Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of...Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods.This study proposed a framework to quantify the response of surface UHI(SUHI)to urban expansion using the annual temperate cycle model.We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat.We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism.Spatially,the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas.Temporally,the increase in SUHI under urban expansion was more significant in daytime compare to nighttime.We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas.Additionally,urban greening led to the decrease in summer daytime SHUI in central urban areas.These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion,providing a scientific basis for prediction and mitigation of UHI.展开更多
In the present study we analyzed the average and extreme temperatures observed and simulated by regional models in the State of Jalisco, Mexico. Data of daily mean, minimum and maximum temperatures of 208 stations dis...In the present study we analyzed the average and extreme temperatures observed and simulated by regional models in the State of Jalisco, Mexico. Data of daily mean, minimum and maximum temperatures of 208 stations distributed all over the State during the period 1971-2000 have been used to study the observed changes in the values of average and extreme temperatures. In addition, an assessment of future scenarios for the average and extreme temperatures associated with the increase in the concentration of greenhouse gases (GHG) was performed using simulations of a PRECIS (Providing Regional Climate for Impact Studies) regional climate modeling to create the climate for present (1971-2000), and future projections for the years 2020, 2050 and 2080. Observational analysis of the 208 stations suggests warming through increased intensity and frequency of hot events, with a decrease in the frequency of cold events. More than 35% to 76% of the stations have a tendency to a decrease in the number of cold events and 39% to 64% of the stations show a growing trend in the hot events. The percentage of stations showing warming through the indices of intensity of the highest maximums, lowest minimum temperatures is 37% to 70% and 30% to 65% of the stations, respectively. Observational analysis for the State of Jalisco as a whole also shows similar results. Anomalies in the average and extreme temperatures per month during the data period show an increase (decrease) in the frequency of hot (cold) events for every month. In general, PRECIS simulations under both scenarios A1B and A2 indicate an increase in warm events and decrease of cold extreme events towards the end of the 21st century. Both show similar patterns, but the scenario A2 shows slightly lower magnitudes of projected changes. Temperatures are likely to increase all year, but it is expected that changes in summer will be more prominent.展开更多
The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and di...The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of(0.71±0.20)°C/100 m and(0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper insummer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.展开更多
基金supported by the National Science Foundation(CBET-1803920)。
文摘Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods.This study proposed a framework to quantify the response of surface UHI(SUHI)to urban expansion using the annual temperate cycle model.We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat.We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism.Spatially,the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas.Temporally,the increase in SUHI under urban expansion was more significant in daytime compare to nighttime.We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas.Additionally,urban greening led to the decrease in summer daytime SHUI in central urban areas.These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion,providing a scientific basis for prediction and mitigation of UHI.
文摘In the present study we analyzed the average and extreme temperatures observed and simulated by regional models in the State of Jalisco, Mexico. Data of daily mean, minimum and maximum temperatures of 208 stations distributed all over the State during the period 1971-2000 have been used to study the observed changes in the values of average and extreme temperatures. In addition, an assessment of future scenarios for the average and extreme temperatures associated with the increase in the concentration of greenhouse gases (GHG) was performed using simulations of a PRECIS (Providing Regional Climate for Impact Studies) regional climate modeling to create the climate for present (1971-2000), and future projections for the years 2020, 2050 and 2080. Observational analysis of the 208 stations suggests warming through increased intensity and frequency of hot events, with a decrease in the frequency of cold events. More than 35% to 76% of the stations have a tendency to a decrease in the number of cold events and 39% to 64% of the stations show a growing trend in the hot events. The percentage of stations showing warming through the indices of intensity of the highest maximums, lowest minimum temperatures is 37% to 70% and 30% to 65% of the stations, respectively. Observational analysis for the State of Jalisco as a whole also shows similar results. Anomalies in the average and extreme temperatures per month during the data period show an increase (decrease) in the frequency of hot (cold) events for every month. In general, PRECIS simulations under both scenarios A1B and A2 indicate an increase in warm events and decrease of cold extreme events towards the end of the 21st century. Both show similar patterns, but the scenario A2 shows slightly lower magnitudes of projected changes. Temperatures are likely to increase all year, but it is expected that changes in summer will be more prominent.
基金supported by the National Key R&D Program of China(2017YFA0605101)the National Natural Science Foundation of China(31770489,41273098 and 31621091)
文摘The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of(0.71±0.20)°C/100 m and(0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper insummer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.