Presented at the 2018 Ocean Salinity Science Team and Salinity Continuity Processing MeetingTwo L-Band (1.4GHz) microwave radiometer missions, the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active and Passive (SMAP) currently provide salinity measurements in the first centimetre below the sea surface. At this depth, salinity is very sensitive to precipitations that dominate variability at small temporal scale, except in river plumes (Amazon, Mississippi, etc.). The rain-related freshening observed with SMOS and SMAP is very consistent between 50°S and 50°N once the salinity error associated to each instrument is take into account. We investigate the influence of rain history on salinity anomaly. By using several microwave RR satellites (Advanced Microwave Scanning Radiometer 2 (AMSR-2), Special Sensor Microwave Imager Sounder 17 (SSMIS-17) and SSMIS-16) and by taking advantage of their different crossing times, we derive a temporal cross-correlation function between salinity freshening and rain rate for different time lags in 6 different areas. We show that the magnitude of the salinity anomaly associated with precipitation is dominated by the instantaneous RR for each area. The apparent correlation between salinity anomaly and rain history can be explained by RR autocorrelation. The relationship between salinity anomaly (DS) and RR is investigated in 6 different areas with RR provided with different algorithms (the Unified Microwave Ocean Retrieval Algorithm (UMORA), the Goddard profiling algorithm (GPROF) and Integrated MultisatellitE Retrievals for GPM (IMERG)). We observe differences in rain rates distribution between the various algorithm that lead to differences in DS versus RR relationship. For a given RR product the slight differences between the DS versus RR relationships in the various areas are explained by changes of wind speed regimes as detected by SMAP wind speed for a given rain rate.