Quality Scoring of the Fengyun 4A Clear Sky Radiance Product

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 18; p. 3658
• Main Authors: Yu, Tianlei, Ma, Gang, Lu, Feng, Zhang, Xiaohu, Zhang, Peng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2021
• Subjects: AGRI water vapor channel; Channels; clear sky radiance; Cloud cover; Data assimilation; Data collection; Field of view; Humidity; Meteorological satellites; Numerical prediction; Numerical weather forecasting; Quality control; Radiance; Remote sensing; Root-mean-square errors; Sensors; Sky; superobservation; Water vapor; Wavelengths; Weather forecasting; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13183658

The Clear Sky Radiance (CSR) product has been widely used instead of Level 1 (L1) geostationary imager data in data assimilation for numerical weather prediction due to its many advantages concerning superobservation methodology. In this study, CSR was produced in two water vapor channels (channels 9 and channel 10, with wavelengths at 5.8–6.7 μm and 6.9–7.3 μm) of the Advanced Geostationary Radiation Imager aboard Fengyun 4A. The root mean square error (RMSE) between CSR observations and backgrounds was used as a quality flag and was predicted by cloud cover, standard deviation (STD), surface type, and elevation of a CSR field of view (FOV). Then, a centesimal scoring system based on the predicted RMSE was set to a CSR FOV that indicates its percentile point in the quality distribution of the whole FOV. Validations of the scoring system demonstrated that the biases of the predicted RMSE were small for all FOVs and that the score was consistent with the predicted RMSE, especially for FOVs with high scores. We suggest using this score for quality control (QC) to replace the QC of cloud cover, STD, and elevation of CSR, and we propose 40 points as the QC threshold for the two channels, above which the predicted RMSE of a CSR is superior to the RMSE of averaged clear-sky L1 data.