Nocturnal boundary layer height estimate from Doppler lidar measurements

Estimating the depth of the stable boundary layer (SBL) from measurement data has been a longstanding problem, both because of its importance for applications and because of its difficulty. Applications include the depth of dilution for air quality and emergency response, and as a scaling depth for numerical weather prediction (NWP) parameterizations of stable mixing processes. It is critical to have accurate determinations of SBL depth h for addressing the issue of what parameters the SBL depth depends upon. The fundamental definition of boundary layer (BL) in general, and SBL specifically, has traditionally been turbulence based—the BL is a turbulent layer adjacent to the earth’s surface. For example, Lenschow et al. (1988) and Caughey et al. (1979) used definitions based on where turbulence quantities drop to a percentage of their surface values. Unfortunately, vertical profiles of turbulence quantities are difficult to measure, so they are not often available for determining h. An important question becomes, can h be diagnosed from meanprofile information? Such quantities as aerosol-layer depth, nocturnal temperature-inversion depth, height of the LLJ maximum, depth of a strong shear layer, and many others have all been compared, with unsatisfactory resolution to the question of which one produces the best estimate. For example, summarizing in 2000, Seibert et al. concluded that the accuracy limitation for available instrumentation at the time was about +/30 % for SBL depth. Tucker et al. (2009) proposed a hierarchy of estimates depending on conditions and data availability, starting with turbulence-based definitions for h, and found they could provide accurate values of h around the clock for many consecutive days, using data from Doppler lidar.