Improved boundary layer depth retrievals from MPLNET

Abstract

[1] Continuous lidar observations of the planetary boundary layer (PBL) depth have been made at the Micropulse Lidar Network (MPLNET) site in Greenbelt, Maryland, since April 2001. However, because of issues with the operational PBL depth algorithm, the data are not reliable for determining seasonal and diurnal trends. Therefore, an improved PBL depth algorithm has been developed which uses a combination of the wavelet technique and image processing. The new algorithm is less susceptible to contamination by clouds and residual layers and, in general, produces lower PBL depths. A 2010 comparison shows the operational algorithm overestimates the daily mean PBL depth when compared to the improved algorithm (1.85 and 1.07 km, respectively). The improved MPLNET PBL depths are validated using radiosonde comparisons, which suggests the algorithm performs well to determine the depth of a fully developed PBL. A comparison with the Goddard Earth Observing System version 5 (GEOS-5) model suggests that the model may underestimate the maximum daytime PBL depth by 410 m during the spring and summer. The best agreement between MPLNET and GEOS-5 occurred during the fall and they differed the most in the winter.

Relationship between Aerosol Optical Depth and Particulate Matter over Singapore: Effects of Aerosol Vertical Distributions

“…At this point of time, MPLNET is processing all data, including that of Singapore, which will be collectively known as "Version 3" and includes an improved PBL height product (Welton, 2015;personal communication). The new PBL height retrieval algorithm uses image processing and fuzzy logic techniques to overcome the shortcomings of wavelet techniques alone (Lewis et al, 2013). Fig.…”

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

“…In particular, numerous studies have been performed to determine daytime convective boundary layer (CBL) topped by the clean, free atmosphere (FA). These studies used different techniques, namely threshold detection (e.g., [18]), the gradient-based method (e.g., [19]), the inflection point method (e.g., [20]), the variance analysis (e.g., [21]), the Haar wavelet approach (e.g., [14]), the combined wavelet and image processing method [22], the ideal profile method (e.g., [23]), and the 2-D gradient approach [24] to derive z i using aerosol LiDAR measurements.…”

“…LiDAR systems are used to monitor daytime z i since: (1) aerosols are good tracers of turbulent mixing; (2) there are over 30 years of studies on aerosol backscatter gradients and variances; (3) there is temporal coverage in the daytime ABL regime; and (4) there is spatial coverage with networks of LiDARs/ceilometers around the world (e.g., [22,24]). However, the development of a z i retrieval algorithm that is both automated and applicable at all times and under different meteorological conditions still remains a challenge (e.g., [13,21]).…”

MPLNET V3 Cloud and Planetary Boundary Layer Detection

“…The Version 3 (V3) PBL retrieval uses the procedure outlined by Lewis et al (2013). The new algorithm uses the first derivative of a Gaussian wavelet in place of the Haar wavelet because it more closely resembles the gradient in…”