No abstract

NOAA's Global Drifter Program (GDP) manages a global array of ;1250 active satellite-tracked surface drifting buoys (''drifters'') in collaboration with numerous national and international partners. To better manage the drifter array and to assess the performance of various drifter manufacturers, it is important to discriminate between drifters that cease transmitting because of internal failure and those that cease because of external factors such as running aground or being picked up. An accurate assessment of where drifters run aground would also allow the observations to be used to more accurately simulate the evolution of floating marine debris and to quantify globally which shores are most prone to the deposit of marine debris. While the drifter Data Assembly Center of the GDP provides a metadata file that includes cause of death, the identified cause for most drifters is simply ''quit transmitting.'' In this study it is shown that a significant fraction of these drifters likely ran aground or were picked up, and a statistical estimate that each drifter ran aground or was picked up is derived.

A dataset of sea surface temperature (SST) estimates is generated from the temperature observations of surface drifting buoys of NOAA’s Global Drifter Program. Estimates of SST at regular hourly time steps along drifter trajectories are obtained by fitting to observations a mathematical model representing simultaneously SST diurnal variability with three harmonics of the daily frequency, and SST low-frequency variability with a first degree polynomial. Subsequent estimates of non-diurnal SST, diurnal SST anomalies, and total SST as their sum, are provided with their respective standard uncertainties. This Lagrangian SST dataset has been developed to match the existing and on-going hourly dataset of position and velocity from the Global Drifter Program.

A dataset of sea surface temperature (SST) estimates is generated from the temperature observations of surface drifting buoys of NOAA's Global Drifter Program. Estimates of SST at regular hourly time steps along drifter trajectories are obtained by fitting to observations a mathematical model representing simultaneously SST diurnal variability with three harmonics of the daily frequency, and SST low-frequency variability with a first degree polynomial. Subsequent estimates of non-diurnal SST, diurnal SST anomalies, and total SST as their sum, are provided with their respective standard uncertainties. This Lagrangian SST dataset has been developed to match the existing hourly dataset of position and velocity from the Global Drifter Program.