National Research Council - Institute of Methodologies for Environmental Analysis

Abstract. Although black carbon (BC) is one of the key atmospheric particulate components driving climate change and air quality, there is no agreement on the terminology that considers all aspects of specific properties, definitions, measurement methods, and related uncertainties. As a result, there is much ambiguity in the scientific literature of measurements and numerical models that refer to BC with different names and based on different properties of the particles, with no clear definition of the terms. The authors present here a recommended terminology to clarify the terms used for BC in atmospheric research, with the goal of establishing unambiguous links between terms, targeted material properties and associated measurement techniques.

We summarize our Raman lidar observations which were carried out in Europe, Asia, and Africa during the past 10 years, with focus on particle extinction‐to‐backscatter ratios (lidar ratios) and Ångström exponents. For the first time, we present statistics on lidar ratios for almost all climatically relevant aerosol types solely based on Raman lidar measurements. Sources of continental particles were in North America and Europe, the Sahara, and south and Southeast and east Asia. The North Atlantic Ocean, and the tropical and South Indian Ocean were the sources of marine particles. The statistics are complemented with lidar ratios describing aged forest fire smoke and pollution from polar regions (Arctic haze) after long‐range transport. In addition, we present particle Ångström exponents for the wavelength range from 355 to 532 nm and from 532 to 1064 nm. We compare our data set of lidar ratios to the recently published AERONET (Aerosol Robotic Network) lidar ratio climatology. That climatology is based on aerosol scattering modeling in which AERONET Sun photometer observations serve as input. Raman lidar measurements of extinction‐to‐backscatter ratios of Saharan dust and urban aerosols differ significantly from the numbers obtained with AERONET Sun photometers. There are also differences for some of the Ångström exponents. Further comparison studies are needed to reveal the reason for the observed differences.

The Paris Agreement aims to limit global mean temperature rise this century to well below 2 °C above pre-industrial levels. This target has wide-ranging implications for Europe and its cities, which are the source of substantial greenhouse gas emissions. This paper reports the state of local planning for climate change by collecting and analysing information about local climate mitigation and adaptation plans across 885 urban areas of the EU-28. A typology and framework for analysis was developed that classifies local climate plans in terms of their alignment with spatial (local, national and international) and other climate related policies. Out of eight types of local climate plans identified in total we document three types of stand-alone local climate plans classified as type A1 (autonomously produced plans), A2 (plans produced to comply with national regulations) or A3 (plans developed for international climate networks). There is wide variation among countries in the prevalence of local climate plans, with generally more plans developed by central and northern European cities. Approximately 66% of EU cities have a type A1, A2, or A3 mitigation plan, 26% an adaptation plan, and 17% a joint adaptation and mitigation plan, while about 33% lack any form of stand-alone local climate plan (i.e. what we classify as A1, A2, A3 plans). Mitigation plans are more numerous than adaptation plans, but planning for mitigation does not always precede planning for adaptation. Our analysis reveals that city size, national legislation, and international networks can influence the development of local climate plans. We found that size does matter as about 80% of the cities with above 500,000 inhabitants have a comprehensive and stand-alone mitigation and/or an adaptation plan (A1). Cities in four countries with national climate legislation (A2), i.e. Denmark, France, Slovakia and the United Kingdom, are nearly twice as likely to produce local mitigation plans, and five times more likely to produce local adaptation plans, compared to cities in countries without such legislation. A1 and A2 mitigation plans are particularly numerous in Denmark, Poland, Germany, and Finland; while A1 and A2 adaptation plans are prevalent in Denmark, Finland, UK and France. The integration of adaptation and mitigation is country-specific and can mainly be observed in two countries where local climate plans are compulsory, i.e. France and the UK. Finally, local climate plans produced for international climate networks (A3) are mostly found in the many countries where autonomous (type A1) plans are less common. This is the most comprehensive analysis of local climate planning to date. The findings are of international importance as they will inform and support decision-making towards climate planning and policy development at national, EU and global level being based on the most comprehensive and up-to-date knowledge of local climate planning available to date.

Abstract. The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite community, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observing system.

More than 130 observation days of the horizontal and vertical extent of Saharan dust intrusions over Europe during the period May 2000 to December 2002 were studied by means of a coordinated lidar network in the frame of the European Aerosol Research Lidar Network (EARLINET). The number of dust events was greatest in late spring, summer, and early autumn periods, mainly in southern (S) and southeastern (SE) Europe. Multiple aerosol dust layers of variable thickness (300–7500 m) were observed. The center of mass of these layers was located in altitudes between 850 and 8000 m. However, the mean thickness of the dust layer typically stayed around 1500–3400 m and the corresponding mean center of mass ranged from 2500 to 6000 m. In exceptional cases, dust aerosols reached northwestern (NW), northern (N), or northeastern (NE) Europe, penetrating the geographical area located between 4°W–28°E (longitude) and 38°N–58°N (latitude). Mean aerosol optical depths (AOD), extinction‐to‐backscatter ratios (lidar ratios, LR), and linear depolarization ratios of desert aerosols ranged from 0.1 to 0.25 at the wavelength of 355 or 351 nm, 30 to 80 sr at 355 or 351 nm, and 10 to 25% at 532 nm, respectively, within the lofted dust plumes. In these plumes typical Saharan dust backscatter coefficients ranged from 0.5 to 2 Mm −1 sr −1 . Southern European stations presented higher variability of the LR values and the backscatter‐related Ångström exponent values (BRAE) (LR: 20–100 sr; BRAE: −0.5 to 3) than northern ones (LR: 30–80 sr; BRAE: −0.5 to 1).

HyMeX-SOP1 collected unprecedented observations of atmosphere, ocean, land, and rivers

Abstract Due to the deep socioeconomic implications, induced seismicity is a timely and increasingly relevant topic of interest for the general public. Cases of induced seismicity have a global distribution and involve a large number of industrial operations, with many documented cases from as far back to the beginning of the twentieth century. However, the sparse and fragmented documentation available makes it difficult to have a clear picture on our understanding of the physical phenomenon and consequently in our ability to mitigate the risk associated with induced seismicity. This review presents a unified and concise summary of the still open questions related to monitoring, discrimination, and management of induced seismicity in the European context and, when possible, provides potential answers. We further discuss selected critical European cases of induced seismicity, which led to the suspension or reduction of the related industrial activities.

The fusion of high spatial resolution panchromatic (PAN) data with simultaneously acquired multispectral (MS) data with the lower spatial resolution is a hot topic, which is often called pansharpening. In this article, we exploit the combination of machine learning techniques and fusion schemes introduced to address the pansharpening problem. In particular, deep convolutional neural networks (DCNNs) are proposed to solve this issue. The latter is combined first with the traditional component substitution and multiresolution analysis fusion schemes in order to estimate the nonlinear injection models that rule the combination of the upsampled low-resolution MS image with the extracted details exploiting the two philosophies. Furthermore, inspired by these two approaches, we also developed another DCNN for pansharpening. This is fed by the direct difference between the PAN image and the upsampled low-resolution MS image. Extensive experiments conducted both at reduced and full resolutions demonstrate that this latter convolutional neural network outperforms both the other detail injection-based proposals and several state-of-the-art pansharpening methods.

Archaeological and cultural heritage (ACH), one of the core carriers of cultural diversity on our planet, has a direct bearing on the sustainable development of mankind. Documenting and protecting ACH is the common responsibility and duty of all humanity. It is governed by UNESCO along with the scientific communities that foster and encourage the use of advanced non-invasive techniques and methods for promoting scientific research into ACH and conservation of ACH sites. The use of remote sensing, a non-destructive tool, is increasingly popular by specialists around the world as it allows fast prospecting and mapping at multiple scales, rapid analysis of multisource datasets, and dynamic monitoring of ACH sites and their surrounding environments. The cost of using remote sensing is lower or even zero in practical applications. In this review, in order to discuss the advantages of airborne and spaceborne remote sensing (ASRS), the principles that make passive (photography, multispectral and hyperspectral) and active (synthetic aperture radar (SAR) and light detection and ranging radar (LiDAR)) imaging techniques suitable for ACH applications are first summarized and pointed out; a review of ASRS and the methodologies used over the past century is then presented together with relevant highlights from well-known research projects. Selected case studies from Mediterranean regions to East Asia illustrate how ASRS can be used effectively to investigate and understand archaeological features at multiple -scales and to monitor and assess the conservation status of cultural heritage sites in the context of sustainable development. An in-depth discussion on the limitations of ASRS and associated remaining challenges is presented along with conclusions and a look at future trends.

A strategy for European Aerosol Research Lidar Network (EARLINET) correlative measurements for Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) has been developed. These EARLINET correlative measurements started in June 2006 and are still in progress. Up to now, more than 4500 correlative files are available in the EARLINET database. Independent extinction and backscatter measurements carried out at high‐performance EARLINET stations have been used for a quantitative comparison with CALIPSO level 1 data. Results demonstrate the good performance of CALIPSO and the absence of evident biases in the CALIPSO raw signals. The agreement is also good for the distribution of the differences for the attenuated backscatter at 532 nm ((CALIPSO‐EARLINET)/EARLINET (%)), calculated in the 1–10 km altitude range, with a mean relative difference of 4.6%, a standard deviation of 50%, and a median value of 0.6%. A major Saharan dust outbreak lasting from 26 to 31 May 2008 has been used as a case study for showing first results in terms of comparison with CALIPSO level 2 data. A statistical analysis of dust properties, in terms of intensive optical properties (lidar ratios, Ångström exponents, and color ratios), has been performed for this observational period. We obtained typical lidar ratios of the dust event of 49 ± 10 sr and 56 ± 7 sr at 355 and 532 nm, respectively. The extinction‐related and backscatter‐related Ångström exponents were on the order of 0.15–0.17, which corresponds to respective color ratios of 0.91–0.95. This dust event has been used to show the methodology used for the investigation of spatial and temporal representativeness of measurements with polar‐orbiting satellites.

A multiyear climatological study of Saharan dust intrusions in the central Mediterranean in terms of aerosol optical parameters vertical profiles is carried out for the first time. Observations are performed at Istituto di Metodologie per l'Analisi Ambientale (IMAA) Raman/elastic lidar station located in Tito Scalo, Potenza (40°36′N, 15°44′E), from May 2000 to April 2003, in the framework of European Aerosol Research Lidar Network (EARLINET). Desert dust aerosols are observed between 1.8 and 9 km in 112 days. Mean values within the desert dust layer of 76 Mm −1 , 1.0 Mm −1 sr −1 and 0.54 Mm −1 sr −1 are observed for aerosol extinction at 355 nm and aerosol backscatter at 355 and 532 nm. Desert dust layer optical depth at 355 nm ranges between 0.001 and 0.68, with a mean of 0.13. The source origin is the central Sahara in about 65% of the cases, the western Sahara in about 31%, and only in four cases the eastern Sahara. The most extended database of Saharan dust lidar ratio data was collected: Values range between 6 and 126 sr following a 3‐modal Gaussian distribution centered at 22, 37 and 57 sr. A mean value of 37 sr is found around the center of the Saharan dust layer. At its extremes, where dust particles are mixed to PBL and free troposphere background aerosols, a mean value of 57 sr is found. Finally, low lidar ratio values of about 22 sr are observed when large amount of dust is transported at low altitudes over the Mediterranean Sea.

An intercomparison of the algorithms used to retrieve aerosol extinction and backscatter starting from Raman lidar signals has been performed by 11 groups of lidar scientists involved in the European Aerosol Research Lidar Network (EARLINET). This intercomparison is part of an extended quality assurance program performed on aerosol lidars in the EARLINET. Lidar instruments and aerosol backscatter algorithms were tested separately. The Raman lidar algorithms were tested by use of synthetic lidar data, simulated at 355, 532, 386, and 607 nm, with realistic experimental and atmospheric conditions taken into account. The intercomparison demonstrates that the data-handling procedures used by all the lidar groups provide satisfactory results. Extinction profiles show mean deviations from the correct solution within 10% in the planetary boundary layer (PBL), and backscatter profiles, retrieved by use of algorithms based on the combined Raman elastic-backscatter lidar technique, show mean deviations from solutions within 20% up to 2 km. The intercomparison was also carried out for the lidar ratio and produced profiles that show a mean deviation from the solution within 20% in the PBL. The mean value of this parameter was also calculated within a lofted aerosol layer at higher altitudes that is representative of typical layers related to special events such as Saharan dust outbreaks, forest fires, and volcanic eruptions. Here deviations were within 15%.

Leaf area index (LAI) is a crucial biophysical variable for agroecosystems monitoring. Conventional vegetation indices (VIs) based on red and near infrared regions of the electromagnetic spectrum, such as the normalized difference vegetation index (NDVI), are commonly used to estimate the LAI. However, these indices commonly saturate at moderate-to-dense canopies (e.g., NDVI saturates when LAI exceeds three). Modified VIs have then been proposed to replace the typical red/green spectral region with the red-edge spectral region. One significant and often ignored aspect of this modification is that the reflectance in the red-edge spectral region is comparatively sensitive to chlorophyll content which is highly variable between different crops and different phenological states. In this study, three improved indices are proposed combining reflectance both in the red and red-edge spectral regions into the NDVI, the modified simple ratio index (MSR), and the green chlorophyll index (CI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">green</sub> ) formula. These improved indices are termed NDVI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> (red and red-edge NDVI), MS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Rred&amp; RE</sub> (red and red-edge MSR index), and CI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> (red and red-edge CI). The indices were tested using RapidEye images and in-situ data from campaigns at Maccarese Farm (Central Rome, Italy), in which four crop types at four different growth stages were measured. We investigated the predictive power of nine VIs for crop LAI estimation, including NDVI, MSR, and CIgreen; the red-edge modified indices: NDVI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Red-edge</sub> , MSR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Red-edge</sub> , and CI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Red-edge</sub> (generally represented by VIRed-edge); and the newly improved indices: NDVI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> , MSR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> , and CI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> (generally represented by VI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> ). The results show that VI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">red&amp; RE</sub> improves the coefficient of determination (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for LAI estimation by 10% in comparison to VI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Red-edge</sub> . The newly improved indices prove to be the powerful alternatives for the LAI estimation of crops with wide chlorophyll range, and may provide valuable information for satellites equipped with red-edge channels (such as Sentinel-2) when applied to precision agriculture.

Multiwavelength lidar, Sun photometer, and radiosonde observations were conducted at Ouarzazate (30.9°N, 6.9°W, 1133 m above sea level, asl), Morocco, in the framework of the Saharan Mineral Dust Experiment (SAMUM) in May–June 2006. The field site is close to the Saharan desert. Information on the depolarization ratio, backscatter and extinction coefficients, and lidar ratio of the dust particles, estimates of the available concentration of atmospheric ice nuclei at cloud level, profiles of temperature, humidity, and the horizontal wind vector as well as backward trajectory analysis are used to study cases of cloud formation in the dust with focus on heterogeneous ice formation. Surprisingly, most of the altocumulus clouds that form at the top of the Saharan dust layer, which reaches into heights of 4–7 km asl and has layer top temperatures of −8°C to −18°C, do not show any ice formation. According to the lidar observations the presence of a high number of ice nuclei (1–20 cm −3 ) does not automatically result in the obvious generation of ice particles, but the observations indicate that cloud top temperatures must typically reach values as low as −20°C before significant ice production starts. Another main finding is that liquid clouds are obviously required before ice crystals form via heterogeneous freezing mechanisms, and, as a consequence, that deposition freezing is not an important ice nucleation process. An interesting case with cloud seeding in the free troposphere above the dust layer is presented in addition. Small water clouds formed at about −30°C and produced ice virga. These virga reached water cloud layers several kilometers below the initiating cloud cells and caused strong ice production in these clouds at temperatures as high as −12°C to −15°C.

Abstract Within the framework of the international field campaign COPS (Convective and Orographically‐induced Precipitation Study), a large suite of state‐of‐the‐art meteorological instrumentation was operated, partially combined for the first time. This includes networks of in situ and remote‐sensing systems such as the Global Positioning System as well as a synergy of multi‐wavelength passive and active remote‐sensing instruments such as advanced radar and lidar systems. The COPS field phase was performed from 01 June to 31 August 2007 in a low‐mountain area in southwestern Germany/eastern France covering the Vosges mountains, the Rhine valley and the Black Forest mountains. The collected data set covers the entire evolution of convective precipitation events in complex terrain from their initiation, to their development and mature phase until their decay. Eighteen Intensive Observation Periods with 37 operation days and eight additional Special Observation Periods were performed, providing a comprehensive data set covering different forcing conditions. In this article, an overview of the COPS scientific strategy, the field phase, and its first accomplishments is given. Highlights of the campaign are illustrated with several measurement examples. It is demonstrated that COPS research provides new insight into key processes leading to convection initiation and to the modification of precipitation by orography, in the improvement of quantitative precipitation forecasting by the assimilation of new observations, and in the performance of ensembles of convection‐permitting models in complex terrain. Copyright © 2010 Royal Meteorological Society

An intercomparison of aerosol backscatter lidar algorithms was performed in 2001 within the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET). The objective of this research was to test the correctness of the algorithms and the influence of the lidar ratio used by the various lidar teams involved in the EARLINET for calculation of backscatter-coefficient profiles from the lidar signals. The exercise consisted of processing synthetic lidar signals of various degrees of difficulty. One of these profiles contained height-dependent lidar ratios to test the vertical influence of those profiles on the various retrieval algorithms. Furthermore, a realistic incomplete overlap of laser beam and receiver field of view was introduced to remind the teams to take great care in the nearest range to the lidar. The intercomparison was performed in three stages with increasing knowledge on the input parameters. First, only the lidar signals were distributed; this is the most realistic stage. Afterward the lidar ratio profiles and the reference values at calibration height were provided. The unknown height-dependent lidar ratio had the largest influence on the retrieval, whereas the unknown reference value was of minor importance. These results show the necessity of making additional independent measurements, which can provide us with a suitable approximation of the lidar ratio. The final stage proves in general, that the data evaluation schemes of the different groups of lidar systems work well.

Hyperspectral images (HSIs) are of crucial importance in order to better understand features from a large number of spectral channels. Restricted by its inner imaging mechanism, the spatial resolution is often limited for HSIs. To alleviate this issue, in this work, we propose a simple and efficient architecture of deep convolutional neural networks to fuse a low-resolution HSI (LR-HSI) and a high-resolution multispectral image (HR-MSI), yielding a high-resolution HSI (HR-HSI). The network is designed to preserve both spatial and spectral information thanks to a new architecture based on: 1) the use of the LR-HSI at the HR-MSI's scale to get an output with satisfied spectral preservation and 2) the application of the attention and pixelShuffle modules to extract information, aiming to output high-quality spatial details. Finally, a plain mean squared error loss function is used to measure the performance during the training. Extensive experiments demonstrate that the proposed network architecture achieves the best performance (both qualitatively and quantitatively) compared with recent state-of-the-art HSI super-resolution approaches. Moreover, other significant advantages can be pointed out by the use of the proposed approach, such as a better network generalization ability, a limited computational burden, and the robustness with respect to the number of training samples. Please find the source code and pretrained models from https://liangjiandeng.github.io/Projects_Res/HSRnet_2021tnnls.html.

Machine learning (ML) is influencing the literature in several research fields, often through state-of-the-art approaches. In the past several years, ML has been explored for pansharpening, i.e., an image fusion technique based on the combination of a multispectral (MS) image, which is characterized by its medium/low spatial resolution, and higher-spatial-resolution panchromatic (PAN) data. Thus, ML for pansharpening represents an emerging research line that deserves further investigation. In this article, we go through some powerful and widely used ML-based approaches for pansharpening that have been recently proposed in the related literature. Eight approaches are extensively compared. Implementations of these eight methods, exploiting a common software platform and ML library, are developed for comparison purposes. The ML framework for pansharpening will be freely distributed to the scientific community. Experimental results using data acquired by five commonly used sensors for pansharpening and well-established protocols for performance assessment (both at reduced resolution and at full resolution) are shown. The ML-based approaches are compared with a benchmark consisting of classical and variational optimization (VO)-based methods. The pros and cons of each pansharpening technique, based on the training-by-examples philosophy, are reported together with a broad computational analysis. The toolbox is provided in <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/liangjiandeng/DLPan-Toolbox</uri> .

Abstract. With the establishment of ceilometer networks by national weather services, a discussion commenced to which extent these simple backscatter lidars can be used for aerosol research. Though primarily designed for the detection of clouds it was shown that at least observations of the vertical structure of the boundary layer might be possible. However, an assessment of the potential of ceilometers for the quantitative retrieval of aerosol properties is still missing. In this paper we discuss different retrieval methods to derive the aerosol backscatter coefficient βp, with special focus on the calibration of the ceilometers. Different options based on forward and backward integration methods are compared with respect to their accuracy and applicability. It is shown that advanced lidar systems such as those being operated in the framework of the European Aerosol Research Lidar Network (EARLINET) are excellent tools for the calibration, and thus βp retrievals based on forward integration can readily be implemented and used for real-time applications. Furthermore, we discuss uncertainties introduced by incomplete overlap, the unknown lidar ratio, and water vapor absorption. The latter is relevant for the very large number of ceilometers operating in the spectral range around λ = 905–910 nm. The accuracy of the retrieved βp mainly depends on the accuracy of the calibration and the long-term stability of the ceilometer. Under favorable conditions, a relative error of βp on the order of 10% seems feasible. In the case of water vapor absorption, corrections assuming a realistic water vapor distribution and laser spectrum are indispensable; otherwise errors on the order of 20% could occur. From case studies it is shown that ceilometers can be used for the reliable detection of elevated aerosol layers below 5 km, and can contribute to the validation of chemistry transport models, e.g., the height of the boundary layer. However, the exploitation of ceilometer measurements is still in its infancy, so more studies are urgently needed to consolidate the present state of knowledge, which is based on a limited number of case studies.

Abstract. In this study we use a new dust product developed using CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations and EARLINET (European Aerosol Research Lidar Network) measurements and methods to provide a 3-D multiyear analysis on the evolution of Saharan dust over North Africa and Europe. The product uses a CALIPSO L2 backscatter product corrected with a depolarization-based method to separate pure dust in external aerosol mixtures and a Saharan dust lidar ratio (LR) based on long-term EARLINET measurements to calculate the dust extinction profiles. The methodology is applied on a 9-year CALIPSO dataset (2007–2015) and the results are analyzed here to reveal for the first time the 3-D dust evolution and the seasonal patterns of dust over its transportation paths from the Sahara towards the Mediterranean and Continental Europe. During spring, the spatial distribution of dust shows a uniform pattern over the Sahara desert. The dust transport over the Mediterranean Sea results in mean dust optical depth (DOD) values up to 0.1. During summer, the dust activity is mostly shifted to the western part of the desert where mean DOD near the source is up to 0.6. Elevated dust plumes with mean extinction values between 10 and 75 Mm−1 are observed throughout the year at various heights between 2 and 6 km, extending up to latitudes of 40° N. Dust advection is identified even at latitudes of about 60° N, but this is due to rare events of episodic nature. Dust plumes of high DOD are also observed above the Balkans during the winter period and above northwest Europe during autumn at heights between 2 and 4 km, reaching mean extinction values up to 50 Mm−1. The dataset is considered unique with respect to its potential applications, including the evaluation of dust transport models and the estimation of cloud condensation nuclei (CCN) and ice nuclei (IN) concentration profiles. Finally, the product can be used to study dust dynamics during transportation, since it is capable of revealing even fine dynamical features such as the particle uplifting and deposition on European mountainous ridges such as the Alps and Carpathian Mountains.