Satellite retrieval of aerosol microphysical and optical parameters using neural networks: a new methodology applied to the Sahara desert dust peak

In order to exploit the full-earth viewing potential of satellite instruments to globally characterise aerosols, new algorithms are required to deduce key microphysical parameters like the particle size distribution and optical parameters associated with scattering and absorption from space remote sensing data. Here, a methodology based on neural networks is developed to retrieve such parameters from satellite inputs and to validate them with ground-based remote sensing data. For key combinations of input variables available from the MODerate resolution Imaging Spectro-radiometer (MODIS) and the Ozone Measuring Instrument (OMI) Level 3 data sets, a grid of 100 feed-forward neural network architectures is produced, each having a different number of neurons and training proportion. The networks are trained with principal components accounting for 98% of the variance of the inputs together with principal components formed from 38 AErosol RObotic NETwork (AERONET) Level 2.0 (Version 2) retrieved parameters as outputs. Daily averaged, co-located and synchronous data drawn from a cluster of AERONET sites centred on the peak of dust extinction in Northern Africa is used for network training and validation, and the optimal network architecture for each input parameter combination is identified with reference to the lowest mean squared error. The trained networks are then fed with unseen data at the coastal dust site Dakar to test their simulation performance. A neural network (NN), trained with co-located and synchronous satellite inputs comprising three aerosol optical depth measurements at 470, 550 and 660 nm, plus the columnar water vapour (from MODIS) and the modelled absorption aerosol optical depth at 500 nm (from OMI), was able to simultaneously retrieve the daily averaged size distribution, the coarse mode volume, the imaginary part of the complex refractive index, and the spectral single scattering albedo – with moderate precision: correlation coefficients in the range 0.368 ≤ R ≤ 0.514. The network failed to recover the spectral behaviour of the real part of the complex refractive index. This new methodological approach appears to offer some potential for moderately accurate daily retrieval of the total volume concentration of the coarse mode of aerosol at the Saharan dust peak in the area of Northern Africa

EFFECT OF WETTING AGENT AND CARBIDE VOLUME FRACTION ON THE WEAR RESPONSE OF ALUMINUM MATRIX COMPOSITES REINFORCED BY WC NANOPARTICLES AND ALUMINIDE PARTICLES

Aluminum matrix composites were prepared by adding submicron sized WC particles into a melt of Al 1050 under mechanical stirring, with the scope to determine: (a) the most appropriate salt flux amongst KBF4 , K2 TiF6 , K3 AlF6 and Na3 AlF6 for optimum particle wetting and distribution and (b) the maximum carbide volume fraction (CVF) for optimum response to sliding wear. The nature of the wetting agent notably affected particle incorporation, with K2 TiF6 providing the greatest particle insertion. A uniform aluminide (in-situ) and WC (ex-situ) particle distribution was attained. Two different sliding wear mechanisms were identified for low CVFs (≤1.5%), and high CVFs (2.0%), depending on the extent of particle agglomeration

Optomechanic Coupling in Ag Polymer Nanocomposite Films

[Image: see text] Particle vibrational spectroscopy has emerged as a new tool for the measurement of elasticity, glass transition, and interactions at a nanoscale. For colloid-based materials, however, the weakly localized particle resonances in a fluid or solid medium renders their detection difficult. The strong amplification of the inelastic light scattering near surface plasmon resonance of metallic nanoparticles (NPs) allowed not only the detection of single NP eigenvibrations but also the interparticle interaction effects on the acoustic vibrations of NPs mediated by strong optomechanical coupling. The “rattling” and quadrupolar modes of Ag/polymer and polymer-grafted Ag NPs with different diameters in their assemblies are probed by Brillouin light spectroscopy (BLS). We present thorough theoretical 3D calculations for anisotropic Ag elasticity to quantify the frequency and intensity of the “rattling” mode and hence its BLS activity for different interparticle separations and matrix rigidity. Theoretically, a liquidlike environment, e.g., poly(isobutylene) (PIB) does not support rattling vibration of Ag dimers but unexpectedly hardening of the extremely confined graft melt renders both activation of the former and a frequency blue shift of the fundamental quadrupolar mode in the grafted nanoparticle Ag@PIB film

Optimizing CALIPSO Saharan dust retrievals

We demonstrate improvements in CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations) dust extinction retrievals over northern Africa and Europe when corrections are applied regarding the Saharan dust lidar ratio assumption, the separation of the dust portion in detected dust mixtures, and the averaging scheme introduced in the Level 3 CALIPSO product. First, a universal, spatially constant lidar ratio of 58 sr instead of 40 sr is applied to individual Level 2 dust-related backscatter products. The resulting aerosol optical depths show an improvement compared with synchronous and collocated AERONET (Aerosol Robotic Network) measurements. An absolute bias of the order of −0.03 has been found, improving on the statistically significant biases of the order of −0.10 reported in the literature for the original CALIPSO product. When compared with the MODIS (Moderate-Resolution Imaging Spectroradiometer) collocated aerosol optical depth (AOD) product, the CALIPSO negative bias is even less for the lidar ratio of 58 sr. After introducing the new lidar ratio for the domain studied, we examine potential improvements to the climatological CALIPSO Level 3 extinction product: (1) by introducing a new methodology for the calculation of pure dust extinction from dust mixtures and (2) by applying an averaging scheme that includes zero extinction values for the non-dust aerosol types detected. The scheme is applied at a horizontal spatial resolution of 1×1 degrees for ease of comparison with the instantaneous and collocated dust extinction profiles simulated by the BSC-DREAM8b dust model. Comparisons show that the extinction profiles retrieved with the proposed methodology reproduce the well-known model biases per subregion examined. The very good agreement of the proposed CALIPSO extinction product with respect to AERONET, MODIS and the BSC-DREAM8b dust model makes this dataset an ideal candidate for the provision of an accurate and robust multiyear dust climatology over northern Africa and Europe

How well do Earth system models reproduce the observed aerosol response to rapid emission reductions? A COVID-19 case study

The spring 2020 COVID-19 lockdowns led to a rapid reduction in aerosol and aerosol precursor emissions. These emission reductions provide a unique opportunity for model evaluation and to assess the potential efficacy of future emission control measures. We investigate changes in observed regional aerosol optical depth (AOD) during the COVID-19 lockdowns and use these observed anomalies to evaluate Earth system model simulations forced with COVID-19-like reductions in aerosols and greenhouse gases. Most anthropogenic source regions do not exhibit statistically significant changes in satellite retrievals of total or dust-subtracted AOD, despite the dramatic economic and lifestyle changes associated with the pandemic. Of the regions considered, only India exhibits an AOD anomaly that exceeds internal variability. Earth system models reproduce the observed responses reasonably well over India but initially appear to overestimate the magnitude of response in East China and when averaging over the Northern Hemisphere (0–70∘ N) as a whole. We conduct a series of sensitivity tests to systematically assess the contributions of internal variability, model input uncertainty, and observational sampling to the aerosol signal, and we demonstrate that the discrepancies between observed and simulated AOD can be partially resolved through the use of an updated emission inventory. The discrepancies can also be explained in part by characteristics of the observational datasets. Overall our results suggest that current Earth system models have potential to accurately capture the effects of future emission reductions.</p

The impact of using assimilated Aeolus wind data on regional WRF-Chem dust simulations

Land–atmosphere interactions govern the process of dust emission and transport. An accurate depiction of these physical processes within numerical weather prediction models allows for better estimating the spatial and temporal distribution of the dust burden and the characterisation of source and recipient areas. In the presented study, the ECMWF-IFS (European Centre for Medium-Range Weather Forecast – Integrated Forecasting System) outputs, produced with and without the assimilation of Aeolus quality-assured Rayleigh–clear and Mie–cloudy horizontal line-of-sight wind profiles, are used as initial or boundary conditions in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate 2-month periods in the spring and autumn of 2020, focusing on a case study in October. The experiments have been performed over the broader eastern Mediterranean and Middle East (EMME) region, which is frequently subjected to dust transport, as it encompasses some of the most active erodible dust sources. Aerosol- and dust-related model outputs (extinction coefficient, optical depth and concentrations) are qualitatively and quantitatively evaluated against ground- and satellite-based observations. Ground-based columnar and vertically resolved aerosol optical properties are acquired through AERONET sun photometers and PollyXT lidar, while near-surface concentrations are taken from EMEP. Satellite-derived vertical dust and columnar aerosol optical properties are acquired through LIVAS (LIdar climatology of Vertical Aerosol Structure) and MIDAS (ModIs Dust AeroSol), respectively. Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when WRF-Chem simulations are initialised with the meteorological fields of Aeolus wind profiles assimilated by the IFS. The improvement varies in space and time, with the most significant impact observed during the autumn months in the study region. Comparison with observation datasets saw a remarkable improvement in columnar aerosol optical depths, vertically resolved dust mass concentrations and near-surface particulate concentrations in the assimilated run against the control run. Reductions in model biases, either positive or negative, and an increase in the correlation between simulated and observed values was achieved for October 2020.</p

Direct radiative effects during intense Mediterranean desert dust outbreaks

The direct radiative effect (DRE) during 20 intense and widespread dust outbreaks, which affected the broader Mediterranean basin over the period March 2000–February 2013, has been calculated with the NMMB-MONARCH model at regional (Sahara and European continent) and short-term temporal (84 h) scales. According to model simulations, the maximum dust aerosol optical depths (AODs) range from  ∼  2.5 to  ∼  5.5 among the identified cases. At midday, dust outbreaks locally induce a NET (shortwave plus longwave) strong atmospheric warming (DREATM values up to 285 W m−2; Niger–Chad; dust AODs up to  ∼  5.5) and a strong surface cooling (DRENETSURF values down to −337 W m−2), whereas they strongly reduce the downward radiation at the ground level (DRESURF values down to −589 W m−2 over the Eastern Mediterranean, for extremely high dust AODs, 4.5–5). During night-time, reverse effects of smaller magnitude are found. At the top of the atmosphere (TOA), positive (planetary warming) DREs up to 85 W m−2 are found over highly reflective surfaces (Niger–Chad; dust AODs up to  ∼  5.5) while negative (planetary cooling) DREs down to −184 W m−2 (Eastern Mediterranean; dust AODs 4.5–5) are computed over dark surfaces at noon. Dust outbreaks significantly affect the mean regional radiation budget, with NET DREs ranging from −8.5 to 0.5 W m−2, from −31.6 to 2.1 W m−2, from −22.2 to 2.2 W m−2 and from −1.7 to 20.4 W m−2 for TOA, SURF, NETSURF and ATM, respectively. Although the shortwave DREs are larger than the longwave ones, the latter are comparable or even larger at TOA, particularly over the Sahara at midday. As a response to the strong surface day-time cooling, dust outbreaks cause a reduction in the regional sensible and latent heat fluxes by up to 45 and 4 W m−2, respectively, averaged over land areas of the simulation domain. Dust outbreaks reduce the temperature at 2 m by up to 4 K during day-time, whereas a reverse tendency of similar magnitude is found during night-time. Depending on the vertical distribution of dust loads and time, mineral particles heat (cool) the atmosphere by up to 0.9 K (0.8 K) during day-time (night-time) within atmospheric dust layers. Beneath and above the dust clouds, mineral particles cool (warm) the atmosphere by up to 1.3 K (1.2 K) at noon (night-time). On a regional mean basis, negative feedbacks on the total emitted dust (reduced by 19.5 %) and dust AOD (reduced by 6.9 %) are found when dust interacts with the radiation. Through the consideration of dust radiative effects in numerical simulations, the model positive and negative biases for the downward surface SW or LW radiation, respectively, with respect to Baseline Surface Radiation Network (BSRN) measurements, are reduced. In addition, they also reduce the model near-surface (at 2 m) nocturnal cold biases by up to 0.5 K (regional averages), as well as the model warm biases at 950 and 700 hPa, where the dust concentration is maximized, by up to 0.4 K. However, improvements are relatively small and do not happen in all episodes because other model first-order errors may dominate over the expected improvements, and the misrepresentation of the dust plumes' spatiotemporal features and optical properties may even produce a double penalty effect. The enhancement of dust forecasts via data assimilation techniques may significantly improve the results.The MDRAF project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 622662. Oriol Jorba and Sara Basart acknowledge the grant CGL2013-46736 and the AXA Research Fund. Carlos Pérez García-Pando acknowledges long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal programme (grant RYC-2015-18690) and grant CGL2017-88911-R of the Spanish Ministry of Economy and Competitiveness. The authors acknowledge support from the EU COST Action CA16202 “International Network to Encourage the Use of Monitoring and Forecasting Dust Products (InDust)”. Simulations were performed with the Marenostrum Supercomputer at the Barcelona Supercomputing Center (BSC). We would like to thank the principal investigators maintaining the BSRN sites used in the present work. The authors would like thank the Arnon Karnieli for his effort in establishing and maintaining SEDE_BOKER AERONET site.Peer ReviewedPostprint (published version

An Assessment of Atmospheric and Meteorological Factors Regulating Red Sea Phytoplankton Growth

This study considers the various factors that regulate nutrients supply in the Red Sea. Multi-sensor observation and reanalysis datasets are used to examine the relationships among dust deposition, sea surface temperature (SST), and wind speed, as they may contribute to anomalous phytoplankton blooms, through time-series and correlation analyses. A positive correlation was found at 0–3 months lag between chlorophyll-a (Chl-a) anomalies and dust anomalies over the Red Sea regions. Dust deposition process was further examined with dust aerosols’ vertical distribution using satellite lidar data. Conversely, a negative correlation was found at 0–3 months lag between SST anomalies and Chl-a that was particularly strong in the southern Red Sea during summertime. The negative relationship between SST and phytoplankton is also evident in the continuously low levels of Chl-a during 2015 to 2016, which were the warmest years in the region on record. The overall positive correlation between wind speed and Chl-a relate to the nutritious water supply from the Gulf of Aden to the southern Red Sea and the vertical mixing encountered in the northern part. Ocean Color Climate Change Initiative (OC-CCI) dataset experience some temporal inconsistencies due to the inclusion of different datasets. We addressed those issues in our analysis with a valid interpretation of these complex relationships