An Improved Iterative Fitting Method to Estimate Nocturnal Residual Layer Height

Characterizing warm atmospheric boundary layer over land by combining Raman and Doppler lidar measurements

PBL plays a critical role in the atmosphere by transferring heat, moisture, and momentum. The warm PBL has a distinct diurnal cycle including daytime convective mixing layer (ML) and nighttime residual layer developments. Thus, for PBL characterization and process study, simultaneous determinations of PBL height (PBLH) and ML height (MLH) are necessary. Here, new approaches are developed to provide reliable PBLH and MLH to characterize warm PBL evolution. The approaches use Raman lidar (RL) water vapor mixing ratio (WVMR) and Doppler lidar (DL) vertical velocity measurements at the Southern Great Plains (SGP) atmospheric observatory, which was established by the Atmospheric Radiation Measurement (ARM) user facility. Compared with widely used lidar aerosol measurements for PBLH, WVMR is a better trace for PBL vertical mixing. For PBLH, the approach classifies PBL water vapor structures into a few general patterns, then uses a slope method and dynamic threshold method to determine PBLH. For MLH, wavelet analysis is used to re-construct 2-D variance from DL vertical wind velocity measurements according to the turbulence eddy size to minimize the impacts of gravity wave and eddy size on variance calculations; then, a dynamic threshold method is used to determine MLH. Remotely-sensed PBLHs and MLHs are compared with radiosonde measurements based on the Richardson number method. Good agreements between them confirm that the proposed new algorithms are reliable for PBLH and MLH characterization. The algorithms are applied to warm seasons' RL and ML measurements at the SGP site for five years to study warm season PBL structure and processes. The weekly composited diurnal evolutions of PBLHs and MLHs in warm climate were provided to illustrate diurnal and seasonal PBL evolutions. This reliable PBLH and MLH dataset will be valuable for PBL process study, model evolution, and PBL parameterization improvement.

Assessing CALIOP-Derived Planetary Boundary Layer Height Using Ground-Based Lidar

Coincident profiles from the space-borne and ground-based lidar measurements provide a unique opportunity to estimate the planetary boundary layer height (PBLH). In this study, PBLHs derived from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) were assessed by comparing them with those obtained from the ground-based lidar at Seoul National University (SNU) in Korea for both day and night from 2006 to 2019, and sounding data. CALIOP-derived PBLHs using wavelet covariance transform (WCT) are generally higher than those derived from the SNU lidar for both day and night. The difference in PBLH tends to increase as the signal-to-noise ratio for CALIOP decreases. The difference also increases as aerosol optical depth increases, implying that the PBLH estimated from CALIOP could be higher than that determined from the SNU lidar because of the signal attenuation within the aerosol layer under optically thick aerosol layer conditions. The higher PBLH for CALIOP in this study is mainly attributed to multiple aerosol layers. After eliminating multilayer cases, the PBLHs estimated from both the lidars showed significantly improved agreement: a mean difference of 0.09 km (R = 0.81) for daytime and 0.25 km (R = 0.51) for nighttime. The results from this study suggest that PBL detection using CALIOP is reliable for daytime if multilayer cases are removed. For nighttime, PBLHs derived from the SNU lidar and CALIOP showed a relatively large difference in frequency distribution compared with sounding data. It suggests that further investigations are needed for nighttime PBLHs, such as investigations about discriminating the residual layer and the difference between lidar-derived PBLH based on the aerosol layer and thermally derived PBLH from radiosonde data for the stable boundary layer during the nighttime.

Summertime Urban Mixing Layer Height over Sofia, Bulgaria

Mixing layer height (MLH) is a crucial parameter for air quality modelling that is still not routinely measured. Common methods for MLH determination use atmospheric profiles recorded by radiosonde but this process suffers from coarse temporal resolution since the balloon is usually launched only twice a day. Recently, cheap ceilometers are gaining popularity in the retrieval of MLH diurnal evolution based on aerosol profiles. This study presents a comparison between proprietary (Jenoptik) and freely available (STRAT) algorithms to retrieve MLH diurnal cycle over an urban area. The comparison was conducted in the summer season when MLH is above the full overlapping height of the ceilometer in order to minimize negative impact of the biaxial LiDAR’s drawback. Moreover, fogs or very low clouds which can deteriorate the ceilometer retrieval accuracy are very unlikely to be present in summer. The MLHs determined from the ceilometer were verified against those measured from the radiosonde, which were estimated using the parcel, lapse rate, and Richardson methods (the Richardson method was used as a reference in this study). We found that the STRAT and Jenoptik methods gave lower MLH values than radiosonde with an underestimation of about 150 m and 650 m, respectively. Additionally, STRAT showed some potential in tracking the MLH diurnal evolution, especially during the day. A daily MLH maximum of about 2000 m was found in the late afternoon (18–19 LT). The Jenoptik algorithm showed comparable results to the STRAT algorithm during the night (although both methods sometimes misleadingly reported residual or advected layers as the mixing layer (ML)). During the morning transition the Jenoptik algorithm outperformed STRAT, which suffers from abrupt changes in MLH due to integrated layer attribution. However, daytime performance of Jenoptik was worse, especially in the afternoon when the algorithm often cannot estimate any MLH (in the period 13–16 LT the method reports MLHs in only 15–30% of all cases). This makes day-to-day tracing of MLH diurnal evolution virtually impracticable. This problem is possibly due to its early version (JO-CloVis 8.80, 2009) and issues with real-time processing of a single profile combined with the low signal-to-noise ratio of the ceilometer. Both LiDAR-based algorithms have trouble in the evening transition since they rely on aerosol signature which is more affected by the mixing processes in the past hours than the current turbulent mixing.