Open AccessA new method for calculating the derivation of meteorological observational data
Author(s) -
Wang Ye-Gui,
Cai Qifa,
Shucai Huang
Publication year - 2010
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.59.4359
Subject(s) - tikhonov regularization , computer science , regularization (linguistics) , scale (ratio) , inverse problem , algorithm , inverse , series (stratigraphy) , mathematics , mathematical optimization , artificial intelligence , physics , mathematical analysis , geology , quantum mechanics , paleontology , geometry
Meteorological observation data have observational errors inevitably. It is an ill-posed inverse problem to perform the derivation of discrete data with observation errors. In order to solve the perplexing problem, this paper puts forward the new algorithm which reconstructs the first-order partial derivatives of the two-dimensional observation data in the rectangular region which is based on the idea of Tikhonov regularization . We test the performance of the algorithm with a series of simulating observation data, the results show that the algorithm is effective and has higher accuracy. It is feasible to analyze meteorological observation data with the algorithm and can enhance the recognizing ability for the small-scale weather systems.