Validation of TROPOMI SIF Products With Improved Geolocation Match Between In Situ and Satellite Measurements

Direct comparison with in situ measurements serves as the primary method for validating TROPOMI SIF products. However, due to geometric errors in satellite data, the exact spatial extent of the nominal validation pixel may not align with the in situ site perfectly. In addressing this challenge, this study proposed, for the first time, a method to precisely identify the validation pixels matching with in situ sites. Moreover, the accuracy of the TROPOMI SIF product was reevaluated with the improved geolocation match method between the satellite pixel and the corresponding in situ site. The results indicate that ignoring the geometric errors of TROPOMI pixels can result in a 49% probability of mismatch between the validation pixel and the in situ site. The errors caused by geolocation mismatch mainly come from two aspects. One is the incorrect extraction of the validation pixel, with a maximum error of 1.385 mWm−2 sr−1 nm−1. The other is the pixel‐scale reference “truth,” which resulted from the improper upscaling function of in situ measurements, and the maximum of this kind of error was 0.445 mWm−2 sr−1 nm−1. With this improved geolocation match method, the TROPOMI SIF product showed a RMSE of 0.58 mWm−2 sr−1 nm−1, a bias of 0.19 mWm−2 sr−1 nm−1, and a R2 of 0.51, which indicate a better performance than without considering geometric location matching errors. Plain Language Summary To rigorously validate TROPOMI SIF products, it is crucial to identify the validation pixel that aligns perfectly with in situ site measurements. However, the geolocation shifts of TROPOMI pixels widely exist, and the magnitude and direction of shifts are random. Consequently, there is a possibility that the nominal validation pixel is mismatched with the in situ site. Currently, there is no effective method to accurately identify the exact validation pixels corresponding to in situ sites. In response to this challenge, this study proposed a novel method to precisely identify the exact validation pixel matched with in situ sites. With this method, the accuracy of the TROPOMI SIF product was reevaluated. The results indicate that the uncertainty of TROPOMI SIF products is overestimated when neglecting the geometric errors of TROPOMI. Key Points An improved geolocation match method between TROPOMI pixels and in situ sites was proposed There is a 49% probability that the TROPOMI pixel is mismatched with the in situ sites when its geometric errors are ignored The geolocation mismatc