# Radiometric Calibration of the Near-Infrared Bands of GF-5-02/DPC for Water Vapor Retrieval
## 5 Discussion  
Due to the systematic radiometric calibration error present in the bands of the DPC that are used for PWV retrieval, the existing DPC PWV data derived from the observations of the uncalibrated DPC have large errors [5]. In order to reduce the error in the DPC PWV data, the DPC at bands at 865 nm and 910 nm used for PWV retrieval is calibrated in this study. It is of interest to determine whether calibrating the DPC at the NIR08 and NIR09 bands can effectively reduce the retrieval error of DPC PWV data. As mentioned earlier, the matching results between the DPC data and AERONET data are randomly split into two sets in a 7:3 ratio. Among them, 30% of the data would be used for the accuracy evaluation of DPC PWV data. Additionally, SuomiNET PWV data, which are independent of AERONET PWV data, are also utilized to validate the DPC PWV data, so as to achieve a more comprehensive accuracy assessment of the DPC PWV data. The accuracy evaluation results of the DPC PWV data based on ground-based PWV data are illustrated in Figure 8.  
Figure 7: The distribution of the values of \(R^{\prime}_{910 nm}/R_{910 nm}\). The black line represents the normal distribution function corresponding to \(R^{\prime}_{910 nm}/R_{910 nm}\). The validation results based on the AERONET PWV data show that the relative error (RE) and mean absolute error (MAE) for the DPC PWV data developed using data before calibration (referred to as data M1) are 0.28 and 0.36 cm, respectively; the RE and MAE for the DPC PWV data developed using the data after recalibration (referred to as data M2) are 0.14 and 0.18 cm, respectively. Data M2 exhibited a reduction of about 50% in both the AERONET and AERONET data. Figure 8: Validation results of PWV data retrieved using DPC data before and after radiometric calibration. (**a**) Validation results of data M1 based on AERONET data. (**b**) Validation results of data M2 based on AERONET data. (**c**) Validation results of data M1 based on SuomiNET data. (**d**) Validation results of data M2 based on SuomiNET data. (**e**) Validation results of data M1 based on both SuomiNET and AERONET data. (**f**) Validation results of data M2 based on both SuomiNET and AERONET data. MAE and RE compared to data M1. The validation results based on SuomiNET PWV data show that the RE and MAE for data M1 are 0.24 and 0.21 cm, respectively; the RE and MAE for data M2 are 0.20 and 0.18 cm, respectively. Compared with data M1, data M2 show a 17% decrease in the RE, and a 14% decrease in the MAE. The validation results based on both the SuomiNET PWV data and AERONET PWV data show that the RE and MAE for data M1 are 0.25 and 0.26 cm, respectively; the RE and MAE for data M2 are 0.18 and 0.18 cm, respectively. Compared with data M1, data M2 show a 28% decrease in the RE, and a 31% decrease in the MAE. For ease of description, the accuracy improvement of data M2 relative to data M1 is abbreviated as AI21. Due to the calibration model used for DPC being constructed based on the AERONET PWV data and the difference between the SuomiNET PWV data and AERONET PWV data [19], it is reasonable that the AI21 calculated based on the SuomiNET PWV data is worse than the AI21 calculated based on the AERONET PWV data. However, regardless of whether the AERONET PWV data or the SuomiNET PWV data are used as reference data, the accuracy of data M2 is significantly superior to that of data M1. The distribution of the absolute errors of the DPC PWV data calculated using both the AERONET PWV data and SuomiNET PWV data is shown in Figure 9. Because of the decreasing sensitivity of the NIR water vapor absorption channel with increasing water vapor content [20], the absolute errors of data M1 and data M2 both increase with the increase in the water vapor content. Overall, data M2 demonstrates smaller absolute errors compared to data M1 across all ranges.