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Title: A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions

Journal Article · · Remote Sensing of Environment
 [1];  [1];  [2]
  1. University of Maryland, College Park, MD (United States)
  2. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)

The planetary boundary layer height (PBLH) is an important parameter for understanding the accumulation of pollutants and the dynamics of the lower atmosphere. Lidar has been used for tracking the evolution of PBLH by using aerosol backscatter as a tracer, assuming aerosol is generally well-mixed in the PBL; however, the validity of this assumption actually varies with atmospheric stability. This is demonstrated here for stable boundary layers (SBL), neutral boundary layers (NBL), and convective boundary layers (CBL) using an 8-year dataset of micropulse lidar (MPL) and radiosonde (RS) measurements at the ARM Southern Great Plains, and MPL at the GSFC site. Due to weak thermal convection and complex aerosol stratification, traditional gradient and wavelet methods can have difficulty capturing the diurnal PBLH variations in the morning and forenoon, as well as under stable conditions generally. Here a new method is developed that combines lidar-measured aerosol backscatter with a stability dependent model of PBLH temporal variation (DTDS). The latter helps “recalibrate” the PBLH in the presence of a residual aerosol layer that does not change in harmony with PBL diurnal variation. The hybrid method offers significantly improved PBLH detection, with better correlation and smaller biases, under most thermodynamic conditions, especially for SBL and CBL. Relying on the physical process of PBL diurnal development, different schemes are developed for growing, maintenance, and decaying periods. Comprehensive evaluation of this new method shows much better tracking of diurnal PBLH variation and significantly smaller biases under various pollution levels.

Research Organization:
Univ. of Maryland, College Park, MD (United States)
Sponsoring Organization:
USDOE Office of Science (SC); National Science Foundation (NSF); National Aeronautics and Space Administration (NASA)
Grant/Contract Number:
SC0018996; AGS1837811; NNX16AN61G
OSTI ID:
1803487
Alternate ID(s):
OSTI ID: 1776188
Journal Information:
Remote Sensing of Environment, Vol. 237, Issue C; ISSN 0034-4257
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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