate generally above 99% and a data accuracy rate close to 100%. Based on the data, according to the existing research results［12］, the paper further controlled the quality of the data: the annual missing or wrong data size should be less than 0.5% of the total annual data; and total missing or wrong data should be less than 0.5% of the total data. The stations that did not meet the above conditions were excluded, if there were missing data in a station that satisfied the conditions, the values of the adjacent station or the mean of the years before and after it were used to fill the blank. Eventually, 545 stations were obtained. The weather stations of this paper do not include Hong Kong, Macao and Taiwan.
Computing method
According to the forecasting standard of "sauna weather" by the Central Meteorological Observatory of China Meteorological Administration, when the daily maximum temperature is equal to or higher than 32 ℃ and the daily mean relative humidity is equal to or higher than 80%, it is called "sauna day". When the daily maximum temperature is equal to or higher than 32 ℃ and the daily mean relative humidity is equal to or higher than 85%, it is called "heavy sauna day".When the daily maximum temperature is equal to or higher than 32 ℃ and the daily mean relative humidity is equal to or higher than 90%, it is called "extreme sauna day". According to the above definition, firstly, this paper analyzed the spatial differentiation characteristics of the total number of sauna days with different intensities in China from 1961 to 2017, namely the distribution characteristics of climate state, and also analyzed the spatial differentiation characteristics of sauna days with different intensities in different ages. In this study, 1961-1980, 1971-1980, 1981-1990, 1991-2000, 2001-2010 and 2011-2017 were referred as the 1960, 1970, 1980, 1990, 2000 and 2010 ages, respectively. Secondly, for the three research periods of 1961-2017, 1961-1990 and 1991-2017, the onedimensional linear trend method was applied to calculate the variation trend of sauna days with different intensities in China. At last, the coefficient of variation was used to characterize the fluctuation characteristics of sauna days with different intensities in different periods. The detailed calculation method is reported in literature［12］. Results and Analysis
Spatial differentiation characteristics of sauna days with different intensities in climate state
From the climate state characteristics, the number of sauna days with different intensities in China from 1961 to 2017 was roughly bounded by the line from central Shandong to central Yunnan, that is, the 800 mm precipitation line, showing a spatial pattern of high in southeast China dand low in northwest China (Fig. 1). Sauna days, heavy sauna days and extreme sauna days in the northwestern region of the line were mostly fewer than 300 (Fig. 1a), 100 (Fig. 1b) and 15 d (Fig. 1c), respectively, while sauna days, heavy sauna days and extreme sauna days in the southeast region of the line were all more than 1 200, 400 and 60 d, respectively. With the increase in the intensity of sauna days, the number of sauna days in climate state in China decreased. From the perspective of different ages, the spatial differentiation characteristics of sauna days with different intensities in China were not much different from those of the sauna days with corresponding intensities in the whole research period (Fig. 2, Fig. 3, Fig. 4). Chinas summer maximum temperature is higher than 32 ℃ in many areas, but the relative humidity is quite different between the east and west and the north and south［19］. In summary, the differentiation patterns of sauna days with different intensities in climate state in China are mainly determined by relative humidity.
Feng KONG. Spatialtemporal Differentiation of Sauna Days with Different Intensities in China from 1961 to 2017
Spatial differentiation characteristics of variation trend of sauna days with different intensities
From the trend of change, the trend of sauna days with different intensities in China from 1961 to 2017 was roughly bounded by the line from Heihe, Heilongjiang Province to Tengchong, Yunnan Province, namely the Hu Huanyong Line. The trend in the west of the line was not significant, while in the east of the line, except the northeast region, there was a pattern of increasing or decreasing mosaic and mainly decreasing trend. The areas where sauna days with different intensities showed an increasing trend were scattered in areas with big topographic relief along rivers and hills (Fig. 5).
After 1990, China entered the stage of rapid urbanization. In order to diagnose the variation characteristics of sauna days with different intensities in China around 1990, we diagnosed the trend of sauna days with different intensities in two periods, and further subtracted the trend of sauna days with different intensities in China in the period of 1961-1990 from that of sauna days with corresponding intensities in the period of 1991-2017 (Fig. 6). From the perspective of the variation trend of sauna days, the variation trend of sauna days in China was not significant in the west of the Hu Huanyong Line in 1961-1990, while in the east of this line, there was a clear differentiation trend of increasing in the south and decreasing in the north, which was roughly bounded by the line from the estuary of the Yangtze River to the western part of Guangxi (Fig. 6a). From 1991 to 2017, the sauna days in China was bounded by the Hu Huanyong Line, showing a pattern of increasing or decreasing mosaic, and compared with 1961-1990, the number of stations with increasing sauna days increased and exhibited a decentralized pattern (Fig. 6b). The trend characteristics of the two time periods showed that compared with 1961-1990, the sauna days in 1991-2017 increased in the area east of the Hu Huanyong Line. The variation trend of sauna days in the Beijing-Tianjin-Hebei region was significantly higher in 1991-2017 than in 1961-1990. The sauna days in the south of the Beijing-Tianjin-Hebei region showed a pattern of increasing or decreasing mosaic (Fig. 6c).
From the trend of heavy sauna days, the number of heavy sauna days in China in the east of the Hu Huanyong line was mainly on the increase from 1961 to 1990. Specifically, the Beijing-Tianjin-Hebei region showed a significant decreasing trend, while the middle and lower reaches of the Yangtze River had a significant increasing trend (Fig. 7a). The area south of the Yangtze River showed a significant spatial differentiation pattern of increasing in the east and increasing or decreasing mosaic in the west, and the western areas exhibited a spatial differentiation pattern dominated by increasing in the south and decreasing in the north. From 1991 to 2017, the stations with increasing heavy sauna days in the east of the Hu Huanyong Line began to expand northward, and the stations showing an increasing trend in the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta regions were clearly clustered (Fig. 7b). The trend characteristics of heavy sauna days in the two periods showed that compared with 1961-1990, the number of stations with increasing heavy sauna days in China in the east of the Hu Huanyong Line increased significantly from 1991 to 2017 overall. In particular, the trend of the number of heavy sauna days in the Bohai Rim region including the Beijing-Tianjin-Hebei region increased significantly (Fig. 7c); and other areas to the east of the Hu Huanyong Line showed a pattern of increasing or decreasing mosaic, and the trend had a subregional differentiation characteristic of a significant increase in the number of days and decreased aggregation.
From the trend of extreme sauna days, the extreme sauna days in China in the east of the Hu Huanyong Line from 1961 to 1990 showed a distribution pattern of increasing or decreasing mosaic, and mainly decreasing trend, especially in the Beijing-Tianjin-Hebei region (Fig. 8a).From 1991 to 2017, extreme sauna days in China increased significantly in the east of the Hu Huanyong Line, especially in the area south of the Huanghuai River Basin (Fig. 8b). The difference in the trend of extreme sauna days between the two periods showed that compared with 1961-1990, the extreme sauna day in China increased significantly in the east of the Hu Huanyong Line from 1997 to 2017, especially in the Beijing-Tianjin-Hebei region, Yangtze-Huaihe River Basin and northern South China (Fig. 8c). In summary, the variation trends of sauna days with different intensities in different time periods in China were bounded by the Hu Huanyong Line. Specifically, the trend of increasing or decreasing in the west of the line was small, and had little difference in different time periods; and in the east of the line, with the development of the rapid urbanization process in 1991-2017, the heat island effect was intensified. The number of stations showing increasing trends of sauna days with different intensities increased significantly, especially in the areas where urban agglomerations were distributed. Spatial differentiation characteristics of fluctuations of sauna days with different intensities
From the perspective of the fluctuation characteristic, the fluctuation characteristics of sauna days with different intensities in China had different differentiation patterns from 1961 to 2017. Specifically, the fluctuation of sauna days was the largest in the northeast region and ecotone between agriculture and animal husbandry with a vulnerable climate, followed by the southeast region, and smallest in the northwest region (Fig. 9a). The spatial differentiation pattern of heavy sauna days had a great consistency with sauna days, and it is worth noting that the stations with large fluctuations in the number of heavy sauna days in the northeast region decreased sharply (Fig. 9b). Compared with the fluctuation characteristics of sauna days, the fluctuation characteristic of heavy sauna days in the southeast region increased generally. The number of extreme sauna days was bounded by the Hu Huanyong Line, showing a spatial differentiation pattern of large fluctuations in the southeast and small fluctuations in the northwest (Fig. 9c).This was mainly due to the large differences in extreme sauna days in the southeast region, while the weather in the northwest region failed to reach the definition of extreme sauna days due to the relatively low relative humidity. In summary, with the increase in the intensity of sauna days, the fluctuation of sauna days in southeastern China had gradually increased, indicating that the risk of hightemperature heat wave changes in the southeast region was increasing.
Further, we compared the fluctuation characteristics and spatial differences of sauna days with different intensities in China before and after 1990, that is, the fluctuation characteristics of the sauna days with different intensities from 1991 to 2017 in China was subtracted by the fluctuation characteristics of sauna days with corresponding intensities from 1961 to 1990 in China. The results are shown in Fig. 10-Fig. 12. From the difference in the fluctuation of sauna days between different time periods, the fluctuation patterns of sauna days in 1961-1990 and 1991-2017 in China were similar (Fig. 10a; Fig. 10b), which were in good agreement with the whole study period (Fig. 9a). The fluctuation characteristics of sauna days in the two periods further indicated that the fluctuations in the country were not much different overall (Fig. 10c), and only the fluctuations in the northeast region showed a pattern of increasing or decreasing mosaic. From the fluctuation difference of heavy sauna days between different time periods, the spatial pattern of the fluctuation characteristics in heavy sauna days from 1961 to 1990 in China was similar to that from 1991 to 2017 (Fig. 11a; Fig. 11b), and both were in good agreement with the whole research period (Fig. 9b). The difference characteristics of the fluctuation of heavy sauna days between the two time periods exhibited that the difference in the fluctuation of heavy sauna days was larger in the ecotone between agriculture and animal husbandry and its vicinity before and after 1900 (Fig. 11c), and was mainly positive, indicating the fluctuation characteristics of the region in 1991-2017 were mainly based on increase. It is suggested that the climate change and urbanization process will increase the variation of heavy sauna days in the region where the climate is fragile.
From the difference in the fluctuation of extreme sauna days, the spatial differentiation patterns of extreme sauna days in 1961-1990 and 1991-2017 in China were similar (Fig. 12a; Fig. 12b), which were in good agreement with the whole study period (Fig. 9c). The fluctuation characteristics of extreme sauna days in the two periods indicated that the fluctuations in the east of the Hu Huanyong Line were quite different, showing a pattern of increasing and decreasing mosaic, and the differences were mainly positive, indicating the fluctuation in extreme sauna days increased in most areas east of the Hu Huanyong Line from 1991 to 2017.
Conclusions and Discussion
Conclusions
In terms of climate state, sauna days with different intensities in China from 1961 to 2017 showed a spatial differentiation pattern of high in the southeast China and low in the northwest China. With the increase of the intensity, the sauna days in southeastern China gradually decreased. In different ages, the spatial differentiation characteristics of sauna days with different intensities in China were in good agreement with the spatial differentiation patterns of sauna days with corresponding intensities in 1961-2017, indicating that sauna days with different intensities had little difference with ages.
In the perspective of variation trend, sauna days with different intensities in China from 1961 to 2017 were bounded by the Hu Huanyong Line. The trend in the west of the line was small, while the eastern region of the line showed a pattern of increasing or decreasing mosaic, and mainly a decreasing trend. The comparison before and after 1990 showed that the sauna days with different intensities in China increased significantly with the rapid development of urbanization from 1991 to 2017. However, the trends of sauna days with different intensities in China from 1961 to 1990 and 1991-2017 had their own subregional characteristics, which were mainly reflected in the different degrees of change in the regions where the increasing and decreasing trends were concentrated. In the fluctuation characteristics, the fluctuations of sauna days with different intensities in China was bounded by the Hu Huanyong Line, showing a spatial pattern of large fluctuations in the southeast China and small fluctuations in the northwest China. And the fluctuations of sauna days and heavy sauna days showed obvious threeblock distribution characteristics, that is, the fluctuation was large in the ecotone between agriculture and animal husbandry and its vicinity, followed by the southeast region, and the smallest in the northwest region. However, there was no such phenomenon in the fluctuation characteristic of extreme sauna days, which showed a southeastnorthwest twoblock differentiation characteristic. The differences in the fluctuations of sauna days with different intensities in China before and after 1990 showed that the fluctuation characteristics of sauna days with different intensities in China in 1961-1990 and 1991-2017 were similar to those in 1961-2017 overall, and the regions with large differences were mainly distributed in the boundary line and its east.
Discussion and prospect
Discussion of the definition of sauna days
The term "sauna days" appeared in the situation of frequent hightemperature heat waves in recent years. Based on the definition of sauna days given by the Central Meteorological Observatory of China Meteorological Administration, this paper analyzed the spatial evolution characteristics of sauna days with different intensities in China. However, it is worth noting that due to the large latitude span in the north and south of China, there is a large difference in relative humidity between the north and the south. Therefore, it is urgent to use the relative standard of sauna days to diagnose the regional spatialtemporal variation characteristics of sauna days. Regional sauna day forecasting standards should be developed through a comparison of sauna days defined by various thresholds.
Quantitative determination of the impacts of climate change and urbanization on sauna days
With rapid urbanization and climate change, it has significantly influenced the number of sauna days in urban areas. So what role does urbanization and climate change play in the increase in sauna days? Which one plays a leading role? This is one of the issues that need urgent attention.Quantitatively determining the impact of natural climate change and human activities characterized by urbanization on the changes in sauna days is not only helpful in understanding the changes in extreme weather and climate events in the context of climate change, but also in understanding the influence depth and breadth of human activities in the process of climate change. Study on the impact of extreme hightemperature heat waves on health risks
The hightemperature heat waves characterized by the number of sauna days directly affect by human health, especially for the public engaged in outdoor work. At present, with the increasing urban population and the aging population in China, the increase in sauna days is bound to have a significant impact on the safe operation and sustainable development of cities. Therefore, it is urgent to quantitatively evaluate the possible impact of extremelyhightemperature heat waves on different populations based on the regional disaster system theory, from the stability of hazard inducing environments, the risk of disasterinducing factors and the vulnerability of hazardaffected bodies, which not only helps to prevent the risks of heatstroke and thermoplegia in different populations, but also helps to understand in depth the ways, processes and mechanisms of the impact of extreme weather and climate events on socioeconomic situation in the context of climate change.
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