Cloud-Aerosol Lidar With Orthogonal Polarization Observations Research Articles

Monitoring biomass burning aerosol transport using CALIOP observations and reanalysis models: a Canadian wildfire event in 2019

Abstract. In May–June 2019, smoke plumes from wildfires in Alberta, Canada, were advected all the way to Europe. To analyze the evolution of the plumes and to estimate the amount of smoke aerosols transported to Europe, retrievals from the spaceborne lidar CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) were used. The plumes were located with the help of a trajectory analysis, and the masses of smoke aerosols were retrieved from the CALIOP observations. The accuracy of the CALIOP mass retrievals was compared with the accuracy of ground-based lidars/ceilometer near the source in North America and after the long-range transport in Europe. Overall, CALIOP and the ground-based lidars/ceilometer produced comparable results. Over North America the CALIOP layer mean mass was 30 % smaller than the ground-based estimates, whereas over southern Europe that difference varied between 12 % and 43 %. Finally, the CALIOP mass retrievals were compared with simulated aerosol concentrations from two reanalysis models: MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) and CAMS (Copernicus Atmospheric Monitoring System). The simulated total column aerosol optical depths (AODs) and the total column mass concentration of smoke agreed quite well with CALIOP observations, but the comparison of the layer mass concentration of smoke showed significant discrepancies. The amount of smoke aerosols in the model simulations was consistently smaller than in the CALIOP retrievals. These results highlight the limitations of such models and more specifically their limitation to reproduce properly the smoke vertical distribution. They indicate that CALIOP is a useful tool monitoring smoke plumes over secluded areas, whereas reanalysis models have difficulties in representing the aerosol mass in these plumes. This study shows the advantages of spaceborne aerosol lidars, e.g., being of paramount importance to monitor smoke plumes, and reveals the urgent need of future lidar missions in space.

Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations

Abstract. For the observation of the global three-dimensional distribution of aerosol composition and the evaluation of the shortwave direct radiative effect (SDRE) by aerosols, we developed a retrieval algorithm that uses observation data from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua. The CALIOP–MODIS retrieval optimizes the aerosol composition to both the CALIOP and MODIS observations in the daytime. Aerosols were assumed to be composed of four aerosol components: water-soluble (WS), light-absorbing (LA), dust (DS), and sea salt (SS) particles. The outputs of the CALIOP–MODIS retrieval are the vertical profiles of the extinction coefficient (αa), single-scattering albedo (ω0), asymmetry factor (g) of total aerosols (WS+LA+DS+SS), and αa of WS, LA, DS, and SS. Daytime observations of CALIOP and MODIS in 2010 were analyzed by the CALIOP–MODIS retrieval. The global means of the aerosol optical depth (τa) at 532 nm were 0.147±0.148 for total aerosols, 0.072±0.085 for WS, 0.027±0.035 for LA, 0.025±0.054 for DS, and 0.023±0.020 for SS. τa of the CALIOP–MODIS retrieval was between those of the CALIPSO and MODIS standard products and was close to the MODIS standard product. The global means of ω0 and g were 0.940±0.038 and 0.718±0.037; these values are in the range of those reported by previous studies. The horizontal distribution of each aerosol component was reasonable; for example, DS was large in desert regions, and LA was large in the major regions of biomass burning and anthropogenic aerosol emissions. The values of τa, ω0, g, and fine and coarse median radii of the CALIOP–MODIS retrieval were compared with those of the AERONET products. τa at 532 and 1064 nm of the CALIOP–MODIS retrieval agreed well with the AERONET products. The ω0, g, and fine and coarse median radii of the CALIOP–MODIS retrieval were not far from those of the AERONET products, but the variations were large, and the coefficients of determination for linear regression between them were small. In the retrieval results for 2010, the clear-sky SDRE values for total aerosols at the top and bottom of the atmosphere were -4.99±3.42 and -13.10±9.93 W m−2, respectively, and the impact of total aerosols on the heating rate was from 0.0 to 0.5 K d−1. These results are generally similar to those of previous studies, but the SDRE at the bottom of the atmosphere is larger than that reported previously. Consequently, comparison with previous studies showed that the CALIOP–MODIS retrieval results were reasonable with respect to aerosol composition, optical properties, and the SDRE.

Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations

Abstract. In this study, we developed a novel algorithm based on the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) observations and dust vertical profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosol optical depth at 10 µm (DAOD10 µm) and the coarse-mode dust effective diameter (Deff) over global oceans. The accuracy of the Deff retrieval is assessed by comparing the dust lognormal volume particle size distribution (PSD) corresponding to retrieved Deff with the in situ-measured dust PSDs from the AERosol Properties – Dust (AER-D), Saharan Mineral Dust Experiment (SAMUM-2), and Saharan Aerosol Long-Range Transport and Aerosol–Cloud-Interaction Experiment (SALTRACE) field campaigns through case studies. The new DAOD10 µm retrievals were evaluated first through comparisons with the collocated DAOD10.6 µm retrieved from the combined Imaging Infrared Radiometer (IIR) and CALIOP observations from our previous study (Zheng et al., 2022). The pixel-to-pixel comparison of the two DAOD retrievals indicates a good agreement (R∼0.7) and a significant reduction in (∼50 %) retrieval uncertainties largely thanks to the better constraint on dust size. In a climatological comparison, the seasonal and regional (2∘×5∘) mean DAOD10 µm retrievals based on our combined MODIS and CALIOP method are in good agreement with the two independent Infrared Atmospheric Sounding Interferometer (IASI) products over three dust transport regions (i.e., North Atlantic (NA; R=0.9), Indian Ocean (IO; R=0.8) and North Pacific (NP; R=0.7)). Using the new retrievals from 2013 to 2017, we performed a climatological analysis of coarse-mode dust Deff over global oceans. We found that dust Deff over IO and NP is up to 20 % smaller than that over NA. Over NA in summer, we found a ∼50 % reduction in the number of retrievals with Deff>5 µm from 15 to 35∘ W and a stable trend of Deff average at 4.4 µm from 35∘ W throughout the Caribbean Sea (90∘ W). Over NP in spring, only ∼5 % of retrieved pixels with Deff>5 µm are found from 150 to 180∘ E, while the mean Deff remains stable at 4.0 µm throughout eastern NP. To the best of our knowledge, this study is the first to retrieve both DAOD and coarse-mode dust particle size over global oceans for multiple years. This retrieval dataset provides insightful information for evaluating dust longwave radiative effects and coarse-mode dust particle size in models.

MERRA-2 reanalysis-aided sea fog detection based on CALIOP observation over North Pacific

Sea fog can lead to a dangerous meteorological hazard over oceans and coastal areas. Cloud-aerosol Lidar with Orthogonal Polarization (CALIOP) is an effective tool to detect sea fog, however it is ineffective for dense fog detection because the lidar signal has been fully attenuated before reaching the layer base. To address this issue by improving dense fog detection, a reanalysis-aided sea fog detection method using CALIOP lidar measurements and MERRA-2 reanalysis dataset is proposed taking the Northwestern Pacific (NP) as study area. In this method, CALIOP lidar measurements are used to locate the ceiling and base of the hydrometeor layers, and extract the candidate fog layers in the Marine Atmospheric Boundary Layer (MABL). Reanalysis dataset are used to identify real fog from the candidate fog layers based on the near-surface meteorological difference under different weather conditions (sea fog, stratus and stratus precipitation). Method validation using in-situ weather records from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) and five climate stations, shows the detection accuracy and false alarm rate of 89.4% and 2.0%, respectively. Most importantly, about 87.4% of dense fogs are successfully discriminated with the aid of reanalysis data. Model application to CALIOP data from 2007 to 2019 shows pronounced spatial and seasonal characteristics of sea fog distribution over NP, with the highest frequency (>40%) found over the Kuril Islands, Sea of Okhotsk and Bering Sea from June to August. The example demonstrates that by using time series CALIOP observations and the proposed method, one may expect spatio-temporally complete sea fog information, which is important especially for remote regions with scarce in-situ measurements (e.g. polar regions). Our research proposes and proves a novel idea of sea fog detection from space by using satellite lidar and reanalysis data, which may benefit the sea fog forecasting and dynamics analysis, by providing unprecedented large-scale high-quality observations, especially over dense fog conditions.

Self-lofting of wildfire smoke in the troposphere and stratosphere: simulations and space lidar observations

Abstract. Wildfire smoke is known as a highly absorptive aerosol type in the shortwave wavelength range. The absorption of sunlight by optically thick smoke layers results in heating of the ambient air. This heating is translated into self-lofting of the smoke up to more than 1 km in altitude per day. This study aims for a detailed analysis of tropospheric and stratospheric smoke lofting rates based on simulations and observations. The main goal is to demonstrate that radiative heating of intense smoke plumes is capable of lofting them from the lower and middle free troposphere (injection heights) up to the tropopause without the need of pyrocumulonimbus (pyroCb) convection. The further subsequent ascent within the lower stratosphere (caused by self-lofting) is already well documented in the literature. Simulations of absorbed solar radiation by smoke particles and resulting heating rates, which are then converted into lofting rates, are conducted by using the ECRAD (European Centre for Medium-Range Weather Forecasts Radiation) scheme. As input parameters thermodynamic profiles from CAMS (Copernicus Atmosphere Monitoring Service) reanalysis data, aerosol profiles from ground-based lidar observations, radiosonde potential temperature profiles, CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) aerosol measurements, and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth retrievals were used. The sensitivity analysis revealed that the lofting rate strongly depends on aerosol optical thickness (AOT), layer depth, layer height, and black carbon (BC) fraction. We also looked at the influence of different meteorological parameters such as cloudiness, relative humidity, and potential temperature gradient. To demonstrate the applicability of our self-lofting model, we compared our simulations with the lofting processes in the stratosphere observed with CALIOP after major pyroCb events (Canadian fires in 2017, Australian fires in 2019–2020). We analyzed long-term CALIOP observations of smoke layers and plumes evolving in the UTLS (upper troposphere and lower stratosphere) height region over Siberia and the adjacent Arctic Ocean during the summer season of 2019. Our results indicate that self-lofting contributed to the vertical transport of smoke. We hypothesize that the formation of a near-tropopause aerosol layer, observed with CALIOP, was the result of self-lofting processes because this is in line with the simulations. Furthermore, Raman-lidar-based aerosol typing (in Leipzig and the High Arctic) clearly indicated the dominance of smoke in the UTLS aerosol layer since August 2019, most probably also the result of smoke self-lofting.

The thermal infrared optical depth of mineral dust retrieved from integrated CALIOP and IIR observations

Recent studies have suggested that global climate models tend to underestimate dust particle size in particular, the very coarse mode, leading to an underestimated direct radiative effect (DRE) of dust in the longwave (LW) thermal infrared (TIR) region. However, the magnitude of LW DRE remains highly uncertain, because of limited observations of dust optical depth at the TIR (DAODTIR). This study presents a simple approach to retrieve the DAODTIR over the oceans during nighttime through synergistic use of observations from the Infrared Imaging Radiometer (IIR) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), both onboard of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. For each cloud-free dust-laden profile identified by the IIR-CALIOP observation, a Lookup-Table (LUT) of the 10.6 μm IIR band brightness temperatures (BT) difference (dBT) under different DAODTIR with respect to their dust-free BTs is constructed based on the CALIOP retrieved dust vertical profile and a priori dust scattering properties using a fast radiative transfer model. Then the DAODTIR is retrieved by projecting the IIR-observed dBT on the LUT. Sensitivity studies show that the DAODTIR retrieval at 10.6 μm is more susceptible to the dust particle size distribution (PSD) assumption than dust refractive indices. To estimate the uncertainty caused by PSD assumption, two DAODTIR retrieval products, one based on the dust PSD from the AERONET at Cape Verde and the other on an in situ measured PSD from the recent Fennec campaign, are provided. The retrieval uncertainty is mainly contributed by the BT difference between the observation and simulation using auxiliary atmospheric data. The climatology of the retrieval from 2013 to 2019 shows reasonable spatiotemporal variations of DAODTIR with the global-averaged value of 0.008 and 0.013 based on different pre-assumed dust PSDs. Climatological results agree reasonably well with two independent DAODTIR retrieval products based on the Infrared Atmospheric Sounding Interferometer (IASI) over the active dust transport regions, such as North and Tropical Atlantic (r = 0.9 and r = 0.8) and Indian Ocean (r = 0.8). The seasonal and interannual variation is also well-compared (r = 0.76) with AERONET coarse-mode AOD at 97 selected sites. The synergic CALIOP observation allows the retrieved DAODTIR to directly compare with the extrapolated DAODTIR from DAOD in the visible (i.e., 532 nm), which helps evaluate the observational constraints on DAODTIR. Our study clearly reveals that the retrieved DAODTIR from IIR is much less susceptible to various uncertainties than converted results from CALIOP. It also offers a unique prospect of collocated active lidar and passive IR observations for retrieving dust DAODTIR.

Methodology to obtain highly resolved SO<sub>2</sub> vertical profiles for representation of volcanic emissions in climate models

Abstract. In this study we describe a methodology to create high-vertical-resolution SO2 profiles from volcanic emissions. We demonstrate the method's performance for the volcanic clouds following the eruption of Sarychev in June 2009. The resulting profiles are based on a combination of satellite SO2 and aerosol retrievals together with trajectory modelling. We use satellite-based measurements, namely lidar backscattering profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instrument, to create vertical profiles for SO2 swaths from the Atmospheric Infrared Sounder (AIRS) aboard the Aqua satellite. Vertical profiles are created by transporting the air containing volcanic aerosol seen in CALIOP observations using the FLEXible PARTicle dispersion model (FLEXPART) while preserving the high vertical resolution using the potential temperatures from the MERRA-2 (Modern-Era Retrospective analysis for Research and Application) meteorological data for the original CALIOP swaths. For the Sarychev eruption, air tracers from 75 CALIOP swaths within 9 d after the eruption are transported forwards and backwards and then combined at a point in time when AIRS swaths cover the complete volcanic SO2 cloud. Our method creates vertical distributions for column density observations of SO2 for individual AIRS swaths, using height information from multiple CALIOP swaths. The resulting dataset gives insight into the height distribution in the different sub-clouds of SO2 within the stratosphere. We have compiled a gridded high-vertical-resolution SO2 inventory that can be used in Earth system models, with a vertical resolution of 1 K in potential temperature, 61 ± 56 m, or 1.8 ± 2.9 mbar.

Three-dimensional climatology, trends, and meteorological drivers of global and regional tropospheric type-dependent aerosols: insights from 13 years (2007–2019) of CALIOP observations

Abstract. Globally gridded aerosol extinction data from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) during 2007–2019 are utilized to investigate the three-dimensional (3D) climatological distribution of tropospheric type-dependent aerosols and to identify the trends in column aerosol optical depth (AOD), partitioned within different altitude regimes, and their meteorological drivers. Using detection samples of layer aerosols, we also yield a 3D distribution of the frequency of occurrence (FoO) of aerosol subtypes classified by CALIOP. The results show that the aerosol extinction coefficient (AEC) shows contrasting vertical distribution patterns over land and ocean, with the former possessing significant geographical dependence, while the enhancement of AEC in the latter is mainly located below 1 km. The vertical structures of the type-dependent AECs, however, are strongly dependent on altitude. When the total AOD (TAOD) is partitioned into the planetary boundary layer (PBL) and the free troposphere (FT), results demonstrate that the PBL and FT contribute 62.08 % and 37.92 %, respectively, of the global tropospheric TAOD averaged over daytime and nighttime. Yet this CALIOP-based partitioning of the different aerosol subtypes in the PBL and FT varies significantly. Among all 12 typical regions of interest analyzed, more than 50 % of TAOD is located in the lower troposphere (0–2 km), while the contribution is less than 2 % above 6 km. In global average terms, we found the aerosol FoO averaged over all layers is 4.45 %, with the largest contribution from “clean marine” (1.79 %) and the smallest from “clean continental” (0.05 %). Overall, the FoO vertical structures of the aerosol layer exhibit a distribution pattern similar to that of AEC. The resulting trend analyses show that CALIOP accurately captures significant regional anomalies in TAOD, as observed in other satellite measurements and aerosol reanalysis. Our correlation analysis between meteorological factors and TAOD suggests the interannual variability of TAOD is related to the variability of precipitation (PPT), volumetric soil moisture (VSM), and wind speed (WS) in the particular regions. For instance, the positive TAOD trend over the equatorial central Pacific is mainly attributable to the increased PPT and decreased WS. In contrast, in dry convective regions dominated by dust and smoke, the interannual variability/trend in TAOD is largely modified by the VSM driven by the PPT. Additionally, we further found that these significant regional correlations are more robust within the PBL and significantly weakened or even reversed within the FT. This highlights the superiority of using the TAOD partitioned within the PBL as a proxy variable for the widely applied TAOD to explore the relationships between atmospheric pollution and meteorology.

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud mask is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using only spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We develop both daytime and nighttime algorithms that are differed by whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. Specially, to eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments on the surface, and, instead of developing independent ML-based algorithms, adding surface variable in an appropriate way may enhance the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we do find that the current AHI cloud mask may overestimate clouds, and our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection for ~5% and reducing the misjudgment for ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product, but may overestimate cloudy pixels as well. Overall, our ML-based algorithms can serve as a reliable method to provide all time cloud mask results for AHI observations, and the surface is suggested to be treated as independent variables for future ML-based algorithm development.

On the best locations for ground-based polar stratospheric cloud (PSC) observations

Abstract. Spaceborne observations of polar stratospheric clouds (PSCs) with the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provide a comprehensive picture of the occurrence of Arctic and Antarctic PSCs as well as their microphysical properties. However, advances in understanding PSC microphysics also require measurements with ground-based instruments, which are often superior to CALIOP in terms of, for example, time resolution, measured parameters, and signal-to-noise ratio. This advantage is balanced by the location of ground-based PSC observations and their dependence on tropospheric cloudiness. CALIPSO observations during the boreal winters from December 2006 to February 2018 and the austral winters 2012 and 2015 are used to assess the effect of tropospheric cloudiness and other measurement-inhibiting factors on the representativeness of ground-based PSC observations with lidar in the Arctic and Antarctic, respectively. Information on tropospheric and stratospheric clouds from the CALIPSO Cloud Profile product (05kmCPro version 4.10) and the CALIPSO polar stratospheric cloud mask version 2, respectively, is combined on a profile-by-profile basis to identify conditions under which a ground-based lidar is likely to perform useful measurements for the analysis of PSC occurrence. It is found that the location of a ground-based measurement together with the related tropospheric cloudiness can have a profound impact on the derived PSC statistics and that these findings are rarely in agreement with polewide results from CALIOP observations. Considering the current polar research infrastructure, it is concluded that the most suitable sites for the expansion of capabilities for ground-based lidar observations of PSCs are Summit and Villum in the Arctic and Mawson, Troll, and Vostok in the Antarctic.

Seasonal migration of cirrus clouds by using CALIOP observations

Cirrus clouds at heights of 10–18 km are investigated for the seasonal migrations based on 3 years observations of CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) in 2008–2012. Past studies have shown cirrus clouds migrate from their winter peaks in the equatorial regions to the maximum latitudes of ± 30° in the boreal summer as the migration of ITCZ (Intertropical Convergence Zone). However, this general picture does not show detailed distributions by including height, seasons and latitudinal dependences considering cirrus extended height and latitudinal coverages. We are also interested in understanding the occurrences of thin cirrus in the tropical tropopause and formation of all cirrus in the extratropics where little studies about their migration have been made. It is not well know if the summer enhancement in the extratropics is only related to the migration or by other factors. Cirrus distributions are studied in two height groups of low ( 15 km), and in three regions of EQ (− 15° to 15° latitudes), NH (15°–30°), and SH (− 15° to − 30°) for different seasons. Our results show a major part of cirrus, the low cirrus, migrate to the extratropics in the summer. Like ITCZ, they stay mostly in the north (64%) less in the south (36%) following the same migration pattern. High cirrus cloud is decoupled from ITCZ with the major part showing a boreal winter peak spread to higher latitudes with seasons. In the extratropics, enhanced production of high cirrus can be attributed to the convective production in the summer monsoons. The summer convective production is used to estimate the formation of equatorial high cirrus in terms of rapid convection or slow ascending with a ratio determined.

New attenuated backscatter profile by removing the CALIOP receiver's transient response

The photomultiplier tubes (PMTs) used to measure altitude-resolved 532 nm backscatter intensity by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) do not recover rapidly following exposure to very high light levels (e.g., from optically dense water clouds). Instead, they exhibit exponentially decaying “noise tails” that can cause substantial misestimates when determining layer base altitudes and deriving cloud extinction coefficients. Here we present a deconvolution correction algorithm to remove these noise tails in the CALIOP level 1 science data products. The corrected 532 nm attenuated backscatter profiles generated by the deconvolution algorithm are evaluated using the corresponding CALIOP observations at 1064 nm and coincident profiles measured at 532 nm by the NASA-Langley airborne high spectral resolution lidar. Results indicate that our deconvolution correction algorithm effectively removes the non-ideal PMT recovery effects on the CALIOP level 1 vertical profiles, showing excellent performance for surface and water cloud lidar returns when the attenuated backscatter coefficients are greater than 0.01 km−1 sr−1.

The 2018 fire season in North America as seen by TROPOMI: aerosol layer height intercomparisons and evaluation of model-derived plume heights

Abstract. Before the launch of the TROPOspheric Monitoring Instrument (TROPOMI), only two other satellite instruments were able to observe aerosol plume heights globally, the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The TROPOMI aerosol layer height is a potential game changer, since it has daily global coverage, and the aerosol layer height retrieval is available in near real time. The aerosol layer height can be useful for aviation and air quality alerts, as well as for improving air quality forecasting related to wildfires. Here, TROPOMI's aerosol layer height product is evaluated with MISR and CALIOP observations for wildfire plumes in North America for the 2018 fire season (June to August). Further, observing system simulation experiments were performed to interpret the fundamental differences between the different products. The results show that MISR and TROPOMI are, in theory, very close for aerosol profiles with single plumes. For more complex profiles with multiple plumes, however, different plume heights are retrieved; the MISR plume height represents the top layer, and the plume height retrieved with TROPOMI tends to have an average altitude of several plume layers. The comparison between TROPOMI and MISR plume heights shows that, on average, the TROPOMI aerosol layer heights are lower, by approximately 600 m, compared to MISR, which is likely due to the different measurement techniques. From the comparison to CALIOP, our results show that the TROPOMI aerosol layer height is more accurate over dark surfaces, for thicker plumes, and plumes between approximately 1 and 4.5 km. MISR and TROPOMI are further used to evaluate the plume height of Environment and Climate Change Canada's operational forecasting system FireWork with fire plume injection height estimates from the Canadian Forest Fire Emissions Prediction System (CFFEPS). The modelled plume heights are similar compared to the satellite observations but tend to be slightly higher with average differences of 270–580 and 60–320 m compared to TROPOMI and MISR, respectively.

The Influence of Elevated Smoke Layers on Stratocumulus Clouds Over the SE Atlantic in the NASA Goddard Earth Observing System (GEOS) Model

AbstractPrevious evaluations of simulated aerosol transport over the south‐east Atlantic by global aerosol models, including the Goddard Earth Observing System (GEOS) atmospheric general circulation model, showed that the bulk of the modeled smoke aerosol layer resided ~1–2 km lower than Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar observations. Using this finding as the motivation, this study examines the changes in model‐simulated cloud properties in response to redistributing the vertical placement of the aerosol over the ocean. Ten years (2006–2015) of CALIOP‐retrieved smoke aerosol extinction profiles were used to redistribute the model‐simulated aerosol mass on a monthly mean basis, keeping the column aerosol mass conserved. The results from the model sensitivity experiments show that elevating the aerosol layer to higher levels in agreement with CALIOP observations causes an increase in cloud fractions by ~33% for shallow marine boundary layers (MBL) and a decrease by ~30% for deeper MBL. For a shallow MBL, aerosol‐induced warming within the cloud layers for the lower altitude aerosol case decreases relative humidity at these levels and leads to a reduction of overall cloud amount compared to the elevated aerosol case. For a deeper MBL, however, aerosol heating within the upper cloud levels in the lower altitude aerosol case increases the underlying MBL stability, which suppresses the cloud vertical extent, enhances cloud cover, and delays the stratocumulus to cumulus transition. Finally, aerosol redistribution impacts on radiative forcing are investigated, which appear to be mainly driven by the changes in cloud area fractions rather than in‐cloud liquid water path changes between the model experiments.

Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors

Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generation, cloud screening must be balanced, so both false cloud-free and false cloudy retrievals are minimized. Many methods used in recent CDRs show signs of clear-conservative cloud screening leading to overestimated cloudiness. This study presents a new cloud screening approach for Advanced Very-High-Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery based on the Bayesian discrimination theory. The method is trained on high-quality cloud observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The method delivers results designed for optimally balanced cloud screening expressed as cloud probabilities together with information on for which clouds (minimum cloud optical thickness) the probabilities are valid. Cloud screening characteristics over 28 different Earth surface categories were estimated. Using independent CALIOP observations (including all observed clouds) in 2010 for validation, the total global hit rates for AVHRR data and the SEVIRI full disk were 82% and 85%, respectively. High-latitude oceans had the best performance, with a hit rate of approximately 93%. The results were compared to the CM SAF cLoud, Albedo, and surface RAdiation dataset from AVHRR data–second edition (CLARA-A2) CDR and showed general improvements over most global regions. Notably, the Kuipers’ Skill Score improved, verifying a more balanced cloud screening. The new method will be used to prepare the new CLARA-A3 and CLAAS-3 (CLoud property dAtAset using SEVIRI, Edition 3) CDRs in the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project.

Retrieving the microphysical properties of opaque liquid water clouds from CALIOP measurements.

Cloud droplet effective radius (CER) and number concentration (CDNC) are two critical microphysical properties of liquid water clouds, which play essential roles in the Earth's radiative energy balance and atmospheric hydrological cycle. Even though many satellite remote sensing techniques have been developed to obtain these two properties, the observations are often limited to the daytime. In this study, a method to estimate CER and CDNC of liquid water clouds over global ocean area during both daytime and nighttime from CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) measurements is presented. The size sensitivity of the dual-wavelength (532 nm & 1064 nm) layer-integrated attenuated backscattering signals from CALIOP is checked and information content for liquid water cloud CER retrieval is found. Taking use of the artificial neural network (ANN) technique, the CER and then the CDNC are estimated from CALIOP by combining the polarization ratio and the dual wavelength attenuated backscattering signals. The comparisons with CER and CDNC estimated from MODIS (Moderate Resolution Imaging Spectroradiometer) during daytime demonstrate the feasibility of this new method. Both the daytime and nighttime CER and CDNC derived from CALIOP observations are presented in this paper and the day-night variation of liquid water cloud is discussed which would provide useful day-night variation of liquid water cloud properties.

New Global View of Above-Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements

Above-low-level-cloud aerosols (ACAs) have gradually gained more interest in recent years; however, the combined aerosol–cloud radiation effects are not well understood. The uncertainty about the radiative effects of aerosols above cloud mainly stems from the lack of comprehensive and accurate retrieval of aerosols and clouds for ACA scenes. In this study, an improved ACA identification and retrieval methodology was developed to provide a new global view of the ACA distribution by combining three-channel CALIOP (The Cloud–Aerosol Lidar with Orthogonal Polarization) observations. The new method can reliably identify and retrieve both thin and dense ACA layers, providing consistent results between the day- and night-time retrieval of ACAs. Then, new four-year (2007 to 2010) global ACA datasets were built, and new seasonal mean views of global ACA occurrence, optical depth, and geometrical thickness were presented and analyzed. Further discussion on the relative position of ACAs to low clouds showed that the mean distance between the ACA layer and the low cloud deck over the tropical Atlantic region is less than 0.2 km. This indicates that the ACAs over this region are more likely to be mixed with low-level clouds, thereby possibly influencing the cloud microphysics over this region, contrary to findings reported from previous studies. The results not only help us better understand global aerosol transportation and aerosol–cloud interactions but also provide useful information for model evaluation and improvements.

Recent Regime Shifts in Mineral Dust Trends Over South Asia From Long-Term CALIPSO Observations

Mineral dust aerosols have significant implications on the regional-hydroclimate, especially over the regions located downwind of dust sources. During the premonsoon season, much of South Asia is characterized by enhanced aerosol loading favored by the transport of mineral dust from the desert regions of West Asia/Northwest India. Vertically resolved backscatter measurements at dual polarization from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to estimate the dust optical depth over the Indian region. Using a decade long data set of CALIOP observations, a shift in long-term trend of dust over the Northwest India, Indo-Gangetic Plain, and West Asia is demonstrated. The decreasing trend in dust loading over the Indian region reversed to increasing after 2013. The interannual variability in premonsoon dust optical depth over Northwest India is found to be associated with winter time rainfall. The interannual variation of tropospheric temperature anomalies over Northwest India did not show a direct correlation with mineral dust loading.

A bulk-mass-modeling-based method for retrieving particulate matter pollution using CALIOP observations

Abstract. In this proof-of-concept paper, we apply a bulk-mass-modeling method using observations from the NASA Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument for retrieving particulate matter (PM) concentration over the contiguous United States (CONUS) over a 2-year period (2008–2009). Different from previous approaches that rely on empirical relationships between aerosol optical depth (AOD) and PM2.5 (PM with particle diameters less than 2.5 µm), for the first time, we derive PM2.5 concentrations, during both daytime and nighttime, from near-surface CALIOP aerosol extinction retrievals using bulk mass extinction coefficients and model-based hygroscopicity. Preliminary results from this 2-year study conducted over the CONUS show a good agreement (r2∼0.48; mean bias of −3.3 µg m−3) between the averaged nighttime CALIOP-derived PM2.5 and ground-based PM2.5 (with a lower r2 of ∼0.21 for daytime; mean bias of −0.4 µg m−3), suggesting that PM concentrations can be obtained from active-based spaceborne observations with reasonable accuracy. Results from sensitivity studies suggest that accurate aerosol typing is needed for applying CALIOP measurements for PM2.5 studies. Lastly, the e-folding correlation length for surface PM2.5 is found to be around 600 km for the entire CONUS (∼300 km for western CONUS and ∼700 km for eastern CONUS), indicating that CALIOP observations, although sparse in spatial coverage, may still be applicable for PM2.5 studies.

Lagrangian simulation of ice particles and resulting dehydration in the polar winter stratosphere.

Polar stratospheric clouds (PSCs) and cold stratospheric aerosols drive heterogeneous chemistry and play a major role in polar ozone depletion. The Chemical Lagrangian Model of the Stratosphere (CLaMS) simulates the nucleation, growth, sedimentation, and evaporation of PSC particles along individual trajectories. Particles consisting of nitric acid trihydrate (NAT), which contain a substantial fraction of the stratospheric nitric acid (HNO3), were the focus of previous modeling work and are known for their potential to denitrify the polar stratosphere. Here, we carried this idea forward and introduced the formation of ice PSCs and related dehydration into the sedimentation module of CLaMS. Both processes change the simulated chemical composition of the lower stratosphere. Due to the Lagrangian transport scheme, NAT and ice particles move freely in three-dimensional space. Heterogeneous NAT and ice nucleation on foreign nuclei as well as homogeneous ice nucleation and NAT nucleation on preexisting ice particles are now implemented into CLaMS and cover major PSC formation pathways.We show results from the Arctic winter 2009/2010 and from the Antarctic winter 2011 to demonstrate the performance of the model over two entire PSC seasons. For both hemispheres, we present CLaMS results in comparison to measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), and the Microwave Limb Sounder (MLS). Observations and simulations are presented on season-long and vortex-wide scales as well as for single PSC events. The simulations reproduce well both the timing and the extent of PSC occurrence inside the entire vortex. Divided into specific PSC classes, CLaMS results show predominantly good agreement with CALIOP and MIPAS observations, even for specific days and single satellite orbits. CLaMS and CALIOP agree that NAT mixtures are the first type of PSC to be present in both winters. NAT PSC areal coverages over the entire season agree satisfactorily. However, cloud-free areas, next to or surrounded by PSCs in the CALIOP data, are often populated with NAT particles in the CLaMS simulations. Looking at the temporal and vortex-averaged evolution of HNO3, CLaMS shows an uptake of HNO3 from the gas into the particle phase which is too large and happens too early in the simulation of the Arctic winter. In turn, the permanent redistribution of HNO3 is smaller in the simulations than in the observations. The Antarctic model run shows too little denitrification at lower altitudes towards the end of the winter compared to the observations. The occurrence of synoptic-scale ice PSCs agrees satisfactorily between observations and simulations for both hemispheres and the simulated vertical redistribution of water vapor (H2O) is in very good agreement with MLS observations. In summary, a conclusive agreement between CLaMS simulations and a variety of independent measurements is presented.