| Abstrakt: |
The magnitude of integrated water vapor (IWV) varies considerably in the spatial‐temporal domain, which demonstrates the significance of high‐spatiotemporal‐resolution IWV observations for atmospheric water vapor distribution monitoring, both locally and globally. Unlike previously published algorithms based on data fusion, an empirical retrieval algorithm is for the first time proposed to directly retrieve high‐temporal‐resolution IWV estimates from near‐infrared radiance observations of the non‐geostationary Ocean and Land Color Instrument (OLCI). The retrieval algorithm is developed based on an observed regression relationship between satellite‐based OLCI‐estimated transmittance and ground‐based Global Navigation Satellite System (GNSS)‐estimated IWV in the temporal domain. The results show that all newly retrieved IWV estimates have an overall good consistency with ground‐based IWV from additional GNSS‐sensed measurements, indicating the feasibility of the retrieval approach. The performance of the retrieval algorithm is acceptable and satisfactory when compared with that of IWV retrievals listed in previous studies. Plain Language Summary: Integrated water vapor (IWV) is the largest natural greenhouse component, which plays a crucially important role in weather, climate, and other related fields. Remote sensing of IWV from satellite‐based instruments provides a unique technique for monitoring atmospheric water vapor distribution at proper spatial and temporal resolutions in both local and global areas. However, non‐geostationary satellite‐retrieved IWV observations have much lower temporal resolutions compared to geostationary satellite‐sensed IWV measurements. The previously published improvements in the temporal resolution of non‐geostationary satellite‐retrieved IWV estimates are primarily performed based on data fusion approaches using reanalysis‐based high‐temporal‐resolution IWV data. We propose a feasible IWV retrieval algorithm for directly retrieving high‐temporal‐resolution IWV data from non‐geostationary Ocean and Land Color Instrument (OLCI)‐sensed near‐infrared radiance observations. For the first time, this study provides implications for the direct retrieval of high‐temporal‐resolution IWV estimates from non‐geostationary satellite measurements. The retrieval algorithm has significant potential to be applicable to other non‐geostationary OLCI‐like instruments, such as Medium Resolution Imaging Spectrometer (MERIS), Medium Resolution Spectral Imager (MERSI), and Moderate Resolution Imaging Spectroradiometer (MODIS). Key Points: For the first time, a relationship between Ocean and Land Color Instrument and Global Navigation Satellite System is observed and definedAn empirical retrieval model is proposed to directly derive high‐temporal‐resolution water vapor from Ocean and Land Color Instrument dataThe newly retrieved water vapor has satisfactory performance when compared with additional Global Navigation Satellite System measurements [ABSTRACT FROM AUTHOR] |
Plný text