Arctic Mixed-Phase Cloud Base Ice Precipitation Properties During the M-PACE Field Campaign ...

• Main Author: Silber, Israel
• Format: Dataset
• Language: English
• Published: Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) 2023
• Subjects: 54 Environmental Sciences; IWC_log;Ice water content;Ni_tot_log;Ice number concentration;Rcb_log;Ice precipitation rate;mu;Ice PSD shape parameter;r_eff;Ice effective radius;Dmax_mean_log;Arithmetic mean ice particle diameter;V_m;mass-weighted ice particle fall velocity;w;Air vertical motion; Arctic
• Online Access: https://dx.doi.org/10.5439/1997411; https://www.osti.gov/servlets/purl/1997411/

Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly-continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This dataset provides a set of 25 samples from the M-PACE field campaign, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation ...