• 论文 •

### 福建省复杂地形下旬平均气温分布式模拟

1. （1. 南京信息工程大学 地理科学学院，南京 210044；2. 江苏省气候中心，南京 210044；3. 湖州市气象局，浙江 湖州 313300）
• 出版日期:2019-03-05 发布日期:2019-03-05
• 通讯作者: 邱新法（1966—），男，浙江湖州人，教授，博士生导师，博士，研究方向“3S”集成与气象应用、地理信息系统应用、资源环境遥感，（E-mail）xfqiu135@nuist.edu.cn。
• 作者简介:李威鹏（1992—），男，河南漯河人，硕士研究生，研究方向为GIS在气象中的应用，（E-mail）nuistlvp@163.com；
• 基金资助:
国家自然科学基金重点项目“中国湿润—干旱过渡带水循环过程对气候变化的响应机制”（41330529）；江苏省第四期“333高层次人才培养工程”科研项目“气候资源定量空间扩展方法研究”（BRA2014373）

### Ten-day Distributed Simulation of Average Temperature in Complex Terrain in Fujian Province

Li Weipeng1, Qiu Xinfa1, Zeng Yan2, Shi Guoping1, Xu Jinqin1 and Wang Dandan1,3

1. (1. Nanjing University of Information Science and Technology, School of Geographical Sciences, Nanjing 210044, China; 2. Jiangsu Climate Center, Nanjing 210044, China; 3. Huzhou Meteorological Bureau, Huzhou 313300, China)
• Online:2019-03-05 Published:2019-03-05

Abstract: Observation data of 33 conventional meteorological stations in Fujian Province and its surrounding areas, from 1960 to 2010, and digital elevation model (DEM) data, were used to examine the effects of altitude, total solar radiation, and effective long-wave radiation on mean temperature of a 10-day period over complex terrain in Fujian Province, China. The spatial distribution of 100 m resolution temperatures was simulated using a distributed model of 10-day temperature. The results showed that: 1)the results of the conventional station calibration showed that the maximum of mean absolute bias error (MAE) was 2.3℃, the minimum was 0.46℃, and the average for the whole year was 0.87℃. The calibration results of the meteorological stations showed that the maximum of MAE was 2.3℃, the minimum temperature was 0.5℃, and the annual average was 0.96℃. 2)The simulation results can reflect the macroscopic distribution and local details of the 10-day’s average temperature. At a macroscopic scale, average temperature was affected by latitude, and temperature gradually increased from north to south. Average temperature in coastal areas was higher than that on land, and average temperature in the mountainous area was significantly lower. At a local scale, due to the influence of topographic factors such as altitude, slope, and aspect, the temperature difference between different aspects was significant. The higher the altitude, the larger the slope, the larger the difference became. The influence of topographic factors on average temperature of 10-day periods exhibited seasonal differences. Topographic factors had the largest influence on 10-day average temperature in winter, and this was reduced. Topographical factors had the weakest influence on average temperature in the spring and summer.