Article
Engineering, Marine
Xiang Xing, Bainian Liu, Weimin Zhang, Jianping Wu, Xiaoqun Cao, Qunbo Huang
Summary: An adaptive scheme for Schur product covariance localization is proposed in this paper, which helps to significantly reduce spurious correlations and provide accurate covariances by adaptively obtaining the localization radius through a certain criterion of correlations with the background ensembles.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Meteorology & Atmospheric Sciences
Anthony T. Weaver, Marcin Chrust, Benjamin Menetrier, Andrea Piacentini
Summary: Modeling and cycling the background-error covariance matrix is an active area of research in data assimilation, especially when using filters to model background-error correlations. Updating the normalization factors on each assimilation cycle can be costly, but methods like randomization can provide accurate estimates. By approximating the normalization matrix as a separable product of two matrices, one for the horizontal and one for the vertical components, accurate estimates can be obtained with a large random sample.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
(2021)
Article
Environmental Sciences
Soon-Young Park, Uzzal Kumar Dash, Jinhyeok Yu
Summary: This study investigates the characteristics of background error covariance (BEC) in air quality models and compares the performance of different data assimilation (DA) methods in PM2.5 predictions. The results show that ensemble Kalman filter (EnKF) and ensemble square root filter (EnSRF) exhibit superior performances among all the methods.
Article
Meteorology & Atmospheric Sciences
Shujun Zhu, Bin Wang, Lin Zhang, Juanjuan Liu, Yongzhu Liu, Jiandong Gong, Shiming Xu, Yong Wang, Wenyu Huang, Li Liu, Yujun He, Xiangjun Wu, Bin Zhao, Fajing Chen
Summary: This study developed an ensemble four-dimensional variational (En4DVar) hybrid data assimilation system and evaluated its performance in terms of analysis quality and forecast skill. The results showed that the En4DVar system has the ability to improve the accuracy of forecasts, mainly due to the flow-dependent ensemble covariance provided by 4DEnVar.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Environmental Sciences
Max Yaremchuk
Summary: The upcoming wide-swath altimetry technology will provide a large volume of ocean surface data, but the errors in these data, especially in error covariance matrix processing, present a challenge. Research shows that an efficient approximation method using a sparse matrix can effectively handle the error covariance matrix with a minor reduction in accuracy.
Article
Environmental Sciences
Max Yaremchuk, Christopher Beattie, Gleb Panteleev, Joseph M. D'Addezio, Scott Smith
Summary: The upcoming technology of wide-swath altimetry from space will allow for better monitoring of the ocean surface, with 4-5 times better spatial resolution and 2-3 times better accuracy than traditional nadir altimeters. Correct treatment of correlated sea surface height errors caused by uncertainties in environmental conditions and on-board interferometer geometry is crucial for taking full advantage of this technology. This study explores the utility of a block-diagonal approximation to the SWOT precision matrix in order to reconstruct sea surface height variability in the region east of Greenland.
Article
Geosciences, Multidisciplinary
Shizhang Wang, Xiaoshi Qiao
Summary: Local DA is a method designed for current data assimilation schemes, combining hybrid and multiscale analyses with parallel computation to reduce errors and improve efficiency.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Astronomy & Astrophysics
Xiangjun Tian, Hongqin Zhang, Xiaobing Feng, Xin Li
Summary: The study introduces i4DVar approach, which corrects all errors as a whole simultaneously, addressing the limitations of the strongly constrained 4DVar and the weakly constrained 4DVar.
EARTH AND SPACE SCIENCE
(2021)
Article
Engineering, Environmental
Sibo Cheng, Jean-Philippe Argaud, Bertrand Iooss, Didier Lucor, Angelique Poncot
Summary: This paper discusses the uncertainty of error covariances in the state estimation of complex physical systems. It proposes a flexible combination of multiple covariance tuning algorithms to improve short-range flow forecast by applying online and offline procedures effectively.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2021)
Article
Meteorology & Atmospheric Sciences
Haohao Sun, Lili Lei, Zhengyu Liu, Liang Ning, Zhe-Min Tan
Summary: An analog offline ensemble Kalman filter (AOEnKF) is proposed, which constructs ensemble priors from a control climate simulation for each assimilation time based on an analog criterion using proxy observations. AOEnKF generates smaller posterior errors and requires much less computational cost compared to the online cycling EnKF (CEnKF). It has the advantages of having a more accurate prior ensemble mean and flow-dependent background error covariances compared to the commonly applied offline EnKF (OEnKF).
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Meteorology & Atmospheric Sciences
Diego S. Carrio, Craig H. Bishop, Shunji Kotsuki
Summary: In the past decade, replacing static climatological forecast error covariance models with hybrid error covariance models has led to significant forecast improvements at major forecasting centres. Empirical demonstrations show the relationship between actual forecast error covariance and corresponding ensemble covariance, with the hybrid model being a better approximation. The hybrid model accounts for the increasing function of horizontal separation distance in static covariance matrix weight and the decreasing function of small ensemble sizes and near-zero negative ensemble covariances in actual forecast error covariance, which can be improved by increasing the ensemble size.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
(2021)
Article
Engineering, Marine
Georgy Shapiro, Jose M. Gonzalez-Ondina
Summary: This paper presents a simple and computationally efficient method for creating a high-resolution regional model nested within a coarse-resolution, data-assimilating parent model. The method, called Nesting with Downscaling and Data Assimilation (NDA), reduces bias and root mean square errors (RMSE) of the child model and ensures it stays close to reality. By using a complete 3D set of output data from the parent model, the child model is able to assimilate observations and reduce errors without going through a complex assimilation process.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Geosciences, Multidisciplinary
Antoine Perrot, Olivier Pannekoucke, Vincent Guidard
Summary: This contribution proposes a new method for forecasting multivariate covariances for atmospheric chemistry using the parametric Kalman filter (PKF). The PKF modelizes the error covariance matrix with a covariance model relying on parameters and then calculates the dynamics. The PKF is extended from univariate to multivariate cases for chemical transport models and is compared with the ensemble Kalman filter (EnKF) in numerical experiments, showing accurate results.
NONLINEAR PROCESSES IN GEOPHYSICS
(2023)
Article
Computer Science, Artificial Intelligence
Sibo Cheng, Mingming Qiu
Summary: In this study, a data-driven approach based on LSTM recurrent neural networks is proposed to improve the accuracy and efficiency of observation covariance specification in data assimilation for dynamical systems. This novel method does not rely on prior error distribution knowledge or assumptions, leading to significant advantages in observation covariance specification, assimilation accuracy, and computational efficiency.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Sibo Cheng, Didier Lucor, Jean-Philippe Argaud
Summary: Accurate estimation of error covariances is crucial for efficient observation compression approaches in data assimilation. A new combination of covariance tuning algorithm and existing PCA-type data compression approaches is proposed to reduce computational cost in real-time updating. The method is validated on a shallow water twin experiment and applied to a challenging industrial hydrological model.
JOURNAL OF COMPUTATIONAL SCIENCE
(2021)
Article
Geosciences, Multidisciplinary
M. Bellacicco, M. Cornec, E. Organelli, R. J. W. Brewin, G. Neukermans, G. Volpe, M. Barbieux, A. Poteau, C. Schmechtig, F. D'Ortenzio, S. Marullo, H. Claustre, J. Pitarch
GEOPHYSICAL RESEARCH LETTERS
(2019)
Article
Meteorology & Atmospheric Sciences
Thibaut Lurton, Yves Balkanski, Vladislav Bastrikov, Slimane Bekki, Laurent Bopp, Pascale Braconnot, Patrick Brockmann, Patricia Cadule, Camille Contoux, Anne Cozic, David Cugnet, Jean-Louis Dufresne, Christian Ethe, Marie-Alice Foujols, Josefine Ghattas, Didier Hauglustaine, Rong-Ming Hu, Masa Kageyama, Myriam Khodri, Nicolas Lebas, Guillaume Levavasseur, Marion Marchand, Catherine Ottle, Philippe Peylin, Adriana Sima, Sophie Szopa, Remi Thieblemont, Nicolas Vuichard, Olivier Boucher
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2020)
Article
Oceanography
Ludivine Conte, Sophie Szopa, Olivier Aumont, Valerie Gros, Laurent Bopp
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2020)
Article
Environmental Sciences
Malika Kheireddine, Giorgio Dall'Olmo, Mustapha Ouhssain, George Krokos, Herve Claustre, Catherine Schmechtig, Antoine Poteau, Peng Zhan, Ibrahim Hoteit, Burton H. Jones
GLOBAL BIOGEOCHEMICAL CYCLES
(2020)
Article
Environmental Sciences
Amelie Saunier, Elena Ormeno, Damien Piga, Alexandre Armengaud, Christophe Boissard, Juliette Lathiere, Sophie Szopa, Anne-Cyrielle Genard-Zielinski, Catherine Fernandez
REGIONAL ENVIRONMENTAL CHANGE
(2020)
Article
Environmental Sciences
M. Cornec, H. Claustre, A. Mignot, L. Guidi, L. Lacour, A. Poteau, F. D'Ortenzio, B. Gentili, C. Schmechtig
Summary: Stratified oceanic systems have Deep Chlorophyll a Maximum (DCM) which can be either Deep Biomass Maximum (DBM) or Deep photoAcclimation Maximum (DAM). A global study using a dataset from over 500 Biogeochemical-Argo floats revealed that the seasonal dynamics of DCMs vary by region and are primarily influenced by light attenuation.
GLOBAL BIOGEOCHEMICAL CYCLES
(2021)
Article
Chemistry, Analytical
Quentin Jutard, Emanuele Organelli, Nathan Briggs, Xiaogang Xing, Catherine Schmechtig, Emmanuel Boss, Antoine Poteau, Edouard Leymarie, Marin Cornec, Fabrizio D'Ortenzio, Herve Claustre
Summary: This study proposes a quality-control procedure to address sensor issues and ensure the accuracy of Argo radiometry data. By conducting additional radiometric measurements at the parking depth and at night, the procedure achieved a high success rate in quality control across the globe. Furthermore, recommendations for future deployments include acquiring daily 1000 dbar measurements and one night profile per year.
Article
Environmental Sciences
Prodromos Zanis, Dimitris Akritidis, Steven Turnock, Vaishali Naik, Sophie Szopa, Aristeidis K. Georgoulias, Susanne E. Bauer, Makoto Deushi, Larry W. Horowitz, James Keeble, Philippe Le Sager, Fiona M. O'Connor, Naga Oshima, Konstantinos Tsigaridis, Twan van Noije
Summary: This study analyzes the impact of climate change on surface ozone from a global modeling perspective and finds that surface ozone concentrations are expected to decrease in regions remote from pollution sources due to global warming, while they may increase in regions close to pollution sources.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Geosciences, Multidisciplinary
Cyril Caram, Sophie Szopa, Anne Cozic, Slimane Bekki, Carlos A. Cuevas, Alfonso Saiz-Lopez
Summary: The atmospheric chemistry of halogenated species plays a significant role in the global chemical sink of tropospheric ozone and affects the oxidising capacity of the troposphere, notably by influencing the atmospheric lifetime of methane. This study implemented tropospheric sources and chemistry of halogens in the LMDZ-INCA model and evaluated their effects on the tropospheric ozone budget. The results showed that the model satisfactorily simulated the impact of halogens on the photo-oxidising system, with a significant decrease in ozone burden, OH, and NOx when tropospheric halogens were considered.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2023)
Article
Geosciences, Multidisciplinary
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurelien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, Jose M. Gutierrez, Johannes Guetschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valerie Masson-Delmotte, Panmao Zhai
Summary: IPCC assessments are a trusted source of scientific evidence for climate negotiations, but the time gap between report cycles creates an information gap. To fill this gap, we compile monitoring datasets based on IPCC report methods to provide annually updated reliable global climate indicators.
EARTH SYSTEM SCIENCE DATA
(2023)
Article
Environmental Sciences
Claudia Tebaldi, Gudfinna Adalgeirsdottir, Sybren Drijfhout, John Dunne, Tamsin L. Edwards, Erich Fischer, John C. Fyfe, Richard G. Jones, Robert E. Kopp, Charles Koven, Gerhard Krinner, Friederike Otto, Alex C. Ruane, Sonia I. Seneviratne, Jana Sillmann, Sophie Szopa, Prodromos Zanis
Summary: The study predicts the future evolution of key risks by analyzing their hazard components, which complements and enriches the treatment of these risks in previous literature. This is of great importance for assessing future risk severity.
CLIMATE RISK MANAGEMENT
(2023)
Article
Geosciences, Multidisciplinary
Pierre Sepulchre, Arnaud Caubel, Jean-Baptiste Ladant, Laurent Bopp, Olivier Boucher, Pascale Braconnot, Patrick Brockmann, Anne Cozic, Yannick Donnadieu, Jean-Louis Dufresne, Victor Estella-Perez, Christian Ethe, Frederic Fluteau, Marie-Alice Foujols, Guillaume Gastineau, Josefine Ghattas, Didier Hauglustaine, Frederic Hourdin, Masa Kageyama, Myriam Khodri, Olivier Marti, Yann Meurdesoif, Juliette Mignot, Anta-Clarisse Sarr, Jerome Servonnat, Didier Swingedouw, Sophie Szopa, Delphine Tardif
GEOSCIENTIFIC MODEL DEVELOPMENT
(2020)
Article
Geosciences, Multidisciplinary
Sophie Szopa, Remi Thieblemont, Slimane Bekki, Svetlana Botsyun, Pierre Sepulchre
CLIMATE OF THE PAST
(2019)
Review
Ecology
Raia Silvia Massad, Juliette Lathiere, Susanna Strada, Mathieu Perrin, Erwan Personne, Marc Stefanon, Patrick Stella, Sophie Szopa, Nathalie de Noblet-Ducoudre
Article
Ecology
Ludivine Conte, Sophie Szopa, Roland Seferian, Laurent Bopp
Article
Environmental Sciences
Muhammad Waqas, Majid Nazeer, Man Sing Wong, Wu Shaolin, Li Hon, Joon Heo
Summary: The socio-economic restriction measures implemented in the United States have significantly reduced nitrogen dioxide (NO2) emissions. The study highlights the impact of factors such as human mobility, population density, income, climate, and stationary sources on the reduction of NO2 at different stations. The research emphasizes the scientific impacts of the NO2 reduction and income inequality revealed by the pandemic on air quality and health disparities.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Guorui Zhi, Jinhong Du, Aizhong Chen, Wenjing Jin, Na Ying, Zhihui Huang, Peng Xu, Di Wang, Jinghua Ma, Yuzhe Zhang, Jiabao Qu, Hao Zhang, Li Yang, Zhanyun Ma, Yanjun Ren, Hongyan Dang, Jianglong Cui, Pengchuan Lin, Zhuoshi He, Jinmin Zhao, Shuo Qi, Weiqi Zhang, Wenjuan Zhao, Yingxin Li, Qian Liu, Chen Zhao, Yi Tang, Peng Wei, Jingxu Wang, Zhen Song, Yao Kong, Xiangzhe Zhu, Yi Shen, Tianning Zhang, Yangxi Chu, Xinmin Zhang, Jiafeng Fu, Qingxian Gao, Jingnan Hu, Zhigang Xue
Summary: An comprehensive emission inventory for China in 2019, which includes both air pollutants and greenhouse gases, was developed in this study. The inventory utilizes existing frameworks and data to provide comparable emissions data and demonstrates the relationship between emissions and economic development.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
I-Ting Ku, Yong Zhou, Arsineh Hecobian, Katherine Benedict, Brent Buck, Emily Lachenmayer, Bryan Terry, Morgan Frazier, Jie Zhang, Da Pan, Lena Low, Amy Sullivan, Jeffrey L. Collett Jr
Summary: Unconventional oil and natural gas development (UOGD) in the United States has expanded rapidly in recent decades, raising concerns about its impact on air quality. This study conducted extensive air monitoring during the development of several large well pads in Broomfield, Colorado, providing a unique opportunity to examine changes in local air toxics and VOC concentrations during well drilling and completions and production. The study identified significant increases in VOC concentrations during drilling operations, highlighting the importance of emissions from synthetic drilling mud. The findings suggest opportunities to mitigate emissions during UOGD operations.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Puji Lestari, Akbar R. Tasrifani, Wiranda I. Suri, Martin J. Wooster, Mark J. Grosvenor, Yusuke Fujii, Vissia Ardiyani, Elisa Carboni, Gareth Thomas
Summary: This study developed field emission factors for various pollutants in peatland fires and estimated the total emissions. Gas samples were collected using an analyzer, while particulate samples were collected using air samplers. The study found significant emissions of CO2, CO, PM2.5, carbon aerosols, water-soluble ions, and elements from the fires in Central Kalimantan, Indonesia in 2019.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Ligang Li, Yuyu Chen, Lu Fan, Dong Sun, Hu He, Yongshou Dai, Yong Wan, Fangfang Chen
Summary: A high-precision retrieval method based on a deep convolutional neural network and satellite remote sensing data is proposed to obtain accurate methane vertical profiles.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Hyung Joo Lee, Toshihiro Kuwayama, Michael Fitzgibbon
Summary: This study investigated the changes in nitrogen dioxide (NO2) air pollution levels and their disparities in California, U.S. during the pandemic of coronavirus disease 2019 (COVID-19). The results showed a decrease in NO2 concentrations, especially in urban and high-traffic areas. However, socially vulnerable populations still experienced higher levels of NO2 exposure. The study suggests that reducing NO2 disparities, particularly racial inequity, can be achieved through continued regulatory actions targeting traffic-related NOx emissions.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Maria Chiara Pietrogrande, Beatrice Biffi, Cristina Colombi, Eleonora Cuccia, Umberto Dal Santo, Luisa Romanato
Summary: This study investigates the chemical composition and oxidative potential of PM10 particles in the Po Valley, Italy, and demonstrates the impact of high levels of atmosphere ammonia. The rural area had significantly higher ammonia concentrations compared to the urban site, resulting in higher levels of secondary inorganic aerosol. Although the SIA components did not contribute significantly to the PM10 oxidative reactivity, they were correlated with the oxidative potential measurements. This suggests that the contribution of SIA to PM oxidative toxicity cannot be ignored.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Natalie Allen, Jan Gacnik, Sarrah M. Dunham-Cheatham, Mae Sexauer Gustin
Summary: Accurate measurement of atmospheric reactive mercury is challenging due to its reactivity and low concentrations. The University of Nevada, Reno Reactive Mercury Active System (RMAS) has been shown to be more accurate than the industry standard, but has limitations including long time resolution and sampling biases. Increasing the sampling flow rate negatively affected RM concentrations, but did not impact the chemical composition of RM captured on membranes.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Chin-Yu Hsu, Wei-Ting Hsu, Ching-Yi Mou, Pei-Yi Wong, Chih-Da Wu, Yu-Cheng Chen
Summary: This study estimated the daily exposure concentrations of PM2.5 for elderly individuals residing in different regions of Taiwan using land use regression with machine learning (LUR_ML) and microenvironmental exposure (ME) models. The accuracy of the models varied across regions, with the ME models exhibiting higher predictions and lower biases. The use of region-specific microenvironmental measurements in the ME model showed potential for accurate prediction of personal PM2.5 exposure.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Xiaohan Si, Kerrie Mengersen, Chuchu Ye, Wenbiao Hu
Summary: This study found that there is an interactive effect between air pollutants and weather factors, which significantly affects influenza transmission. Future research should consider the interactive effects between pollutants and temperature or humidity to evaluate the environment-influenza association.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Luxi Xu, Ruijun Xu, Yunshao Ye, Rui Wang, Jing Wei, Chunxiang Shi, Qiaoxuan Lin, Ziquan Lv, Suli Huang, Qi Tian, Yuewei Liu
Summary: This study aimed to evaluate the impact of ambient air pollution on hospital admissions for angina. The results showed that exposure to ambient particulate matter, sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone are associated with an increased risk of hospital admissions for angina. The association with nitrogen dioxide exposure was found to be the strongest.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Xinyu Yu, Man Sing Wong, Majid Nazeer, Zhengqiang Li, Coco Yin Tung Kwok
Summary: This study proposes a novel method to address the challenge of missing values in satellite-derived AOD products and creates a comprehensive daily AOD dataset for the Guangdong-Hong Kong-Macao Greater Bay Area. By reconstructing missing values and developing a new model, the derived dataset outperforms existing products and agrees well with ground-based observations. Additionally, the dataset exhibits consistent temporal patterns and more spatial details.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Yidan Zhang, Yifan Xu, Bo Peng, Wu Chen, Xiaoyu Cui, Tianle Zhang, Xi Chen, Yuan Yao, Mingjin Wang, Junyi Liu, Mei Zheng, Tong Zhu
Summary: This study developed a sensitive method to measure the metallic components of atmospheric fine particulate matter (PM2.5) and compared the results with different analysis methods. The concentrations of metallic components in personal PM2.5 samples were found to be significantly different from corresponding fixed-site samples. Personal sampling can reduce exposure misclassifications, and measuring metallic components is useful for exploring health risks and identifying sources of PM2.5.
ATMOSPHERIC ENVIRONMENT
(2024)
Review
Environmental Sciences
Jamie Leonard, Lea Ann El Rassi, Mona Abdul Samad, Samantha Prehn, Sanjay K. Mohanty
Summary: Increasing concentrations of microplastics in the Earth's atmosphere could have adverse effects on ecosystems and human health. The deposition rate of airborne microplastics is influenced by both land use and climate, and a global analysis suggests that climate may have a greater impact on the concentration and deposition rate of microplastics than land use.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Tian Zhou, Xiaowen Zhou, Zining Yang, Carmen Cordoba-Jabonero, Yufei Wang, Zhongwei Huang, Pengbo Da, Qiju Luo, Zhijuan Zhang, Jinsen Shi, Jianrong Bi, Hocine Alikhodja
Summary: This study investigated the long-range transport and effects of North African and Middle Eastern dust in East Asia using lidar observations and model simulations. The results showed that the dust originated from multiple sources and had a long transport time. The vertical distribution of the dust was found to be crucial for assessing its impacts.
ATMOSPHERIC ENVIRONMENT
(2024)