Search

The results of the ATHLI16 (ATHens Lidar Intercomparison) campaign, held in Athens from 26/09 to 07/10 2016 are presented. The campaign was performed within the Lidar Calibration Centre activities (EU H2020 ACTRIS-2 project) to assess the performance of the EOLE lidar system (NTUA, Athens, Greece), operating within EARLINET, by comparing against the EARLINET reference lidar system MUSA (CNR-IMAA, Potenza, Italy). For both lidars only products retrieved by the EARLINET Single Calculus Chain have been compared.

A comprehensive analysis of the seasonal variability of the optical properties of Saharan dust aerosols over Athens, Greece, is presented for a 17-year time period (2000-2016), as derived from multi-wavelength Raman lidar measurements (57 dust events with more than 80 hours of measurements). The profiles of the derived aerosol optical properties (aerosol backscatter and extinction coefficients, lidar ratio and aerosol Ångström exponent) at 355 nm are presented. For these dust events we found a mean value of the lidar ratio of ~52±13 sr at 355 nm and of ~58±8 sr (not shown) at 532 nm (2-4 km a.s.l. height). For our statistical analysis, presented here, we used monthly-mean values and time periods under cloud-free conditions. The number of dust events was greatest in late spring, summer, and early autumn periods. In this paper we also present a selected case study (04 April 2016) of desert dust long-range transport from the Saharan desert.

In this paper we studied the temporal evolution of the Planetary Boundary Layer height (PBLH) over the basin of Athens, Greece during a 5-year period (2011-2016) using data from the EOLE Raman lidar system. The lidar data (range-corrected lidar signals-RCS) were selected around 12:00 UTC and 00:00 UTC for a total of 332 cases: 165 days and 167 nights. Extended Kalman filtering techniques were used for the determination of the PBLH. Moreover, several well established techniques for the PBLH estimation based on lidar data were also tested for a total of 35 cases. Comparisons with the PBLH values derived from radiosonde data were also performed. The mean PBLH over Athens was found to be of the order of 1617±324 m at 12:00 UTC and of 892±130 m at 00:00 UTC, for the period examined. The mean PBLH growth rate was found to be about 170±64 m h-1 and 90±17 m h-1, during daytime and nighttime, respectively.

The EOLE multi-wavelength aerosol Ramandepolarization lidar, and the AIAS depolarization lidar, in synergy with a sun photometer (CIMEL), were used, in the period 2007-2016, to provide the vertical profiles of the aerosol optical properties over Athens, Greece. More than 30 biomass burning events (fresh and aged smoke particles) were observed, with smoke layers between 1.5 up to 4-5 km height, while their duration ranged from 1-3 days. Lidar ratio (LR) values ranged from 40-105 sr (at 355 nm) and from 40-100 sr (at 532 nm), while the linear particle depolarization ratio (LPDR) at both 355 and 532 nm, remained

Multi-wavelength aerosol Raman lidar measurements with elastic depolarization at 532 nm were combined with sun photometry during the HYGRA-CD campaign over Athens, Greece, on May-June 2014. We retrieved the aerosol optical [3 aerosol backscatter profiles (baer) at 355-532-1064 nm, 2 aerosol extinction (aaer) profiles at 355-532 nm and the aerosol linear depolarization ratio (δ) at 532 nm] and microphysical properties [effective radius (reff), complex refractive index (m), single scattering albedo (ω)]. We present a case study of a long distance transport (~3.500-4.000 km) of biomass burning particles mixed with dust from the Russian Federation-Kazakhstan regions arriving over Athens on 21-23 May 2014 (1.7-3.5 km height). On 23 May, between 2-2.75 km we measured mean lidar ratios (LR) of 35 sr (355 nm) and 42 sr (532 nm), while the mean Ångström exponent (AE) aerosol backscatter-related values (355nm/532nm and 532nm/1064nm) were 2.05 and 1.22, respectively; the mean value of δ at 532 nm was measured to be 9%. For that day the retrieved mean aerosol microphysical properties at 2-2.75 km height were: reff=0.26 μm (fine mode), reff=2.15 μm (coarse mode), m=1.36+0.00024i, ω=0.999 (355 nm, fine mode), ω=0.992(355 nm, coarse mode), ω=0.997 (532 nm, fine mode), and ω=0.980 (532 nm, coarse mode).

Measurements of cloud condensation nuclei (CCN) concentrations between 0.2-1.0% supersaturation and aerosol size distribution were performed at an urban background site of Athens during HygrA-CD. The site is affected by local and long-range transported emissions as portrayed by the external mixing of the particles, as the larger ones appear to be more hygroscopic and more CCN-active than smaller ones. Activation fractions at all supersaturations exhibit a diurnal variability with minimum values around noon, which are considerably lower than unity. This reinforces the conclusion that the aerosol is mostly externally mixed between “fresher”, less hygroscopic components with more aged, CCN active constituents.

Combined multi-wavelength aerosol Raman lidar and sun photometry measurements were performed during the HYGRA-CD campaign over Athens, Greece during May-June 2014. The retrieved aerosol optical properties (3 aerosol backscatter at 355-532-1064 nm and 2 aerosol extinction profiles at 355-532 nm) were used as input to an inversion code to retrieve the aerosol microphysical properties (effective radius reff and number concentration N) using regularization techniques. Additionally, the volume concentration profile was derived for fine particles using the LIRIC code. In this paper we selected a complex case study of long-range transport of mixed aerosols (biomass burning particles mixed with dust) arriving over Athens between 10-12 June 2014 in the 1.5-4 km height. Between 2-3 km height we measured mean lidar ratios (LR) ranging from 45 to 58 sr (at 355 and 532 nm), while the Ångström exponent (AE) aerosol extinction-related values (355nm/532nm) ranged between 0.8-1.3. The retrieved values of reff and N ranged from 0.19±0.07 to 0.22±0.07 μm and 460±230 to 2200±2800 cm-3, respectively. The aerosol linear depolarization ratio (δ) at 532 nm was lower than 5-7% (except for the Saharan dust cases, where δ~10-15%).

The retrieval of cloud parameters from the atmospheric Sentinel missions requires Earth reflectance measurements from a set of spectral bands. The ground pixels of the involved spectral bands should be fully aligned, but when they are not, special treatment is required within the operational algorithms. This so-called inter-band spatial misregistration of passive spectrometers is present when the Earth reflectance measurements in different spectral bands are captured by different spectrometers. The cloud retrieval algorithm requires reflectance measurements in the UV(ultraviolet)–VIS (visible) band, where the first cloud parameter (i.e., radiometric cloud fraction) is retrieved from OCRA (Optical Cloud Recognition Algorithm). In addition, Earth reflectances in the NIR (near-infrared) band are needed for the retrieval of two additional cloud parameters (i.e., cloud height and cloud albedo or cloud-top height and optical thickness) from the ROCINN (Retrieval of Cloud Information using Neural Networks) algorithm. In the former TROPOMI (TROPOspheric Monitoring Instrument)/S5P (Sentinel-5 Precursor) retrieval, a coregistration scheme of the derived cloud parameters from the source band to the target band based on pre-calculated mapping weights from UV–VIS to NIR and vice versa is applied. In this paper we present a new scheme for the coregistration of the TROPOMI cloud parameters using collocated VIIRS (Visible Infrared Imaging Radiometer Suite)/SNPP (Suomi National Polar-orbiting Partnership) information. The new coregistration scheme based on the VIIRS data improves the TROPOMI cloud product quality and allows the addition of cloud information for the first (westernmost) TROPOMI UVIS ground pixel. In practice, the latter means that a significant number of valid data points are included in the TROPOMI cloud, total ozone, SO2 and HCHO product since 26 November 2023 (orbit 31705), when the new coregistration scheme became operational. From a comparison analysis between the two techniques, we found that the largest differences mainly appear for inhomogeneous scenes. From a validation exercise of TROPOMI against VIIRS in the across-track direction, we found that the old coregistration scheme tends to smooth out cloud structures along the scan line, whereas such structures can be maintained with the new scheme. The need to implement a similar inter-band spatial coregistration scheme is foreseen for the Sentinel-4/MTG-S (Meteosat Third Generation – Sounder) and Sentinel-5/MetOp-SG (Meteorological Operational Satellite – Second Generation) missions. In the case of the Sentinel-4 instrument, the external cloud information will originate from collocated data captured by the FCI (Flexible Combined Imager) on board the MTG-I (Meteosat Third Generation – Imager) satellite. [ABSTRACT FROM AUTHOR]

The retrieval of cloud parameters from the atmospheric Sentinel missions require Earth reflectance measurements from a set of spectral bands. Frequently, the ground pixel footprints of the involved spectral bands are not fully aligned and therefore, special treatment is required within the operational algorithms. This so-called inter-band spatial mis-registration of passive spectrometers is present when the Earth reflectance measurements in different spectral bands are captured by different spectrometers. The cloud retrieval algorithm requires reflectance measurements in the UV (ultraviolet)/VIS (visible) band, where the first cloud parameter (i.e., radiometric cloud fraction) is retrieved from the OCRA (Optical Cloud Recognition Algorithm) algorithm. In addition, Earth reflectances in the NIR (near-infrared) band are needed for the retrieval of two additional cloud parameters (i.e., cloud height and cloud albedo or cloud-top height and optical thickness) from the ROCINN (Retrieval of Cloud Information using Neural Networks) algorithm. In the former TROPOMI (TROPOspheric Monitoring Instrument)/S5P (Sentinel-5 Precursor) retrieval, a co-registration scheme of the derived cloud parameters from the source band to the target band based on pre-calculated mapping weights from UV/VIS to NIR, and vice versa, is applied. In this paper we present a new scheme for the co-registration of the TROPOMI cloud parameters using collocated VIIRS (Visible Infrared Imaging Radiometer Suite)/SNPP (Suomi National Polar-orbiting Partnership) information. A great benefit of the new co-registration scheme based on the VIIRS data is that it improves the overall quality of the TROPOMI cloud products and, in addition, it allows the re-construction of the cloud parameters on the first UV/VIS detector pixel, which was impossible with the former scheme based on the static mapping tables. The latter practically means that a significant number of valid data points are added to the TROPOMI cloud, total ozone, SO2 and HCHO product since November 26th 2023 (orbit 31705), when the UPAS version 2.6 with the new co-registration scheme was activated operationally. From a comparison analysis between the two techniques, we found that the largest differences mainly appear for inhomogeneous scenes. From a validation exercise of TROPOMI against VIIRS in the across-track flight direction, we found that the old co-registration scheme tends to smooth out cloud structures along the scanline, whereas such structures can be maintained with the new scheme. The need to implement a similar inter-band spatial co-registration scheme is foreseen for the Sentinel-4/MTG-S (Meteosat Third Generation - Sounder) and Sentinel-5/MetOp-SG (Meteorological Operational Satellite - Second Generation) missions. In the case of Sentinel-4 instrument, the external cloud information will originate from collocated FCI (Flexible Combined Imager) data, on board the MTG-I (Meteosat Third Generation - Imager) satellite. [ABSTRACT FROM AUTHOR]

Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2 × 1014 molec/cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5 × 1014 molec/cm2 for polluted conditions. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes are captured. For AMF calculation, the climatological surface albedo data is replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a clouds-as-layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the clouds-as-reflecting-boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30-60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the improved tropospheric NO2 data shows good correlations for nine European urban/suburban stations with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average. [ABSTRACT FROM AUTHOR]

Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data derived from Copernicus Sentinel-5 Precursor (S5P) TROPOMI radiance measurements: cloud top height and cloud optical thickness (retrieved with the S5P OCRA/ROCINN_CAL algorithm), cloud height (S5P OCRA/ROCINN_CRB and S5P FRESCO) and radiometric cloud fraction (all three algorithms). The analysis combines: (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS and OMI O2-O2), and (iii) ground-based validation with respect to correlative observations (2018-04-30 to 2020-02-27) from the CLOUDNET network of ceilometers, lidars and radars. Peculiar geographical patterns were identified, and will be mitigated in future releases of the cloud data products. Zonal mean latitudinal variation of S5P cloud properties are similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud top height and cloud optical thickness, and with CLOUDNET cloud top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud top height is below the cloud top height of VIIRS and of CLOUDNET, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the CLOUDNET cloud mean height for the low clouds, but match on an average better with the CLOUDNET cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the CLOUDNET observations. [ABSTRACT FROM AUTHOR]

An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle-dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parametrization over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS(CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a Cloud-As-Layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current Clouds-as-Reflecting-Boundaries (CRB) model, which assumes the clouds as Lambertian reflectors. Improvements in the AMF calculation affect the tropospheric NO2 columns on average within ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and aerosol-induced cloud parameters (implicit aerosol correction). Compared to the implicit aerosol correction through the CRB cloud parameters, the use of CAL reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAXDOAS) measurements at the BIRA-IASB Xianghe station. The improved tropospheric NO2 dataset shows good agreement with coincident ground-based measurements with a correlation coefficient of 0.94 and a relative difference of −9.9 % on average. [ABSTRACT FROM AUTHOR]

The operational TROPOMI/Sentinel-5 Precursor cloud parameters are retrieved using OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) algorithms that have been successfully applied to the prior operational processing of GOME/ERS-2 and GOME-2 MetOp-A/B data. The ROCINN algorithm retrieves cloud height, cloud optical thickness and cloud albedo from NIR measurements in and around the oxygen A-band (~760nm) taking as a-priori the radiometric cloud fraction (Loyola et al., 2018). The latter is computed by the OCRA algorithm which is based on a broad-band UV/VIS color space approach (Lutz et al., 2016). Two models which treat the clouds differently are implemented in the ROCINN algorithm. The first approach called Clouds-as-Reflecting-Boundaries (CRB) assumes that the cloud is a reflecting surface whereas the second and more realistic model called Clouds-as-Layers (CAL) represents the cloud as a homogeneous cluster of scattering spherical particles. The loose formation of the Suomi-NPP satellite with Sentinel-5 Precursor (S5P) enables the direct comparison of the TROPOMI cloud properties against VIIRS cloud products. The ROCINN cloud parameters (i.e., cloud top height and optical thickness) from S5P are compared against the VIIRS cloud product developed by NASA. The VIIRS products are re-gridded to the footprints of TROPOMI. The initial results showed high correlation with a negative bias for the cloud top height and a positive bias for the cloud optical thickness. The bias in the cloud optical thickness is significantly smaller for the continental clouds and the bias in the cloud top height is smaller for the marine clouds. Some discrepancies have been observed for the convective clouds associated with a high top above 6 km and large optical thickness over 23, following the cloud classification from the international satellite cloud climatology project (ISCCP). Other discrepancies have been also identified on ice phase clouds like cirrus/cirrostratus. The improvement of the retrieved cloud top height in deep convective and ice clouds is a challenge for the coming Copernicus mission Sentinel-4 which is planned to be launched in 2023. The latter involves a better parameterization of ice crystal. [ABSTRACT FROM AUTHOR]

The Copernicus mission Sentinel-5 Precursor is focused on trace gas, aerosol and cloud retrieval and operates in the UV/VIS/NIR/SWIR spectral region.In this work we present the algorithms for retrieving the operational cloud products from TROPOMI onboard Sentinel-5 Precursor. The cloud retrieval algorithms OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) have their heritage with GOME/ERS-2 and GOME-2 MetOp-A/B, where they have already been successfully implemented in an operational environment.OCRA employs a broad band color space approach and, in combination with a set of cloud-free reflectance background composite maps, determines a radiometric cloud fraction by making use of the assumption that clouds usually have a higher reflectance than the surrounding surface and that the cloud reflectance is almost wavelength independent across the UV/VIS/NIR wavelength region. The ROCINN algorithm retrieves cloud top height, cloud optical thickness and cloud albedo from NIR measurements in and around the oxygen A-band, taking as a priori input the cloud fraction computed by OCRA.The cloud parameters retrieved by ROCINN are provided for two different cloud models. One which treats clouds more realistically as layers of scattering water droplets (clouds-as-layers, CAL) and one which treats clouds as simple Lambertian reflectors (clouds-as-reflecting boundaries, CRB).The current implementation status and setup of the algorithms is presented along with monthly statistics for the cloud parameters, individual application examples as well as satellite-to-satellite comparisons with VIIRS on Suomi-NPP. [ABSTRACT FROM AUTHOR]