| Summary: | A better understanding of Arctic cloud and aerosol properties, structure and formation is essential to understand the specific response of the Arctic in the context of global climate change. A lack of coherent high vertical and temporal resolution observations of cloud particles, aerosols moisture advection (i.e. water vapor) and thermodynamics, creates large uncertainties in current model estimates of cloud properties and inhibits our understanding of cloud radiative and precipitation impacts on the surface. As a result, current weather and climate models poorly parameterize clouds over the Arctic and more specifically over the Greenland Ice Sheet (GIS). A reduction in this uncertainty is particularly important above the GIS, where clouds act as sinks and sources to the ice mass balance by modulating the surface radiation budget and available precipitable water. To gain the understanding necessary to reduce this uncertainty, a new autonomous multi-wavelength, polarized Raman lidar is proposed for development and deployment at the NSFʼs observatory in Summit, Greenland. The new lidar observations will employ multiple wavelengths and polarizations to observe elastic and inelastic scattering from the Arctic atmosphere enabling regular retrieval of temperature, water vapor and extinction profiles. This combination of observational capability will create a coherent dataset of high-resolution thermodynamic, cloud and aerosol observations through the Arctic troposphere and lower stratosphere above Summit. Broadly, this addition to the NSF Observatory at Summit, Greenland as part of the larger Arctic Observing Network fits well within the Study of Environmental Arctic Change (SEARCH) implementation plan. Thus, this instrument will significantly enhance Arctic observing infrastructure and advance observations and understanding of change in the Arctic. The proposed instrumentation and observations are the first of their kind on the GIS and will expand the existing, although modest, network of such measurements across the Arctic. This project will also provide a unique experience and educational opportunity through the combination of fieldwork and subsequent data processing for graduate students at the University of Colorado.
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