Lidar Retrievals Research Articles

Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars

Abstract. The objective of this paper and its companion (Wing et al., 2018) is to show that ground-based lidar temperatures are a stable, accurate, and precise data set for use in validating satellite temperatures at high vertical resolution. Long-term lidar observations of the middle atmosphere have been conducted at the Observatoire de Haute-Provence (OHP), located in southern France (43.93∘ N, 5.71∘ E), since 1978. Making use of 20 years of high-quality co-located lidar measurements, we have shown that lidar temperatures calculated using the Rayleigh technique at 532 nm are statistically identical to lidar temperatures calculated from the non-absorbing 355 nm channel of a differential absorption lidar (DIAL) system. This result is of interest to members of the Network for the Detection of Atmospheric Composition Change (NDACC) ozone lidar community seeking to produce validated temperature products. Additionally, we have addressed previously published concerns of lidar–satellite relative warm bias in comparisons of upper-mesospheric and lower-thermospheric (UMLT) temperature profiles. We detail a data treatment algorithm which minimizes known errors due to data selection procedures, a priori choices, and initialization parameters inherent in the lidar retrieval. Our algorithm results in a median cooling of the lidar-calculated absolute temperature profile by 20 K at 90 km altitude with respect to the standard OHP NDACC lidar temperature algorithm. The confidence engendered by the long-term cross-validation of two independent lidars and the improved lidar temperature data set is exploited in Wing et al. (2018) for use in multi-year satellite validations.

Characteristics of Optically Thin Coastal Florida Cumuli Derived From Surface‐Based Lidar Measurements

AbstractThe optical depths and sizes of optically thin passive shallow cumuli are characterized with a micropulse lidar. The measurements are from a coastal south Florida location spanning a 10‐week synoptically suppressed winter time period with almost no upper‐level clouds present. Clouds are distinguished from aerosol through visual comparison to zenith‐viewing time‐lapse camera images, establishing an instrument‐specific particle backscatter coefficient threshold. Sun photometers provide a continuous independent aerosol optical depth estimate applied within the lidar retrieval of cloud optical depth. The focus is on clouds that do not attenuate the lidar signal. Clouds with optical depths less than one constitute more than 13% of the sampled data set, with decreasing optical depths occurring more frequently. Most of the clouds are less than 60 m thick and are located below 1 km. The optically thin regions occur most frequently in individual 15‐s samples, corresponding to a horizontal width of less than 100 m, with occasional stratiform segments extending up to 2 km. Many segments border optically thicker regions, but some are self‐contained, reflecting small‐scale humidity variations near‐saturation. To our knowledge, this study is the first to apply micropulse lidar data toward characterizing these low, shallow, broken clouds, too small for robust characterization from space but whose ubiquitiousness renders them radiatively important.

Retrieval of Cloud Condensation Nuclei Number Concentration Profiles From Lidar Extinction and Backscatter Data

AbstractThe vertical distribution of aerosols and their capability of serving as cloud condensation nuclei (CCN) are important for improving our understanding of aerosol indirect effects. Although ground‐based and airborne CCN measurements have been made, they are generally scarce, especially at cloud base where it is needed most. We have developed an algorithm for profiling CCN number concentrations using backscatter coefficients at 355, 532, and 1,064 nm and extinction coefficients at 355 and 532 nm from multiwavelength lidar systems. The algorithm considers three distinct types of aerosols (urban industrial, biomass burning, and dust) with bimodal size distributions. The algorithm uses look‐up tables, which were developed based on the ranges of aerosol size distributions obtained from the Aerosol Robotic Network, to efficiently find optimal solutions. CCN number concentrations at five supersaturations (0.07–0.80%) are determined from the retrieved particle size distributions. Retrieval simulations were performed with different combinations of systematic and random errors in lidar‐derived extinction and backscatter coefficients: systematic errors range from −20% to 20% and random errors are up to 15%, which fall within the typical error ranges for most current lidar systems. The potential of this algorithm to retrieve CCN concentrations is further evaluated through comparisons with surface‐based CCN measurements with near‐surface lidar retrievals. This retrieval algorithm would be valuable for aerosol‐cloud interaction studies for which virtually none has employed CCN at cloud base because of the lack of such measurements.

Multisatellite Multisensor Observations of a Sub-Plinian Volcanic Eruption: The 2015 Calbuco Explosive Event in Chile

A-train satellite data, acquired during the Calbuco volcano (Chile) sub-Plinian eruption in April 2015, are discussed to explore the complementarity of spaceborne observations in the microwave (MW), thermal infrared (TIR), and visible wavelengths for both near-source plume and distal ash clouds. The analysis shows that TIR-based detection techniques are not suitable near the volcanic vent where rising convective columns are associated with large optical depths. Detection and parametric estimates of near-source tephra mass loading and plume height from MW radiometric data, available 69 min after the eruption onset, are proposed. Results indicate a maximum plume altitude of about 21 km above the sea level and an ash mass of $3.65 \times 10^{10}$ kg, in agreement with mass values obtained from empirical formulas, but less than proximal–distal mass deposit of $1.86 \times 10^{11}$ kg. This discrepancy may be explained by extrapolating Advanced Technology Microwave Sounder-based estimates to 6 h, thus obtaining a total mass of about $1.90 \times 10^{11}$ kg. Distal volcanic cloud retrievals are derived from TIR imagery and results show a good agreement between Moderate-Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) retrievals of total mass taking into account the overpass time shift. If only the overlapping pixels between MODIS and VIIRS are considered, the respective estimates are $1.90 \times 10^{9}$ kg and $1.80 \times 10^{9}$ kg. TIR radiometric estimates of distal ash cloud height and mass loadings are also compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar retrievals. For low-to-medium optically thick ash cloud, average Cloud-Aerosol Lidar with Orthogonal Polarization-derived mass loading is about 0.8 g/m2 against 0.4 g/m2 from VIIRS and 1.4 g/m2 from MODIS.

Airborne measurements of CO<sub>2</sub> column concentrations made with a pulsed IPDA lidar using a multiple-wavelength-locked laser and HgCdTe APD detector

Abstract. Here we report on measurements made with an improved CO2 Sounder lidar during the ASCENDS 2014 and 2016 airborne campaigns. The changes made to the 2011 version of the lidar included incorporating a rapidly wavelength-tunable, step-locked seed laser in the transmitter, using a much more sensitive HgCdTe APD detector and using an analog digitizer with faster readout time in the receiver. We also improved the lidar's calibration approach and the XCO2 retrieval algorithm. The 2014 and 2016 flights were made over several types of topographic surfaces from 3 to 12 km aircraft altitudes in the continental US. The results are compared to the XCO2 values computed from an airborne in situ sensor during spiral-down maneuvers. The 2014 results show significantly better performance and include measurement of horizontal gradients in XCO2 made over the Midwestern US that agree with chemistry transport models. The results from the 2016 airborne lidar retrievals show precisions of ∼ 0.7 parts per million (ppm) with 1 s averaging over desert surfaces, which is an improvement of about 8 times compared to similar measurements made in 2011. Measurements in 2016 were also made over fresh snow surfaces that have lower surface reflectance at the laser wavelengths. The results from both campaigns showed that the mean values of XCO2 retrieved from the lidar consistently agreed with those based on the in situ sensor to within 1 ppm. The improved precision and accuracy demonstrated in the 2014 and 2016 flights should benefit future airborne science campaigns and advance the technique's readiness for a space-based instrument.

An Evaluation of the Shortwave Direct Aerosol Radiative Forcing Using CALIOP and MODIS Observations

AbstractIn this study, all‐sky ShortWave Direct Aerosol Radiative Forcing (SWDARF) at the top of atmosphere is estimated using the method of Oikawa et al. (2013) applied to two generations of Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 products, i.e., version 2 (V2) and version 3 (V3), and the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product. The estimated SWDARF in Oikawa et al. (2013) was based on CALIPSO V2 product, which contained significant errors in cloud clearing and low‐altitude aerosols. This error was corrected in V3, resulting in greatly improved and significantly different aerosol and cloud distributions. In clear‐sky conditions, the magnitude of aerosol optical thickness underestimation becomes smaller and SWDARF becomes more negative using the V3 product. In addition, above‐cloud aerosols, which cause positive SWDARF, are less frequently detected and below‐cloud aerosols are more frequently detected in the V3 product than in the V2 product, so that cloudy‐sky SWDARF becomes more negative using the V3 product. From these results, clear‐sky, cloudy‐sky, and all‐sky SWDARFs become more negative using the V3 product than the V2 product. The magnitude of negative SWDARF using the V3 product is more than twice as large as the V2 product under all‐sky conditions due to V3 improvements in the lidar retrieval algorithms. Considering the uncertainties of aerosol and cloud measurements, annual zonal averages of clear‐sky, cloudy‐sky, and all‐sky SWDARFs from 60°S to 60°N are estimated as −4.0 ± 0.2, −1.1 ± 0.3, and −2.1 ± 0.2 Wm−2 from the V3 product.

Constraining lidar stand-alone retrievals with lunar photometry measurements

This study combines atmospheric optical information measured with lidar and nocturnal photometers in order to find configurations that allow for the retrieval of particle microphysical properties without “3+2” lidar setups. It has been carried out using data measured at the EARLINET Granada station during the experimental campaign SLOPE in the framework of ACTRIS-2 project.

Lidar stand-alone retrieval of atmospheric aerosol microphysical properties during SLOPE

Two cases from SLOPE campaign at Granada are analyzed in terms of particle microphysical properties using novel software developed at Potsdam University. Multiwavelength Raman lidar measurements of particle extinction and backscatter coefficients as well as linear particle depolarization ratios are used as input for the software. The result of the retrieval is a 2-dimensional particle volume distribution as a function of radius and aspect ratio, from which the particle microphysical properties are obtained.

Investigating the size, shape and surface roughness dependence of polarization lidars with light-scattering computations on real mineral dust particles: Application to dust particles' external mixtures and dust mass concentration retrievals

Our understanding of the contribution of mineral dust to the Earth's radiative budget is limited by the complexity of these particles, which present a wide range of sizes, are highly-irregularly shaped, and are present in the atmosphere in the form of particle mixtures. To address the spatial distribution of mineral dust and atmospheric dust mass concentrations, polarization lidars are nowadays frequently used, with partitioning algorithms allowing to discern the contribution of mineral dust in two or three-component particle external mixtures. In this paper, we investigate the dependence of the retrieved dust backscattering (βd) vertical profiles with the dust particle size and shape. For that, new light-scattering numerical simulations are performed on real atmospheric mineral dust particles, having determined mineralogy (CAL, DOL, AGG, SIL), derived from stereogrammetry (stereo-particles), with potential surface roughness, which are compared to the widely-used spheroidal mathematical shape model. For each dust shape model (smooth stereo-particles, rough stereo-particles, spheroids), the dust depolarization, backscattering Ångström exponent, lidar ratio are computed for two size distributions representative of mineral dust after long-range transport. As an output, two Saharan dust outbreaks involving mineral dust in two, then three-component particle mixtures are studied with Lyon (France) UV–VIS polarization lidar. If the dust size matters most, under certain circumstances, βd can vary by approximately 67% when real dust stereo-particles are used instead of spheroids, corresponding to variations in the dust backscattering coefficient as large as 2Mm−1·sr−1. Moreover, the influence of surface roughness in polarization lidar retrievals is for the first time discussed. Finally, dust mass-extinction conversion factors (ηd) are evaluated for each assigned shape model and dust mass concentrations are retrieved from polarization lidar measurements. From spheroids to stereo-particles, ηd increases by about 30%. We believe these results may be useful for our understanding of the spatial distribution of mineral dust contained in an aerosol external mixture and to better quantify dust mass concentrations from polarization lidar experiments.

Creating Aerosol Types from CHemistry (CATCH): A New Algorithm to Extend the Link Between Remote Sensing and Models

AbstractCurrent remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH‐derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first‐generation airborne High Spectral Resolution Lidar (HSRL‐1) retrievals during the Ship‐Aircraft Bio‐Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH‐derived aerosol types are determined by multivariate clustering of model‐calculated variables that have been trained using retrievals of aerosol types from HSRL‐1. CATCH‐derived aerosol types (with the exception of smoke) compare well with HSRL‐1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System‐ with Chemistry (GEOS‐Chem) model. Spatial distributions of CATCH‐derived aerosol types for the North American model domain during July/August 2014 show that aerosol type‐specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model‐generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL‐1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

Mapping Snow Depth From Ka-Band Interferometry: Proof of Concept and Comparison With Scanning Lidar Retrievals

This letter presents the first demonstration of millimeter-wave single-pass interferometric synthetic aperture radar (InSAR) for snow-depth mapping. Maps are presented over the Tuolumne River Basin region of the Sierra Nevada, CA, USA, and compared with those collected by a scanning lidar onboard the NASA Airborne Snow Observatory for the same region on the same snow day. For this observation, the snow surface was wet and melting and as such penetration of the electromagnetic wave into the snow volume can be effectively neglected. Despite the rugged terrain, heavy tree-cover, and very low snow-volume, depth maps had a standard deviation <1 m with the largest differences occurring on slopes exceeding 40°. While additional evaluation is needed with demonstration of the InSAR capability over a greater range of conditions and terrain, these results are promising. InSAR for snow-depth mapping holds significant advantages for a spaceborne mission if proven viable as it can operate through cloud cover, day or night, and measure snowpack when wet or melting.

Optical Backscattering Measured by Airborne Lidar and Underwater Glider

The optical backscattering from particles in the ocean is an important quantity that has been measured by remote sensing techniques and in situ instruments. In this paper, we compare estimates of this quantity from airborne lidar with those from an in situ instrument on an underwater glider. Both of these technologies allow much denser sampling of backscatter profiles than traditional ship surveys. We found a moderate correlation (R = 0.28, p &lt; 10−5), with differences that are partially explained by spatial and temporal sampling mismatches, variability in particle composition, and lidar retrieval errors. The data suggest that there are two different regimes with different scattering properties. For backscattering coefficients below about 0.001 m−1, the lidar values were generally greater than the glider values. For larger values, the lidar was generally lower than the glider. Overall, the results are promising and suggest that airborne lidar and gliders provide comparable and complementary information on optical particulate backscattering.

Remote sensing ice supersaturation inside and near cirrus clouds: a case study in the subtropics

AbstractCombining vertically resolved lidar retrievals of water vapor and cloud detection, we document a 2‐day subtropical cirrus case study over La Réunion (20.9°S–55.5°E) in March 2005, focusing on the conditions of ice supersaturation inside and near the observed cloud. Using satellite observations, we describe the synoptic conditions leading to cloud formation. Supersaturation occurs 25% of the time within the cirrus, up to 35% in its middle segment, where relative humidity goes beyond 150%. In clear‐sky areas, relative humidity stays consistently low, especially in profiles without clouds. High‐troposphere atmospheric waves could initiate the formation of supersaturation conditions, especially on 16 March.

Shortwave direct radiative effects of above-cloud aerosols over global oceans derived from 8 years of CALIOP and MODIS observations

Abstract. In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DREs) of above-cloud aerosols (ACAs) over global oceans using 8 years (2007–2014) of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: southeastern (SE) Atlantic region, where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over the African Savanna; tropical northeastern (TNE) Atlantic and the Arabian Sea, where ACAs are predominantly windblown dust from the Sahara and Arabian deserts, respectively; and the northwestern (NW) Pacific, where ACAs are mostly transported smoke and polluted dusts from Asian. From radiative transfer simulations based on CALIOP–MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in the TNE Atlantic Ocean and the Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m−2 (range of −0.03 to 0.06 W m−2) at TOA. The DREs at surface and within the atmosphere are −0.15 W m−2 (range of −0.09 to −0.21 W m−2), and 0.17 W m−2 (range of 0.11 to 0.24 W m−2), respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region, the JJA (July–August) seasonal mean cloudy-sky DRE is about 0.7 W m−2 (range of 0.2 to 1.2 W m−2) at TOA. All our DRE computations are publicly available1. The uncertainty in our DRE computations is mainly caused by the uncertainties in the aerosol optical properties, in particular aerosol absorption, the uncertainties in the CALIOP operational aerosol optical thickness retrieval, and the ignorance of cloud and potential aerosol diurnal cycle. In situ and remotely sensed measurements of ACA from future field campaigns and satellite missions and improved lidar retrieval algorithm, in particular vertical feature masking, would help reduce the uncertainty. 1 https://drive.google.com/folderview?id=0B6gKx4dgNY0GMVYzcEd0bkZmRmc&amp;amp;usp=sharing

Laboratory investigations of mineral dust near-backscattering depolarization ratios

Recently, there has been increasing interest to derive the fractions of fine- and coarse-mode dust particles from polarization lidar measurements. For this, assumptions of the backscattering properties of the complex dust particles have to be made either by using empirical data or particle models. Laboratory measurements of dust backscattering properties are important to validate the assumptions made in the lidar retrievals and to estimate their uncertainties. Here, we present laboratory measurements of linear and circular near-backscattering (178°) depolarization ratios of over 200 dust samples measured at 488 and 552nm wavelengths. The measured linear depolarization ratios ranged from 0.03 to 0.36 and were strongly dependent on the particle size. The strongest size-dependence was observed for fine-mode particles as their depolarization ratios increased almost linearly with particle median diameter from 0.03 to 0.3, whereas the coarse-mode particle depolarization values stayed rather constant with a mean linear depolarization ratio of 0.27. The depolarization ratios were found to be insensitive to the dust source region or thin coating of the particles or to changes in relative humidity. We compared the measurements with results of three different scattering models. With certain assumptions for model particle shape, all the models were capable of correctly describing the size-dependence of the measured dust particle, albeit the model particles significantly differed in composition, shape and degree of complexity. Our results show potential for distinguishing the dust fine- and coarse-mode distributions based on their depolarization properties and, thus, can serve the lidar community as an empirical reference.

Retrieval of water vapor mixing ratio from a multiple channel Raman-scatter lidar using an optimal estimation method.

Lidar measurements of the atmospheric water vapor mixing ratio provide an excellent complement to radiosoundings and passive, ground-based remote sensors. Lidars are now routinely used that can make high spatial-temporal resolution measurements of water vapor from the surface to the stratosphere. Many of these systems can operate during the day and night, with operation only limited by clouds thick enough to significantly attenuate the laser beam. To enhance the value of these measurements for weather and climate studies, this paper presents an optimal estimation method (OEM) to retrieve the water vapor mixing ratio, aerosol optical depth profile, Ångstrom exponent, lidar constants, detector dead times, and measurement backgrounds from multichannel vibrational Raman-scatter lidars. The OEM retrieval provides the systematic uncertainties due to the overlap function, calibration factor, air density and Rayleigh-scatter cross sections, in addition to the random uncertainties of the retrieval due to measurement noise. The OEM also gives the vertical resolution of the retrieval as a function of height, as well as the height to which the contribution of the a priori is small. The OEM is applied to measurements made by the Meteoswiss Raman Lidar for Meteorological Observations (RALMO) in the day and night for clear and cloudy conditions. The retrieved water vapor mixing ratio is in excellent agreement with both the traditional lidar retrieval method and coincident radiosoundings.

Comparing Water Vapor Mixing Ratio Profiles and Cloud Vertical Structure from Multiwavelength Raman Lidar Retrievals and Radiosounding Measurements

A study of comparison of water vapor mixing ratio profiles, relative humidity profiles, and cloud vertical structures using two different instruments, a multiwavelength Aerosol-Depolarization-Raman lidar and radiosoundings, is presented. The observations were taken by the lidar located in Warsaw center and the radiosoundings located about 30km to the North in Legionowo (Poland). We compared the ground-based remote sensing technology with in-situ method in order to improve knowledge about water content thought the atmosphere and cloud formation. The method used for retrieving the cloud vertical structure can be improved comparing the radiosonde results with the lidar observations, which show promising results.

Case Study on Combined Lidar-Photometer Retrieval of Volcanic ASH Properties

We study the benefit of considering sun-/sky-photometer measurements in a microphysical lidar retrieval. Furthermore, to assess the importance of the aerosol model employed by the retrieval, we compare results obtained using a spheroid aerosol model with results using an advanced aerosol model that considers irregular particle shapes. Preliminary results are shown for the mass extinction conversion factor and the single scattering albedo during a measurement case of long-range-transported volcanic ash.

A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans

Abstract The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the postfrontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low-level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime postfrontal precipitation.

Performance Evaluation of the Boundary-Layer Height from Lidar and the Weather Research and Forecasting Model at an Urban Coastal Site in the North-East Iberian Peninsula

We evaluate planetary boundary-layer (PBL) parametrizations in the Weather Research and Forecasting (WRF) numerical model, with three connected objectives: first, for a 16-year period, we use a cluster analysis algorithm of three-day back-trajectories to determine general synoptic flow patterns over Barcelona, Spain arriving at heights of 0.5, 1.5, and 3 km; to represent the lower PBL, upper PBL, and lower free troposphere, respectively. Seven clusters are determined at each arriving altitude. Regional recirculations account for 54 % of the annual total at 0.5 km, especially in summertime. In the second objective, we assess a time-adaptive approach using an extended Kalman filter to estimate PBL height from backscatter lidar returns at 1200 UTC $$\pm $$ 30 min for 45 individual days during a seven-year period. PBL heights retrieved with this technique are compared with three classic methods used in the literature to estimate PBL height from lidar. The methods are validated against PBL heights calculated from daytime radiosoundings. Lidar and radiosonde estimated PBL heights are classified under objectively-determined synoptic clusters. With the final objective, WRF model-simulated PBL heights are validated against lidar estimates using eight unique PBL schemes as inputs. Evaluation of WRF model-simulated PBL heights are performed under different synoptic situations. Determination coefficients with lidar estimates indicate the non-local assymetric convective model scheme is the most reliable, with the widely-tested local Mellor–Yamada–Janjic scheme showing the weakest correlations with lidar retrievals. Overall, there is a systematic underestimation of PBL height simulated in the WRF model.