This dataset presents air-sea interaction fluxes derived from meteorological and sea surface (thermosalinometer) data collected between 2013 and 2023 aboard the research vessel Ramon Margalef (RM) operated by the Spanish Institute of Oceanography (IEO; IEO-CSIC since 2022). The files include sensible (SHFL) and latent (LHFL) heat  (positive towards the atmosphere), as well as momentum fluxes (MOFL, representing wind stress directed towards the sea surface). These were computed using the bulk aerodynamic approximation (Large and Yeager, 2009), which include atmospheric and oceanic measurements. Accordingly, the datasets also provide both meteorological and thermosalinometer data recorded along the vessel's trajectory, which are essential for these calculations. Meteorological variables used for calculations include atmospheric pressure at sea level (ATMS), air temperature (DRYT), relative humidity (RELH), wind speed (WSPD), and total incident radiation (RDIN), which encompasses both longwave and shortwave components. Although RDIN is not directly used for flux calculations, it is included because it complements the heat storage balance of the ocean alongside the flux variables. The sea surface temperature is stored as TEMP. The monthly files are stored in monthly Medar/Medatlas-format (Lowry et al., 2002). with hourly resolution. They are named as follows: "29RM_YYYYMM.dat", where "29RM" identifies the vessel (according to C17 SeaDataNet vocabulary),"YYYY" represents the year, and "MM" indicates the month. The dataset has undergone quality control procedures in accordance with SeaDataNet guidelines (Schaap and Lowry, 2010). As per the Medar/Medatlas format, quality control flags are included in an additional column to supplement the described variables The calculation of air-sea interaction fluxes depends on the simultaneous availability of meteorological and thermosalinometer data. When the required variables are unavailable, the flux columns are omitted. However, the remaining experimental variables are preserved, as they provide independent scientific value, contributing to the interpretation of flux signs, trends, proportionality, and behavior.