Characterizing the Vertical Distribution of Aerosols using Multiwavelength Lidar Data

Principal Investigator(s):
Richard Ferrare, NASA Langley Research Center

Atmospheric particles, or aerosols, are derived from a variety of man-made and natural sources and are important atmospheric components that affect the Earth’s radiation budget and climate. Aerosols affect Earth’s climate directly, by scattering and absorbing solar radiation, and indirectlyby altering the lifetime and development of clouds, which in turn affect the scattering and  absorption of radiation. Uncertainties associated with aerosol radiative forcing (ARF) estimates are among the leading causes of discrepancies in climate simulations and complicate Earth System studies that increasingly depend on understanding how atmospheric composition and its anthropogenic disturbances interact with other components of the Earth system. Since aerosol radiative forcing depends strongly on the vertical distribution of aerosols, the height of the aerosol layer must be known to assess these impacts.

Global models have been increasingly used to assess aerosol impacts on climate change scenarios as well as how aerosols impact regional air quality. Since some of the largest uncertainties in model simulations of climate change are associated with aerosols, evaluating how these models portray aerosol characteristics is vital for determining uncertainties in climate change simulations and isolating deficiencies that weaken model efficacy. Since aerosol radiative forcing depends strongly on the vertical distribution of aerosols, the height of the aerosol layer must be known to assess these impacts.

Model intercomparisons have shown large diversity in how models represent the vertical distribution of aerosols. Since this variability in model performance exists in part because of insufficient measurement evaluations of model simulations, DOE ARM is investigating new methods to remotely measure the vertical distribution of aerosols and derive their optical and microphysical properties. During the Combined HSRL And Raman lidar Measurement Study (CHARMS), DOE ARM investigated the synergistic use of SGP Raman lidar and High Spectral Resolution Lidar (HSRL) measurements to improve the ARM observational capability of aerosols.  The continuous (24/7) operation of these co-located lidars during the ten-week CHARMS mission (mid-July through September 2015) allowed the acquisition of a unique, multiwavelength ground-based lidar dataset for studying the vertical distribution of aerosol properties above the SGP.

Recent advances in both lidar retrieval theory and algorithm development demonstrate that retrievals using such advanced multiwavelength lidar measurements can constrain aerosol optical and microphysical properties, greatly increasing the utility of the remotely sensed aerosol observations. Based on this work, our group at NASA’s Langley Research Center (LaRC) has developed and demonstrated automated algorithms for retrieving aerosol optical and microphysical properties from airborne multiwavelength lidar data. DOE ARM has funded the NASA LaRC lidar research group to apply these algorithms to the CHARMS measurements and produce a dataset of aerosol optical and microphysical parameters.

We propose to leverage and extends these efforts to use this unique and powerful CHARMS dataset to examine three timely and important science problems. We propose the following activities:

  1. Classify vertical distribution of aerosols and apportion aerosol optical thickness and extinction to aerosol type and use these results to evaluate models

We have previously used multiwavelength lidar datasets, similar to the CHARMS dataset, to characterize the vertical distribution of aerosol extinction and aerosol type. We propose to characterize the aerosol distributions over the SGP using the CHARMS dataset in a similar manner. The retrieved aerosol types will help inform and improve model simulations of aerosol sources and transport.

  1. Characterize how aerosol optical and microphysical properties vary near and below clouds

We will examine the behavior of aerosols both below and beside clouds using the CHARMS measurements and simultaneous relative humidity profiles derived from the Raman lidar water vapor and Raman lidar/AERI temperature profiles. These analyses provide constraints that may help to explain and even resolve the considerable diversity in how models represent how aerosol scattering increases with high relative humidity.

  1. Relate retrieved aerosol properties to cloud condensation nuclei (CCN) concentrations

We will investigate the use of lidar data to develop better proxies for CCN concentrations.  We plan to relate these retrieved CCN values to the aerosol types derived from the CHARMS data.  These studies will provide a valuable dataset of aerosol, relative humidity, and CCN below and between clouds to constrain models.  The multiwavelength lidar measurements will allow us to investigate the use of lidar data to develop better proxies for CCN aloft with the spatial and temporal coverage required to constrain models.