LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

Amiridis, Vassilis; Marinou, Eleni; Tsekeri, Alexandra; Wandinger, Ulla; Schwarz, Anja; Giannakaki, Elina; Mamouri, Rodanthi-Elisavet; Kokkalis, Panagiotis; Binietoglou, Ioannis; Solomos, Stavros; Herekakis, Themistocles; Kazadzis, Stelios; Gerasopoulos, E.; Proestakis, Emmanouil; Kottas, Michael; Balis, D.; Papayannis, A.; Kontoes, Charalampos; Kourtidis, Konstantinos; Papagiannopoulos, Nikolaos; Mona, Lucia; Pappalardo, Gelsomina; Rille, Olivier Le; Ansmann, Albert

doi:10.5194/acp-15-7127-2015

Cited by 124 publications

(136 citation statements)

References 59 publications

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“…Tian et al (2017) obtained similar results from comparison with lidar measurements in SACOL (China). A comparison of the CALIOP AOD climatological product against spatially and temporally co-located AERONET observations is discussed in Amiridis et al (2015). In their Fig.…”

Section: Caliopmentioning

confidence: 99%

“…In this paper, the ESA-LIVAS ("LIdar climatology of Vertical Aerosol Structure for spacebased lidar simulation studies" project) database is used. LI-VAS is developed based on CALIPSO v3 L2 Aerosol and Cloud Profile products towards a global multi-wavelength (355, 532, 1064, 1570 and 2050 nm) aerosol and cloud optical database on a uniform 1 • × 1 • grid resolution (Amiridis et al, 2015). Here, the CALIPSO-based ESA-LIVAS product (via http://lidar.space.noa.gr:8080/livas/) is used to provide the three-dimensional climatology of the aerosol distribution over China for the period January 2007-December 2015.…”

Section: Caliopmentioning

confidence: 99%

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Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

et al. 2018

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Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the columnintegrated extinction (aerosol optical depth -AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995-2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed.The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a compariPublished by Copernicus Publications on behalf of the European Geosciences Union.

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Section: Caliopmentioning

confidence: 99%

Section: Caliopmentioning

confidence: 99%

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

et al. 2018

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“…LIVAS addresses the wavelength dependency of aerosol properties for many laser operating wavelengths including 532 nm. The LIVAS data set has been evaluated against AERONET in Amiridis et al (2015), showing realistic and representative mean state aerosol optical depth values in 532 nm and making this data set ideal for synergistic use with other satellite products.…”

Section: Livas Climatology Databasementioning

confidence: 99%

“…LIVAS is a 3-D multi-wavelength global aerosol and cloud optical database (Amiridis et al, 2015). This database provides averaged profiles of aerosol optical properties over 9 years (1 January 2007-31 December 2015 from the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data on a uniform grid of 1 • × 1 • .…”

Section: Livas Climatology Databasementioning

confidence: 99%

An exploratory study on the aerosol height retrieval from OMI measurements of the 477  nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach

et al. 2017

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Abstract. This paper presents an exploratory study on the aerosol layer height (ALH) retrieval from the OMI 477 nm O 2 −O 2 spectral band. We have developed algorithms based on the multilayer perceptron (MLP) neural network (NN) approach and applied them to 3-year (2005-2007) OMI cloudfree scenes over north-east Asia, collocated with MODIS Aqua aerosol product. In addition to the importance of aerosol altitude for climate and air quality objectives, our long-term motivation is to evaluate the possibility of retrieving ALH for potential future improvements of trace gas retrievals (e.g. NO 2 , HCHO, SO 2 ) from UV-visible air quality satellite measurements over scenes including high aerosol concentrations. This study presents a first step of this longterm objective and evaluates, from a statistic point of view, an ensemble of OMI ALH retrievals over a long time period of 3 years covering a large industrialized continental region. This ALH retrieval relies on the analysis of the O 2 −O 2 slant column density (SCD) and requires an accurate knowledge of the aerosol optical thickness, τ . Using MODIS Aqua τ (550 nm) as a prior information, absolute seasonal differences between the LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS) and average OMI ALH, over scenes with MODIS τ (550 nm) ≥ 1.0, are in the range of 260-800 m (assuming single scattering albedo ω 0 = 0.95) and 180-310 m (assuming ω 0 = 0.9).OMI ALH retrievals depend on the assumed aerosol single scattering albedo (sensitivity up to 660 m) and the chosen surface albedo (variation less than 200 m between OMLER and MODIS black-sky albedo). Scenes with τ ≤ 0.5 are expected to show too large biases due to the little impact of particles on the O 2 −O 2 SCD changes. In addition, NN algorithms also enable aerosol optical thickness retrieval by exploring the OMI reflectance in the continuum. Comparisons with collocated MODIS Aqua show agreements between −0.02 ± 0.45 and −0.18 ± 0.24, depending on the season. Improvements may be obtained from a better knowledge of the surface albedo and higher accuracy of the aerosol model. Following the previous work over ocean of Park et al. (2016), our study shows the first encouraging aerosol layer height retrieval results over land from satellite observations of the 477 nm O 2 −O 2 absorption spectral band.

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“…The a priori vertical profile of desert dust concentration is obtained from the LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies (LIVAS) monthly 1 • × 1 • climatology derived from CALIOP data (Amiridis et al, 2015). The conversion from 532 nm extinction to particle number concentration is done using the cross section of the aerosol particles used in MAPIR.…”

Section: Passive Instrument Dust Height Retrievalsmentioning

confidence: 99%

Comparison of dust-layer heights from active and passive satellite sensors

et al. 2018

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Abstract. Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosollayer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosollayer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOPderived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5-0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

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LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

Cited by 124 publications

References 59 publications

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

An exploratory study on the aerosol height retrieval from OMI measurements of the 477  nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach

Comparison of dust-layer heights from active and passive satellite sensors

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LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET

Cited by 124 publications

References 59 publications

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O&lt;sub&gt;2&lt;/sub&gt; − O&lt;sub&gt;2&lt;/sub&gt; spectral band using a neural network approach

Comparison of dust-layer heights from active and passive satellite sensors

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An exploratory study on the aerosol height retrieval from OMI measurements of the 477  nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach