Retrieval of atmospheric temperature and humidity profiles from FY-3E MWTS and MWHS data using deep learning neural networks

Shengxiang Meng; Tianxu Zhang; Gengming Jiang; Hongxia Ye

doi:10.1117/12.3020954

19 January 2024 Retrieval of atmospheric temperature and humidity profiles from FY-3E MWTS and MWHS data using deep learning neural networks

Shengxiang Meng, Tianxu Zhang, Gengming Jiang, Hongxia Ye

Author Affiliations +

Proceedings Volume 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023); 1298023 (2024) https://doi.org/10.1117/12.3020954
Event: Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 2023, Lianyungang, China

Abstract

Atmospheric temperature and humidity profiles are key parameters in weather forecasting and climate studies. This paper addresses the retrieval of atmospheric temperature and humidity profiles from the data acquired by the Microwave Temperature Sounder (MWTS) and the Microwave Humidity Sounder (MWHS) on Fengyun 3E (FY-3E) satellite using deep learning neural networks. The four-layer back-propagation neural network (BPNN) and the back-propagation dendritic neural network (BDNN) are firstly constructed, and then they are trained and validated using the matching samples between FY-3E MWTS/MWHS data and the fifth European Centre for Medium-Range Weather Forecasts(ECMWF) Re-analysis (ERA5) data. The results show that the BDNN method is better than the traditional linear regression method and the BPNN method. Over ocean, the root mean square errors (RMSEs) of the temperature and humidity profiles retrieval are less than 2.0 K and 1.0 g/kg, respectively, whereas they are, respectively, less than3.0Kand 2.0 g/kg over land.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shengxiang Meng, Tianxu Zhang, Gengming Jiang, and Hongxia Ye "Retrieval of atmospheric temperature and humidity profiles from FY-3E MWTS and MWHS data using deep learning neural networks", Proc. SPIE 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 1298023 (19 January 2024); https://doi.org/10.1117/12.3020954

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available