On June 29–30, 2019, the Barcelona Dust Forecast Center with Non‐hydrostatic Multiscale Model (NMMB/BSC‐Dust) and the Navy Aerosol Analysis and Prediction System forecasted huge amounts of mineral ...dust over Poland. The Hybrid Single Particle Lagrangian Integrated Trajectory model confirmed uniquely fast (120 hr) long‐range air‐mass transport form North Africa to Poland. This remarkable dust event was observed using lidar at the Aerosol, Clouds and Trace Gases Research InfraStructure site in Warsaw, Central Poland; the only site equipped with Raman‐Mie polarization water vapor lidar in East‐Central Europe. The excellent capabilities of PollyXT lidar allowed to obtain an impressive number of 31 full sets of aerosol optical properties profiles, which enabled study of dust properties evolution on a rare hourly scale. The analyses were completed with the separation of fine and coarse mode dust particles form non‐dust particles using the POlarization‐LIdar PHOtometer Networking algorithm. Huge amount of an exceptionally pure mineral dust from Sahara measured in the free troposphere was characterized by a gradually decreasing coarse dust fraction (76%–21%) with a peak of fine dust fraction (67%) and particle linear depolarization ratio (26%) in the middle of the event. Within the boundary layer, a local urban dust mixed with pollution was observed with fine mode dust particles dominating (44%) and lower particle linear depolarization ratio (7.4%). The influx of pure mineral dust has been unique to this geographical region and will therefore be a reference point for future research and comparative studies.
Key Points
Unusually fast, uniform, and quasi‐stable pure mineral dust inflow form Sahara Desert to East‐Central Europe
Advected Saharan dust composed of significant fractions of fine and coarse mode dust particles evolving in time
Local urban/agro dust with no evidence of coarse mode particles
We use the Generalized Retrieval of Aerosol Surface Properties algorithm (GRASP) to compare with dust concentration profiles derived from the NMME-DREAM model for a specific dust episode. The GRASP ...algorithm provides the possibility of deriving columnar and vertically-resolved aerosol properties from a combination of lidar and sun-photometer observations. Herein, we apply GRASP for analysis of a Saharan dust outburst observed during the “PREparatory: does dust TriboElectrification affect our ClimaTe” campaign (PreTECT) that took place at the North coast of Crete, at the Finokalia ACTRIS station. GRASP provides column-averaged and vertically resolved microphysical and optical properties of the particles. The retrieved dust concentration profiles are compared with modeled concentration profiles derived from the NMME-DREAM dust model. To strengthen the results, we use dust concentration profiles from the POlarization-LIdar PHOtometer Networking method (POLIPHON). A strong underestimation of the maximum dust concentration is observed from the NMME-DREAM model. The reported differences between the retrievals and the model indicate a high potential of the GRASP algorithm for future studies of dust model evaluation.
During August 2016, a quasi-stationary high-pressure system spreading over Central and North-Eastern Europe, caused weather conditions that allowed for 24/7 observations of aerosol optical properties ...by using a complex multi-wavelength PollyXT lidar system with Raman, polarization and water vapour capabilities, based at the European Aerosol Research Lidar Network (EARLINET network) urban site in Warsaw, Poland. During 24–30 August 2016, the lidar-derived products (boundary layer height, aerosol optical depth, Ångström exponent, lidar ratio, depolarization ratio) were analysed in terms of air mass transport (HYSPLIT model), aerosol load (CAMS data) and type (NAAPS model) and confronted with active and passive remote sensing at the ground level (PolandAOD, AERONET, WIOS-AQ networks) and aboard satellites (SEVIRI, MODIS, CATS sensors). Optical properties for less than a day-old fresh biomass burning aerosol, advected into Warsaw’s boundary layer from over Ukraine, were compared with the properties of long-range transported 3–5 day-old aged biomass burning aerosol detected in the free troposphere over Warsaw. Analyses of temporal changes of aerosol properties within the boundary layer, revealed an increase of aerosol optical depth and Ångström exponent accompanied by an increase of surface PM10 and PM2.5. Intrusions of advected biomass burning particles into the urban boundary layer seem to affect not only the optical properties observed but also the top height of the boundary layer, by moderating its increase.
This paper presents preliminary results of using an extended POLIPHON method for separation of dust and non-dust aerosol backscatter coefficient, applied on a case study of 9th August 2013. That day, ...long-range transport of mineral dust over EARLINET-ACTRIS lidar site in Warsaw was observed with the 8-channel PollyXT-UW lidar. The dust particles were also observed by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite. The backward trajectories calculated using the HYSPLIT model confirmed the air-mass transport from Northern Africa. Results yield possible dust separation for the mixture of dust with other aerosol types, such as pollution, marine type, etc.
Earlinet validation of CATS L2 product Proestakis, Emmanouil; Amiridis, Vassilis; Kottas, Michael ...
EPJ Web of Conferences,
01/2018, Letnik:
176
Journal Article, Conference Proceeding, Publication
Recenzirano
Odprti dostop
The Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS), is a lidar system providing vertically resolved aerosol and cloud profiles since February 2015. In this study, ...the CATS aerosol product is validated against the aerosol profiles provided by the European Aerosol Research Lidar Network (EARLINET). This validation activity is based on collocated CATS-EARLINET measurements and the comparison of the particle backscatter coefficient at 1064nm.
The representation of cloud microphysical processes contributes substantially
to the uncertainty of numerical weather simulations. In part, this is owed to
some fundamental knowledge gaps in the ...underlying processes due to the
difficulty of observing them directly. On the path to closing these gaps, we present
a setup for the systematic characterization of differences between numerical
weather model and radar observations for convective weather situations. Radar
observations are introduced which provide targeted dual-wavelength and
polarimetric measurements of convective clouds with the potential to provide
more detailed information about hydrometeor shapes and sizes. A convection-permitting regional weather model setup is established using five different
microphysics schemes (double-moment, spectral bin (“Fast Spectral Bin
Microphysics”, FSBM), and particle property
prediction (P3)). Observations are compared to hindcasts which are created with
a polarimetric radar forward simulator for all measurement days. A
cell-tracking algorithm applied to radar and model data facilitates comparison
on a
cell object basis. Statistical comparisons of radar observations and numerical
weather model runs are presented on a data set of 30 convection days. In
general, simulations show too few weak and small-scale convective cells.
Contoured frequency by altitude diagrams of radar signatures reveal deviations
between the schemes and observations in ice and liquid phase. Apart from the P3
scheme, high reflectivities in the ice phase are simulated too frequently.
Dual-wavelength
signatures demonstrate issues of most schemes to correctly represent ice
particle size distributions, producing too large or too dense graupel particles.
Comparison of polarimetric radar signatures reveals issues of all schemes except
the FSBM to correctly represent rain particle size distributions.
Cloud and precipitation processes are still a main source of
uncertainties in numerical weather prediction and climate change
projections. The Priority Programme “Polarimetric Radar Observations meet
...Atmospheric Modelling (PROM)”, funded by the German Research Foundation
(Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis that
many uncertainties relate to the lack of observations suitable to challenge
the representation of cloud and precipitation processes in atmospheric
models. Such observations can, however, at present be provided by the
recently installed dual-polarization C-band weather radar network of the
German national meteorological service in synergy with cloud radars and
other instruments at German supersites and similar national networks
increasingly available worldwide. While polarimetric radars potentially
provide valuable in-cloud information on hydrometeor type, quantity,
and microphysical cloud and precipitation processes, and atmospheric models
employ increasingly complex microphysical modules, considerable knowledge
gaps still exist in the interpretation of the observations and in the
optimal microphysics model process formulations. PROM is a coordinated
interdisciplinary effort to increase the use of polarimetric radar
observations in data assimilation, which requires a thorough evaluation and
improvement of parameterizations of moist processes in atmospheric models.
As an overview article of the inter-journal special issue “Fusion of radar
polarimetry and numerical atmospheric modelling towards an improved
understanding of cloud and precipitation processes”, this article outlines
the knowledge achieved in PROM during the past 2 years and gives
perspectives for the next 4 years.
Ice growth processes within clouds affect the type and amount of precipitation. Hence, the importance of an accurate
representation of ice microphysics in numerical weather and numerical
climate ...models has been confirmed by several studies. To better constrain
ice processes in models, we need to study ice cloud regions before and
during monitored precipitation events. For this purpose, two radar
instruments facing each other were used to collect complementary
measurements. The C-band POLDIRAD weather radar from the German Aerospace
Center (DLR) in Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from the
Ludwig Maximilians University of Munich (LMU) were used to monitor
stratiform precipitation in the vertical cross-sectional area between the two
instruments. The logarithmic difference of radar reflectivities at two
different wavelengths (54.5 and 8.5 mm), known as the dual-wavelength ratio, was
exploited to provide information about the size of the detected ice
hydrometeors, taking advantage of the different scattering behavior in the
Rayleigh and Mie regime. Along with the dual-wavelength ratio, differential
radar reflectivity measurements from POLDIRAD provided information about the
apparent shape of the detected ice hydrometeors. Scattering simulations
using the T-matrix method were performed for oblate and horizontally aligned
prolate ice spheroids of varying shape and size using a realistic particle
size distribution and a well-established mass–size relationship. The
combination of dual-wavelength ratio, radar reflectivity, and differential
radar reflectivity measurements as well as scattering simulations was used
for the development of a novel retrieval for ice cloud microphysics. The
development of the retrieval scheme also comprised a method to estimate the
hydrometeor attenuation in both radar bands. To demonstrate this approach, a
feasibility study was conducted on three stratiform snow events which were
monitored over Munich in January 2019. The ice retrieval can provide ice
particle shape, size, and mass information which is in line with differential
radar reflectivity, dual-wavelength ratio, and radar reflectivity
observations, respectively, when the ice spheroids are assumed to be oblates
and to follow the mass–size relation of aggregates. When combining two
spatially separated radars to retrieve ice microphysics, the beam width
mismatch can locally lead to significant uncertainties. However, the
calibration uncertainty is found to cause the largest bias for the averaged
retrieved size and mass. Moreover, the shape assumption is found to be
equally important to the calibration uncertainty for the retrieved size,
while it is less important than the calibration uncertainty for the
retrieval of ice mass. A further finding is the importance of the
differential radar reflectivity for the particle size retrieval directly
above the MIRA-35 cloud radar. Especially for that observation geometry, the
simultaneous slantwise observation from the polarimetric weather radar
POLDIRAD can reduce ambiguities in retrieval of the ice particle size by
constraining the ice particle shape.
We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the ...Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50 km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90 min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1 %, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3 %.
We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the ...Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS). The study employs correlative CATS and EARLINET backscatter measurements within 50km distance between the ground station and the ISS overpass and as close in time as possible, typically within 90min, from February 2015 to September 2016. The results demonstrate the good agreement of CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig-Germany, Évora-Portugal and Dushanbe-Tajikistan are analysed here to demonstrate the performance of CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions CATS is in good agreement with EARLINET, independently of daytime/nighttime conditions. CATS low negative biases, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds, may lead to systematic deviations and slight underestimations of the total Aerosol Optical Depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, may lead to non-representative, unrealistic and cloud contaminated aerosol profiles. The distributions of backscatter coefficient biases show the relatively good agreement between the CATS and EARLINET measurements, although on average underestimations are observed, 22.3% during daytime and 6.1% during nighttime.
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