Diurnal Bias Correction of FY-4B AGRI Water Vapor Channels with Time-Shifted Solar Elevation Angle

<p indent="0mm">The infrared channels of the FY-4B advanced geosynchronous radiation imagers (AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the initial field quality and the forecasting accuracy of the model. This study assimilated FY-4B AGRI data into the CMA-MESO model and analyzed the bias characteristics and correction methods. Analysis of the AGRI data revealed a clear diurnal variation in the bias, which was positively correlated with the solar elevation angle. However, the diurnal variation in the bias lagged behind the solar elevation angle, likely owing to temperature changes and delayed instrument responses resulting from solar radiation. To address this issue, we propose a correction method that utilizes the solar elevation angle after an optimal time shift. Using the time-shifted solar elevation angle as a predictor effectively reduces the diurnal variation in bias and significantly improves the correction effect. This approach provides theoretical support for the assimilation of FY-4B AGRI data into mesoscale numerical weather predictions, thereby enhancing the reliability of the assimilation results.

Authors

Publication Details

Journal
Journal of Tropical Meteorology
Published
2026-01-14
DOI
https://doi.org/10.3724/j.1006-8775.2025.036
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

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article

Diurnal Bias Correction of FY-4B AGRI Water Vapor Channels with Time-Shifted Solar Elevation Angle

Jia-yun SONG, Hao-fei SUN, Yun-fan YANG, Wei Han
Journal of Tropical Meteorology
Meteorological Phenomena and Simulations
article

Diurnal Bias Correction of FY-4B AGRI Water Vapor Channels with Time-Shifted Solar Elevation Angle

Jia-yun SONG, Hao-fei SUN, Yun-fan YANG, Wei Han
article en

Abstract

<p indent="0mm">The infrared channels of the FY-4B advanced geosynchronous radiation imagers (AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the initial field quality and the forecasting accuracy of the model. This study assimilated FY-4B AGRI data into the CMA-MESO model and analyzed the bias characteristics and correction methods. Analysis of the AGRI data revealed a clear diurnal variation in the bias, which was positively correlated with the solar elevation angle. However, the diurnal variation in the bias lagged behind the solar elevation angle, likely owing to temperature changes and delayed instrument responses resulting from solar radiation. To address this issue, we propose a correction method that utilizes the solar elevation angle after an optimal time shift. Using the time-shifted solar elevation angle as a predictor effectively reduces the diurnal variation in bias and significantly improves the correction effect. This approach provides theoretical support for the assimilation of FY-4B AGRI data into mesoscale numerical weather predictions, thereby enhancing the reliability of the assimilation results.

Journal of Tropical MeteorologyVol. 32(1)
National Natural Science Foundation of China, European Centre for Medium-Range Weather Forecasts, National Key Research and Development Program of China
Openalex Percentile: Top 54%
Meteorological Phenomena and Simulations
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