Mapping ARM radar observations to microphysical processes in mixed-phase single-layer cloud
Poster PDF
Authors
Katia Lamer — Brookhaven National Laboratory
Wanda Szyrmer — McGill University - Dept. of Atmospheric and Oceanic Science
Ann M. Fridlind — NASA - Goddard Institute for Space Studies
Eugene E. Clothiaux — Pennsylvania State University
Andrew Ackerman — NASA - Goddard Institute for Space Studies
George Tselioudis — NASA - Goddard Institute for Space Studies
Pavlos Kollias — Stony Brook University
Category
Microphysics (cloud and/or aerosol)
Description
Low-level clouds have been identified as the cloud type contributing the largest uncertainty to future climate simulations. Their radiative impacts are a function of cloud optical depth, water content, and phase. While mesoscale variability may serve as a dominant control on cloud occurrence, the cloud temperature, liquid and ice water path, and accessible ice nuclei concentrations are amongst the factors that may control which microphysical processes (e.g. drizzle, deposition, aggregation, and riming) are active, impacting local phase partitioning. The objective of this study is to develop a radar-based microphysical process strength scale that will serve to identify the active microphysical processes within single-layer mixed-phase clouds.
Here, we exploit the richness and information content of long-term observations from profiling Doppler radar and other sensors (e.g. lidar, radiometer, sondes) at the ARM North Slope of Alaska (NSA) site. Using an approach similar to that used in warm clouds, we attempt to isolate distinct signatures in profiles of radar Doppler moments and decompose a large radar dataset into basic modes. These modes are then clustered with respect to liquid water path and cloud layer temperature to relate them to microphysical processes. An analytical model that accounts for microphysical processes such as deposition, aggregation, and riming serves as an aid to interpret the basis modes of radar observations. Outputs from this analysis are designed to evaluate general circulation model (GCM) process strength statistics at the North Slope of Alaska (NSA) site, namely to evaluate drizzle strength over the transition from warm to ice-containing clouds, and to evaluate riming and aggregation strength within ice-containing clouds. The development of such process-level understanding within a particular cloud layer and weather state is a key step toward addressing the complexities of mixed-phase clouds and improving their representation in numerical models
