本文利用丽江站1960~2019年逐日平均气温、相对湿度资料,统计分析了丽江市近60a人体舒适度指数的等级分布特征,利用线性趋势研究人体舒适度指数的年际变化特征和季节变化特征。研究结果表明:(1) 丽江市人体舒适度指数等级在2~6级间变化...本文利用丽江站1960~2019年逐日平均气温、相对湿度资料,统计分析了丽江市近60a人体舒适度指数的等级分布特征,利用线性趋势研究人体舒适度指数的年际变化特征和季节变化特征。研究结果表明:(1) 丽江市人体舒适度指数等级在2~6级间变化,主要集中在3~5级,其中舒适度4级日数最多,在全年1~12月中均有出现,舒适度5级日数次之;(2) 丽江市最舒适的月份为5~9月,其次为2~4月、10~11月,最不舒适的月份为1月、12月;(3) 1960~2019年丽江年均人体舒适度指数存在非常显著的上升趋势,线性趋势为0.30/10a,于2019年达到最高值,人体舒适度指数平均值为56.22,属于舒适度4级;(4) 丽江地区四季的人体舒适度指数从高到低为夏季、春季、秋季、冬季,四季的人体舒适度指数均存在显著的上升趋势,其中冬季的上升趋势最明显,线性趋势达到0.40/10a,春、夏季次之,秋季最低。Based on the daily average temperature and relative humidity data of Lijiang Station from 1960 to 2019, this paper analyzed the grade distribution characteristics of Human Comfort Index in Lijiang City in the past 60 years, and used the linear trend to study the interannual and seasonal variation characteristics of Human Comfort Index. The results showed that: (1) The Human Comfort Index in Lijiang City ranges from level 2 to level 6, predominantly falling within levels 3 to 5, among which the number of days with comfort level 4 was the largest, which appeared from January to December throughout the year, followed by the number of days with comfort level 5;(2) The most comfortable months in Lijiang are from May to September, followed by February to April and October to November, and the most uncomfortable months are January and December. (3) From 1960 to 2019, the average annual Human Comfort Index in Lijiang had a very significant upward trend, with a linear trend of 0.30/10a, reaching the highest value in 2019, and the average Human Comfort Index was 56.22, corresponding to comfort level 4. (4) The Human Comfort Index in Lijiang area from high to low in summer, spring, autumn and winter, and there was a significant upward trend in the four seasons, among which the upward trend was the most obvious in winter, with a linear trend of 0.40/10a, followed by spring and summer, and the lowest in autumn.展开更多
利用AMSR-E观测的土壤表层亮温资料,采用简化修正的单通道算法模型(Single Channel Algorithm,SCA),反演青藏高原地区夏季2011年6-8月的表层土壤湿度。为对比验证反演结果,利用高原东部和中部的玛曲观测网和那曲观测网CTP-SMTMN(Soil Mo...利用AMSR-E观测的土壤表层亮温资料,采用简化修正的单通道算法模型(Single Channel Algorithm,SCA),反演青藏高原地区夏季2011年6-8月的表层土壤湿度。为对比验证反演结果,利用高原东部和中部的玛曲观测网和那曲观测网CTP-SMTMN(Soil Moisture and Temperature Monitoring Netw ork on the central Tibetan Plateau)的土壤湿度观测数据,以及NASA和VUA-NASA两种均基于AM SR-E的反演土壤湿度产品进行验证。结果表明:(1)与VUA-NASA产品和修改后的SCA模型反演结果相比,NASA产品在像元和区域尺度上相关系数较低,MAE(Mean Absolute Error)和RMSE(Root M ean Square Error)较高,明显低估了两个地区的土壤湿度。(2)VUA-NASA产品在玛曲地区表现良好,在那曲地区虽然相关系数较高,但MAE和RMSE同样较高,导致精度较差。(3)对比其他两种产品,修改后的SCA模型反演结果在两个地区表现出较高的相关系数(接近0.800)、较低的MAE(接近0.050m^3·m^(-3))和RMSE(接近0.060 m^3·m^(-3)),有着较高的精度。因此,可以认为修改后的SCA模型可以应用于青藏高原地区土壤湿度动态监测,为研究青藏高原地区的天气和气候变化影响及水循环过程提供了参考和借鉴。展开更多
文摘本文利用丽江站1960~2019年逐日平均气温、相对湿度资料,统计分析了丽江市近60a人体舒适度指数的等级分布特征,利用线性趋势研究人体舒适度指数的年际变化特征和季节变化特征。研究结果表明:(1) 丽江市人体舒适度指数等级在2~6级间变化,主要集中在3~5级,其中舒适度4级日数最多,在全年1~12月中均有出现,舒适度5级日数次之;(2) 丽江市最舒适的月份为5~9月,其次为2~4月、10~11月,最不舒适的月份为1月、12月;(3) 1960~2019年丽江年均人体舒适度指数存在非常显著的上升趋势,线性趋势为0.30/10a,于2019年达到最高值,人体舒适度指数平均值为56.22,属于舒适度4级;(4) 丽江地区四季的人体舒适度指数从高到低为夏季、春季、秋季、冬季,四季的人体舒适度指数均存在显著的上升趋势,其中冬季的上升趋势最明显,线性趋势达到0.40/10a,春、夏季次之,秋季最低。Based on the daily average temperature and relative humidity data of Lijiang Station from 1960 to 2019, this paper analyzed the grade distribution characteristics of Human Comfort Index in Lijiang City in the past 60 years, and used the linear trend to study the interannual and seasonal variation characteristics of Human Comfort Index. The results showed that: (1) The Human Comfort Index in Lijiang City ranges from level 2 to level 6, predominantly falling within levels 3 to 5, among which the number of days with comfort level 4 was the largest, which appeared from January to December throughout the year, followed by the number of days with comfort level 5;(2) The most comfortable months in Lijiang are from May to September, followed by February to April and October to November, and the most uncomfortable months are January and December. (3) From 1960 to 2019, the average annual Human Comfort Index in Lijiang had a very significant upward trend, with a linear trend of 0.30/10a, reaching the highest value in 2019, and the average Human Comfort Index was 56.22, corresponding to comfort level 4. (4) The Human Comfort Index in Lijiang area from high to low in summer, spring, autumn and winter, and there was a significant upward trend in the four seasons, among which the upward trend was the most obvious in winter, with a linear trend of 0.40/10a, followed by spring and summer, and the lowest in autumn.
文摘利用AMSR-E观测的土壤表层亮温资料,采用简化修正的单通道算法模型(Single Channel Algorithm,SCA),反演青藏高原地区夏季2011年6-8月的表层土壤湿度。为对比验证反演结果,利用高原东部和中部的玛曲观测网和那曲观测网CTP-SMTMN(Soil Moisture and Temperature Monitoring Netw ork on the central Tibetan Plateau)的土壤湿度观测数据,以及NASA和VUA-NASA两种均基于AM SR-E的反演土壤湿度产品进行验证。结果表明:(1)与VUA-NASA产品和修改后的SCA模型反演结果相比,NASA产品在像元和区域尺度上相关系数较低,MAE(Mean Absolute Error)和RMSE(Root M ean Square Error)较高,明显低估了两个地区的土壤湿度。(2)VUA-NASA产品在玛曲地区表现良好,在那曲地区虽然相关系数较高,但MAE和RMSE同样较高,导致精度较差。(3)对比其他两种产品,修改后的SCA模型反演结果在两个地区表现出较高的相关系数(接近0.800)、较低的MAE(接近0.050m^3·m^(-3))和RMSE(接近0.060 m^3·m^(-3)),有着较高的精度。因此,可以认为修改后的SCA模型可以应用于青藏高原地区土壤湿度动态监测,为研究青藏高原地区的天气和气候变化影响及水循环过程提供了参考和借鉴。
