) and preferentially in the inactive stage of the Madden-Julian oscillation. Its diurnal harmonic has an exponential vertical structure with a depth scale of 4-5 m (dependent on chlorophyll concentration), consistent with forcing by absorption of solar radiation. The effective sea surface temperature (SST) anomaly due to the diurnal warm layer often reaches 0.88C in the afternoon, with a daily mean of 0.28C, rectifying the diurnal cycle onto longer time scales. This SST anomaly drives an anomalous flux of 4 W m 22 that cools the ocean. Alternatively, in a climate model where this process is unresolved, this represents an erroneous flux that warms the ocean. A simple model predicts a diurnal warm layer to occur on 30%-50% of days across the tropical warm pool. On the remaining days, with low solar radiation and high wind speeds, a residual diurnal cycle is observed by the Seaglider, with a diurnal harmonic of temperature that decreases linearly with depth. As wind speed increases, this already weak temperature gradient decreases further, tending toward isothermal conditions.

Highlights Sea surface salinity retrieved from SMAP radiometer is validated with in situ data  SMAP achieved 0.2 PSU accuracy on a monthly basis in tropics comparing with Argo OI  SMAP can track large salinity changes occurred within a month consistent with buoy  SMAP SSS retrieved in Mediterranean sea and BOB assessed with ship TSG and Argo STS Highlights (for review) Abstract 11 12 Sea surface salinity (SSS) retrieved from SMAP radiometer measurements is validated 13 with in situ salinity measurements collected from Argo floats, tropical moored buoys and 14 ship-based thermosalinograph (TSG) data. SMAP SSS achieved accuracy of 0.2 PSU on a 15 monthly basis in comparison with Argo gridded data in the tropics and mid--16 latitudes. In tropical oceans, time series comparison of salinity measured at 1 m by 17 moored buoys indicates that SMAP can track large salinity changes occurred within a 18 month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and 19 exclude erroneous jumps or drift in some real--time buoy data from assessment of 20 satellite retrieval. The resulting SMAP--buoy matchup analysis leads to an average 21 standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale; the 22 average standard deviation reduced to 0.17 PSU and the correlation improved to 0.8 on 23 monthly scale. SMAP L3 daily maps reveals salty water intrusion from the Arabian Sea 24 into the Bay of Bengal during the Indian summer monsoon, consistent with the daily 25 *Manuscript Click here to download Manuscript: SMAP_SSS_validation_RSE.pdf 29

5The Bay of Bengal (BoB) plays a fundamental role in controlling the weather systems that make up the South Asian summer monsoon system. In particular, the southern BoB has cooler sea surface temperature (SST) that influence ocean-atmosphere interaction and impact on the monsoon. Compared to the southeast, the southwestern BoB is cooler, more saline, receives much less rain, and is influenced by the Summer Monsoon Current (SMC). To examine the impact of these features on the monsoon, the BoB Boundary Layer Experiment (BoBBLE) was jointly undertaken by India and the UK during June

The strong stratification of the Bay of Bengal (BoB) causes rapid variations in sea surface temperature (SST) that influence the development of monsoon rainfall systems. This stratification is driven by the salinity difference between the fresh surface waters of the northern bay and the supply of warm, salty water by the Southwest Monsoon Current (SMC). Despite the influence of the SMC on monsoon dynamics, observations of this current during the monsoon are sparse. Using data from high-resolution in situ measurements along an east–west section at 8°N in the southern BoB, we calculate that the northward transport during July 2016 was between 16.7 and 24.5 Sv (1 Sv ≡ 106 m3 s−1), although up to ⅔ of this transport is associated with persistent recirculating eddies, including the Sri Lanka Dome. Comparison with climatology suggests the SMC in early July was close to the average annual maximum strength. The NEMO 1/12° ocean model with data assimilation is found to faithfully represent the variability of the SMC and associated water masses. We show how the variability in SMC strength and position is driven by the complex interplay between local forcing (wind stress curl over the Sri Lanka Dome) and remote forcing (Kelvin and Rossby wave propagation). Thus, various modes of climatic variability will influence SMC strength and location on time scales from weeks to years. Idealized one-dimensional ocean model experiments show that subsurface water masses advected by the SMC significantly alter the evolution of SST and salinity, potentially impacting Indian monsoon rainfall.