CAJ | 학술논문

为了解决加密自动气象站资料的时空分辨率高，对资料中各个要素场插值计算时耗长，难以应用到对实时性要求高的业务系统中的问题，提出一种改进的Kriging算法，针对加密自动站的空间分布和气象学特点，预先对自动站分区，并对要素场插值的算法流程进行优化，提高其计算速度，以满足相关业务对气象数据实时性的要求。实验结果证明，本方法插值结果更接近实际观测值，且计算速度提升了约20倍。
위료해결가밀자동기상참자료적시공분변솔고，대자료중각개요소장삽치계산시모장，난이응용도대실시성요구고적업무계통중적문제，제출일충개진적Kriging산법，침대가밀자동참적공간분포화기상학특점，예선대자동참분구，병대요소장삽치적산법류정진행우화，제고기계산속도，이만족상관업무대기상수거실시성적요구。실험결과증명，본방법삽치결과경접근실제관측치，차계산속도제승료약20배。
Due to the high spatial and temporal resolution in AWS data,interpolation calculation for element ifelds in the data is too time consuming,so as it is dififcult to apply to the business system of high real-time demand.To solve this problem,this paper presents an improved Kriging algorithm.Optimize the interpolation algorithm processes for element ifelds,according to the space distribution characteristics of AWS,and the characteristics of meteorology,so as to improve the computing speed and to meet the real-time requirements of some business systems.The test results show that the interpolation results using the improved method is closer to the observed values,and the computation time reduced approximately 20 times.