地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (11): 1613-1621.doi: 10.12082/dqxxkx.2018.180222

• 地理空间分析综合应用 • 上一篇    下一篇

南京市高温热浪时空分布研究

周洋1(), 祝善友1,*(), 华俊玮2, 刘祎1, 向嘉敏1, 丁文3   

  1. 1. 南京信息工程大学 遥感与测绘工程学院,南京 210044
    2. 滁州市气象局,滁州 233299
    3. 南京长天测绘技术有限公司, 南京 211100
  • 收稿日期:2018-05-07 修回日期:2018-08-22 出版日期:2018-11-20 发布日期:2018-11-28
  • 通讯作者: 祝善友 E-mail:zhouyangnuist@163.com;zsyzgx@163.com
  • 作者简介:

    作者简介:周 洋(1994-),男,汉,江苏南京人,硕士生,主要研究方向热红外遥感与气象应用。E-mail: zhouyangnuist@163.com

  • 基金资助:
    国家自然科学基金项目(41571418、41401471);江苏省“青蓝工程”项目

Spatio-temporal Distribution of High Temperature Heat Wave in Nanjing

ZHOU Yang1(), ZHU Shanyou1,*(), HUA Junwei2, LIU Yi1, XIANG Jiamin1, DING Wen3   

  1. 1. School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science&Technology, Nanjing 210044, China;
    2. Chuzhou meteorological bureau, Chuzhou 233299, China
    3. Nanjing Changtian Surveying and Technology Co, Nanjing 211100, China
  • Received:2018-05-07 Revised:2018-08-22 Online:2018-11-20 Published:2018-11-28
  • Contact: ZHU Shanyou E-mail:zhouyangnuist@163.com;zsyzgx@163.com
  • Supported by:
    National Natural Science Foundation of China, No.41571418、41401471;Project of "Blue Project" in Jiangsu Province.

摘要:

在全球气候变暖的背景下,城市夏季高温热浪已经成为城市最严重的气象灾害之一,给城市居民健康和经济发展带来了巨大的影响。以2013年8月7日-13日的南京高温热浪灾害事件为例,基于Landsat 8 OLI 卫星遥感数据、MODIS卫星遥感数据和气象站点数据,在MODIS地表温度降尺度基础上,估算近地表气温,进而结合空气相对湿度的空间插值数据计算南京地区100 m分辨率的炎热指数和高温热浪指数,分析其时空分布特征。结果表明:在这次高温热浪演变过程中,南京炎热指数呈现先升高后降低的变化趋势,8月11日炎热指数最高,平均达到86.99,12日降到最低值,平均值为85.05;高温热浪强度主要集中于轻度热浪与中度热浪,随着时间的推移,其范围也呈现先扩大后减小的趋势;在空间分布上,南京北部及中心城区的炎热指数较高,主要表现为中度热浪,而南部地区及中心城区周边郊区较低,主要为轻度热浪,山体和水域炎热指数则最低,多为无热浪。

关键词: 南京, 高温热浪, 炎热指数, 高温热浪指数, 时空分布

Abstract:

Under the background of global warming, the urban heat wave in summer has become one of the most serious meteorological disasters, which has brought tremendous impact on the health and economic development of urban residents. Taking the heat wave disaster event occurred in Nanjing from August 7 to 13, 2013 as an example, the near-surface air temperatures were estimated based on the downscaled MODIS land surface temperature using the Landsat 8 OLI image data, MODIS data products, and field-measurement meteorological data. Combined with the spatial interpolation data of the relative humidity, the hot index and the high temperature heat-wave index at the resolution of 100m were calculated, and then their spatial and temporal distribution characteristics were analyzed. The results show that during the evolution of the high temperature heat wave in Nanjing, the hot index increased firstly and then decreased with time. The hot index was highest on Aug. 11th with an average of 86.99, and it fell off to the lowest value of 85.05 on Aug. 12th; the heat wave intensity mainly concentrates on mild and moderate degrees, and its range also shows a tendency of expanding firstly and then decreasing with time. In terms of spatial distribution, the hot index is higher in northern region and central urban areas and mainly display as a moderate heat wave, while the heat index in the southern suburbs and central suburbs is lower and the heat wave is mild, and the mountain and the water areas have the lowest heat index.

Key words: Nanjing, heat waves, hot index, high temperature heat-wave index, spatial and temporal distribution