Comparison of Machine-Learning Algorithms for Near-Surface Air-Temperature Estimation from FY-4A AGRI Data
Joint Authors
Zhang, Shenglan
Deng, Xiaobo
Zhou, Ke
Liu, Hailei
Wang, Hao
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-06
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Six machine-learning approaches, including multivariate linear regression (MLR), gradient boosting decision tree, k-nearest neighbors, random forest, extreme gradient boosting (XGB), and deep neural network (DNN), were compared for near-surface air-temperature (Tair) estimation from the new generation of Chinese geostationary meteorological satellite Fengyun-4A (FY-4A) observations.
The brightness temperatures in split-window channels from the Advanced Geostationary Radiation Imager (AGRI) of FY-4A and numerical weather prediction data from the global forecast system were used as the predictor variables for Tair estimation.
The performance of each model and the temporal and spatial distribution of the estimated Tair errors were analyzed.
The results showed that the XGB model had better overall performance, with R2 of 0.902, bias of −0.087°C, and root-mean-square error of 1.946°C.
The spatial variation characteristics of the Tair error of the XGB method were less obvious than those of the other methods.
The XGB model can provide more stable and high-precision Tair for a large-scale Tair estimation over China and can serve as a reference for Tair estimation based on machine-learning models.
American Psychological Association (APA)
Zhou, Ke& Liu, Hailei& Deng, Xiaobo& Wang, Hao& Zhang, Shenglan. 2020. Comparison of Machine-Learning Algorithms for Near-Surface Air-Temperature Estimation from FY-4A AGRI Data. Advances in Meteorology،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1127206
Modern Language Association (MLA)
Zhou, Ke…[et al.]. Comparison of Machine-Learning Algorithms for Near-Surface Air-Temperature Estimation from FY-4A AGRI Data. Advances in Meteorology No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1127206
American Medical Association (AMA)
Zhou, Ke& Liu, Hailei& Deng, Xiaobo& Wang, Hao& Zhang, Shenglan. Comparison of Machine-Learning Algorithms for Near-Surface Air-Temperature Estimation from FY-4A AGRI Data. Advances in Meteorology. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1127206
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1127206