18 research outputs found
Assessment of the total precipitable water from a sun photometer, microwave radiometer and radiosondes at a continental site in southeastern Europe
In this study, we discuss the differences in the total precipitable water
(TPW), retrieved from a Cimel sun photometer operating at a continental site
in southeast Europe, between version 3 (V3) and version 2 (V2) of the
AErosol RObotic NETwork (AERONET) algorithms. In addition, we evaluate the
performance of the two algorithms comparing their product with the TPW
obtained from a collocated microwave radiometer and nearby radiosondes during
the period 2007–2017. The TPW from all three instruments was highly
correlated, showing the same annual cycle, with lower values during winter
and higher values during summer. The sun photometer and the microwave radiometer
depict the same daily cycle, with some discrepancies during early morning and
late afternoon due to the effect of solar zenith angle on the measurements of
the photometer. The TPW from V3 of the AERONET algorithm has small
differences compared with V2, mostly related to the use of the new
laboratory-based temperature coefficients used in V3. The microwave
radiometer measurements are in good agreement with those obtained by the
radiosonde, especially during night-time when the differences between the two
instruments are almost negligible. The comparison of the sun photometer data
with high-quality independent measurements from radiosondes and the radiometer
shows that the absolute differences between V3 and the other two datasets are
slightly higher compared with V2. However, V3 has a lower dependence from the
TPW and the internal sensor temperature, indicating a better performance of
the retrieving algorithm. The calculated one-sigma uncertainty for V3 as
estimated, from the comparison with the radiosondes, is about 10 %, which is
in accordance with previous studies for the estimation of uncertainty for V2.
This uncertainty is further reduced to about 6 % when AERONET V3 is
compared with the collocated microwave radiometer. To our knowledge, this is
the first in-depth analysis of the V3 TPW, and although the findings presented
here are for a specific site, we believe that they are representative of
other mid-latitude continental stations.</p
A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals
Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research Infra-Structure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAM-ABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1-6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 mu g m(-3) at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies
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A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals
Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies
Experimental techniques for the calibration of lidar depolarization channels in EARLINET
Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range that is generally accepted in the literature
Assessment of aerosol's mass concentrations from measured linear particle depolarization ratio (vertically resolved) and simulations
Multi-wavelength depolarization Raman lidar measurements from Magurele,
Romania are used in this study along with simulated mass-extinction
efficiencies to calculate the mass concentration profiles of different
atmospheric components, due to their different depolarization contribution to
the 532 nm backscatter coefficient. Linear particle depolarization ratio
(δpart) was computed using the relative amplification factor
and the system-dependent molecular depolarization. The low depolarizing
component was considered as urban/smoke, with a mean δpart
of 3%, while for the high depolarizing component (mineral dust) a mean
δpart of 35% was assumed.
For this study 11 months of lidar measurements were analysed. Two study cases
are presented in details: one for a typical Saharan dust aerosol intrusion,
10 June 2012 and one for 12 July 2012 when a lofted layer consisting of
biomass burning smoke extended from 3 to 4.5 km height.
Optical Properties of Aerosols and Clouds software package (OPAC)
classification and conversion factors were used to calculate mass
concentrations. We found that calibrated depolarization measurements are
critical in distinguishing between smoke-reach aerosol during the winter and
dust-reach aerosol during the summer, as well as between elevated aerosol
layers having different origins. Good agreement was found between lidar
retrievals and DREAM- Dust REgional Atmospheric Model forecasts in cases of
Saharan dust. Our method was also compared against LIRIC (The
Lidar/Radiometer Inversion Code) and very small differences were observed
Assessing the Long Term Stability of the Depolarization Constant for the Cluj Station
The study aims to assess the additional systematic error caused by the assessment of the depolarization constant. Based on the long time assessment of this constant, a mean value and a standard deviation can be retrieved. A sensitivity study could assess the deviation of the depolarization value in high and low depolarizing atmospheric layers. Based on these deviations, the systematic error of the calibration is retrieved and included in the final depolarization products
Assessing the Long Term Stability of the Depolarization Constant for the Cluj Station
The study aims to assess the additional systematic error caused by the assessment of the depolarization constant. Based on the long time assessment of this constant, a mean value and a standard deviation can be retrieved. A sensitivity study could assess the deviation of the depolarization value in high and low depolarizing atmospheric layers. Based on these deviations, the systematic error of the calibration is retrieved and included in the final depolarization products
ESA Airborne 3+2+2 HSRL for Aladin/Atlid CAL/VAL
This paper presents the design study for an airborne multi-wavelength HSRL system to be installed on board of a Hawker Beechcraft King Air C90-GTx aircraft. The system is aimed at profiling the aerosol extinction, backscatter and depolarization layer distributions in IR, VIS and UV spectral rang
MULTIPLY: Development of a European HSRL airborne facility
MULTIPLY is a novel airborne high spectral resolution lidar (HSRL) currently under development by a consortium of European institutions from Romania, Germany, Greece, and Poland. Its aim is to contribute to calibration and validations activities of the upcoming ESA aerosol sensing missions like ADM-Aeolus, EarthCARE and the Sentinel-3/-4/-5/-5p which include products related to atmospheric aerosols. The effectiveness of these missions depends on independent airborne measurements to develop and test the retrieval methods, and validate mission products following launch. The aim of ESA's MULTIPLY project is to design, develop, and test a multi-wavelength depolarization HSRL for airborne applications. The MULTIPLY lidar will deliver the aerosol extinction and backscatter coefficient profiles at three wavelengths (355nm, 532nm, 1064nm), as well as profiles of aerosol intensive parameters (Ångström exponents, extinction-to-backscatter ratios, and linear particle depolarization ratios)
High-resolution airborne imaging DOAS-measurements of NO<sub>2</sub> above Bucharest during AROMAT
In this study we report on airborne imaging DOAS measurements of NO2 from two flights performed in Bucharest during the AROMAT campaign (Airborne ROmanian Meeasurements of Aerosols an Trace gases) in September 2014. These measurements were performed with the Airborne imaging Differential Optical Absorption Spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP) and provide nearly gapless maps of column densities of NO2 below the aircraft with a high spatial resolution of better than 100 m. The airmass factors, which are needed to convert the measured differential Slant Column Densities (dSCDs) to Vertical Column Densities (VCDs) have a strong dependence on the surface reflectance, which has to be accounted for in the retrieval. This is especially important for measurements above urban areas, where the surface properties vary strongly. As the instrument is not radiometrically calibrated, we have developed a method to derive the surface reflectance from measured intensities at the aircraft. This method is based on radiative transfer calculation with SCIATRAN and a reference area for which the surface reflectance is known. While surface properties are clearly seen in the NO2 dSCD results, this effect is successfully corrected for in the VCD results. Furthermore we investigate the influence of aerosols on the retrieval for a variety of aerosol profiles that were measured in the context of the AROMAT campaigns. The results of two research flights are presented which reveal distinct horizontal distribution patterns and strong spatial gradients of NO2 across the city. Pollution levels range from background values in the outskirts located upwind of the city to about 4 × 1016 molec cm−2 in the polluted city center. Validation against two co-located mobile car-DOAS measurements yields good agreement between the datasets with correlation cofficients of R = 0.94 and R = 0.85, respectively. Estimations on the NOx emission rate of Bucharest for the two flights yield emission rates of 15.1 ± 9.4 mol s−1 and 13.6 ± 8.4 mol s−1, respectively