Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010

• Main Authors: Quentin Coopman, Timothy J. Garrett, Jerome Riedi, Douglas P. Finch
• Format: Dataset
• Language: unknown
• Published: Arctic Data Center 2017
• Subjects: Arctic
• Online Access: https://doi.org/10.18739/A2K00F

A growing body of research indicates that biomass and industrial aerosols from mid-latitudes have a broad range of effects on arctic climatological systems. Pollutant aerosols directly and indirectly perturb solar reflection and thermal radiative emission in the atmosphere, and soot accelerates melting when it accumulates on snow. Nonetheless, much remains unknown about how pollution plumes are modifying arctic cloud properties and precipitation. Consequently, the impact of pollution on the arctic climate system is not well understood. Past research into aerosol-cloud interactions in the Arctic has generally focused on small time and spatial scales, using a combination of aircraft and numerical modeling work. Less research has investigated these processes over climatological time scales and pan-Arctic spatial scales. In this data set researchers co-localized space-based observations with numerical model and reanalysis output to spatially and temporally co-localized pollution, cloud, and meteorological parameters. This package contains a Python script that contains a function (Read_PM*) to read input files (.p) and provides co-localized information of cloud microphysical properties, CO concentration, and atmospheric parameters.