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Lin Y, Takano Y, Gu Y, Wang Y, Zhou S, Zhang T, Zhu K, Wang J, Zhao B, Chen G, Zhang D, Fu R, Seinfeld J. Characterization of the aerosol vertical distributions and their impacts on warm clouds based on multi-year ARM observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166582. [PMID: 37634734 DOI: 10.1016/j.scitotenv.2023.166582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 08/29/2023]
Abstract
Aerosol vertical distribution plays a crucial role in cloud development and thus precipitation since both aerosol indirect and semi-direct effects significantly depend on the relative position of aerosol layer in reference to cloud, but its precise influence on cloud remains unclear. In this study, we integrated multi-year Raman Lidar measurements of aerosol vertical profiles from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) facility with available Value-Added Products of cloud features to characterize aerosol vertical distributions and their impacts on warm clouds over the continental and marine ARM atmospheric observatories, i.e., Southern Great Plains (SGP) and Eastern North Atlantic (ENA). A unimodal seasonal distribution of aerosol optical depths (AODs) with a peak in summer is found at upper boundary layer over SGP, while a bimodal distribution is observed at ENA for the AODs at lower levels with a major winter-spring maximum. The diurnal mean of upper-level AOD at SGP shows a maximum in the early evening. According to the relative positions of aerosol layers to clouds we further identify three primary types of aerosol vertical distribution, including Random, Decreasing, and Bottom. It is found that the impacts of aerosols on cloud may or may not vary with aerosol vertical distribution depending on environmental conditions, as reflected by the wide variations of the relations between AOD and cloud properties. For example, as AOD increases, the liquid water paths (LWPs) tend to be reduced at SGP but enhanced at ENA. The relations of cloud droplet effective radius with AOD largely depend on aerosol vertical distributions, particularly showing positive values in the Random type under low-LWP condition (<50 g m-2). The distinct features of aerosol-cloud interactions in relation to aerosol vertical distribution are likely attributed to the continental-marine contrast in thermodynamic environments and aerosol conditions between SGP and ENA.
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Affiliation(s)
- Yun Lin
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States.
| | - Yoshihide Takano
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - Yu Gu
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - Yuan Wang
- Department of Earth System Science, Stanford University, Stanford, CA, United States
| | - Shujun Zhou
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - Tianhao Zhang
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - Kuilin Zhu
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - Jingyu Wang
- National Institute of Education, Nanyang Technological University, Singapore
| | - Bin Zhao
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States
| | - Gang Chen
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - Damao Zhang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States
| | - Rong Fu
- Department of Atmospheric and Oceanic Sciences, Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, United States
| | - John Seinfeld
- California Institute of Technology, Pasadena, CA 91125, United States
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Merdji AB, Xu X, Lu C, Habtemicheal BA, Li J. Accuracy assessment and climatology of MODIS aerosol optical properties over North Africa. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:13449-13468. [PMID: 36129653 DOI: 10.1007/s11356-022-22997-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 09/07/2022] [Indexed: 06/15/2023]
Abstract
In this study, the aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) product was compared with ground-based measurements at five sites of the Aerosol Robotic Network (AERONET) in North Africa. The MODIS AOD showed a good correlation coefficient of ~0.78, a very small mean bias error of 0.009, and a root mean square error of 0.126 with AERONET. The Dark Target/Deep Blue (DT/DB) algorithm showed better performance at low aerosol loading while underestimating AOD at higher aerosol loading, mainly for coarse-dominated aerosol types. This work also showed the benefits of using MODIS retrievals as a reliable data source for aerosols and providing a long-term aerosol type classification. The primary aerosol type is dust emitted from the Sahara Desert, and the dusty atmosphere becomes gradually mixed with pollution aerosols approaching the coastal region. The annual mean MODIS AOD at 550 nm and Ångström exponent at 412-650 nm (AE) ranged from 0.17 to 0.45 and from 0.13 to 1.25, respectively, in Algeria between 2001 and 2019. Lower AOD (< 0.22) and higher AE (> 1) were found in the northern region, while the highest AOD (0.35 to 0.45) and the lowest AE (< 0.25) were observed over the Tanezrouft desert in southern Algeria. The seasonal mean AOD was highest in summer, while the lowest was in winter due to very high easterly and northeasterly Harmattan surface wind over Zone of Chotts and the Tidikelt Depression, respectively. The negative AOD trends observed over Algeria could be partially connected to the decline (increase) in surface (850 hPa) winds over potential dust source areas in southern Algeria.
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Affiliation(s)
- Abou Bakr Merdji
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
| | - Xiaofeng Xu
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China.
| | - Chunsong Lu
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
| | - Birhanu Asmerom Habtemicheal
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
- Department of Physics, Wollo University, P.O. Box 1145, Dessie, Ethiopia
| | - Junjun Li
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
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Liu X, Chen S, Guo Z, Zhou H, Chen Y, Kang Y, Liu Q, Huang G, Liu T, Chen C, He Q. The influence of dusts on radiation and temperature over the eastern Asia with a regional climate model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 792:148351. [PMID: 34147814 DOI: 10.1016/j.scitotenv.2021.148351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/05/2021] [Accepted: 06/05/2021] [Indexed: 06/12/2023]
Abstract
In order to investigate the climate effects of dusts, a regional climate model (RegCM 4.6) with the dust scheme was used to simulate the direct radiative forcing and air temperature response at 2 m near surface of dusts over the eastern Asia. Two sets of experiments were conducted, one with and one without dust aerosols. The experiment covered the main dust occurrence months from March to May for 8 years (2011-2018), and the simulation results were evaluated against ground station, reanalysis and satellite data. The model captured the spatiotemporal distribution of dust AOD and mass loading over the eastern Asia. However, it tended to underestimate the dust AOD and mass loading over the downwind of the dust source region and the Taklimakan Desert, and overestimate them over the north Xinjiang. The direct net radiative forcing including shortwave and longwave was up to -20 W·m-2 at the surface and -10 W·m-2 at the TOA over the dust source region due to the dominant negative shortwave forcing. The only exception of positive forcing at the TOA was observed along the western boundaries of the Tibetan Plateau due to the semi-persistent ice and snow cover. The dusts tended to warm the atmosphere more than 18 W·m-2 and cool the surface locally up to -0.7 °C. Among the 5 sub-areas, the largest averaged regional direct radiative forcing induced by dusts appeared over the central Inner Mongolia in May with the value of -3.0 ± 2.1, -12.2 ± 4.1 and 9.2 ± 4.4 W·m-2 at the TOA, surface and in the atmosphere, respectively. The results indicated that the model simulation for dusts should be further improved and the dust effects should be included in the estimates of climate change over the eastern Asia.
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Affiliation(s)
- Xin Liu
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China
| | - Shuyi Chen
- College of Engineering, China University of Geosciences, Wuhan 430074, PR China
| | - Zijia Guo
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China
| | - Haijiang Zhou
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China
| | - Yonghang Chen
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China.
| | - Yanming Kang
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China.
| | - Qiong Liu
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China
| | - Guan Huang
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China
| | - Tongqiang Liu
- College of Environmental Science and Engineering, Donghua University, Shanghai 201620, PR China
| | - Chunmei Chen
- College of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou 310018, PR China
| | - Qing He
- Institute of Desert Meteorology China Meteorological Administration, Urumqi 830001, PR China
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Cheng Y, Dai T, Zhang H, Xin J, Chen S, Shi G, Nakajima T. Comparison and evaluation of the simulated annual aerosol characteristics over China with two global aerosol models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 763:143003. [PMID: 33168256 DOI: 10.1016/j.scitotenv.2020.143003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 08/01/2020] [Accepted: 10/06/2020] [Indexed: 06/11/2023]
Abstract
In this study, simulations of the annual mean aerosol budget, aerosol optical properties, and surface mass concentration in 2006 in China are performed with two aerosol interactive global atmosphere models, namely, the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) coupled with the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) and the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM) coupled with the Canadian Aerosol Module (CAM) online. The observed and simulated aerosol optical depths (AODs) exhibit similar horizontal distributions with large values over eastern and central China, and sulfate aerosols contribute the main differences between the AODs simulated by NICAM and BCC_AGCM. The simulated sulfate and dust surface concentrations are more consistent with observations compared with the simulated carbonaceous surface concentrations, and both models can reproduce the decreasing tendency of the sulfate surface concentration from urban sites to rural sites. However, the dust emission and deposition levels in China simulated by BCC_AGCM are three times as high as those simulated by NICAM, and the major sink processes of the anthropogenic sulfate, black carbon (BC), and organic carbon (OC) aerosols over China are very different between the two models. The emission and deposition results, which are closely related to the model-assumed aerosol particle size distribution, indicate that the current aerosol size distribution used in the two models should be further improved. The differences in dust emission parameterizations also lead significant discrepancies in aerosol cycles and the dust emission scheme is an important factor determining the magnitudes of global and regional dust emission fluxes.
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Affiliation(s)
- Yueming Cheng
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China; State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Tie Dai
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China; State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
| | - Hua Zhang
- Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081, China
| | - Jinyuan Xin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Shenwei Chen
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China; State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Guangyu Shi
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China; State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
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5
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Niu B, Zhang X, Piao S, Janssens IA, Fu G, He Y, Zhang Y, Shi P, Dai E, Yu C, Zhang J, Yu G, Xu M, Wu J, Zhu L, Desai AR, Chen J, Bohrer G, Gough CM, Mammarella I, Varlagin A, Fares S, Zhao X, Li Y, Wang H, Ouyang Z. Warming homogenizes apparent temperature sensitivity of ecosystem respiration. SCIENCE ADVANCES 2021; 7:7/15/eabc7358. [PMID: 33837072 PMCID: PMC8034862 DOI: 10.1126/sciadv.abc7358] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 02/24/2021] [Indexed: 06/02/2023]
Abstract
Warming-induced carbon loss through terrestrial ecosystem respiration (Re) is likely getting stronger in high latitudes and cold regions because of the more rapid warming and higher temperature sensitivity of Re (Q 10). However, it is not known whether the spatial relationship between Q 10 and temperature also holds temporally under a future warmer climate. Here, we analyzed apparent Q 10 values derived from multiyear observations at 74 FLUXNET sites spanning diverse climates and biomes. We found warming-induced decline in Q 10 is stronger at colder regions than other locations, which is consistent with a meta-analysis of 54 field warming experiments across the globe. We predict future warming will shrink the global variability of Q 10 values to an average of 1.44 across the globe under a high emission trajectory (RCP 8.5) by the end of the century. Therefore, warming-induced carbon loss may be less than previously assumed because of Q 10 homogenization in a warming world.
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Affiliation(s)
- Ben Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xianzhou Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Shilong Piao
- College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
| | - Ivan A Janssens
- Department of Biology, University of Antwerpen, Universiteitsplein 1, Wilrijk B-2610, Belgium
| | - Gang Fu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongtao He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yangjian Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Peili Shi
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Erfu Dai
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Chengqun Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jing Zhang
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Guirui Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Ming Xu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jianshuang Wu
- Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, 100081 Beijing, China
| | - Liping Zhu
- Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
| | - Ankur R Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Jiquan Chen
- Department of Geography, Michigan State University, East Lansing, MI 48823, USA
| | - Gil Bohrer
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Christopher M Gough
- Department of Biology, Virginia Commonwealth University, Richmond, VA 23284-2012, USA
| | - Ivan Mammarella
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, P.O. Box 68, Helsinki FI-00014, Finland
| | - Andrej Varlagin
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow 119071, Russia
| | - Silvano Fares
- National Research Council of Italy, Institute of BioEconomy, Via dei Taurini 19, 00100 Rome, Italy
| | - Xinquan Zhao
- Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China
| | - Yingnian Li
- Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China
| | - Huiming Wang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhu Ouyang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Chen S, Huang C, Kuo Y, Tseng Y, Gu Y, Earl K, Chen C, Choi Y, Liou K. Impacts of Saharan Mineral Dust on Air-Sea Interaction over North Atlantic Ocean Using a Fully Coupled Regional Model. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2021; 126:e2020JD033586. [PMID: 33816041 PMCID: PMC8008257 DOI: 10.1029/2020jd033586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/05/2020] [Accepted: 01/10/2021] [Indexed: 06/12/2023]
Abstract
This study examines the modifications of air-sea coupling processes by dust-radiation-cloud interactions over the North Atlantic Ocean using a high-resolution coupled atmosphere-wave-ocean-dust (AWOD) regional model. The dust-induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3-month numerical experiments are conducted, and they differ only in the activation and deactivation of dust-radiation-cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20-30 W m-2. Over the dust plume region, the dust effect creates a low-pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from -0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic.
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Affiliation(s)
- Shu‐Hua Chen
- Department of Land, Air, and Water ResourcesUniversity of CaliforniaDavisCAUSA
| | - Chu‐Chun Huang
- Department of Land, Air, and Water ResourcesUniversity of CaliforniaDavisCAUSA
| | - Yi‐Chun Kuo
- Institute of OceanographyNational Taiwan UniversityTaipeiTaiwan
| | - Yu‐Heng Tseng
- Institute of OceanographyNational Taiwan UniversityTaipeiTaiwan
| | - Yu Gu
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
- NASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Kenneth Earl
- Department of Land, Air, and Water ResourcesUniversity of CaliforniaDavisCAUSA
| | - Chih‐Ying Chen
- Department of Land, Air, and Water ResourcesUniversity of CaliforniaDavisCAUSA
- Research Center for Environmental ChangesAcademia SinicaTaipeiTaiwan
| | - Yonghan Choi
- Department of Land, Air, and Water ResourcesUniversity of CaliforniaDavisCAUSA
- Korea Polar Research InstituteIncheonSouth Korea
| | - Kuo‐Nan Liou
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
- NASA Goddard Space Flight CenterGreenbeltMDUSA
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Spatiotemporal Distribution of Major Aerosol Types over China Based on MODIS Products between 2008 and 2017. ATMOSPHERE 2020. [DOI: 10.3390/atmos11070703] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Knowledge of aerosol-type distribution is critical to the evaluation of aerosol–climate effects. However, research on aerosol-type distribution covering all is limited. This study characterized the spatiotemporal distribution of major aerosol types over China by using MODerate resolution Imaging Spectroradiometer (MODIS) products from 2008 to 2017. Two aerosol-type classification methods were combined to achieve this goal. One was for relatively high aerosol load (AOD ≥ 0.2) using aerosol optical depth (AOD) and aerosol relative optical depth (AROD) and the other was for low aerosol load (AOD < 0.2) using land use and population density information, which assumed that aerosols are closely related to local emissions. Results showed that the dominant aerosol-type distribution has a distinct spatial and temporal pattern. In western China, background aerosols (mainly dust/desert dust and continent aerosol) dominate with a combined occurrence ratio over 70% and they have slight variations on seasonal scale. While in eastern China, the dominant aerosols show strong seasonal variations. Spatially, mixed aerosols dominate most parts of eastern China in spring due to the influence of long-range transported dust from Taklamakan and Gobi desert and urban/industry aerosols take place in summer due to strong photochemical reactions. Temporally, mixed and urban/industry aerosols co-dominate eastern China.
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Lin W, Dai J, Liu R, Zhai Y, Yue D, Hu Q. Integrated assessment of health risk and climate effects of black carbon in the Pearl River Delta region, China. ENVIRONMENTAL RESEARCH 2019; 176:108522. [PMID: 31202046 DOI: 10.1016/j.envres.2019.06.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Revised: 05/27/2019] [Accepted: 06/03/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND Black carbon (BC) caused by incomplete combustion of fossil and bio-fuel has a dual effect on health and climate. There is a need for systematic approaches to evaluation of health outcomes and climate impacts relevant to BC exposure. OBJECTIVES We propose and illustrate for the first time, to our knowledge, an integrated analysis of a region-specific health model with climate change valuation module to quantify the health and climate consequences of BC exposure. METHODS Based on the data from regional air pollution monitoring stations from 2013 to 2014 in the Pearl River Delta region (PRD), China, we analyzed the carcinogenic and non-carcinogenic effects and the relative risk of cause-specific mortality due to BC exposure in three typical cities of the PRD (i.e. Guangzhou, Jiangmen and Huizhou). The radiative forcing (RF) and heating rate (HR) were calculated by the Fu-Liou-Gu (FLG) plane-parallel radiation model and the conversion of empirical formula. We further connected the health and climate impacts by calculating the excess mortalities attributed to climate warming due to BC. RESULTS Between 2013 and 2014, carcinogenic risks of adults and children due to BC exposure in the PRD were higher than the recommended limits (1 × 10-6 to 1 × 10-4), resulting in an excess of 4.82 cancer cases per 10,000 adults (4.82 × 10-4) and an excess of 1.97 cancer cases per 10,000 children (1.97 × 10-4). Non-carcinogenic risk caused by BC was not found. The relative risks of BC exposure on mortality were higher in winter and dry season. The atmospheric RFs of BC were 26.31 W m-2, 26.41 W m-2, and 22.45 W m-2 for Guangzhou, Jiangmen and Huizhou, leading to a warming of the atmosphere in the PRD. The estimated annual excess mortalities of climate warming due to BC were 5052 (95% CI: 1983, 8139), 5121 (95% CI: 2010, 8249) and 4363 (95% CI: 1712, 7032) for Guangzhou, Jiangmen and Huizhou, respectively. CONCLUSION Our estimates suggest that current levels of BC exposure in the PRD region posed a considerable risk to human health and the climate. Reduction of BC emission could lead to substantial health and climate co-benefits.
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Affiliation(s)
- Weiwei Lin
- School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jiajia Dai
- School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Run Liu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
| | - Yuhong Zhai
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China
| | - Dingli Yue
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China.
| | - Qiansheng Hu
- School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China.
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The cascade of global trade to large climate forcing over the Tibetan Plateau glaciers. Nat Commun 2019; 10:3281. [PMID: 31337754 PMCID: PMC6650455 DOI: 10.1038/s41467-019-10876-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 06/05/2019] [Indexed: 11/21/2022] Open
Abstract
Black carbon (BC) aerosols constitute unique and important anthropogenic climate forcers that potentially accelerate the retreat of glaciers over the Himalayas and Tibetan Plateau (HTP). Here we show that a large amount of BC emissions produced in India and China—a region of BC emissions to which the HTP is more vulnerable compared with other regions—are related to the consumption of goods and services in the USA and Europe through international trade. These processes lead to a virtual transport pathway of BC from distant regions to the HTP glaciers. From a consumption perspective, the contribution from India to the HTP glaciers shows a rapid increasing trend while the contributions from the USA, Europe, and China decreased over the last decade. International trade aggravates the BC pollution over the HTP glaciers and may cause significant climate change there. Global efforts toward reducing the cascading of BC emissions to Asia, especially the Indian subcontinent, are urgently needed. To trace the sources of Black Carbon being transported into the Tibetan Plateau is crucial for guiding an effective mitigation strategy. Here the authors utilized the adjoint of the Goddard Earth Observing System-Chem model and find that international trade aggravates the BC pollution over the HTP glacier regions and may cause significant climate change.
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Shi H, Jiang Z, Zhao B, Li Z, Chen Y, Gu Y, Jiang JH, Lee M, Liou KN, Neu JL, Payne VH, Su H, Wang Y, Witek M, Worden J. Modeling Study of the Air Quality Impact of Record-Breaking Southern California Wildfires in December 2017. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2019; 124:6554-6570. [PMID: 32455093 PMCID: PMC7243153 DOI: 10.1029/2019jd030472] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 05/17/2019] [Indexed: 05/22/2023]
Abstract
We investigate the air quality impact of record-breaking wildfires in Southern California during 5-18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high-resolution (375 × 375 m2) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM2.5) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM2.5 simulation results. Biases in PM2.5 simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14-day averaged PM2.5 concentrations by up to 231.2 μg/m3 over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire-induced PM2.5 accounts for 14-42% of the annual total PM2.5 exposure in areas impacted by the fire plumes.
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Affiliation(s)
- Hongrong Shi
- Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, CA, USA
| | - Zhe Jiang
- Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, CA, USA
| | - Bin Zhao
- Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, CA, USA
| | - Zhijin Li
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Yang Chen
- Department of Earth System Science, University of California, Irvine, CA, USA
| | - Yu Gu
- Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, CA, USA
| | - Jonathan H Jiang
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Meemong Lee
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Kuo-Nan Liou
- Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, CA, USA
| | - Jessica L Neu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Vivienne H Payne
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Hui Su
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Yuan Wang
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Marcin Witek
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - John Worden
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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Zhao B, Jiang JH, Diner DJ, Su H, Gu Y, Liou KN, Jiang Z, Huang L, Takano Y, Fan X, Omar AH. Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets. ATMOSPHERIC CHEMISTRY AND PHYSICS 2018; 18:11247-11260. [PMID: 31068974 PMCID: PMC6501591 DOI: 10.5194/acp-18-11247-2018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
The climatic and health effects of aerosols are strongly dependent on the intra-annual variations in their loading and properties. While the seasonal variations of regional aerosol optical depth (AOD) have been extensively studied, understanding the temporal variations in aerosol vertical distribution and particle types is also important for an accurate estimate of aerosol climatic effects. In this paper, we combine the observations from four satellite-borne sensors and several ground-based networks to investigate the seasonal variations of aerosol column loading, vertical distribution, and particle types over three populous regions: the Eastern United States (EUS), Western Europe (WEU), and Eastern and Central China (ECC). In all three regions, column AOD, as well as AOD at heights above 800 m, peaks in summer/spring, probably due to accelerated formation of secondary aerosols and hygroscopic growth. In contrast, AOD below 800m peaks in winter over WEU and ECC regions because more aerosols are confined to lower heights due to the weaker vertical mixing. In the EUS region, AOD below 800m shows two maximums, one in summer and the other in winter. The temporal trends in low-level AOD are consistent with those in surface fine particle (PM2.5) concentrations. AOD due to fine particles (< 0.7 μm diameter) is much larger in spring/summer than in winter over all three regions. However, the coarse mode AOD (> 1.4 μm diameter), generally shows small variability, except that a peak occurs in spring in the ECC region due to the prevalence of airborne dust during this season. When aerosols are classified according to sources, the dominant type is associated with anthropogenic air pollution, which has a similar seasonal pattern as total AOD. Dust and sea-spray aerosols in the WEU region peak in summer and winter, respectively, but do not show an obvious seasonal pattern in the EUS region. Smoke aerosols, as well as absorbing aerosols, present an obvious unimodal distribution with a maximum occurring in summer over the EUS and WEU regions, whereas they follow a bimodal distribution with peaks in August and March (due to crop residue burning) over the ECC region.
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Affiliation(s)
- Bin Zhao
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
| | - Jonathan H. Jiang
- Jet propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - David J. Diner
- Jet propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Hui Su
- Jet propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Yu Gu
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
| | - Kuo-Nan Liou
- Jet propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Zhe Jiang
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
| | - Lei Huang
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
| | - Yoshi Takano
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
| | - Xuehua Fan
- Joint Institute for Regional Earth System Science and Engineering and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA
| | - Ali H. Omar
- NASA Langley Research Center, Hampton, Virginia, USA
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Li Z, Guo J, Ding A, Liao H, Liu J, Sun Y, Wang T, Xue H, Zhang H, Zhu B. Aerosol and boundary-layer interactions and impact on air quality. Natl Sci Rev 2017. [DOI: 10.1093/nsr/nwx117] [Citation(s) in RCA: 387] [Impact Index Per Article: 55.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Air quality is concerned with pollutants in both the gas phase and solid or liquid phases. The latter are referred to as aerosols, which are multifaceted agents affecting air quality, weather and climate through many mechanisms. Unlike gas pollutants, aerosols interact strongly with meteorological variables with the strongest interactions taking place in the planetary boundary layer (PBL). The PBL hosting the bulk of aerosols in the lower atmosphere is affected by aerosol radiative effects. Both aerosol scattering and absorption reduce the amount of solar radiation reaching the ground and thus reduce the sensible heat fluxes that drive the diurnal evolution of the PBL. Moreover, aerosols can increase atmospheric stability by inducing a temperature inversion as a result of both scattering and absorption of solar radiation, which suppresses dispersion of pollutants and leads to further increases in aerosol concentration in the lower PBL. Such positive feedback is especially strong during severe pollution events. Knowledge of the PBL is thus crucial for understanding the interactions between air pollution and meteorology. A key question is how the diurnal evolution of the PBL interacts with aerosols, especially in vertical directions, and affects air quality. We review the major advances in aerosol measurements, PBL processes and their interactions with each other through complex feedback mechanisms, and highlight the priorities for future studies.
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Affiliation(s)
- Zhanqing Li
- State Key Laboratory of Earth Surface Processes and Resource Ecology, GCESS, Beijing Normal University, Beijing 1000875, China
- Department of Atmospheric and Oceanic Sciences, University of Maryland, MD 21029, USA
| | - Jianping Guo
- State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Aijun Ding
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Hong Liao
- School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianjun Liu
- Department of Atmospheric and Oceanic Sciences, University of Maryland, MD 21029, USA
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Tijian Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Huiwen Xue
- Department of Atmospheric and Oceanic Sciences, Peking University, Beijing 100871, China
| | - Hongsheng Zhang
- Department of Atmospheric and Oceanic Sciences, Peking University, Beijing 100871, China
| | - Bin Zhu
- School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Enhanced PM 2.5 pollution in China due to aerosol-cloud interactions. Sci Rep 2017; 7:4453. [PMID: 28667308 PMCID: PMC5493654 DOI: 10.1038/s41598-017-04096-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Accepted: 05/09/2017] [Indexed: 11/08/2022] Open
Abstract
Aerosol-cloud interactions (aerosol indirect effects) play an important role in regional meteorological variations, which could further induce feedback on regional air quality. While the impact of aerosol-cloud interactions on meteorology and climate has been extensively studied, their feedback on air quality remains unclear. Using a fully coupled meteorology-chemistry model, we find that increased aerosol loading due to anthropogenic activities in China substantially increases column cloud droplet number concentration and liquid water path (LWP), which further leads to a reduction in the downward shortwave radiation at surface, surface air temperature and planetary boundary layer (PBL) height. The shallower PBL and accelerated cloud chemistry due to larger LWP in turn enhance the concentrations of particulate matter with diameter less than 2.5 μm (PM2.5) by up to 33.2 μg m-3 (25.1%) and 11.0 μg m-3 (12.5%) in January and July, respectively. Such a positive feedback amplifies the changes in PM2.5 concentrations, indicating an additional air quality benefit under effective pollution control policies but a penalty for a region with a deterioration in PM2.5 pollution. Additionally, we show that the cloud processing of aerosols, including wet scavenging and cloud chemistry, could also have substantial effects on PM2.5 concentrations.
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Impacts of internally and externally mixed anthropogenic sulfate and carbonaceous aerosols on East Asian climate. ACTA ACUST UNITED AC 2011. [DOI: 10.1007/s13351-011-0508-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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15
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Gu Y, Liou KN, Ou SC, Fovell R. Cirrus cloud simulations using WRF with improved radiation parameterization and increased vertical resolution. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd014574] [Citation(s) in RCA: 77] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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16
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García OE, Expósito FJ, Díaz JP, Díaz AM. Radiative forcing under mixed aerosol conditions. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2009jd013625] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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17
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Lee WL, Liou KN, Hall A. Parameterization of solar fluxes over mountain surfaces for application to climate models. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd014722] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Chen X, Wu J. Numerical Simulation of the Direct Effects on Climate in East Asia Induced by Carbonaceous Aerosol. ACTA ACUST UNITED AC 2011. [DOI: 10.1016/j.proenv.2011.09.031] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Gu Y, Liou KN, Chen W, Liao H. Direct climate effect of black carbon in China and its impact on dust storms. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd013427] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Randles CA, Ramaswamy V. Absorbing aerosols over Asia: A Geophysical Fluid Dynamics Laboratory general circulation model sensitivity study of model response to aerosol optical depth and aerosol absorption. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2008jd010140] [Citation(s) in RCA: 84] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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