MPL-VERT

Enhanced MPL Vertical Resolution at CAPE-K

15 April 2024 - 15 September 2025

Lead Scientist: Gerald Mace

Observatory: AMF

Given the importance of constraining cloud droplet number concentrations (Nd) in low-level clouds, we have developed two methods for retrieving Nd from surface-based remote sensing that emphasize the information content in lidar measurements. We have developed methods using a simple lidar forward model that demonstrates that the depth to the maximum in lidar attenuated backscatter (Rmax) is strongly sensitive to Nd when some measure of the liquid water content vertical profile is given or assumed. Knowledge of Rmax to within 5 m can constrain Nd to within several tens of percent. However, operational lidars run by ARM provide vertical resolutions of 15 m, making a direct calculation of Nd from Rmax very uncertain. Therefore, in this IOP we will implement a high-vertical-resolution data collection mode of 5 m that will allow us to fully explore the capability of this methodology to derive Nd.  Using a published Bayesian optimal estimation algorithm that brings additional information to the inversion such as lidar-derived extinction and radar reflectivity near cloud top, we expect to demonstrate that reasonable characterizations of Nd and effective radius (re) to within approximately a factor of 2 and 30%, respectively.  Validation will be provided by comparing surface-derived cloud properties with MODIS satellite and aircraft data collected during CAPE-K.