A First Case Study of CCN Concentrations from Spaceborne Lidar Observations

We present here the first cloud condensation nuclei (CCN) concentration profiles derived from measurements with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), for different aerosol types at a supersaturation of 0.15%. CCN concentrations, along with the corresponding uncertainties, were inferred for a nighttime CALIPSO overpass on 9 September 2011, with coincident observations with the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft, within the framework of the Evaluation of CALIPSO’s Aerosol Classification scheme over Eastern Mediterranean (ACEMED) research campaign over Thessaloniki, Greece. The CALIPSO aerosol typing is evaluated, based on data from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. Backward trajectories and satellite-based fire counts are used to examine the origin of air masses on that day. Our CCN retrievals are evaluated against particle number concentration retrievals at different height levels, based on the ACEMED airborne measurements and compared against CCN-related retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard Terra and Aqua product over Thessaloniki showing that it is feasible to obtain CCN concentrations from CALIPSO, with an uncertainty of a factor of two to three

TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements

Water vapor plays an important role in the greenhouse effect, rendering it an atmospheric constituent that requires continuous and global monitoring by different types of remote sensing instruments. The TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI/S5P) Total Column Water Vapor (TCWV) is a new product retrieved from the visible blue spectral range (435–455 nm), using an algorithm that was originally developed for the GOME-2/MetOp sensors. For the purposes of this work, 2.5 years of continuous satellite observations at high spatial resolution are validated against co-located (in space and in time) precipitable water Level 2.0 (quality-assured) ground-based measurements from the NASA AERONET (AErosol RObotic NETwork). The network uses Cimel Sun photometers located at approximately 1300 stations globally to monitor precipitable water among other products. Based on data availability, 369 of the stations were used in this study. The two datasets, satellite- and ground-based, were co-located, and the relative differences of the comparisons were calculated and statistically analyzed. The Pearson correlation coefficient of the two products is found to be 0.91, and the mean bias of the overall relative percentage differences is of the order of −2.7 %. For the Northern Hemisphere midlatitudes (30–60∘ N), where the density of the ground-based stations is high, the mean relative bias was found to be −1.8 %, while in the tropics (±15∘) the TROPOMI TCWV product has a relative dry bias of up to −10 %. The effect of various algorithm and geophysical parameters, such as air mass factor, solar zenith angle, clouds and albedo, is also presented and discussed. It was found that the cloud properties affect the validation results, leading the TCWV to a dry bias of −20 % for low cloud heights (cloud top pressure (CTP) >800 hPa). Moreover, cloud albedo introduces a wet bias of 15 % when it is below 0.3 and a dry bias up to −25 % when the clouds are more reflective. Overall, the TROPOMI/S5P TCWV product, on a global scale and for moderate albedo and cloudiness, agrees well at  % with the AERONET observations but probably within about −8 % to −13 % with respect to the “truth”

Est-ce qu'une forme presque sphérique est "LE NOUVEAU NOIR" pour la fumée?

International audienceWe present smoke lidar measurements from the Canadian fires of 2017. The advected smoke layers over Europe are detected at both tropospheric and stratospheric heights, with the latter presenting non-typical values of the Linear Particle Depolarization Ratio (LPDR) with strong wavelength dependence from the UV to the Near-IR. Specifically, the LPDR values are of the order of 22, 18 and 4% at 355, 532 and 1064 nm respectively. In an attempt to interpret these results, we apply the hypothesis that smoke particles have near-spherical and/or more complicated shapes. Scattering calculations with the T-matrix code revealed that the near-spherical shape is able to reproduce the observed LPDR and LR values of the stratospheric smoke particles at the three measurement wavelengths.Nous présentons les mesures du lidar de fumée des incendies canadiens de 2017. Les couches de fumée advectées sur l'Europe sont détectées à la fois à des hauteurs troposphériques et stratosphériques, ces dernières présentant des valeurs atypiques du rapport de dépolarisation linéaire des particules (LPDR) avec une forte dépendance de longueur d'onde de l'UV au proche IR. Plus précisément, les valeurs LPDR sont de l'ordre de 22, 18 et 4% à 355, 532 et 1064 nm respectivement. Pour tenter d'interpréter ces résultats, nous appliquons l'hypothèse que les particules de fumée ont des formes quasi sphériques et/ou plus complexes. Les calculs de diffusion avec le code de la matrice T ont révélé que la forme quasi-sphérique est capable de reproduire les valeurs LPDR et LR observées des particules de fumée stratosphériques aux trois longueurs d'onde de mesure

Detecting volcanic sulfur dioxide plumes in the Northern Hemisphere using the Brewer spectrophotometer, other networks, and satellite observations

This paper demonstrates that SO 2 columnar amounts have significantly increased following the five largest volcanic eruptions of the past decade in the Northern Hemisphere. A strong positive signal was detected by all the existing networks either ground based (Brewer, EARLINET, AirBase) or from satellites (OMI, GOME-2). The study particularly examines the adequacy of the existing Brewer network to detect SO 2 plumes of volcanic origin in comparison to other networks and satellite platforms. The comparison with OMI and 45 GOME-2 SO 2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses. It is shown that the Brewer instrument is capable of detecting significant columnar SO 2 increases following large volcanic eruptions, when SO 2 levels rise well above the instrumental noise of daily observations, estimated to be of the order of 2 DU. A model exercise from the MACC project shows that the large increases of SO 2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local sources or ship emissions but are clearly linked to the eruption. We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modeling could be created which can be used to forecast high SO 2 values both at ground level and in air flight corridors following future eruptions

Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption

The Copernicus Atmosphere Monitoring Service(CAMS), operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Com-mission, provides daily analyses and 5 d forecasts of atmospheric composition, including forecasts of volcanic sulfur dioxide (SO2) in near real time. CAMS currently assimilates total column SO2products from the GOME-2 instruments on MetOp-B and MetOp-C and the TROPOMI instrument on Sentinel-5P, which give information about the location and strength of volcanic plumes. However, the operational TROPOMI and GOME-2 data do not provide any information about the height of the volcanic plumes, and therefore some prior assumptions need to be made in the CAMS data assimilation system about where to place the resulting SO2increments in the vertical. In the current operational CAMS configuration, the SO2increments are placed in the mid-troposphere, around 550 hPa or 5 km. While this gives good results for the majority of volcanic emissions, it will clearly be wrong for eruptions that inject SO2at very different altitudes, in particular exceptional events where part of the SO2plume reaches the stratosphere.A new algorithm, developed by the German Aerospace Centre (DLR) for GOME-2 and TROPOMI, optimized in the frame of the ESA-funded Sentinel-5P Innovation–SO2Layer Height Project, and known as the Full-Physics Inverse Learning Machine (FP_ILM) algorithm, retrieves SO2 layer height from TROPOMI in near real time (NRT) in addition to the SO2column. CAMS is testing the assimilation of these products, making use of the NRT layer height information to place the SO2increments at a retrieved altitude. Assimilation tests with the TROPOMI SO2layer height data for the Raikoke eruption in June 2019 show that the resulting CAMSSO2plume heights agree better with IASI plume height data than operational CAMS runs without the TROPOMI SO2layer height information and show that making use of the additional layer height information leads to improved SO2 forecasts. Including the layer height information leads to higher modelled total column SO2values in better agreement with the satellite observations. However, the plume area and SO2burden are generally also overestimated in the CAMS analysis when layer height data are used. The main reason for this overestimation is the coarse horizontal resolution used in the minimizations. By assimilating the SO2layer height data, the CAMS system can predict the overall location of the Raikoke SO2plume up to 5 d in advance for about 20 dafter the initial eruption, which is better than with the operational CAMS configuration (without prior knowledge of the plume height) where the forecast skill is much more reduced for longer forecast lead times

Volcanic SO2 layer height by TROPOMI/S5P: evaluation against IASI/MetOp and CALIOP/CALIPSO observations

Volcanic eruptions eject large amounts of ash and trace gases such as sulfur dioxide (SO2) into the atmosphere. A significant difficulty in mitigating the impact of volcanic SO2 clouds on air traffic safety is that these gas emissions can be rapidly transported over long distances. The use of space-borne instruments enables the global monitoring of volcanic SO2 emissions in an economical and risk-free manner. Within the European Space Agency (ESA) Sentinel-5p+ Innovation project, the S5P SO2 layer height (S5P+I: SO2LH) activities led to the improvements of the retrieval algorithm and generation of the corresponding near real-time S5P SO2 LH products. These are currently operationally provided, in near real-time, by the German Aerospace Center (DLR) within the framework of the Innovative Products for Analyses of Atmospheric Composition (INPULS) project. The main aim of this paper is to present its extensive verification, accomplished within the S5P+I: SO2LH project, over major recent volcanic eruptions, against collocated space-borne measurements from the IASI/Metop and CALIOP/CALIPSO instruments as well as assess its impact on the forecasts provided by the Copernicus Atmospheric Monitoring Service (CAMS). The mean difference between S5P and IASI observations for the Raikoke 2019, the Nishinoshima 2020 and the La Soufrière-St Vincent 2021 eruptive periods is ∼ 0.5 ± 3 km, while for the Taal 2020 eruption, a larger difference was found, between 3 ± 3 km and 4 ± 3 km. The comparison of the daily mean SO2 LH further demonstrates the capabilities of this near real-time product, with slopes between 0.8 and 1 and correlation coefficients ranging between 0.6 and 0.8. Comparisons between the S5P SO2 LH and the CALIOP/CALIPSO ash plumes revealed an expected bias at -2.5 ± 2 km, considering that the injected SO2 and ash plume locations do not always coincide over an eruption. Furthermore, the CAMS assimilation of the S5P SO2 LH product led to much improved model output against the non-assimilated IASI LH, with a mean difference of 1.5 ± 2 km, compared to the original CAMS analysis, and improved the geographical spread of the Raikoke volcanic plume following the eruptive days

An EARLINET early warning system for atmospheric aerosol aviation hazards

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network's preparedness to offer insight into natural hazards that affect the aviation sector. © 2020 Author(s)

Lidar intercomparisons on algorithm and system level in the frame of EARLINET.

EARLINET (European Aerosol Research Lidar Network to Establish an Aerosol Climatology) is a joint project of 19 lidar groups operating aerosol lidar systems at 21 stations over a large part of Europe, plus one group focussing on mathematical problems associated with the retrieval of aerosol properties from lidar observations. The main goal of EARLINET is to establish a comprehensive statistically representative data set of the aerosol vertical distribution. For this purpose, each lidar group performs vertical aerosol soundings on a routine basis three times a week on preselected days and times. Additionally several special measurements (e.g. on Saharan dust, temporal cycles, rural and urban differences, long and medium range transport) are part of the project.Peer ReviewedPostprint (published version

An EARLINET early warning system for atmospheric aerosol aviation hazards

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network’s preparedness to offer insight into natural hazards that affect the aviation sector.ACTRIS-2 654109ACTRIS preparatory phase 739530EUNADICS-AV 723986E-shape (EuroGEOSS Showcases: Applications Powered by Europe) 820852Ministry of Research and Innovation, Ontario 19PFE/17.10.2018Romanian National Core Program 18N/2019European Commission European Commission Joint Research Centre 72569

Validation of the TROPOMI/S5P aerosol layer height using EARLINET lidars

The purpose of this study is to investigate the ability of the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) to derive accurate geometrical features of lofted aerosol layers, selecting the Mediterranean Basin as the study area. Comparisons with ground-based correlative measurements constitute a key component in the validation of passive and active satellite aerosol products. For this purpose, we use ground-based observations from quality-controlled lidar stations reporting to the European Aerosol Research Lidar Network (EARLINET). An optimal methodology for validation purposes has been developed and applied using the EARLINET optical profiles and TROPOMI aerosol products, aiming at the in-depth evaluation of the TROPOMI aerosol layer height (ALH) product for the period 2018 to 2022 over the Mediterranean Basin. Seven EARLINET stations were chosen, taking into consideration their proximity to the sea, which provided 63 coincident aerosol cases for the satellite retrievals. In the following, we present the first validation results for the TROPOMI/S5P ALH using the optimized EARLINET lidar products employing the automated validation chain designed for this purpose. The quantitative validation at pixels over the selected EARLINET stations illustrates that the TROPOMI ALH product is consistent with the EARLINET lidar products, with a high correlation coefficient R=0.82 (R=0.51) and a mean bias of -0.51±0.77 km and -2.27±1.17 km over ocean and land, respectively. Overall, it appears that aerosol layer altitudes retrieved from TROPOMI are systematically lower than altitudes from the lidar retrievals. High-albedo scenes, as well as low-aerosol-load scenes, are the most challenging for the TROPOMI retrieval algorithm, and these results testify to the need to further investigate the underlying cause. This work provides a clear indication that the TROPOMI ALH product can under certain conditions achieve the required threshold accuracy and precision requirements of 1 km, especially when only ocean pixels are included in the comparison analysis. Furthermore, we describe and analyse three case studies in detail, one dust and two smoke episodes, in order to illustrate the strengths and limitations of the TROPOMI ALH product and demonstrate the presented validation methodology. The present analysis provides important additions to the existing validation studies that have been performed so far for the TROPOMI S5P ALH product, which were based only on satellite-to-satellite comparisons.</p