Recent Submissions

  • Parallel Hierarchical Matrix Technique to Approximate Large Covariance Matrices, Likelihood Functions and Parameter Identi fication

    Litvinenko, Alexander; Berikov, V.; Genton, Marc G.; Keyes, David E.; Kriemann, R.; Sun, Ying (2021-03-01) [Presentation]
    We develop the HLIBCov package, which is using parallel hierarchical (H-) matrices to: 1) Approximate large dense inhomogeneous covariance matrices with a log-linear computational cost and storage requirement. 2) Compute matrix-vector product, Cholesky factorization and inverse with a log-linear complexity. 3) Identify unknown parameters of the covariance function (variance, smoothness, and covariance length). These unknown parameters are estimated by maximizing the joint Gaussian log-likelihood function. To demonstrate the numerical performance, we identify three unknown parameters in an example with 2,000,000 locations on a PC-desktop.
  • Photoactive Layer Design Rules for Efficient and Stable Nonfullerene Solar Cells

    Baran, Derya (Fundació Scito, 2021-01-25) [Presentation]
    The efficiency of organic photovoltaics have seen a phenomenal increase in the last couple of years with the discovery of small molecule nonfullerene acceptors (NFAs). Molecular design strategies of the photoactive layer have boosted the performance with intelligent interface engineering beyond 18% so far. One way to boost the performance of the NFA devices is to add a third component in the photoactive layer, known as ternary approach. Most of the record efficiency devices have been reported adopting this strategy in the field of OPV. However, there is still a lack of understanding how to design a third component to achieve both efficient and stable devices with no burn-in at the first 100h of operation. In order to bring OPV technology into commercial applications in solar windows, building integrated PV, agrivoltaics or even in integrated circuits one would need not only efficient but also reliable devices. In this talk, I will focus on how to design the photoactive layer components and morphology so that we would have state-of-the-art performances along with improved photostability.
  • Ultrafast Energy Transfer Triggers Ionization Energy Offset Dependence of Quantum Efficiency in Low-bandgap Non-fullerene Acceptor Solar Cells

    Gorenflot, Julien; Laquai, Frédéric; Firdaus, Yuliar; De Castro, Catherine S. P.; Harrison, George; Khan, Jafar Iqbal; Markina, Anastasia; Balawi, Ahmed; Dela Peña, Top Archie; Liu, Wenlan; Liang, Ru-Ze; Sharma, Anirudh; Karuthedath, Safakath; Zhang, Weimin; Lin, Yuanbao; Alarousu, Erkki; Anjum, Dalaver H.; Beaujuge, Pierre; De Wolf, Stefaan; McCulloch, Iain; Anthopoulos, Thomas D.; Baran, Derya; Andrienko, Denis; Paleti, Sri Harish Kumar (Fundació Scito, 2021-01-25) [Presentation]
    In bulk heterojunction (BHJ) solar cells, the heterojunction interface between electron donor and acceptor drives the exciton-to-charge conversion, yet it also adds to energy and carrier losses. In principle, in low-bandgap non-fullerene acceptor (NFA) BHJs both electron affinity (EA) and ionization energy (IE) offsets should equally control the internal quantum efficiency (IQE). Allegedly, exciton-to-charge conversion is efficient even for close-to-zero offsets. Here, we rebut both notions and demonstrate that counterintuitively, the charge transfer from the exciton rather than the further charge separation is the limiting step controlled by the IE offset and secondly, that sizeable IE offsets are required to reach high exciton-to charge conversion efficiency. We find that efficient Förster Resonant Energy Transfer to the low bandgap acceptor precedes the charge transfer, which thus always occurs via hole transfer from the acceptor, hence the unimportance of the EA offset. We discuss the reasons for the threshold IE offset in terms of interface energetics and find that two physical parameters are sufficient to describe the evolution of the IQE with IE offset on a very large range of material systems. Our model also explain other experimental observations such as the difficulty of observing CT states emission and absorption in NFA based systems.
  • In Situ Investigation and Photovoltaic Devices: Sequential Formation of Tunable-Bandgap Mixed-Halide Lead-based Perovskites

    Barrit, Dounya; Zhang, Yalan; Tang, Ming-Chun; Li, Ruipeng; Smilgies, Detlef-M.; Liu, Shengzhong (Frank); Anthopoulos, Thomas D.; Amassian, Aram; Zhao, Kui (Fundació Scito, 2020-10-23) [Presentation]
    Inorganic−organic hybrid perovskite films of MAPb(IxBr1-x)3 (0 ˂ x ˂ 1) represents a path for efficient multi-junction or tandem solar cells due to their tunable bandgap (1.60-2.24 eV). Here, sequential solution deposition is adapted to enable a direct observation and a full understanding of the phase transformation from Pb(IxBr1-x)2 precursors to perovskites. This method has been successfully applied toward the fabrication of homogenous perovskite layers allowing an improvement of optoelectronic properties and device performance. In situ grazing incidence wide-angle X-ray scattering (GIWAXS) measurements are performed to present a detailed view of the effects of solvent, lead halide film solvation, and Br incorporation and alloying on the transformation behavior. Supported by other techniques such as in situ optical reflectance, absorption, x-ray diffraction, and steady-state/time-resolved photoluminescence, the measurements indicate a strong tendency of lead halide solvation prior to crystallization during solution-casting Pb(IxBr1-x)2 precursor from a dimethyl sulfoxide (DMSO) solvent with the Br alloying leading to weakened solvation of Pb(IxBr1-x)2×DMSO. We demonstrate a room temperature conversion of perovskite and high-quality films with tunable bandgap reaching a higher power conversion efficiency of 16.42% based on MAPb(I0.9Br0.1)3 due to highly efficient intramolecular exchange between DMSO molecules and organic cations. These findings highlight the benefits that solvation of the precursor phases, together with bromide incorporation can have on the microstructure, morphology and optoelectronic properties of these films, providing a viable alternative approach to one-step synthesis approach used for mixed ion perovskite thin films.
  • Joint seismic and electromagnetic inversion for reservoir mapping using a deep learning aided feature-oriented approach

    Zhang, Yanhui; Mazen Hittawe, Mohamad; Katterbauer, Klemens; Marsala, Alberto F.; Knio, Omar; Hoteit, Ibrahim (Society of Exploration Geophysicists, 2020-09-30) [Conference Paper]
    As more and more types of geophysical measurements informing about different characteristics of subsurface formations are available, effectively synergizing the information from these measurements becomes critical to enhance deep reservoir characterization, determine interwell fluid distribution and ultimately maximize oil recovery. In this study, we develop a feature-based model calibration workflow by combining the power of ensemble methods in data integration and deep learning techniques in feature segmentation. The performance of the developed workflow is demonstrated with a synthetic channelized reservoir model, in which crosswell seismic and electromagnetic (EM) data are jointly inverted.
  • Contact Linearizability of Scalar Ordinary Differential Equations of Arbitrary Order

    Liu, Yang; Lyakhov, Dmitry; Michels, Dominik L. (2020-09-15) [Presentation]
    We consider the problem of the exact linearization of scalar nonlinear ordinary differential equations by contact transformations. This contribution is extending the previous work by Lyakhov, Gerdt, and Michels addressing linearizability by means of point transformations. We have restricted ourselves to quasi-linear equations solved for the highest derivative with a rational dependence on the occurring variables. As in the case of point transformations, our algorithm is based on simple operations on Lie algebras such as computing the derived algebra and the dimension of the symmetry algebra. The linearization test is an efficient algorithmic procedure while finding the linearization transformation requires the computation of at least one solution of the corresponding system of the Bluman-Kumei equation.
  • FULLY PRINTED RADIO FREQUENCY ELECTRONICS: FLEXIBLE, WEARABLE AND DISPOSABLE

    Shamim, Atif (IEEE, 2020-09-08) [Presentation]
    With the advent of wearable sensors and internet of things (IoT), there is a new focus on electronics which can be bent so that they can be worn or mounted on non-planar objects. Due to large volume (billions of devices), there is a requirement that the cost is extremely low, to the extent that they become disposable. The flexible and low-cost aspects can be addressed through additive manufacturing technologies such as inkjet, screen and 3D printing. This talk introduces additive manufacturing as an emerging technique to realize low cost, flexible, wearable antennas and sensors for IoT applications. The ability to print electronics on unconventional mediums such as plastics, papers, and textiles has opened up a plethora of new applications. In this talk, various innovative antenna and sensor designs will be shown that have been realized through additive manufacturing. A multilayer process will be presented where dielectrics are also printed in addition to the metallic parts, thus demonstrating fully printed components. Many new functional inks and their use in tunable and reconfigurable RF components will be shown. In the end, many system level examples will be shown, primarily for wireless sensing applications. The promising results of these designs indicate that the day when electronics can be printed like newspapers and magazines through roll-to-roll and reelto-reel printing is not far away.
  • Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks

    Ben Hammouda, Chiheb; Ben Rached, Nadhir; Tempone, Raul (2020-08-20) [Presentation]
    The multilevel Monte Carlo (MLMC) method for continuous time Markov chains, first introduced by Anderson and Higham (SIAM Multiscal Model. Simul. 10(1), 2012), is a highly efficient simulation technique that can be used to estimate various statistical quantities for stochastic reaction networks (SRNs), and in particular for stochastic biological systems. Unfortunately, the robustness and performance of the multilevel method can be deteriorated due to the phenomenon of high kurtosis, observed at the deep levels of MLMC, which leads to inaccurate estimates for the sample variance. In this work, we address cases where the high kurtosis phenomenon is due to catastrophic coupling (characteristic of pure jump processes where coupled consecutive paths are identical in most of the simulations, while differences only appear in a very small proportion), and introduce a pathwise dependent importance sampling technique that improves the robustness and efficiency of the multilevel method. Our analysis, along with the conducted numerical experiments, demonstrates that our proposed method significantly reduces the kurtosis at the deep levels of MLMC, and also improves the strong convergence rate. Due to the complexity theorem of MLMC and given a pre-selected tolerance, TOL, this results in an improvement of the complexity from O(TOL^{-2} (log(TOL))^2) in the standard case to O(TOL^{-2}).
  • Numerical Smoothing with Multilevel Monte Carlo for Efficient Option Pricing and Density Estimation

    Bayer, Christian; Ben Hammouda, Chiheb; Tempone, Raul (2020-08-12) [Presentation]
    When approximating the expectation of a functional of a certain stochastic process, the robustness and performance of multilevel Monte Carlo (MLMC) method, may be highly deteriorated by the low regularity of the integrand with respect to the input parameters. To overcome this issue, a smoothing procedure is needed to uncover the available regularity and improve the performance of the MLMC estimator. In this work, we consider cases where we cannot perform an analytic smoothing. Thus, we introduce a novel numerical smoothing technique based on root-finding combined with a one dimensional integration with respect to a single well-chosen variable. Our study is motivated by option pricing problems and our main focus is on dynamics where a discretization of the asset price is needed. Through our analysis and numerical experiments, we demonstrate how numerical smoothing significantly reduces the kurtosis at the deep levels of MLMC, and also improves the strong convergence rate, when using Euler scheme. Due to the complexity theorem of MLMC, and given a pre-selected tolerance, $\text{TOL}$, this results in an improvement of the complexity from $\mathcal{O}\left(\text{TOL}^{-2.5}\right)$ in the standard case to $\mathcal{O}\left(\text{TOL}^{-2} \log(\text{TOL})^2\right)$. Moreover, we show how our numerical smoothing combined with MLMC enables us also to estimate density functions, which standard MLMC (without smoothing) fails to achieve.
  • Importance sampling for a robust and efficient multilevel Monte Carlo estimator

    Ben Hammouda, Chiheb; Ben Rached, Nadhir; Tempone, Raul (2020-08-11) [Presentation]
    The multilevel Monte Carlo (MLMC) method for continuous time Markov chains, first introduced by Anderson and Higham (SIAM Multiscal Model. Simul. 10(1), 2012), is a highly efficient simulation technique that can be used to estimate various statistical quantities for stochastic reaction networks (SRNs), and in particular for stochastic biological systems. Unfortunately, the robustness and performance of the multilevel method can be deteriorated due to the phenomenon of high kurtosis, observed at the deep levels of MLMC, which leads to inaccurate estimates for the sample variance. In this work, we address cases where the high kurtosis phenomenon is due to catastrophic coupling (characteristic of pure jump processes where coupled consecutive paths are identical in most of the simulations, while differences only appear in a very small proportion), and introduce a pathwise dependent importance sampling technique that improves the robustness and efficiency of the multilevel method. Our analysis, along with the conducted numerical experiments, demonstrates that our proposed method significantly reduces the kurtosis at the deep levels of MLMC, and also improves the strong convergence rate. Due to the complexity theorem of MLMC and given a pre-selected tolerance, TOL, this results in an improvement of the complexity from O(TOL^{-2} (log(TOL))^2) in the standard case to O(TOL^{-2}), which is the optimal complexity of the MLMC estimator. We achieve all these improvements with a negligible additional cost since our IS algorithm is only applied a few times across each simulated path.
  • Hierarchical Approximation Methods for Option Pricing and Stochastic Reaction Networks

    Ben Hammouda, Chiheb (2020-07-02) [Presentation]
    In biochemically reactive systems with small copy numbers of one or more reactant molecules, stochastic effects dominate the dynamics. In the first part of this thesis, we design novel efficient simulation techniques for a reliable and robust estimation of various statistical quantities for stochastic biological and chemical systems under the framework of Stochastic Reaction Networks (SRNs). In systems characterized by having simultaneously fast and slow timescales, existing discrete state-space stochastic path simulation methods can be very slow. In the first work in this part, we propose a novel hybrid multilevel Monte Carlo (MLMC), which uses a novel split-step implicit tau-leap scheme at the coarse levels, where the explicit scheme is not applicable due to numerical instability issues. Our analysis illustrates the advantage of our proposed method over MLMC combined with the explicit scheme. In a second work related to the first part, we solve another challenge present in this context called the high kurtosis phenomenon. We address cases where the high kurtosis, observed for the MLMC estimator, is due to catastrophic coupling. We propose a novel method that provides a more reliable and robust multilevel estimator. Our approach combines the MLMC method with a pathwise-dependent importance sampling technique for simulating the coupled paths. Through our theoretical estimates and numerical analysis, we show that our approach not only improves the robustness of the multilevel estimator by reducing the kurtosis significantly but also improves the strong convergence rate, and consequently, the complexity rate of the MLMC method. We achieve all these improvements with a negligible additional cost. In the second part of this thesis, we design novel numerical methods for pricing financial derivatives. Option pricing can be formulated as an integration problem, which is usually challenging due to a combination of two complications: 1) The high dimensionality of the input space, and 2) The low regularity of the integrand on the input parameters. We address these challenges by using different techniques for smoothing the integrand to uncover the available regularity and improve quadrature methods' convergence behavior. We develop different ways of smoothing that depend on the characteristics of the problem at hand. Then, we approximate the resulting integrals using hierarchical quadrature methods. In the first work in this part, we design a fast method for pricing European options under the rough Bergomi model. This model exhibits several numerical and theoretical challenges. As a consequence, classical numerical methods for pricing become either inapplicable or computationally expensive. In our approach, we first smoothen the integrand analytically and then use quadrature methods. These quadrature methods are coupled with Brownian bridge construction and Richardson extrapolation, to approximate the resulting integral. Numerical examples with different parameter constellations exhibit the performance of our novel methodology. Indeed, our hierarchical methods demonstrate substantial computational gains compared to the MC method, which is the prevalent method in this context. In the second work in this part, we consider cases where we cannot perform an analytic smoothing. Consequently, we perform a numerical smoothing based on root-finding techniques, with a particular focus on cases where discretization of the asset price dynamics is needed. We illustrate the advantage of our approach, which combines numerical smoothing with adaptive sparse grids' quadrature, over the MC approach. Furthermore, we demonstrate that our numerical smoothing procedure improves the robustness and the complexity rate of the MLMC estimator. Finally, our numerical smoothing, coupled with MLMC, enables us also to estimate density functions efficiently.
  • Assessment of Air Pollution in the Middle East Using Reanalyses Products and High-resolution WRF-Chem Simulations

    Ukhov, Alexander; Mostamandi, Suleiman; Flemming, Johannes; DaSilva, Arlindo; Krotkov, Nick; Li, Can; Alshehri, Yasser Mohammed; Anisimov, Anatolii; Fioletov, V.; McLinden, C.; Shevchenko, Illia; Stenchikov, Georgiy L. (Copernicus GmbH, 2020-03-09) [Presentation]
    The Middle East is notorious for high air pollution that affects both air-quality and regional climate. The Middle East generates about 30% of world dust annually and emits about 10% of anthropogenic SO$_{2}$. In this study we use Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA) data assimilation products, and a regional Weather Research and Forecasting model (10 km resolution) coupled with Chemistry (WRF-Chem) to evaluate natural and anthropogenic air pollution in the ME. The SO$_{2}$ anthropogenic emissions used in WRF-Chem are updated using the independent satellite SO$_{2}$ emission dataset obtained from the Ozone Monitoring Instrument (OMI) observations onboard NASA EOS Aura satellite. Satellite and ground-based aerosol optical depth (AOD) observations, as well as Particulate Matter (PM) and SO$_{2}$ in situ measurements for 2015-2016, were used for validation and model evaluation.  Although aerosol fields in regional WRF-Chem and global assimilation products are quite consistent, WRF-Chem, due to its higher spatial resolution and novel OMI SO$_{2}$ emissions, is preferable for analysis of regional air-quality over the ME. We found that conventional emission inventories (EDGAR-4.2, MACCity, and HTAP-2.2) have uncertainties in the location and magnitude of SO$_{2}$ sources in the ME and significantly underestimate SO$_{2}$ emissions in the Arabian Gulf. CAMS reanalysis tends to overestimate PM$_{2.5}$ and underestimate PM$_{10}$ concentrations. In the coastal areas, MERRA2 underestimates sulfate and tends to overestimate sea salt concentrations. The WRF-Chem’s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. The major contributor to PM (~75–95%) is mineral dust. In the ME urban centers and near oil recovery fields, non-dust aerosols (primarily sulfate) contribute up to 26% into PM$_{2.5}$. The contribution of sea salt into PM can rich up to 5%. The contribution of organic matter into PM prevails over black carbon. SO$_{2}$ surface concentrations in major ME cities frequently exceed European air-quality limits.
  • Test of Dust Emission Over the Middle East

    Mostamandi, Suleiman; Stenchikov, Georgiy L.; Ukhov, Alexander; Shevchenko, Illia; Engelbrecht, Johann; Alshehri, Yasser Mohammed; Anisimov, Anatolii (Copernicus GmbH, 2020-03-09) [Presentation]
    Abstract The dust emission simulated within the up-to-date global and regional models differs by almost an order of magnitude. The models are tuned to reproduce the observed aerosol optical depth (AOD) that, with some caveats, reflects the dust mass retained in the atmosphere. However, the amount of dust suspended in the atmosphere is controlled independently by the dust emission and deposition; therefore, only AOD observations are insufficient to constrain both these processes. To calculate the dust emission over the Middle East (ME), in this study, we employ dust deposition observations, AERONET AOD, micro-pulse lidar, and satellite observations to constrain the WRF-Chem simulations. The dust deposition is measured on a monthly bases for 2015-2019 using passive samplers over six sites over land and the sea. We compare the WRF-Chem simulations, conducted with 10-km grid spacing, with the recent MERRA-2 and CAMS reanalysis. WRF-Chem is configured with the GOCART dust scheme. We calculate the meteorological and aerosol initial and boundary conditions using the MERRA-2 reanalysis.  We evaluated the dust regional mass balance controlled by emission, deposition, and cross-boundary transport. The smallest dust particles are transported at vast distances while the heaviest ones deposit inside of the domain. Since the model accounts for dust particles with radii
  • Volcanic ash chemical aging from multiple observational constraints for the Pinatubo eruption

    Abdelkader, Mohamed; Stenchikov, Georgiy L.; Bruhl, Christoph; Lelieveld, Jos (Copernicus GmbH, 2020-03-09) [Presentation]
      Condensation of sulfuric acid formed from the co-injected sulfur dioxide on volcanic ash particles, so-called chemical aging, increases the particle size and changes their microphysical and optical properties. The larger aged particles have a higher removal rate, which reduces their lifetime. On the other hand, the aging increases the scattering cross-section, and therefore the ash optical depth is increasing due to aging. The uptake of sulfuric acid by volcanic ash delays the formation of new sulfate particles depending on the level of aging, which is characterized by the number of sulfuric acid layers coating a single ash particle (i.e., monolayers). Both the formation of sulfate aerosols and sulfuric acid uptake by ash particles affect the development of a volcanic plume and its radiative impact. We employ the ECHAM5/MESSy atmospheric chemistry general circulation model (EMAC) to simulate the chemical aging of volcanic ash in the 1991 Pinatubo eruption volcanic plume. We emit 17Mt of SO$_{2}$ and 75Mt of fine ash. Two aerosol modes represent ash size distribution: accumulation and coarse with 0.23 and 3.4 um median radii, respectively. We allow the sulfuric acid to condense on the ash particles and assume different levels of aging (from not aged to highly aged). We use independent observations for sulfur dioxide, volcanic ash mass, volcanic ash optical depth, and plume coverage area from the Advanced Very-High-Resolution Radiometer (AVHRR) observations and total optical depth from the Stratospheric Aerosol and Gas Experiment II (SAGE II). We constrain the number of monolayers on ash particles by testing simulated ash surface area and optical depth calculated within a fully coupled online stratospheric-tropospheric chemistry model against observations. The level of volcanic ash aging strongly affects the surface area of the volcanic ash plume, ranging from 3x10$^{6 }$km$^{2}$ to 6x10$^{6}$ km$^{2}$, compared to 3.8x10$^{6}$km$^{2}$ from AVHRR retrievals. The volcanic ash optical depth, averaged over the volcanic plume area, ranges between 2 and 3.6. Using five monolayer coating assumption allows us to better reproduce the observed SO$_{2}$ mass, its decay rate, total plume surface area, and ash optical depth. Most of the coarse ash particles are removed within a week after the eruption reducing the amount of sulfuric acid within the volcanic plume. The smaller particles have much longer residence time and continue to uptake sulfuric acid for more than three months.    
  • Interaction of the Vertical Profile of Dust Aerosols with Land/sea Breezes over the Eastern Coast of the Red Sea from LIDAR and High-resolution WRF-Chem Simulations

    Parajuli, Sagar P.; Stenchikov, Georgiy L.; Ukhov, Alexander; Shevchenko, Illia (Copernicus GmbH, 2020-03-09) [Presentation]
    <p>With the advances in modeling approaches, and the application of satellite and ground-based data in dust-related research, our understanding of the dust cycle is significantly improved in recent decades. However, two aspects of the dust cycle, the vertical profiles and diurnal cycles of dust aerosols have not been understood adequately, mainly due to the sparsity of observations. A micro-pulse LIDAR has been operating at the King Abdullah University of Science and Technology (KAUST) campus located on the east coast of the Red Sea (22.3N, 39.1E), measuring the backscattering from atmospheric aerosols at a high temporal resolution for several years since 2015. It is the only operating LIDAR system over the Arabian Peninsula. We use this LIDAR data together with other collocated observations and high-resolution WRF-Chem model simulations to study the 3-d structure of aerosols, with a focus on dust over the Red Sea Arabian coastal plains.&#160;</p><p>Firstly, we investigate the vertical profiles of aerosol extinction and concentration in terms of their seasonal and diurnal variability. Secondly, using the hourly model output and observations, we study the diurnal cycle of aerosols over the site. Thirdly, we explore the interactions between dust aerosols and land/sea breezes, which are the critical components of the local diurnal circulation in the region.&#160;</p><p>We found a substantial variation in the vertical profile of aerosols in different seasons. There is also a marked difference in the daytime and nighttime vertical distribution of aerosols in the study site, as shown by LIDAR data. A prominent dust layer is observed at ~5-7km at night in the LIDAR data, corresponding to the long-range transported dust of non-local origin. The vertical profiles of aerosol extinction are consistently reproduced in LIDAR, MERRA-2 reanalysis, and CALIOP data, as well as in WRF-Chem simulations in all seasons. Our results show that the sea breezes are much deeper (~1km) than the land breezes (~200m), and both of them prominently affect the distribution of dust aerosols over the study site. Sea breezes mainly trap the dust aerosols near the coast, brought by the northeasterly trade winds from inland deserts, causing elevated dust maxima at the height of ~1.5km. Also, sea and land breezes intensify dust emissions from the coastal region in daytime and nighttime, respectively. Such dust emissions caused by sea breezes and land breezes are most active in spring and winter. Finally, WRF-Chem successfully captures the onset, demise, and the height of some large-scale dust events as compared to LIDAR data qualitatively.&#160;</p>
  • Particulate Monitoring and Evaluation of the Low-cost Sensors Performance at the Middle East

    Alshehri, Yasser Mohammed; Alghamdi, Mansour; Khoder, Mamdouh; Almehmadi, Fahd; Bamuneef, Amer; Moathen, Rayan; Stenchikov, Georgiy L. (Copernicus GmbH, 2020-03-09) [Presentation]
    Key Words:Air Quality; Air Pollution Monitoring; Low-Cost Sensors; Reference Methods, Microsensors, Experimental Campaign&#160;Abstract: Air quality in the Middle East (ME) is strongly affected by desert dust besides anthropogenic pollutants. The health hazards associated with particulate matter (PM) are the most severe in this desert region. The enhancement of Air quality monitoring is needed to implement abatement strategies and stimulate environmental awareness among citizens. Several techniques are used to monitor PM concentration. The air quality monitoring stations (AQMS) equipped with certified instrumentation is the most reliable option. However, AQMSs are quite expensive and require regular maintenance. Another option is low-cost sensors (LCS) that seen as&#160;innovative&#160;tools for future smart cities. They are cost-effective and allow to increase the spatial coverage of air-quality measurements as the number of conventional AQMS is generally quite small, so the current density of the monitoring stations in the Middle East is low. In this work, we evaluated the PM air-quality climatology in the major cities in Saudi Arabia (Jeddah, Riyadh, and Dammam) for four years between 2016 and continued until 2020. We used the measurement data that were conducted by&#160;the Saudi Authority for Industrial Cities and Technology Zones (MODON)&#160;using certified reference AQMS installed inside the suburban areas of the three major cities in Saudi Arabia. Also, we tested the performance of the five LCS systems for eight months, starting in May 2019 and continued until January 2020. For this purpose, we set AQMS with the PM reference instrumentation (based on beta-ray absorption) side-by-side with five different LCS systems (based on light scattering) in the industrial part of Jeddah city. We collected, filtered, validated PM data, and applied standard measurement and calibration procedures.The AQMS measurements show that in Summer, the daily mean PM concentrations exceed the World Health Organization (WHO) limits for PM2.5 and PM10 almost every day in Jeddah, Riyadh, and Dammam. The WHO limits are also frequently violated in the winter months. The AQMS measurements reliably show dust storm spikes when PM pollution is extremely high while all the LCSs fail to capture these severe events. We found that LCS and AQMS PM measurements are poorly correlated in Summer, but show slightly better results in fair-weather Winter days when humidity and temperature are low. But they still cannot capture severe dust events.
  • Discrete changes in fault free-face roughness: constraining past earthquakes characteristics

    Zielke, Olaf; Benedetti, Lucilla; Mai, Paul Martin; Rizza, Magali; Fleury, Jules; Pousse Beltran, Lea; Puliti, Irene; Pace, Bruno (Copernicus GmbH, 2020-03-09) [Presentation]
    A driving motivator in many active tectonics studies is to learn more about the recurrence large and potentially destructive earthquakes, providing the means to assess the respective fault&#8217;s future seismic behavior. Doing so requires long records of earthquake recurrence. The lack of sufficiently long instrumental seismic records (that would be best suited for this task) has led to the development of other approaches that may constrain the recurrence of surface rupturing earthquakes along individual faults. These approaches take different forms, depending on the specific tectonic and geographic conditions of an investigated region. For example, around the Mediterranean Sea, we frequently find bedrock scarps along normal faults. Assuming that bedrock (i.e., fault free-face) exposure is caused by the occurrence of sub-sequent large earthquakes, we may measure certain rock properties to constrain the time and size of past earthquakes as well as the fault&#8217;s geologic slip-rate. A now-classic example in this regard is the measurement of $^{36}$Cl concentrations along exposed fault scarps in limestones. For the presented study, we looked at another property of the exposed fault free-face, namely its morphologic roughness. We aim to identify whether fault free-face roughness contains information to constrain earthquake occurrence and fault slip-rates following the assumption that &#160;sub-sequent exposure to the elements and sub-areal erosional conditions may leave a signal in how rough (or smooth) the fault free-face is (assuming a somewhat uniform pre-exposure roughness). Here, we present observations of fault free-face surface roughness for the Mt. Vettore fault (last ruptured in 2016) and the Rocca Preturo fault (The underlying models of fault free-face morphology were generated using the Structure-from-Motion approach and a large suite of unregistered optical images.). Employing different metrics to quantify morphologic roughness, we were indeed able to observe a) an increase in surface roughness with fault scarp height (i.e., longer exposure to sub-areal erosion causes higher roughness), and b) distinct (rather than gradual) changes in surface roughness, suggesting a correlation to individual exposure events such as earthquakes. Hence, fault free-face morphology of bedrock faults may serve as an additional metric to reconstruct earthquake recurrence patterns.
  • ENSO sensitivity to radiative forcing

    Predybaylo, Evgeniya; Stenchikov, Georgiy L.; Wittenberg, Andrew; Osipov, Sergey (Copernicus GmbH, 2020-03-09) [Presentation]
    To improve El Ni&#241;o / Southern Oscillation (ENSO) predictions and projections in a changing climate, it is essential to better understand ENSO&#8217;s sensitivities to external radiative forcings. Strong volcanic eruptions can help to clarify ENSO&#8217;s sensitivities, mechanisms, and feedbacks. Strong explosive volcanic eruptions inject millions of tons of sulfur dioxide into the stratosphere, where they are converted into sulfate aerosols. For equatorial volcanoes, these aerosols can spread globally, scattering and absorbing incoming sunlight, and inducing a global-mean surface cooling. Despite this global-mean cooling effect, paleo data confirm remarkable warming of the eastern equatorial Pacific in the two years after a tropical eruption, with a shift towards an El Ni&#241;o-like state. To illuminate this response and explain why it tends to occur during particular seasons and ENSO phases, we present a unified framework that includes the roles of the seasonal cycle, stochastic wind forcing, eruption magnitude, and various tropical Pacific climate feedbacks. Analyzing over 20,000 years of large-ensemble simulations from the GFDL-CM2.1 climate model forced by volcanic eruptions, we find that the ENSO response comprises both stochastic and deterministic components, which vary depending on the perturbation season and the ocean preconditioning. For boreal winter eruptions, stochastic dispersion largely obscures the deterministic response, being the largest for the strong El Ni&#241;o preconditioning. Deterministic El Ni&#241;o-like responses to summer eruptions are well seen on neutral ENSO and weak to moderate El Ni&#241;o preconditioning and grow with the eruption magnitude. The relative balance of these components determines the predictability and strength of the ENSO response. The results clarify why previous studies obtained seemingly conflicting results.
  • Rayleigh wave ellipticity measurements in the North Tanzanian Divergence (Eastern African Rift)

    Parisi, Laura; Berbellini, Andrea; Mai, Paul Martin (Copernicus GmbH, 2020-03-09) [Presentation]
    Rayleigh wave ellipticity depends, in theory, only on the Earth structure below a seismic station, offering the advantage of a &#8220;single-station&#8221; method to infer crustal properties. Therefore, ellipticity measurements can be used to construct pseudo 3-D shear velocity models of the earth structure using even seismic stations that did not record simultaneously.&#160;&#160; Based on that, we carried-out ellipticity measurements by using teleseismic waveforms recorded by the OPS seismic network we deployed at the western flank of the North Tanzanian Divergence between June 2016 and May 2018, covering 17 sites. We then expanded our measurements on the waveforms recorded by the adjacent CRAFTI seismic network from January 2013 and December 2014, available on IRIS, which comprised more than 30 sites.&#160; While the OPS network covers the transition between the Tanzania Craton and North Tanzanian Divergence, the CRAFTI network is entirely contained in the North Tanzanian Divergence. Therefore, the imaging that can be obtained by integrating the two asynchronous passive seismology experiments will help to better understand the dynamics of this segment of the eastern branch of the Eastern African Rift. Preliminary results show heterogeneity structure that are in agreement with previous tomographic studies based on ambient noise cross-correlation and body-waves arrival-times. In regions where previous seismological studies are not available, results match the known geological structure of the transition between the Tanzanian Craton and the North Tanzanian Divergence. This demonstrates that measurements of ellipticity can be a useful and integrative tool for earth structure imaging, especially at the edges of the active rifts where the seismicity is scarce.

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