Assessment of two aerosol optical thickness retrieval algorithms applied to MODIS aqua and terra measurements in Europe

© Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 LicenseThe aim of the present study is to validate AOT (aerosol optical thickness) and A° ngström exponent (α), obtained from MODIS (MODerate resolution Imaging Spectroradiometer) Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground) with the SAER (Satellite AErosol Retrieval) algorithm and with MODIS Collection 5 (c005) standard product retrievals (10 km horizontal resolution), against AERONET (AErosol RObotic NETwork) sun photometer observations over land surfaces in Europe. An inter-comparison of AOT at 0.469 nm obtained with the two algorithms has also been performed. The time periods investigated were chosen to enable a validation of the findings of the two algorithms for a maximal possible variation in sun elevation. The satellite retrievals were also performed with a significant variation in the satellite-viewing geometry, since Aqua and Terra passed the investigation area twice a day for several of the cases analyzed. The validation with AERONET shows that the AOT at 0.469 and 0.555 nm obtained with MODIS c005 is within the expected uncertainty of one standard deviation of the MODIS c005 retrievals (1AOT =±0.05±0.15 ·AOT). The AOT at 0.443 nm retrieved with SAER, but with a much finer spatial resolution, also agreed reasonably well with AERONET measurements. The majority of the SAER AOT values are within the MODIS c005 expected uncertainty range, although somewhat larger average absolute deviation occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between AOT from SAER and AERONET is, however, substantially larger for the wavelength 488 nm. This means that the values are, to a larger extent, outside of the expected MODIS uncertainty range. In addition, both satellite retrieval algorithms are unable to estimate accurately, although the MODIS c005 algorithm performs better. Based on the inter-comparison of the SAER and MODIS c005 algorithms, it was found that SAER on the whole is able to obtain results within the expected uncertainty range of MODIS Aqua and Terra observations.Peer reviewe

Assessing lidar-based classification schemes for polar stratospheric clouds based on 16 years of measurements at Esrange, Sweden

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License CC BY-NC-ND 3.0 https://creativecommons.org/licenses/by-nc-nd/3.0/, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.Lidar measurements of polar stratospheric clouds (PSCs) are commonly analyzed in classification schemes that apply the backscatter ratio and the particle depolarization ratio. This similarity of input data suggests comparable results of different classification schemes - despite measurements being performed with a variety of mostly custom-made instruments. Based on a time series of 16 years of lidar measurements at Esrange (68°N, 21°E), Sweden, we show that PSC classification differs substantially depending on the applied scheme. The discrepancies result from varying threshold values of lidar-derived parameters used to define certain PSC types. The resulting inconsistencies could impact the understanding of long-term PSC observations documented in the literature. We identify two out of seven considered classification schemes that are most likely to give reliable results and should be used in future lidar-based studies. Using polarized backscatter ratios gives the advantage of increased contrast for observations of weakly backscattering and weakly depolarizing particles. Improved confidence in PSC classification can be achieved by a more comprehensive consideration of the effect of measurement uncertainties. The particle depolarization ratio is the key to a reliable identification of different PSC types. Hence, detailed information on the calibration of the polarization-sensitive measurement channels should be provided to assess the findings of a study. Presently, most PSC measurements with lidar are performed at 532 nm only. The information from additional polarization-sensitive measurements in the near infrared could lead to an improved PSC classification. Coincident lidar-based temperature measurements at PSC level might provide useful information for an assessment of PSC classification. Key Points Assessment of PSC classification schemes Statistical analysis of PSC observations Recommendations for lidar-based PSC studiesPeer reviewe

Profiling of fine and coarse particle mass : Case studies of Saharan dust and Eyjafjallajökull/Grimsvötn volcanic plumes

© Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 LicenseThe polarization lidar photometer networking (POLIPHON) method introduced to separate coarse-mode and fine-mode particle properties of Eyjafjallajokull volcanic aerosols in 2010 is extended to cover Saharan dust events as well. Furthermore, new volcanic dust observations performed after the Grimsvotn volcanic eruptions in 2011 are presented. The retrieval of particle mass concentrations requires mass-specific extinction coefficients. Therefore, a review of recently published mass-specific extinction coefficients for Saharan dust and volcanic dust is given. Case studies of four different scenarios corroborate the applicability of the profiling technique: (a) Saharan dust outbreak to central Europe, (b) Saharan dust plume mixed with biomass-burning smoke over Cape Verde, and volcanic aerosol layers originating from (c) the Eyjafjallajokull eruptions in 2010 and (d) the Grimsvotn eruptions in 2011. Strong differences in the vertical aerosol layering, aerosol mixing, and optical properties are observed for the different volcanic eventsPeer reviewe

Aerosol-type classification based on AERONET version 3 inversion products

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.This study proposes an aerosol-type classification based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) provided in the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product. We compare our aerosol-type classification with an earlier method that uses fine-mode fraction (FMF) and SSA. Our new method allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols: pure dust (PD), dust-dominated mixed plume (DDM), and pollutant-dominated mixed plume (PDM). We test the aerosol classification at AERONET sites in East Asia that are frequently affected by mixtures of Asian dust and biomass-burning smoke or anthropogenic pollution. We find that East Asia is strongly affected by pollution particles with high occurrence frequencies of 50 % to 67 %. The distribution and types of pollution particles vary with location and season. The frequency of PD and dusty aerosol mixture (DDM+PDM) is slightly lower (34 % to 49 %) than pollution-dominated mixtures. Pure dust particles have been detected in only 1 % of observations. This suggests that East Asian dust plumes generally exist in a mixture with pollution aerosols rather than in pure form. In this study, we have also considered data from selected AERONET sites that are representative of anthropogenic pollution, biomass-burning smoke, and mineral dust. We find that average aerosol properties obtained for aerosol types in our PLDR–SSA-based classification agree reasonably well with those obtained at AERONET sites representative for different aerosol types.Peer reviewe

Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements

The satellite-based cloud condensation nuclei (CCN) proxies used to quantify the aerosolcloud interactions (ACIs) are column integrated and do not guarantee the vertical co-location of aerosols and clouds. This has encouraged the use of height-resolved measurements of spaceborne lidars for ACI studies and led to advancements in lidar-based CCN retrieval algorithms. In this study, we present a comparison between the number concentration of CCN (nCCN) derived from ground-based in situ and spaceborne lidar cloud-aerosol lidar with orthogonal polarization (CALIOP) measurements. On analysing their monthly time series, we found that about 88% of CALIOP nCCN estimates remained within a factor of 1.5 of the in situ measurements. Overall, the CALIOP estimates of monthly nCCN were in good agreement with the in situ measurements with a normalized mean error of 71%, normalized mean bias of 39% and correlation coefficient of 0.68. Based on our comparison results, we point out the necessary measures that should be considered for global nCCN retrieval. Our results show the competence of CALIOP in compiling a global height- and type-resolved nCCN dataset for use in ACI studies

Trends in MODIS and AERONET derived aerosol optical thickness over Northern Europe

Long-term Aqua and Terra MODIS (MODerate resolution Imaging Spectroradiometer) Collections 5.1 and 6.1 (c051 and c061, respectively) aerosol data have been combined with AERONET (AERosol RObotic NETwork) ground-based sun photometer observations to examine trends in aerosol optical thickness (AOT, at 550 nm) over Northern Europe for the months April to September. For the 1927 and 1559 daily coincident measurements that were obtained for c051 and c061, respectively, MODIS AOT varied by 86 and 90%, respectively, within the predicted uncertainty of one standard deviation of the retrieval over land (ΔAOT = ±0.05 ± 0.15·AOT). For the coastal AERONET site Gustav Dalen Tower (GDT), Sweden, larger deviations were found for MODIS c051 and c061 (79% and 75%, respectively, within predicted uncertainty). The Baltic Sea provides substantially better statistical representation of AOT than the surrounding land areas and therefore favours the investigations of trends in AOT over the region. Negative trends of 1.5% and 1.2% per year in AOT, based on daily averaging, were found for the southwestern Baltic Sea from MODIS c051 and c061, respectively. This is in line with a decrease of 1.2% per year in AOT at the AERONET station Hamburg. For the western Gotland Basin area, Sweden, negative trends of 1.5%, 1.1% and 1.6% per year in AOT have been found for MODIS c051, MODIS c061 and AERONET GDT, respectively. The strongest trend of –1.8% per year in AOT was found for AERONET Belsk, Poland, which can be compared to –1.5% per day obtained from MODIS c051 over central Poland. The trends in MODIS and AERONET AOT are nearly all statistically significant at the 95% confidence level. The strongest aerosol sources are suggested to be located southwest, south and southeast of the investigation area, although the highest prevalence of pollution events is associated with air mass transport from southwest.Peer reviewe

Spaceborne observations of low surface aerosol concentrations in the Stockholm region

© 2016 M. Tesche et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.This article investigates the feasibility of using spaceborne observations of aerosol optical thickness (AOT) derived with the Moderate Resolution Imaging Spectroradiometer (MODIS) for monitoring of fine particulate matter (PM2.5) in an environment of low aerosol loading. Previous studies of the AOT-to-PM2.5 relationship benefit from the large range of observed values. The Stockholm region features a comprehensive network of ground-based monitoring stations that generally show PM2.5 values <20 µg m−3. MODIS AOT at 555 nm is usually <0.20 and in good agreement with ground-based sun photometer observations in this region. We use MODIS Collection 5 AOT data with a horizontal resolution of 10 km×10 km and ground-based in-situ PM2.5 observations to derive an AOT-to-PM2.5 relationship that can be used to estimate fields of PM2.5. This has been carried out with respect to the months from April to September of the period 2000–2013. Relative average absolute deviations of 33–55 % (mean of 45 %) are obtained between MODIS-retrieved and ground-based PM2.5. The root mean square error is 0.2159 µg m−3 between retrieved and measured PM2.5. From spaceborne lidar observations, it is found that elevated aerosol layers are generally sparse in the Stockholm region. This favours remote sensing of PM2.5 from space. The deviations found between measured and retrieved PM2.5 are mainly attributed to infrequent situations of inhomogeneous aerosol layering for which column-integrated observations cannot be connected to surface conditions. Using MODIS Collection 6 data with a resolution of 3 km×3 km in a case study actually gives far fewer results than the coarser Collection 5 product. This is explained by the complex geography of the Stockholm region with a coastline and an abundance of lakes, which seems to induce biases in the retrieval of AOT at higher spatial resolution.Peer reviewedFinal Published versio

Vertical profiling of aerosol optical properties with multiwavelength aerosol lidar during the Saharan Mineral Dust Experiments

Die vorliegende Arbeit beschäftigt sich mit der Auswertung und den Ergebnissen von Mehrwellenlängen–Polarisations–Ramanlidarmessungen, die im Rahmen des Saharastaubschließungsexperiments Saharan Mineral Dust Experiment (SAMUM) durchgeführt wurden. Das SAMUM–Projekt erstreckte sich über zwei Intensivmesszeiträume im Mai und Juni 2006 in Marokko (SAMUM–1) und im Januar und Februar 2008 auf den Kapverdischen Inseln (SAMUM–2). Desweiteren werden zusätzliche Lidarmessungen besprochen, die im Mai und Juni 2008 auf den Kapverdischen Inseln durchgeführt wurden. Die geometrischen und optischen Eigenschaften der während dieser Experimente mit mehreren hochmodernen Lidargeräten beobachteten Mineralstaub- und Biomassenverbrennungsaerosolschichten werden anhand von Fallstudien und mehrwöchigen, höhenaufgelösten Mittelwerten beschrieben. Zudem werden Kalibrierungen und Korrekturen vorgestellt, die zur Qualitätssicherung der gewonnenen Messdaten durchgeführt wurden. Ein im Rahmen der Arbeit entwickeltes, auf quantitativen Messungen des linearen Partikeldepolarisationsverhältnisses basierendes Verfahren zur höhenaufgelösten Trennung der Anteile von Mineralstaub und Biomassenverbrennungsaerosol an den während SAMUM–2 gemessenen Rücktreu- und Extinktionsprofilen wird vorgestellt und angewandt. Die Auswertung der Mehrwellenlängenlidarmessungen der SAMUM–Kampagnen ermöglichte eine spektral aufgelöste Charakterisierung der optischen Eigenschaften von Saharastaubpartikeln. Besondere Aufmerksamkeit wurde auf die Bestimmung der intensiven Parameter Extinktions–zu–Rückstreuverhältnis (Lidarverhältnis), lineares Partikeldepolarisationsverhältnis sowie Ångströmexponent der Rückstreu- und Extinktionskoeffizienten gelegt. Die im Rahmen von SAMUM bei den Wellenlängen 355, 532 und 1064 nm durchgeführten Lidarmessungen ergaben mittlere Lidarverhältnisse von 55±5 sr für reinen Saharastaub. Während SAMUM wurden außerdem erstmals quantitative Messergebnisse des linearen Partikeldepolarisationsverhältnisses von reinem Saharastaub bei mehreren Wellenlängen gewonnen. Die mittleren Werte dieser Größe lagen bei 0.26±0.06 (355 und 1064 nm), 0.31±0.03 (532 nm) und 0.37±0.07 (710 nm). Diese Erkenntnisse liefern wichtige Informationen für die Auswertung von Messungen mit weniger fortschrittlichen Lidargeräten. Die durch SAMUM gewonnenen Erkenntnisse der optischen Eigenschaften von Mineralstaub erlauben eine eindeutige Identifikation des Staubanteils in Aerosolschichten im Abluftbereich der Wüsten. Zudem wurden Richtgrößen ermittelt, die zur Validierung von Modellen zur Beschreibung von Lichtstreuung an großen, nicht–kugelförmigen Teilchen verwendet werden können. Derartige Streumodelle werden für die Auswertung von Messungen der optischen Eigenschaften von Mineralstaubpartikeln mit passiven Sensoren benötigt und befinden sich zur Zeit eher in einer frühen Entwicklungsphase.:1 Introduction 1 2 The SAMUM Campaigns 5 2.1 Concept and Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Dust Sources in Northern Africa . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Aerosol in the Outflow Region of West Africa . . . . . . . . . . . . . . 8 2.4 Field Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3 Theory 17 3.1 Light Scattering in the Atmosphere . . . . . . . . . . . . . . . . . . . . 17 3.2 Lidar Principle and Lidar Equation . . . . . . . . . . . . . . . . . . . . 21 3.3 Basic Lidar Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.3.1 Elastic–backscatter Lidar . . . . . . . . . . . . . . . . . . . . . . 24 3.3.2 Raman Lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.3.3 High Spectral Resolution Lidar . . . . . . . . . . . . . . . . . . 27 3.3.4 Polarization Lidar . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4 Aerosol Characterization with Lidar 33 4.1 Aerosol Typing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 4.2 Aerosol–type Separation . . . . . . . . . . . . . . . . . . . . . . . . . . 34 4.3 Inversion with Regularization . . . . . . . . . . . . . . . . . . . . . . . 38 5 Instrumentation 43 5.1 MULIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5.2 POLIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 5.3 HSRL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 5.4 BERTHA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 5.4.1 System Properties and Data Analysis . . . . . . . . . . . . . . . 45 5.4.2 Measurement of the Linear Volume Depolarization Ratio . . . . 48 5.4.3 Corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5.4.3.1 Overlap Correction . . . . . . . . . . . . . . . . . . . . 52 5.4.3.2 Polarization–dependent Receiver Transmission . . . . . 54 5.4.3.3 Depolarization Extrapolation . . . . . . . . . . . . . . 61 5.5 Sun Photometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 5.6 Radiosonde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 5.7 Backward Trajectories . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 6 Results 67 6.1 SAMUM–1, Morocco, Summer . . . . . . . . . . . . . . . . . . . . . . . 67 6.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 6.1.2 Measurement Case: 15 May 2006 . . . . . . . . . . . . . . . . . 69 6.1.3 Measurement Case: 3 June 2006 . . . . . . . . . . . . . . . . . . 73 6.1.4 General Findings and Discussion . . . . . . . . . . . . . . . . . 78 6.2 SAMUM–2a, Cape Verde, Winter . . . . . . . . . . . . . . . . . . . . . 87 6.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 6.2.2 Measurement Case: 31 January 2008 . . . . . . . . . . . . . . . 89 6.2.3 General Findings and Discussion . . . . . . . . . . . . . . . . . 96 6.3 SAMUM–2b, Cape Verde, Summer . . . . . . . . . . . . . . . . . . . . 107 6.3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.3.2 Measurement Case: 3–4 June 2008 . . . . . . . . . . . . . . . . 108 6.3.3 General Findings and Discussion . . . . . . . . . . . . . . . . . 112 7 SAMUMmary: Milestones and Outlook 119 8 Appendix 127 8.1 Error Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 8.1.1 Backscatter Coefficients . . . . . . . . . . . . . . . . . . . . . . 128 8.1.2 Extinction Coefficients . . . . . . . . . . . . . . . . . . . . . . . 131 8.1.3 Lidar Ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 8.1.4 Ångström Exponents . . . . . . . . . . . . . . . . . . . . . . . . 133 8.1.5 Volume Depolarization Ratios . . . . . . . . . . . . . . . . . . . 134 8.1.6 Particle Depolarization Ratios . . . . . . . . . . . . . . . . . . . 137 8.2 List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 8.3 List of Symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

On the spectral depolarisation and lidar ratio of mineral dust provided in the AERONET version 3 inversion product

Knowledge of the particle lidar ratio (Sγ) and the particle linear depolarisation ratio (δγ) for different aerosol types allows for aerosol typing and aerosol-Type separation in lidar measurements. Reference values generally originate from dedicated lidar observations but might also be obtained from the inversion of AErosol RObotic NETwork (AERONET) sun/sky radiometer measurements. This study investigates the consistency of spectral Sγ and δγ provided in the recently released AERONET version 3 inversion product for observations of undiluted mineral dust in the vicinity of the following major deserts: Gobi, Sahara, Arabian, Great Basin, and Great Victoria. Pure dust conditions are identified by an Angström exponent < 0:4 and a fine-mode fraction < 0:1. The values of spectral Sγ are found to vary for the different source regions but generally show an increase with decreasing wavelength. The feature correlates to AERONET, retrieving an increase in the imaginary part of the refractive index with decreasing wavelength. The smallest values of Sγ D 35- 45 sr are found for mineral dust from the Great Basin desert, while the highest values of 50-70 sr have been inferred from AERONET observations of Saharan dust. Values of Sγ at 675, 870, and 1020 nm seem to be in reasonable agreement with available lidar observations, while those at 440 nm are up to 10 sr higher than the lidar reference. The spectrum of δγ shows a maximum of 0.26-0.31 at 1020 nm and decreasing values as wavelength decreases. AERONET-derived δγ values at 870 and 1020 nm are in line with the lidar reference, while values of 0.19-0.24 at 440 nm are smaller than the independent lidar observations by a difference of 0.03 to 0.08. This general behaviour is consistent with earlier studies based on AERONET version 2 products.Peer reviewe

Reconciling aerosol light extinction measurements from spaceborne lidar observations and in situ measurements in the Arctic

© Author(s) 2014. This work is distributed under the Creative Commons Attribution 3.0 License.In this study we investigate to what degree it is possible to reconcile continuously recorded particle light extinction coefficients derived from dry in situ measurements at Zeppelin station (78.92° N, 11.85° E; 475 m above sea level), Ny-Ålesund, Svalbard, that are recalculated to ambient relative humidity, as well as simultaneous ambient observations with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. To our knowledge, this represents the first study that compares spaceborne lidar measurements to optical aerosol properties from short-term in situ observations (averaged over 5 h) on a case-by-case basis. Finding suitable comparison cases requires an elaborate screening and matching of the CALIOP data with respect to the location of Zeppelin station as well as the selection of temporal and spatial averaging intervals for both the ground-based and spaceborne observations. Reliable reconciliation of these data cannot be achieved with the closest-approach method, which is often used in matching CALIOP observations to those taken at ground sites. This is due to the transport pathways of the air parcels that were sampled. The use of trajectories allowed us to establish a connection between spaceborne and ground-based observations for 57 individual overpasses out of a total of 2018 that occurred in our region of interest around Svalbard (0 to 25° E, 75 to 82° N) in the considered year of 2008. Matches could only be established during winter and spring, since the low aerosol load during summer in connection with the strong solar background and the high occurrence rate of clouds strongly influences the performance and reliability of CALIOP observations. Extinction coefficients in the range of 2 to 130 Mmg-1 at 532 nm were found for successful matches with a difference of a factor of 1.47 (median value for a range from 0.26 to 11.2) between the findings of in situ and spaceborne observations (the latter being generally larger than the former). The remaining difference is likely to be due to the natural variability in aerosol concentration and ambient relative humidity, an insufficient representation of aerosol particle growth, or a misclassification of aerosol type (i.e., choice of lidar ratio) in the CALIPSO retrieval.Peer reviewe