Aerosol characterization over a Central Asian site: long-term lidar profiling at Dushanbe, Tajikistan (March 2015 – August 2016)

For the first time, a comprehensive characterization of optical, microphysical, and cloud-relevant properties of Central Asian aerosol particles with a state-of-the-art lidar has been performed. This study fills a gap between observations in Eastern Mediterranean (e.g., in Greece, Cyprus, and Israel) and Eastern Asian (e.g, in China, Korea, and Japan) aerosol monitoring. During the Central Asian Dust Experiment (CADEX), an automatic multiwavelength polarization Raman lidar PollyXT was operated in Dushanbe, Tajikistan, from 17 March 2015 until 31 August 2016. During the 18-month campaign, on 487 days, lidar data has been acquired for a time period of at least 3 h. On 308 of these days, the lidar ran even longer than 20 h. 328 manually analyzed profiles of nighttime observations build the data basis of this study and cover well the annual cycle of dust and pollution aerosol layering. Thorough quality assurance and calibration efforts have been made before, during, and after the measurement campaign. With the lidar, vertical profiles of the particle backscatter coefficient at 355 nm, 532 nm, and 1064 nm, of the particle extinction coefficient at 355 nm and 532 nm, and of the particle linear depolarization ratio at 355 nm and 532 nm wavelength were determined. From these quantities, lidar ratios and backscatter-related and extinction-related Ångström exponents were derived. Furthermore, the optical properties were converted to mass concentration and cloud-relevant parameters (CCN and INP concentration) by means of the recently developed lidar technique POLIPHON

Central Asian Dust Experiment (CADEX): Multiwavelength polarization Raman lidar observations in Tajikistan

For the first time lidar measurements of vertical aerosol profiles are conducted in Tajikistan/Central Asia. These measurements just started on March 17th, 2015. They are performed within the Central Asian Dust Experiment (CADEX) in Dushanbe and they will last at least one year. The deployed system for these observations is an updated version of the multiwavelength polarization Raman lidar PollyXT. Vertical profiles of the backscatter coefficient, the extinction coefficient, and the particle depolarization ratio are measured by this instrument. A first and preliminary measurement example of an aerosol layer over Dushanbe is shown

Ice nucleation efficiency of natural dust samples in the immersion mode

A total of 12 natural surface dust samples, which were surface-collected on four continents, most of them in dust source regions, were investigated with respect to their ice nucleation activity. Dust collection sites were distributed across Africa, South America, the Middle East, and Antarctica. Mineralogical composition has been determined by means of X-ray diffraction. All samples proved to be mixtures of minerals, with major contributions from quartz, calcite, clay minerals, K-feldspars, and (Na, Ca)-feldspars. Reference samples of these minerals were investigated with the same methods as the natural dust samples. Furthermore, Arizona test dust (ATD) was re-evaluated as a benchmark. Immersion freezing of emulsion and bulk samples was investigated by differential scanning calorimetry. For emulsion measurements, water droplets with a size distribution peaking at about 2 µm, containing different amounts of dust between 0.5 and 50 wt % were cooled until all droplets were frozen. These measurements characterize the average freezing behaviour of particles, as they are sensitive to the average active sites present in a dust sample. In addition, bulk measurements were conducted with one single 2 mg droplet consisting of a 5 wt % aqueous suspension of the dusts/minerals. These measurements allow the investigation of the best ice-nucleating particles/sites available in a dust sample. All natural dusts, except for the Antarctica and ATD samples, froze in a remarkably narrow temperature range with the heterogeneously frozen fraction reaching 10 % between 244 and 250 K, 25 % between 242 and 246 K, and 50 % between 239 and 244 K. Bulk freezing occurred between 255 and 265 K. In contrast to the natural dusts, the reference minerals revealed ice nucleation temperatures with 2–3 times larger scatter. Calcite, dolomite, dolostone, and muscovite can be considered ice nucleation inactive. For microcline samples, a 50 % heterogeneously frozen fraction occurred above 245 K for all tested suspension concentrations, and a microcline mineral showed bulk freezing temperatures even above 270 K. This makes microcline (KAlSi3O8) an exceptionally good ice-nucleating mineral, superior to all other analysed K-feldspars, (Na, Ca)-feldspars, and the clay minerals. In summary, the mineralogical composition can explain the observed freezing behaviour of 5 of the investigated 12 natural dust samples, and partly for 6 samples, leaving the freezing efficiency of only 1 sample not easily explained in terms of its mineral reference components. While this suggests that mineralogical composition is a major determinant of ice-nucleating ability, in practice, most natural samples consist of a mixture of minerals, and this mixture seems to lead to remarkably similar ice nucleation abilities, regardless of their exact composition, so that global models, in a first approximation, may represent mineral dust as a single species with respect to ice nucleation activity. However, more sophisticated representations of ice nucleation by mineral dusts should rely on the mineralogical composition based on a source scheme of dust emissions

Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction

Recent advancements in natural language processing (NLP) methods have significantly improved their performance. However, more complex NLP models are more difficult to interpret and computationally expensive. Therefore, we propose an approach to dictionary creation that carefully balances the trade-off between complexity and interpretability. This approach combines a deep neural network architecture with techniques to improve model explainability to automatically build a domain-specific dictionary. As an illustrative use case of our approach, we create an objective dictionary that can infer conflict intensity from text data. We train the neural networks on a corpus of conflict reports and match them with conflict event data. This corpus consists of over 14,000 expert-written International Crisis Group (ICG) CrisisWatch reports between 2003 and 2021. Sensitivity analysis is used to extract the weighted words from the neural network to build the dictionary. In order to evaluate our approach, we compare our results to state-of-the-art deep learning language models, text-scaling methods, as well as standard, nonspecialized, and conflict event dictionary approaches. We are able to show that our approach outperforms other approaches while retaining interpretability

Lidar/radar approach to quantify the dust impact on ice nucleation in mid and high level clouds

We present the first attempt of a closure experiment regarding the relationship between ice nucleating particle concentration (INPC) and ice crystal number concentration (ICNC), solely based on active remote sensing. The approach combines aerosol and cloud observations with polarization lidar, Doppler lidar, and cloud radar. Several field campaigns were conducted on the island of Cyprus in the Eastern Mediterranean from 2015-2018 to study heterogeneous ice formation in altocumulus and cirrus layers embedded in Saharan dust. A case study observed on 10 April 2017 is discussed in this contribution. © 2019 The Authors, published by EDP Sciences

Modifications in aerosol physical, optical and radiative properties during heavy aerosol events over Dushanbe, Central Asia

The location of Central Asia, almost at the center of the global dust belt region, makes it susceptible for dust events. The studies on atmospheric impact of dust over the region are very limited despite the large area occupied by the region and its proximity to the mountain regions (Tianshan, Hindu Kush-Karakoram-Himalayas, and Tibetan Plateau). In this study, we analyse and explain the modification in aerosols’ physical, optical and radiative properties during various levels of aerosol loading observed over Central Asia utilizing the data collected during 2010–2018 at the AERONET station in Dushanbe, Tajikistan. Aerosol episodes were classified as strong anthropogenic, strong dust and extreme dust. The mean aerosol optical depth (AOD) during these three types of events was observed a factor of ~3, 3.5 and 6.6, respectively, higher than the mean AOD for the period 2010–2018. The corresponding mean fine-mode fraction was 0.94, 0.20 and 0.16, respectively, clearly indicating the dominance of fine-mode anthropogenic aerosol during the first type of events, whereas coarse-mode dust aerosol dominated during the other two types of events. This was corroborated by the relationships among various aerosol parameters (AOD vs. AE, and EAE vs. AAE, SSA and RRI). The mean aerosol radiative forcing (ARF) at the top of the atmosphere (ARFTOA), the bottom of the atmosphere (ARFBOA), and in the atmosphere (ARFATM) were −35 ± 7, −73 ± 16, and 38 ± 17 Wm−2 during strong anthropogenic events, −48 ± 12, −85 ± 24, and 37 ± 15 Wm−2 during strong dust event, and −68 ± 19, −117 ± 38, and 49 ± 21 Wm−2 during extreme dust events. Increase in aerosol loading enhanced the aerosol-induced atmospheric heating rate to 0.5–1.6 K day−1 (strong anthropogenic events), 0.4–1.9 K day−1 (strong dust events) and 0.8–2.7 K day−1 (extreme dust events). The source regions of air masses to Dushanbe during the onset of such events are also identified. Our study contributes to the understanding of dust and anthropogenic aerosols, in particular the extreme events and their disproportionally high radiative impacts over Central Asia

Validation of Aeolus wind products above the Atlantic Ocean

In August 2018, the first Doppler wind lidar in space called Atmospheric Laser Doppler Instrument (ALADIN) was launched on board the satellite Aeolus by the European Space Agency (ESA). Aeolus measures profiles of one horizontal wind component (i.e., mainly the west-east direction) in the troposphere and lower stratosphere on a global basis. Furthermore, profiles of aerosol and cloud properties can be retrieved via the high spectral resolution lidar (HSRL) technique. The Aeolus mission is supposed to improve the quality of weather forecasts and the understanding of atmospheric processes. We used the opportunity to perform a unique validation of the wind products of Aeolus by utilizing the RV Polarstern cruise PS116 from Bremerhaven to Cape Town in November/December 2018. Due to concerted course modifications, six direct intersections with the Aeolus ground track could be achieved in the Atlantic Ocean west of the African continent. For the validation of the Aeolus wind products, we launched additional radiosondes and used the EARLINET/ACTRIS lidar Polly XT for atmospheric scene analysis. The six analyzed cases prove that Aeolus is able to measure horizontal wind speeds in the nearly west-east direction. Good agreements with the radiosonde observations could be achieved for both Aeolus wind products-the winds observed in clean atmospheric regions called Rayleigh winds and the winds obtained in cloud layers called Mie winds (according to the responsible scattering regime). Systematic and statistical errors of the Rayleigh winds were less than 1.5 and 3.3ms-1, respectively, when compared to radiosonde values averaged to the vertical resolution of Aeolus. For the Mie winds, a systematic and random error of about 1ms-1 was obtained from the six comparisons in different climate zones. However, it is also shown that the coarse vertical resolution of 2km in the upper troposphere, which was set in this early mission phase 2 months after launch, led to an underestimation of the maximum wind speed in the jet stream regions. In summary, promising first results of the first wind lidar space mission are shown and prove the concept of Aeolus for global wind observations. © 2020 Author(s)

Aerosol layer heights above Tajikistan during the CADEX campaign

Mineral dust influences climate and weather by direct and indirect effects. Surrounded by dust sources, Central Asian countries are affected by atmospheric mineral dust on a regular basis. Climate change effects like glacier retreat and desertification are prevalent in Central Asia as well. Therefore, the role of dust in the climate system in Central Asia needs to be clarified and quantified. During the Central Asian Dust EXperiment (CADEX) first lidar observations in Tajikistan were conducted. Long-term vertically resolved aerosol measurements were performed with the multiwavelength polarization Raman lidar PollyXT from March 2015 to August 2016 in Dushanbe, Tajikistan. In this contribution, a climatology of the aerosol layer heights is presented, which was retrieved from the 18-month lidar measurements. Automatic detection based on backscatter coefficient thresholds were used to retrieve the aerosol layer heights and yield similar layer heights as manual layer height determination. The significant aerosol layer height has a maximum in summer and a minimum in winter. The highest layers occurred in spring, but in summer uppermost layer heights above 6 km AGL are frequent, too. © 2019 The Authors, published by EDP Sciences