Open AccessAn Optimal Scheduling Method for Numerical Weather Model Assimilation with Dense Observations
Author(s) -
Xingguo Cheng,
Yuxing Zhuang,
Jiaqing Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/4/042027
Subject(s) - data assimilation , computer science , grid , numerical weather prediction , scheduling (production processes) , meteorology , algorithm , mathematical optimization , environmental science , initial value problem , real time computing , mathematics , geology , geography , geodesy , mathematical analysis
In this paper, the scheduling problem of dense observation data in a numerical weather model assimilation system is studied and an algorithm of "deal-reveal" is proposed. The algorithm identifies the area where all dense observation stations are located, and then obtains a certain number of grid point on which the value represents the stations quantity overlaid on it. The algorithm selects the stations with maximum value corresponding to the dense observation data iteratively and make the amount of each batch of dense observation stations as more as possible to reduce the batch number, enhances the overall performance of the system finally.