Version 11 2021-09-09, 02:36Version 11 2021-09-09, 02:36
Version 10 2019-11-05, 02:19Version 10 2019-11-05, 02:19
Version 9 2019-11-05, 01:15Version 9 2019-11-05, 01:15
Version 8 2019-05-15, 23:05Version 8 2019-05-15, 23:05
Version 7 2017-11-28, 21:55Version 7 2017-11-28, 21:55
Version 6 2017-11-27, 22:09Version 6 2017-11-27, 22:09
Version 5 2017-07-25, 16:10Version 5 2017-07-25, 16:10
Version 4 2017-07-18, 22:33Version 4 2017-07-18, 22:33
Version 3 2017-06-28, 18:26Version 3 2017-06-28, 18:26
Version 2 2017-06-28, 17:09Version 2 2017-06-28, 17:09
Version 1 2017-06-28, 16:49Version 1 2017-06-28, 16:49
dataset
posted on 2019-05-15, 23:05authored byArmin SorooshianArmin Sorooshian, Alexander B MacDonald, Hossein Dadashazar, Kelvin H Bates, Matthew M Coggon, Jill S Craven, Ewan Crosbie, Scott P Hersey, Natasha Hodas, Jack J Lin, Arnaldo N Marty, Lindsay C Maudlin, Andrew R Metcalf, Shane M Murphy, Luz T Padro, Gouri Prabhakar, Tracey A Rissman, Taylor Shingler, Varuntida Varutbangkul, Zhen Wang, Roy K Woods, Patrick Y Chuang, Athanasios Nenes, Haflidi H Jonsson, Richard C Flagan, John H Seinfeld
Airborne data of meteorology, aerosol, and cloud properties that have been harmonized from seven field campaigns during July-August periods between 2005 and 2018 off the California coast. A consistent set of instruments were deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 129 flight days, amounting to 588 total flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity), cloud drop size distributions across a broad diameter range, different sampling inlets to distinguish between clear air aerosol and droplet residual particles in cloud, and cloud water composition. The data set is suitable for studies associated with
aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing
to sharp aerosol perturbations from ship traffic and biomass burning. The
data set can be used for model initialization and synergistic application with meteorological
models and remote sensing data to improve understanding of the very
interactions that comprise the largest uncertainty in the effect of
anthropogenic emissions on radiative forcing.
Funding
Office of Naval Research: N00014‐04‐1‐0118, N00014-10-1-0200, N00014-11-1-0783, N00014‐10‐1‐0811, N00014-16-1-2567, N00014‐04‐1‐0018.