FENG Yanying,LU Huiguo,JIANG Juanping.Research on Interpolation Method based on Portable Automatic Weather Station Data[J].Journal of Chengdu University of Information Technology,2022,37(04):386-391.[doi:10.16836/j.cnki.jcuit.2022.04.004]
基于便携式自动气象站数据的插值方法研究
- Title:
- Research on Interpolation Method based on Portable Automatic Weather Station Data
- 文章编号:
- 2096-1618(2022)04-0386-06
- Keywords:
- portable automatic weather stations; meteorological data processing; air temperature interpolation; atmospheric pressure interpolation
- 分类号:
- TP274+.2
- 文献标志码:
- A
- 摘要:
- 便携式自动气象站常设在偏远无人区，受各种因素影响，其观测数据经常有缺测，使用数据插值方法提高数据连续性，可为后续研究打下重要基础。选取设在青藏高原西部无人区的7个便携式自动气象站2020年11月至2021年10月的气温、气压数据进行插值研究。气温在时间域、气压在空间域的插值方法选用最邻近插值、线性插值、三次样条插值及立方插值法。对于气温的时间插值，选取时间作为自变量，对应的气温值为因变量构建插值函数，结果表明，线性插值法插值效果最好，并且在温度较低的第一季度和第四季度插值精度高于第三季度、第二季度。对于气压的空间插值，选取海拔高度作为自变量，对应的气压值作为因变量构建插值函数，结果表明，立方插值效果最好。气温在空间域的插值方法选用反距离加权法、克里金插值法、样条函数法及基于三角形的三次插值法，通过插值目标站点周围台站的经纬度、气温值构建插值函数，结果表明，克里金插值法明显优于其他3种插值方法。
- Abstract:
- Portable automatic weather stations are often deployed in remote uninhabited areas. Due to various factors, the observation data are often missing. Using data interpolation method to improve data continuity can provide an important basis for subsequent research. In this paper, the temperature and pressure data of seven portable automatic stations deployed in the unmanned area of the western Qinghai-Tibet Plateau from November 2020 to October 2021 are selected for interpolation research. The nearest interpolation, linear interpolation, cubic spline interpolation and cubic interpolation method are selected for the interpolation of temperature in time domain and air pressure in space domain. For the time interpolation of temperature, the time is selected as the independent variable, and the corresponding temperature value is the dependent variable to construct the interpolation function. The results show that the linear interpolation method has the best interpolation effect, and the interpolation accuracy in the first and fourth quarters of the lower temperature is higher than that in the third and second quarters; for the spatial interpolation of air pressure, the altitude is selected as the independent variable, and the corresponding air pressure value is used as the dependent variable to construct the interpolation function. The results show that the cubic interpolation effect is the best. The inverse distance weighting method, Kriging interpolation method, spline function method and triangle-based cubic interpolation method are selected for the interpolation of temperature in the spatial domain. The interpolation function is constructed by interpolating the longitude and latitude of stations around the target site and the temperature value. The results show that the Kriging interpolation method is significantly better than the other three interpolation methods.
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备注/Memo
收稿日期:2021-12-08
基金项目:国家自然科学基金资助项目(42075129)