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- ItemIncreasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: Evaluation of candidate approaches with MODIS observations(Katlenburg-Lindau : Copernicus, 2020) Werner, Frank; Deneke, HartwigThis study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native ≈ 3km×3km spatial resolution of the narrowband channels to ≈ 1km×1km. These methods make use of SEVIRI's coincident broadband high-resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1km×1km MODIS radiances, which are reprojected to the horizontal grid of the HRV channel and serve as reference for the evaluation. By using these radiances, smoothed with the modulation transfer function of the native SEVIRI channels, as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈ 14 and ≈ 6μm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈ 89gm-2 and ≈ 177cm-3, respectively. For τ , these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint and by applying most of the presented downscaling schemes. Uncertainties in retrieved reff at the native SEVIRI resolution are smaller, and the improvements from downscaling the observations are less obvious than for τ. Nonetheless, the right choice of downscaling scheme yields noticeable improvements in the retrieved reff. Furthermore, the improved reliability in retrieved cloud products results in significantly reduced uncertainties in derived WL and ND. In particular, one downscaling approach provides clear improvements for all cloud products compared to those obtained from SEVIRI's standard resolution and is recommended for future downscaling endeavors. This work advances efforts to mitigate impacts of scale mismatches among channels of multiresolution instruments on cloud retrievals. © Author(s) 2020.
- Item3+2 + X : what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?(Katlenburg-Lindau : Copernicus, 2019) Tesche, Matthias; Kolgotin, Alexei; Haarig, Moritz; Burton, Sharon P.; Ferrare, Richard A.; Hostetler, Chris A.; Müller, DetlefThe typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β C 2α or 3 + 2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of d that exceed 0.10 at 532 nm, i.e. in the presence of nonspherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring d at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of d taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of d will give lower values of the single-scattering albedo than the traditional 3 + 2 data set. We find that input data sets that include d355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and d532 in a methodology applied in aerosol-type separation. The use of d355 in data sets of two or three d? reduces the spheroid fraction that is retrieved when using d532 and d1064. Use of the latter two parameters without accounting for d355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three d instead of two δ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3 + 2 + d355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of d355 that are indistinguishable from those found for mineral dust. We therefore conclude that - depending on measurement capability - the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2Cδ355 or 3 + 2 + δ355 + δ532. © 2019 The Author(s).
- ItemGARRLiC and LIRIC: Strengths and limitations for the characterization of dust and marine particles along with their mixtures(Katlenburg-Lindau : Copernicus, 2017) Tsekeri, Alexandra; Lopatin, Anton; Amiridis, Vassilis; Marinou, Eleni; Igloffstein, Julia; Siomos, Nikolaos; Solomos, Stavros; Kokkalis, Panagiotis; Engelmann, Ronny; Baars, Holger; Gratsea, Myrto; Raptis, Panagiotis I.; Binietoglou, Ioannis; Mihalopoulos, Nikolaos; Kalivitis, Nikolaos; Kouvarakis, Giorgos; Bartsotas, Nikolaos; Kallos, George; Basart, Sara; Schuettemeyer, Dirk; Wandinger, Ulla; Ansmann, Albert; Chaikovsky, Anatoli P.; Dubovik, OlegThe Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marinedominated and dust-marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.
- ItemPeakTree: A framework for structure-preserving radar Doppler spectra analysis(Göttingen : Copernicus GmbH, 2019) Radenz, M.; Bühl, J.; Seifert, P.; Griesche, H.; Engelmann, R.Clouds are frequently composed of more than one particle population even at the smallest scales. Cloud radar observations frequently contain information on multiple particle species in the observation volume when there are distinct peaks in the Doppler spectrum. Multi-peaked situations are not taken into account by established algorithms, which only use moments of the Doppler spectrum. In this study, we propose a new algorithm that recursively represents the subpeaks as nodes in a binary tree. Using this tree data structure to represent the peaks of a Doppler spectrum, it is possible to drop all a priori assumptions on the number and arrangement of subpeaks. The approach is rigid, unambiguous and can provide a basis for advanced analysis methods. The applicability is briefly demonstrated in two case studies, in which the tree structure was used to investigate particle populations in Arctic multilayered mixed-phase clouds, which were observed during the research vessel Polarstern expedition PS106 and the Atmospheric Radiation Measurement Program BAECC campaign.
- ItemSeparation of the optical and mass features of particle components in different aerosol mixtures by using POLIPHON retrievals in synergy with continuous polarized Micro-Pulse Lidar (P-MPL) measurements(Katlenburg-Lindau : Copernicus, 2018) Córdoba-Jabonero, Carmen; Sicard, Michaël; Ansmann, Albert; del Águila, Ana; Baars, HolgerThe application of the POLIPHON (POlarization-LIdar PHOtometer Networking) method is presented for the first time in synergy with continuous 24/7 polarized Micro-Pulse Lidar (P-MPL) measurements to derive the vertical separation of two or three particle components in different aerosol mixtures, and the retrieval of their particular optical properties. The procedure of extinction-to-mass conversion, together with an analysis of the mass extinction efficiency (MEE) parameter, is described, and the relative mass contribution of each aerosol component is also derived in a further step. The general POLIPHON algorithm is based on the specific particle linear depolarization ratio given for different types of aerosols and can be run in either 1-step (POL-1) or 2 steps (POL-2) versions with dependence on either the 2- or 3-component separation. In order to illustrate this procedure, aerosol mixing cases observed over Barcelona (NE Spain) are selected: a dust event on 5 July 2016, smoke plumes detected on 23 May 2016 and a pollination episode observed on 23 March 2016. In particular, the 3-component separation is just applied for the dust case: a combined POL-1 with POL-2 procedure (POL-1/2) is used, and additionally the fine-dust contribution to the total fine mode (fine dust plus non-dust aerosols) is estimated. The high dust impact before 12:00 UTC yields a mean mass loading of 0.6±0.1 g m'2 due to the prevalence of Saharan coarse-dust particles. After that time, the mean mass loading is reduced by two-thirds, showing a rather weak dust incidence. In the smoke case, the arrival of fine biomass-burning particles is detected at altitudes as high as 7 km. The smoke particles, probably mixed with less depolarizing non-smoke aerosols, are observed in air masses, having their origin from either North American fires or the Arctic area, as reported by HYSPLIT back-trajectory analysis. The particle linear depolarization ratio for smoke shows values in the 0.10-0.15 range and even higher at given times, and the daily mean smoke mass loading is 0.017±0.008 g m'2, around 3 % of that found for the dust event. Pollen particles are detected up to 1.5 km in height from 10:00 UTC during an intense pollination event with a particle linear depolarization ratio ranging between 0.10 and 0.15. The maximal mass loading of Platanus pollen particles is 0.011±0.003 g m'2, representing around 2 % of the dust loading during the higher dust incidence. Regarding the MEE derived for each aerosol component, their values are in agreement with others referenced in the literature for the specific aerosol types examined in this work: 0.5±0.1 and 1.7±0.2 m2 g'1 are found for coarse and fine dust particles, 4.5±1.4 m2 g'1 is derived for smoke and 2.4±0.5 m2 g'1 for non-smoke aerosols with Arctic origin, and a MEE of 2.4±0.8 m2 g'1 is obtained for pollen particles, though it can reach higher or lower values depending on predominantly smaller or larger pollen grain sizes. Results reveal the high potential of the P-MPL system, a simple polarization-sensitive elastic backscatter lidar working in a 24/7 operation mode, to retrieve the relative optical and mass contributions of each aerosol component throughout the day, reflecting the daily variability of their properties. In fact, this procedure can be simply implemented in other P-MPLs that also operate within the worldwide Micro-Pulse Lidar Network (MPLNET), thus extending the aerosol discrimination at a global scale. Moreover, the method has the advantage of also being relatively easily applicable to space-borne lidars with an equivalent configuration such as the ongoing Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on board NASA CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) and the forthcoming Atmospheric Lidar (ATLID) on board the ESA EarthCARE mission.
- ItemAerosol hygroscopicity parameter derived from the light scattering enhancement factor measurements in the North China Plain(Göttingen : Copernicus, 2014) Chen, J.; Zhao, C.S.; Ma, N.; Yan, P.The relative humidity (RH) dependence of aerosol light scattering is an essential parameter for accurate estimation of the direct radiative forcing induced by aerosol particles. Because of insufficient information on aerosol hygroscopicity in climate models, a more detailed parameterization of hygroscopic growth factors and resulting optical properties with respect to location, time, sources, aerosol chemistry and meteorology are urgently required. In this paper, a retrieval method to calculate the aerosol hygroscopicity parameter, κ, is proposed based on the in situ measured aerosol light scattering enhancement factor, namely f(RH), and particle number size distribution (PNSD) obtained from the HaChi (Haze in China) campaign. Measurements show that f(RH) increases sharply with increasing RH, and that the time variance of f(RH) is much greater at higher RH. A sensitivity analysis reveals that the f(RH) is more sensitive to the aerosol hygroscopicity than PNSD. f(RH) for polluted cases is distinctly higher than that for clean periods at a specific RH. The derived equivalent κ, combined with the PNSD measurements, is applied in the prediction of the cloud condensation nuclei (CCN) number concentration. The predicted CCN number concentration with the derived equivalent κ agrees well with the measured ones, especially at high supersaturations. The proposed calculation algorithm of κ with the f(RH) measurements is demonstrated to be reasonable and can be widely applied.
- ItemUnderstanding aerosol microphysical properties from 10 years of data collected at Cabo Verde based on an unsupervised machine learning classification(Katlenburg-Lindau : EGU, 2022) Gong, Xianda; Wex, Heike; Müller, Thomas; Henning, Silvia; Voigtländer, Jens; Wiedensohler, Alfred; Stratmann, FrankThe Cape Verde Atmospheric Observatory (CVAO), which is influenced by both marine and desert dust air masses, has been used for long-term measurements of different properties of the atmospheric aerosol from 2008 to 2017. These properties include particle number size distributions (PNSD), light-absorbing carbon (LAC) and concentrations of cloud condensation nuclei (CCN) together with their hygroscopicity. Here we summarize the results obtained for these properties and use an unsupervised machine learning algorithm for the classification of aerosol types. Five types of aerosols, i.e., marine, freshly formed, mixture, moderate dust and heavy dust, were classified. Air masses during marine periods are from the Atlantic Ocean and during dust periods are from the Sahara Desert. Heavy dust was more frequently present during wintertime, whereas the clean marine periods were more frequently present during springtime. It was observed that during the dust periods CCN number concentrations at a supersaturation of 0.30g% were roughly 2.5 times higher than during marine periods, but the hygroscopicity (κ) of particles in the size range from g1/4g30 to g1/4g175gnm during marine and dust periods were comparable. The long-term data presented here, together with the aerosol classification, can be used as a basis to improve our understanding of annual cycles of the atmospheric aerosol in the eastern tropical Atlantic Ocean and on aerosol-cloud interactions and it can be used as a basis for driving, evaluating and constraining atmospheric model simulations.
- ItemNew particle formation in the Svalbard region 2006-2015(Katlenburg-Lindau : EGU, 2017) Heintzenberg, Jost; Tunved, Peter; Galí, Martí; Leck, CarolineEvents of new particle formation (NPF) were analyzed in a 10-year data set of hourly particle size distributions recorded on Mt. Zeppelin, Spitsbergen, Svalbard. Three different types of NPF events were identified through objective search algorithms. The first and simplest algorithm utilizes short-term increases in particle concentrations below 25 nm (PCT (percentiles) events). The second one builds on the growth of the sub-50 nm diameter median (DGR (diameter growth) events) and is most closely related to the classical "banana type" of event. The third and most complex, multiple-size approach to identifying NPF events builds on a hypothesis suggesting the concurrent production of polymer gel particles at several sizes below ca. 60 nm (MEV (multisize growth) events). As a first and general conclusion, we can state that NPF events are a summer phenomenon and not related to Arctic haze, which is a late winter to early spring feature. The occurrence of NPF events appears to be somewhat sensitive to the available data on precipitation. The seasonal distribution of solar flux suggests some photochemical control that may affect marine biological processes generating particle precursors and/or atmospheric photochemical processes that generate condensable vapors from precursor gases. Notably, the seasonal distribution of the biogenic methanesulfonate (MSA) follows that of the solar flux although it peaks before the maxima in NPF occurrence. A host of ancillary data and findings point to varying and rather complex marine biological source processes. The potential source regions for all types of new particle formation appear to be restricted to the marginal-ice and open-water areas between northeastern Greenland and eastern Svalbard. Depending on conditions, yet to be clarified new particle formation may become visible as short bursts of particles around 20 nm (PCT events), longer events involving condensation growth (DGR events), or extended events with elevated concentrations of particles at several sizes below 100 nm (MEV events). The seasonal distribution of NPF events peaks later than that of MSA and DGR, and in particular than that of MEV events, which reach into late summer and early fall with open, warm, and biologically active waters around Svalbard. Consequently, a simple model to describe the seasonal distribution of the total number of NPF events can be based on solar flux and sea surface temperature, representing environmental conditions for marine biological activity and condensation sink, controlling the balance between new particle nucleation and their condensational growth. Based on the sparse knowledge about the seasonal cycle of gel-forming marine microorganisms and their controlling factors, we hypothesize that the seasonal distribution of DGR and, more so, MEV events reflect the seasonal cycle of the gel-forming phytoplankton.
- ItemCloud top heights and aerosol layer properties from EarthCARE lidar observations: The A-CTH and A-ALD products(Katlenburg-Lindau : Copernicus, 2023) Wandinger, Ulla; Haarig, Moritz; Baars, Holger; Donovan, David; van Zadelhoff, Gerd-JanThe high-spectral-resolution Atmospheric Lidar (ATLID) on the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) provides vertically resolved information on aerosols and clouds with unprecedented accuracy. Together with the Cloud Profiling Radar (CPR), the Multi-Spectral Imager (MSI), and the Broad-Band Radiometer (BBR) on the same platform, it allows for a new synergistic view on atmospheric processes related to the interaction of aerosols, clouds, precipitation, and radiation at the global scale. This paper describes the algorithms for the determination of cloud top height and aerosol layer information from ATLID Level 1b (L1b) and Level 2a (L2a) input data. The ATLID L2a Cloud Top Height (A-CTH) and Aerosol Layer Descriptor (A-ALD) products are developed to ensure the provision of atmospheric layer products in continuation of the heritage from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Moreover, the products serve as input for synergistic algorithms that make use of data from ATLID and MSI. Therefore, the products are provided on the EarthCARE joint standard grid (JSG). A wavelet covariance transform (WCT) method with flexible thresholds is applied to determine layer boundaries from the ATLID Mie co-polar signal. Strong features detected with a horizontal resolution of 1 JSG pixel (approximately 1ĝ€¯km) or 11 JSG pixels are classified as thick or thin clouds, respectively. The top height of the uppermost cloud layer together with information on cloud layering are stored in the A-CTH product for further use in the generation of the ATLID-MSI Cloud Top Height (AM-CTH) synergy product. Aerosol layers are detected as weaker features at a resolution of 11 JSG pixels. Layer-mean optical properties are calculated from the ATLID L2a Extinction, Backscatter and Depolarization (A-EBD) product and stored in the A-ALD product, which also contains the aerosol optical thickness (AOT) of each layer, the stratospheric AOT, and the AOT of the entire atmospheric column. The latter parameter is used to produce the synergistic ATLID-MSI Aerosol Column Descriptor (AM-ACD) later in the processing chain. Several quality criteria are applied in the generation of A-CTH and A-ALD, and respective information is stored in the products. The functionality and performance of the algorithms are demonstrated by applying them to common EarthCARE test scenes. Conclusions are drawn for the application to real-world data and the validation of the products after the launch of EarthCARE.
- ItemCloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products(Katlenburg-Lindau : Copernicus, 2023) Hünerbein, Anja; Bley, Sebastian; Horn, Stefan; Deneke, Hartwig; Walther, AndiThe EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol-cloud-radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150km swath and a pixel sampling at 500m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.