The surface drifting buoys, or drifters, of the Global Drifter Program (GDP) are predominantly tracked by the Argos positioning system, providing drifter locations with O(100 m) errors at nonuniform temporal intervals, with an average interval of 1.2 h since January 2005. This data set is thus a rich and global source of information on high‐frequency and small‐scale oceanic processes, yet is still relatively understudied because of the challenges associated with its large size and sampling characteristics. A methodology is described to produce a new high‐resolution global data set since 2005, consisting of drifter locations and velocities estimated at hourly intervals, along with their respective errors. Locations and velocities are obtained by modeling locally in time trajectories as a first‐order polynomial with coefficients obtained by maximizing a likelihood function. This function is derived by modeling the Argos location errors with t location‐scale probability distribution functions. The methodology is motivated by analyzing 82 drifters tracked contemporaneously by Argos and by the Global Positioning System, where the latter is assumed to provide true locations. A global spectral analysis of the velocity variance from the new data set reveals a sharply defined ridge of energy closely following the inertial frequency as a function of latitude, distinct energy peaks near diurnal and semidiurnal frequencies, as well as higher‐frequency peaks located near tidal harmonics as well as near replicates of the inertial frequency. Compared to the spectra that can be obtained using the standard 6‐hourly GDP product, the new data set contains up to 100% more spectral energy at some latitudes.

Sea surface temperature variations over the equatorial Pacific associated with the El Niño/Southern Oscillation (ENSO) produce changes in climates across the globe. Here we report evidence from observationally constrained ocean data for the initiation of warm ENSO events (El Niños) resulting from subsurface equatorial Pacific heat content increases related to tropical/extratropical sea level pressure (SLP) changes over the North Pacific. We hypothesize that the increase in heat content is a response to SLP‐generated variations in the North Pacific trade winds, which we term trade wind charging of the equatorial Pacific. Experiments using a high‐resolution numerical ocean model verify that the charging of subsurface heat content along the equatorial Pacific can be induced by SLP‐generated trade wind variations. Furthermore, analysis of the numerical model results and historical observations indicates that the trade wind–induced ocean heat content increases are sufficiently large to initiate the onset of El Niño events, which mature approximately 12 months after the trade wind forcing itself.

Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) is a multinational program initiated in 1997 in the tropical Atlantic to improve our understanding and ability to predict ocean‐atmosphere variability. PIRATA consists of a network of moored buoys providing meteorological and oceanographic data transmitted in real time to address fundamental scientific questions as well as societal needs. The network is maintained through dedicated yearly cruises, which allow for extensive complementary shipboard measurements and provide platforms for deployment of other components of the Tropical Atlantic Observing System. This paper describes network enhancements, scientific accomplishments and successes obtained from the last 10 years of observations, and additional results enabled by cooperation with other national and international programs. Capacity building activities and the role of PIRATA in a future Tropical Atlantic Observing System that is presently being optimized are also described.

Data from two boundary arrays deployed along 34.5°S are combined to produce the first continuous in situ time series observations of the basin‐wide meridional overturning circulation (MOC) in the South Atlantic. Daily estimates of the MOC between March 2009 and December 2010 range between 3 Sv and 39 Sv (1 Sv = 10⁶ m³ s⁻¹) after a 10 day low‐pass filter is applied. Much of the variability in this ∼20 month record occurs at periods shorter than 100 days. Approximately two‐thirds of the MOC variability is due to changes in the geostrophic (baroclinic plus barotropic) volume transport, with the remainder associated with the direct wind‐forced Ekman transport. When low‐pass filtered to match previously published analyses in the North Atlantic, the observed temporal standard deviation at 34.5°S matches or somewhat exceeds that observed by time series observations at 16°N, 26.5°N, and 41°N. For periods shorter than 20 days the basin‐wide MOC variations are most strongly influenced by Ekman flows, while at periods between 20 and 90 days the geostrophic flows tend to exert slightly more control over the total transport variability of the MOC. The geostrophic shear variations are roughly equally controlled by density variations on the western and eastern boundaries at all time scales captured in the record. The observed time‐mean MOC vertical structure and temporal variability agree well with the limited independent observations available for confirmation.

Six years of simultaneous moored observations near the western and eastern boundaries of the South Atlantic are combined with satellite winds to produce a daily time series of the basin‐wide meridional overturning circulation (MOC) volume transport at 34.5°S. The results demonstrate that barotropic and baroclinic signals at both boundaries cause significant transport variations, and as such must be concurrently observed. The data, spanning ~20 months during 2009–2010 and ~4 years during 2013–2017, reveal a highly energetic MOC record with a temporal standard deviation of 8.3 Sv, and strong variations at time scales ranging from a few days to years (peak‐to‐peak range = 54.6 Sv). Seasonal transport variations are found to have both semiannual (baroclinic) and annual (Ekman and barotropic) timescales. Interannual MOC variations result from both barotropic and baroclinic changes, with density profile changes at the eastern boundary having the largest impact on the year‐to‐year variations.