Surface energy budget and meteorology measurements from the Arctic Mobile Observing System (AMOS) Ice Gateway-Heavy buoy #004, Beaufort Sea August 2022 through September 2022

The data set is comprised of meteorology and surface energy budget observations from an Atmospheric Surface Flux Station (ASFS, Cox et al. 2023) mounted to Ice Gateway Buoy - Heavy #004 (IGB-H-004) deployed in open water in the Beaufort Sea near the freeze-up period in September 2022. This was an experimental use of the ASFS in collaboration with the Office of Naval Research's Arctic Mobile Observing System (AMOS). Meteorology (temperature, humidity, and pressure), as well as upwelling and downwelling shortwave and longwave broadband radiative fluxes were acquired from a boom approximately 2 meters (m) above the surface. Winds were acquired from a short mast approximately 4 m above the surface. The measurements are stored in daily netCDF files. The "slow" files include 1 minute (min) averages (and standard deviations) of all measured variables, which were acquired at 10 hertz (Hz) (winds) or at 10 second (sec) intervals (all others). The "fast" files include measurements of 3-dimensional wind velocities (in station coordinates) and acoustic temperature at 10-Hz resolution. The "turb" files include 10 min averages for turbulent heat flux variables (derived using eddy-covariance and bulk methodology), as well as ancillary information and diagnostics. The processing and instrumentation approaches are adapted from Cox et al. (2023) with important details specific to the IGB-H-004 experiment found in the methods sections below. The objective of the ASFS component of the AMOS campaign was experimental testing of a low-power, autonomous collection of surface energy budget variables from an intermittently ice-bound buoy platform. A caveat to consider when using the data is that uncertainties are generally larger for most variables, in particular due to the system having variable tilt, which at times was large and/or rapidly fluctuating. Decisions about tolerance for platform level are left to the discretion of the user (measurements of platform level are found in the data). We consider this a level 1 dataset comprised of organized and formatted data (including metadata) and application of technical corrections, as well as the addition of basic quality control with limitations as described.