skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Mixed layer height retrievals using MicroPulse Differential Absorption Lidar
Abstract. Accurate measurement of the mixed layer height (MLH) is a key observational capability necessary for many studies in weather forecasting, air quality assessment, and surface-atmosphere exchange. However, continuous MLH monitoring with backscatter lidars remains challenging under complex atmospheric conditions, including cloudy conditions and in the presence of residual layers. This study evaluates two complementary MLH retrieval algorithms using a single MicroPulse Differential Absorption Lidar (MPD): an aerosol-based approach that analyzes aerosol backscatter gradients with a wavelet technique and a thermodynamic technique based on the vertical structure of virtual potential temperature profiles. Both techniques were compared against MLH estimates from radiosondes, a Doppler wind lidar, and a high-resolution weather model using data from the M2HATS field campaign in Tonopah, NV, USA, supplemented by a smaller dataset from Boulder, CO, USA. The aerosol method achieved high temporal resolution and agreement with radiosonde MLH estimates under convective conditions (R2= 0.819–0.919), but its MLH estimates deviated from other methods during morning and evening transitions due to residual layer interference. The thermodynamic method avoided these problems but had coarser resolution and degraded instrument performance beneath clouds (R2= 0.661–0.845). Because lidar generally cannot penetrate clouds, conditions with clouds at or below the MLH are not considered, while those with clouds above the MLH are retained. The study highlights the strengths and weaknesses of each method. Together, they offer a path toward more reliable automatic MLH monitoring with a single instrument by capturing when different MLH definitions converge.  more » « less
Award ID(s):
2234047
PAR ID:
10654175
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
Atmospheric Measurement Technologies
Date Published:
Journal Name:
Atmospheric Measurement Techniques
Volume:
18
Issue:
21
ISSN:
1867-8548
Page Range / eLocation ID:
6069 to 6092
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, Atmospheric Measurement Techniques)
    Abstract. During the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign, held in the summer of 2019 in northern Wisconsin, USA, active and passive ground-based remote sensing instruments were deployed to understand the response of the planetary boundary layer to heterogeneous land surface forcing. These instruments include radar wind profilers, microwave radiometers, atmospheric emitted radiance interferometers, ceilometers, high spectral resolution lidars, Doppler lidars, and collaborative lower-atmospheric mobile profiling systems that combine several of these instruments. In this study, these ground-based remote sensing instruments are used to estimate the height of the daytime planetary boundary layer, and their performance is compared against independent boundary layer depth estimates obtained from radiosondes launched as part of the field campaign. The impact of clouds (in particular boundary layer clouds) on boundary layer depth estimations is also investigated. We found that while all instruments are overall able to provide reasonable boundary layer depth estimates, each of them shows strengths and weaknesses under certain conditions. For example, radar wind profilers perform well during cloud-free conditions, and microwave radiometers and atmospheric emitted radiance interferometers have a very good agreement during all conditions but are limited by the smoothness of the retrieved thermodynamic profiles. The estimates from ceilometers and high spectral resolution lidars can be hindered by the presence of elevated aerosol layers or clouds, and the multi-instrument retrieval from the collaborative lower atmospheric mobile profiling systems can be constricted to a limited height range in low-aerosol conditions. 
    more » « less
  2. (, Journal of applied remote sensing)
    The planetary boundary layer height (PBLH) is an essential parameter for weather forecasting and climate modeling. The primary methods for obtaining the PBLH include radiosonde measurements of atmospheric parameters and lidar measurements, which track aerosol layers in the lower atmosphere. Radiosondes provide the parameters to determine the PBLH but cannot monitor changes over a diurnal cycle. Lidar instruments can track the temporal variability of the PBLH and account for spatial variability when operated in a network configuration. The networkable micropulse DIAL (MPD) instruments for thermodynamic profiling are based on diode-laser technology that is eye-safe and cost-effective and has demonstrated long-term autonomous operation. We present a retrieval algorithm for determining the PBLH from the quantitative aerosol profiling capability of the high spectral resolution channel of the MPD. The PBLH is determined using a Haar wavelet transform (HWT) method that tracks aerosol layers in the lower atmosphere. The PBLH from the lidar is compared with the PBLH determined from potential temperature profiles from radiosondes. In many cases, good agreement among the PBLH retrievals was seen. However, the radiosonde retrieval often missed the lowest inversion layer when several layers were present, while the HWT could track the lowest layer. 
    more » « less
  3. ; ; (, Atmospheric Chemistry and Physics)
    Abstract. The states of coupling between clouds andsurface or boundary layer have been investigated much more extensively formarine stratocumulus clouds than for continental low clouds, partly due tomore complex thermodynamic structures over land. A manifestation is a lackof robust remote sensing methods to identify coupled and decoupled cloudsover land. Following the idea for determining cloud coupling over the ocean,we have generalized the concept of coupling and decoupling to low cloudsover land, based on potential temperature profiles. Furthermore, by usingample measurements from lidar and a suite of surface meteorologicalinstruments at the U.S. Department of Energy's Atmospheric RadiationMeasurement Program's Southern Great Plains site from 1998 to 2019, we havedeveloped a method to simultaneously retrieve the planetary boundary layer(PBL) height (PBLH) and coupled states under cloudy conditions during thedaytime. The new lidar-based method relies on the PBLH, the liftedcondensation level, and the cloud base to diagnose the cloud coupling. Thecoupled states derived from this method are highly consistent with thosederived from radiosondes. Retrieving the PBLH under cloudy conditions, whichhas been a persistent problem in lidar remote sensing, is resolved in thisstudy. Our method can lead to high-quality retrievals of the PBLH undercloudy conditions and the determination of cloud coupling states. With thenew method, we find that coupled clouds are sensitive to changes in the PBLwith a strong diurnal cycle, whereas decoupled clouds and the PBL are weaklyrelated. Since coupled and decoupled clouds have distinct features, our newmethod offers an advanced tool to separately investigate them in climatesystems. 
    more » « less
  4. ; ; ; ; ; ; ; ; (, Atmospheric Measurement Techniques)
    Abstract. Remote sensing measurements have been widely used to estimate the planetary boundary layer height (PBLHT). Each remote sensing approach offers unique strengths and faces different limitations. In this study, we use machine learning (ML) methods to produce a best-estimate PBLHT (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. Three ML models – random forest (RF) classifier, RF regressor, and light gradient-boosting machine (LightGBM) – were trained on a dataset from 2017 to 2023 that included radiosonde, various remote sensing PBLHT estimates, and atmospheric meteorological conditions. Evaluations indicated that PBLHT-BE-ML from all three models improved alignment with the PBLHT derived from radiosonde data (PBLHT-SONDE), with LightGBM demonstrating the highest accuracy under both stable and unstable boundary layer conditions. Feature analysis revealed that the most influential input features at the SGP site were the PBLHT estimates derived from (a) potential temperature profiles retrieved using Raman lidar (RL) and atmospheric emitted radiance interferometer (AERI) measurements (PBLHT-THERMO), (b) vertical velocity variance profiles from Doppler lidar (PBLHT-DL), and (c) aerosol backscatter profiles from micropulse lidar (PBLHT-MPL). The trained models were then used to predict PBLHT-BE-ML at a temporal resolution of 10 min, effectively capturing the diurnal evolution of PBLHT and its significant seasonal variations, with the largest diurnal variation observed over summer at the SGP site. We applied these trained models to data from the ARM Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) field campaign (EPC), where the PBLHT-BE-ML, particularly with the LightGBM model, demonstrated improved accuracy against PBLHT-SONDE. Analyses of model performance at both the SGP and EPC sites suggest that expanding the training dataset to include various surface types, such as ocean and ice-covered areas, could further enhance ML model performance for PBLHT estimation across varied geographic regions. 
    more » « less
  5. ; ; (, Journal of Atmospheric and Oceanic Technology)
    Abstract Micropulse differential absorption lidar (MPD) for water vapor, temperature, and aerosol profiling have been developed, demonstrated, and are addressing the needs of the atmospheric science community for low-cost ground-based networkable instruments capable of long-term monitoring of the lower troposphere. The MPD instruments use a diode-laser-based (DLB) architecture that can easily be adapted for a wide range of applications. In this study, a DLB direct detection Doppler lidar based on the current MPD architecture is modeled to better understand the efficacy of the instrument for vertical wind velocity measurements with the long-term goal of incorporating these measurements into the current network of MPD instruments. The direct detection Doppler lidar is based on a double-edge receiver that utilizes two Fabry-Perot interferometers and a vertical velocity retrieval that requires the ancillary measurement of the backscatter ratio, which is the ratio of the total backscatter coefficient to the molecular backscatter coefficient. The modeling in this paper accounts for the major sources of error. It indicates that the vertical velocity can be retrieved with an error of less than 0.56 m s −1 below 4 km with a 150-m range resolution and an averaging time of five minutes. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email