Investigation of the Relationship Between Turbulence and Drizzle Onset and Development in Continental and Marine Stratiform Low-level Clouds Using ARM Observations

Abstract:

The response of shallow cloud systems to changes in atmospheric greenhouse gases and aerosols is a major source of uncertainty limiting the accuracy of predictions of future climate. Factors contributing to this uncertainty are drizzle formation and intensity. Drizzle is ubiquitous in low-level clouds, and the two primary parameters that control the production (autoconversion) and development (accretion) of drizzle are liquid water path (LWP) and aerosol loading. While LWP is the dominant parameter controlling the production and development of drizzle, several numerical studies and field observations have provided evidence of an aerosol role in drizzle suppression. However, it remains unclear to what extent small-scale turbulence influences the production and development of drizzle in low-level stratiform clouds. Here, we use observations from the US Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployments in the Black Forest, Germany, from April to December 2007 and at the Azores from June 2009 to December 2010. Several days of continental and maritime stratocumulus clouds are identified. Using synergy between ground-based aerosol observing systems and active and passive remote-sensing instruments, time series of LWP, cloud condensation nuclei (CCN) number concentration (N_CCN), and cloud base drizzle rate (R_CB) are derived (Mann et al., 2014). This dataset is conditionally sampled with respect to LWP and N_CCN, and for each subset within a specific range of LWP and N_CCN values, several additional parameters are estimated to provide information on drizzle onset, drizzle growth and in-cloud turbulence. In particular, the profiling cloud radar Doppler spectra dataset is used to estimate the radar Doppler spectrum skewness, a particularly sensitive parameter in the detection of drizzle onset (Kollias et al., 2011). The rate of drizzle growth is determined using average profiles of radar reflectivity and mean Doppler velocity. In addition, we derive in-cloud turbulent eddy dissipation rates using time-series of radar Doppler velocities and radar Doppler spectrum width observations (Borque et al., 2014). All of these new parameters are utilized to investigate the level of turbulence in low stratiform clouds and its relationship to drizzle onset and growth.