一種基于動態(tài)參數(shù)的氣象要素空間插值方法及其試驗結(jié)果分析

doi:10.12306/2023jms.0057

首頁 > 過刊瀏覽>2025年第45卷第3期 >441-453. DOI:10.12306/2023jms.0057

一種基于動態(tài)參數(shù)的氣象要素空間插值方法及其試驗結(jié)果分析
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                        10.12306/2023jms.0057
                    
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中圖分類號:P468.0
基金項目:國家自然科學(xué)基金資助項目(42075115);國家重點研發(fā)計劃資助項目(2018YFC1505804)

A method for spatial interpolation of meteorological elements based on dynamic parameters and analysis of experimental results

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為解決氣象要素空間插值方法中不能動態(tài)選取各插值點最鄰近的參考點個數(shù)或者影響半徑的問題,以及針對氣象要素的空間位置擬合函數(shù)適用性問題,本文提出一種基于動態(tài)參數(shù)的氣象要素空間插值方法。該方法采用淺層級聯(lián)前饋神經(jīng)網(wǎng)絡(luò)對插值的參考點進行非線性擬合,并考慮到距離、水平角、高度差因素進行基于梯度變換的空間插值,最后將這三個因素的權(quán)重綜合成空間權(quán)重,作為插值點最鄰近參考點個數(shù)動態(tài)選取的先驗評估指標,從而降低了插值方法參數(shù)設(shè)置難度并提高了插值的準確性?；?022年中國陸地區(qū)域的實驗結(jié)果表明:該方法和方向反距離加權(quán)法(Aspect and Inverse Distance Weighted,AIDW)、普通克里金插值法(Ordinary Kriging,OK)、薄盤光譜樣條插值法(Thin-Plate Smoothing Spline,TPSS)相比較,在氣溫和絕對濕度插值上的平均誤差最小,其中氣溫比誤差第二小的TPSS的MAE降低0.23 ℃、RMSE降低0.44 ℃、絕對濕度比TPSS的MAE降低0.06 g·m^-3、RMSE降低了0.12 g·m^-3。

Abstract:

To solve the problem that the number of nearest reference points or influence radius on each interpolation point cannot be dynamically selected in the spatial interpolation method of meteorological elements, and to solve the applicability of fitting function for spatial location to meteorological elements, a spatial interpolation method of meteorological elements based on dynamic parameters was proposed. In the method, shallow cascade back propagation neural network was used for nonlinear fitting of reference points, and the spatial interpolation of interpolation points was completed on three factors: distance, horizontal angle and height difference basis of gradient transformation, finally, the weights of three factors were synthesized into spatial weights, which were used as a pre-evaluation index for dynamic selection of the number of nearest reference points, thus the method could reduce the difficulty of parameter setting and improve the accuracy of interpolation method. The experimental results based on the Chinese land area of 2022 show that compared with Aspect and Inverse Distance Weighted(AIDW), Ordinary Kriging(OK) and Thin-Plate Smoothing Spline(TPSS), the method's average error in the interpolation of air temperature and absolute humidity are the smallest, where the MAE of air temperature decreased by 0.23℃ and the RMSE decreased by 0.44 ℃ compared with TPSS whose average errors are the second smallest; the MAE of absolute humidity decreased by 0.06 g·m^-3 and the RMSE decreased by 0.12 g·m^-3 compared with TPSS.

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樊仲欣,李進喜,姚琦,譚桂容.一種基于動態(tài)參數(shù)的氣象要素空間插值方法及其試驗結(jié)果分析.氣象科學(xué),2025,45(3):441-453 FAN Zhongxin, LI Jinxi, YAO Qi, TAN Guirong. A method for spatial interpolation of meteorological elements based on dynamic parameters and analysis of experimental results. Journal of the Meteorological Sciences,2025,45(3):441-453

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收稿日期:2023-05-19
最后修改日期:2023-06-19
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在線發(fā)布日期: 2025-08-30
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