First triple-wavelength lidar observations of depolarization and extinction-to-backscatter ratios of Saharan dust

Two layers of Saharan dust observed over Leipzig, Germany, in February and March 2021 were used to provide the first-ever lidar measurements of the dust lidar ratio (extinction-to-backscatter ratio) and linear depolarization ratio at all three classical lidar wavelengths (355, 532 and 1064 nm). The pure-dust conditions during the first event exhibit lidar ratios of 47 ± 8, 50 ± 5 and 69 ± 14 sr and particle linear depolarization ratios of 0.242 ± 0.024, 0.299 ± 0.018 and 0.206 ± 0.010 at wavelengths of 355, 532 and 1064 nm, respectively. The second, slightly polluted-dust case shows a similar spectral behavior of the lidar and depolarization ratio with values of the lidar ratio of 49 ± 4, 46 ± 5 and 57 ± 9 sr and the depolarization ratio of 0.174 ± 0.041, 0.298 ± 0.016 and 0.242 ± 0.007 at 355, 532 and 1064 nm, respectively. The results were compared with Aerosol Robotic Network (AERONET) version 3 (v3) inversion solutions and the Generalized Retrieval of Aerosol and Surface Properties (GRASP) at six and seven wavelengths. Both retrieval schemes make use of a spheroid shape model for mineral dust. The spectral slope of the lidar ratio from 532 to 1064 nm could be well reproduced by the AERONET and GRASP retrieval schemes. Higher lidar ratios in the UV were retrieved by AERONET and GRASP. The enhancement was probably caused by the influence of fine-mode pollution particles in the boundary layer which are included in the columnar photometer measurements. Significant differences between the measured and retrieved wavelength dependence of the particle linear depolarization ratio were found. The potential sources for these uncertainties are discussed.

Two-year statistics of columnar-ice production in stratiform clouds over Hyytiälä, Finland: environmental conditions and the relevance to secondary ice production

Formation of ice particles in clouds at temperatures of −10 ∘C or warmer was documented by using ground-based radar observations. At these temperatures, the number concentration of ice-nucleating particles (INPs) is not only expected to be small, but this number is also highly uncertain. In addition, there are a number of studies reporting that the observed number concentration of ice particles exceeds expected INP concentrations, indicating that other ice generation mechanisms, such as secondary ice production (SIP), may play an important role in such clouds. To identify formation of ice crystals and report conditions in which they are generated, W-band cloud radar Doppler spectra observations collected at the Hyytiälä station for more than 2 years were used. Given that at these temperatures ice crystals grow mainly as columns, which have distinct linear depolarization ratio (LDR) values, the spectral LDR was utilized to identify newly formed ice particles. It is found that in 5 %–13 % of clouds, where cloud top temperatures are −12 ∘C or warmer, production of columnar ice is detected. For colder clouds, this percentage can be as high as 33 %; 40 %–50 % of columnar-ice-producing events last less than 1 h, while 5 %–15 % can persist for more than 6 h. By comparing clouds where columnar crystals are produced and to the ones where these crystals are absent, the columnar-ice-producing clouds tend to have larger values of liquid water path and precipitation intensity. The columnar-ice-producing clouds were subdivided into three categories, using the temperature difference, ΔT, between the altitudes where columns are first detected and cloud top. The cases where ΔT is less than 2 K are typically single-layer shallow clouds where needles are produced at the cloud top. In multilayered clouds where 2 K < ΔT, columns are produced in a layer that is seeded by ice particles falling from above. This classification allows us to study potential impacts of various SIP mechanisms, such as the Hallet–Mossop process or freezing breakup, on columnar-ice production. To answer the question whether the observed ice particles are generated by SIP in the observed single-layer shallow clouds, ice particle number concentrations were retrieved and compared to several INP parameterizations. It was found that the ice number concentrations tend to be 1–3 orders of magnitude higher than the expected INP concentrations.

First triple-wavelength lidar observations of depolarization and extinction-to-backscatter ratios of Saharan dust

Two Saharan dust layers observed over Leipzig in February and March 2021 were used to provide the first ever lidar measurements of the extinction coefficient at 1064 nm for desert dust. The advanced multiwavelength Raman polarization lidar was able to provide, for the first time, the lidar ratio (extinction-to-backscatter ratio) and particle linear depolarization ratio at all three classical lidar wavelengths (355, 532 and 1064 nm). The pure dust conditions during the first event exhibit lidar ratios of 47±8, 50±5 and 63±13 sr and particle linear depolarization ratios of 0.260±0.026, 0.298±0.017 and 0.214±0.025 at the wavelengths of 355, 532 and 1064 nm, respectively. The second, slightly polluted dust case shows a similar spectral behavior with values of the lidar ratio of 52±8, 47±5 and 61±10 sr and the depolarization ratio of 0.188±0.053, 0.270±0.017 and 0.242±0.007 at 355, 532 and 1064 nm, respectively. The results were compared to AERONET v3 inversions and GRASP retrievals at six and seven wavelengths, which could reproduce the spectral slope of the lidar ratio from 532 to 1064 nm. The spectral slope of the particle linear depolarization ratio could not be reproduced by the AERONET inversions, especially at 1064 nm.

Experimental assessment of a micro-pulse lidar system in comparison with reference lidar measurements for aerosol optical properties retrieval

Simultaneous observations of a polarized micro-pulse lidar (P-MPL) system and two reference European Aerosol Research Lidar Network lidars running at the Leipzig site Germany, 51.4∘ N, 12.4∘ E; 125 m a.s.l.) were performed during a comprehensive 2-month field intercomparison campaign in summer 2019. An experimental assessment regarding both the overlap (OVP) correction of the P-MPL signal profiles and the volume linear depolarization ratio (VLDR) analysis, together with its impact on the retrieval of the aerosol optical properties, is achieved; the experimental procedure used is also described. The optimal lidar-specific OVP function is experimentally determined, highlighting that the one delivered by the P-MPL manufacturer cannot be used long. Among the OVP functions examined, the averaged function between those obtained from the comparison of the P-MPL observations with those of the other two reference lidars seems to be the best proxy at both near- and far-field ranges. In addition, the impact of the OVP function on the accuracy of the retrieved profiles of the total particle backscatter coefficient (PBC) and the particle linear depolarization ratio (PLDR) is examined. The VLDR profile is obtained and compared with that derived from the reference lidar, showing that it needs to be corrected by a small offset value with good accuracy. Once P-MPL measurements are optimally (OVP, VLDR) corrected, both the PBC and PLDR profiles can be accurately derived and are in good agreement with reference aerosol retrievals. Overall, as a systematic requirement for lidar systems, an adequate OVP function determination and VLDR testing analysis needs to be performed on a regular basis to correct the P-MPL measurements in order to derive suitable aerosol products. A dust event observed in Leipzig in June 2019 is used for illustration.

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

Multiyear statistics of columnar ice production in stratiform clouds over Hyytiälä, Finland

Formation of ice particles in clouds at the temperatures of −10 °C or warmer was documented by using ground-based remote sensing observations. At these temperatures, the number concentration of ice nucleating particles (INP) is not only expected to be small, but also this number is highly uncertain. In addition, there are a number of studies reporting that the observed number concentration of ice particles exceeds expected INP concentrations, indicating that other ice generation mechanisms, such as secondary ice production (SIP), may play an important role in such clouds. To identify the formation of ice crystals and report conditions in which they are generated, W-band cloud radar Doppler spectra observations collected at the Hyytiälä station for more than two years were used. Given that at these temperatures ice crystals grow mainly as columns, which have distinct linear depolarization ratio (LDR) values, spectral LDR was utilized to identify newly formed ice particles. Our results indicate that that the columnar ice production took place in 5 to 13 % of clouds, where cloud top temperatures were −12 °C or higher. For colder clouds, this percentage can be as high as 33 %. 40 ~ 50 % of columnar-ice-producing events last less than 1 hour, while 5 ~ 15 % can persist for more than 6 hours. By comparing clouds where columnar crystals were produced with the ones where these crystals were absent, we found that the columnar-ice-producing clouds tend to have larger values of liquid water path and precipitation intensity. The columnar-ice-producing clouds were subdivided into subcategories, using the temperature difference, Δ T, between the altitudes where columns are first detected and the cloud top altitude. The cases where Δ T is less than 2 °C are typically single-layer shallow clouds where needles are produced at the cloud top. In multilayered clouds, where Δ T > 2 °C, columns are produced in a layer that is seeded by ice particles falling from above. This classification allows to study potential impacts of various SIP mechanisms, such as Hallet-Mossop process or freezing breakup, on columnar ice production. To answer the question whether the observed ice particles are generated by SIP in the observed single-layer shallow clouds, ice particle number concentrations were retrieved and compared to several INP parameterizations. It was found that the ice number concentrations tend to be 1 ~ 3 orders of magnitude higher than the expected INP concentrations.

Melting Layer Detection and Observation with the NCAR Airborne W-Band Radar

A melting layer detection algorithm is developed for the NCAR 94 GHz airborne cloud radar (HIAPER CloudRadar, HCR). The detection method is based on maxima in the linear depolarization ratio and a discontinuity in the radial velocity field. A melting layer field is added to the radar data, which provides detected, interpolated, and estimated altitudes of the melting layer and the altitude of the 0 °C isotherm detected in model temperature data. The icing level is defined as the lowest melting layer, and the cloud data are flagged as either above (cold) or below (warm) the icing level. Analysis of the detected melting layer shows that the offset between the 0 °C isotherm and the actual melting layer varies with cloud type: in heavy convection sampled in the tropics, the melting layer is found up to 500 m below the 0 °C isotherm, while in shallow clouds, the offset is much smaller or sometimes vanishes completely. A relationship between the offset and the particle fall speed both above and below the melting layer is established. Special phenomena, such as a lowering of the melting layer towards the center of storms or split melting layers, were observed.

Aerosol particle depolarization ratio at 1565 nm measured with a Halo Doppler lidar

The depolarization ratio is a valuable parameter for lidar-based aerosol categorization. Usually, the aerosol particle depolarization ratio is determined at relatively short wavelengths of 355 nm and/or 532 nm, but some multi-wavelength studies including longer wavelengths indicate strong spectral dependency. Here, we investigate the capabilities of Halo Photonics StreamLine Doppler lidars to retrieve the particle linear depolarization ratio at the 1565 nm wavelength. We utilize collocated measurements with another lidar system, PollyXT at Limassol, Cyprus, and at Kuopio, Finland, to compare the depolarization ratio observed by the two systems. For mineral-dust-dominated cases we find typically a slightly lower depolarization ratio at 1565 nm than at 355 and 532 nm. However, for dust mixed with other aerosol we find a higher depolarization ratio at 1565 nm. For polluted marine aerosol we find a marginally lower depolarization ratio at 1565 nm compared to 355 and 532 nm. For mixed spruce and birch pollen we find a slightly higher depolarization ratio at 1565 nm compared to 532 nm. Overall, we conclude that Halo Doppler lidars can provide a particle linear depolarization ratio at the 1565 nm wavelength at least in the lowest 2–3 km above ground.

Microphysical and Polarimetric Radar Modeling of Hydrometeor Refreezing

A unique polarimetric radar signature indicative of hydrometeor refreezing during ice pellet events has been documented in several recent studies, yet the underlying microphysical causes remain unknown. The signature is characterized by enhancements in differential reflectivity (ZDR), specific differential phase (KDP), and linear depolarization ratio (LDR), and a reduction in co-polar correlation coefficient (ρhv) within a layer of decreasing radar reflectivity factor at horizontal polarization (ZH). In previous studies, the leading hypothesis for the observed radar signature is the preferential refreezing of small drops. Here, a simplified, one-dimensional, explicit bin microphysics model is developed to simulate the refreezing of fully melted hydrometeors, and coupled with a polarimetric radar forward operator to quantify the impact of preferential refreezing on simulated radar signatures. The modeling results demonstrate that preferential refreezing is insufficient by itself to produce the observed signatures. In contrast, simulations considering an ice shell growing asymmetrically around a freezing particle (i.e., emulating a thicker ice shell on the bottom of a falling particle) produce realistic ZDR enhancements, and also closely replicate observed features in ZH, KDP, LDR, and ρhv. Simulations that assume no increase in particle wobbling with freezing produce an even greater ZDR enhancement, but this comes at the expense of reducing the LDR enhancement. It is suggested that the polarimetric refreezing signature is instead strongly related to both the distribution of the unfrozen liquid portion within a freezing particle, and the orientation of this liquid with respect to the horizontal.

Global Aerosol Classification Based on Aerosol Robotic Network (AERONET) and Satellite Observation

The particle linear depolarization ratio (PLDR) and single scatter albedo (SSA) in 1020 nm from the Aerosol Robotic Network (AERONET) level 2.0 dataset was utilized among 52 stations to identify dust and dust dominated aerosols (DD), pollution dominated mixture (PDM), strongly absorbing aerosols (SA) and weakly absorbing aerosols (WA), investigate their spatial and temporal distribution, net radiative forcing and radiative forcing efficiency in global range, and further compare with VIIRS Deep Blue Production. The conclusion about net radiative forcing suggests that the high values of radiative forcing from dust and dust dominated aerosols, pollution dominated mixture both mainly come from western Africa. Strongly absorbing aerosols in South Africa and India contribute greatly to the net radiative forcing and the regions with relative high values of weakly absorbing aerosols are mainly located at East Asia and India. Lastly, the observation of VIIRS Deep Blue satellite monthly averaged products depicts the characteristics about spatial distribution of four kinds of aerosol well, the result from ground-based observation presents great significant to validate the measurements from remote sensing technology.