Three Years of Airborne Observations During NASA Activate: A Statistical Summary of Chemical, Optical, and Microphysical Aerosol Properties Over the Western North Atlantic Ocean
Airborne observations are critical to understanding Earth’s climate system and surface-level air quality by providing both spatial and vertical information that is not possible through ground measurement networks or satellite observations. Airborne platforms allow assessments of long-range transport, vertical redistribution, boundary-layer dynamics, and cloud-aerosol-interactions that are critical to model evaluation and satellite validation. Still, the high cost and effort of aircraft operations can limit measurement campaigns to short, focused time periods. Multiple deployments are often necessary for seasonal comparisons, and results can be limited if target phenomenon are infrequent. Subsequent analyses typically focus on case studies, especially if deployment conditions are climatologically anomalous. The NASA ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) mission was designed to overcome these limitations by operating semi-continuously over multiple months during multiple seasons. Flight plans were intentionally simple, repetitive, and systematic to provide a statistically robust dataset that could be utilized similarly to a ground-network. Here, we present an overview of three years (2020-2022) of aerosol measurements from the NASA HU-25 Falcon aircraft supporting the ACTIVATE mission. Data from 179 flights were considered, the majority of which were based at NASA Langley Research Center and flown locally over the Wester North Atlantic Ocean just east of Hampton, VA, USA. Airmass characteristics tended to transition from continental outflow near the coast to mostly marine over the open ocean. Seasonal, diurnal, spatial, and vertical trends in aerosol microphysical, optical, and chemical properties are discussed in the context of synoptic scale meteorology. Statistical benefits of the ACTIVATE sampling strategy are discussed with regard to future model evaluation.