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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume XLII-3/W10
https://doi.org/10.5194/isprs-archives-XLII-3-W10-261-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLII-3-W10-261-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
07 Feb 2020
THUNDERSTORM WEATHER ANALYSIS BASED ON XGBOOST ALGORITHM
L. L. Liu
College of Surveying and Mapping Geographic Information, Guilin University of Technology, Gulin, Guangxi, China
H. C. Liu
College of Surveying and Mapping Geographic Information, Guilin University of Technology, Gulin, Guangxi, China
C. F. Zhu
College of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China
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Short summary
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The existing ZTD models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data for modeling. This model considers the daily-cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
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Short summary
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The existing ZTD models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data for modeling. This model considers the daily-cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
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Q. T. Wan, L. L. Liu, L. K. Huang, W. Zhou, Y. Z. Yang, and Z. X. Chen
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J. M. Su, L. L. Liu, Q. T. Wan, Y. Z. Yang, and F. F. Li
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F. F. Li, L. L. Liu, L. K. Huang, W. Zhou, and S. Wang
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H. Peng, L. K. Huang, C. Li, L. L. Liu, S. Wang, and S. Wang
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X. C. Li, L. L. Liu, and L. K. Huang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 605–611, https://doi.org/10.5194/isprs-archives-XLII-3-W10-605-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-605-2020, 2020
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