2026-10-14T20:03:15Z https://www.scidb.cn/oai

10.57760/sciencedb.deos.0000c 2026-09-02T16:49:00Z

2026-09-02 GDCM-SSMI4: pass-specific reconstruction of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) ocean atmosphere fields while preserving observational lineage doi:10.57760/sciencedb.deos.0000c en Long-term passive microwave observations conducted by the ‘Special Sensor Microwave Imager’ (SSM/I) and the ‘Special Sensor Microwave Imager/Sounding’ (SSMIS) provide a consistent satellite data set for studying four variables—sea surface water vapour, near-surface wind speed, liquid water in clouds, and precipitation rate—which link water vapour, momentum, cloud and precipitation processes between the ocean and the atmosphere. However, due to polar orbit sampling, inversion filtering, and coverage limitations caused by overflights and satellite platforms, the daily records remain spatially incomplete, with discrepancies between the ascending and descending branches as well as across different satellite platforms. This paper introduces GDCM-SSMI4, a 1° globally gridded SSM/I and SSMIS reconstruction dataset generated using the previously published ‘Generalised Data Completion Model’ (GDCM) and released as two pass-specific sub-products organised by satellite platform, namely GDCM-SSMI4-ASC and GDCM-SSMI4-DES, covering water vapour, wind speed, cloud liquid water and precipitation rate. Independent validation of missing regions based on the intersection of a random strip mask and the original observation mask indicates a high degree of consistency between the reconstructed values and the original values selected by the strips: the correlation coefficients are 0.998–0.999 for water vapour, approximately 0.996 for wind speed, 0.992–0.994 for cloud liquid water, and 0.985–0.986 for precipitation intensity; whereas ERA5 is used solely as a reference for same-day cross-products. GDCM-SSMI4 is intended for application in fields including transit-based climatology, platform-based satellite data analysis, model and reanalysis comparisons, benchmarking of reconstruction methods, and the development of downstream ocean–atmosphere data products; its repository and DOI information will be finalised upon official release. seawater vapour; near-surface wind speed; liquid water in clouds and precipitation rate Haoyu Wang PUBLIC https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank