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Meng J, Huang Y, Leung DM, Li L, Adebiyi AA, Ryder CL, Mahowald NM, Kok JF. Improved Parameterization for the Size Distribution of Emitted Dust Aerosols Reduces Model Underestimation of Super Coarse Dust. GEOPHYSICAL RESEARCH LETTERS 2022; 49:e2021GL097287. [PMID: 35866061 PMCID: PMC9286626 DOI: 10.1029/2021gl097287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/28/2022] [Accepted: 04/05/2022] [Indexed: 06/15/2023]
Abstract
Aircraft measurement campaigns have revealed that super coarse dust (diameter >10 μm) surprisingly accounts for approximately a quarter of aerosols by mass in the atmosphere. However, most global aerosol models either underestimate or do not include super coarse dust abundance. To address this problem, we use brittle fragmentation theory to develop a parameterization for the emitted dust size distribution that includes emission of super coarse dust. We implement this parameterization in the Community Earth System Model (CESM) and find that it brings the model in good agreement with aircraft measurements of super coarse dust close to dust source regions. However, the CESM still underestimates super coarse dust in dust outflow regions. Thus, we conclude that the model underestimation of super coarse atmospheric dust is in part due to the underestimation of super coarse dust emission and likely in part due to errors in deposition processes.
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Affiliation(s)
- Jun Meng
- Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
| | - Yue Huang
- Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
- Now at Earth InstituteColumbia UniversityNew YorkNYUSA
- Now at NASA Goddard Institute for Space StudiesNew YorkNYUSA
| | - Danny M. Leung
- Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
| | - Longlei Li
- Department of Earth and Atmospheric SciencesCornell UniversityIthacaNYUSA
| | - Adeyemi A. Adebiyi
- Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
- Now at Department of Life & Environmental SciencesUniversity of CaliforniaMercedCAUSA
| | | | | | - Jasper F. Kok
- Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesCAUSA
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Evaluation of Nine Operational Models in Forecasting Different Types of Synoptic Dust Events in the Middle East. GEOSCIENCES 2021. [DOI: 10.3390/geosciences11110458] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
This study investigates four types of synoptic dust events in the Middle East region, including cyclonic, pre-frontal, post-frontal and Shamal dust storms. For each of these types, three intense and pervasive dust events are analyzed from a synoptic meteorological and numerical simulation perspective. The performance of 9 operational dust models in forecasting these dust events in the Middle East is qualitatively and quantitatively evaluated against Terra-MODIS observations and AERONET measurements during the dust events. The comparison of model AOD outputs with Terra-MODIS retrievals reveals that despite the significant discrepancies, all models have a relatively acceptable performance in forecasting the AOD patterns in the Middle East. The models enable to represent the high AODs along the dust plumes, although they underestimate them, especially for cyclonic dust storms. In general, the outputs of the NASA-GEOS and DREAM8-MACC models present greater similarity with the satellite and AERONET observations in most of the cases, also exhibiting the highest correlation coefficient, although it is difficult to introduce a single model as the best for all cases. Model AOD predictions over the AERONET stations showed that DREAM8-MACC exhibited the highest R2 of 0.78, followed by NASA_GEOS model (R2 = 0.74), which both initially use MODIS data assimilation. Although the outputs of all models correspond to valid time more than 24 h after the initial time, the effect of data assimilation on increasing the accuracy is important. The different dust emission schemes, soil and vegetation mapping, initial and boundary meteorological conditions and spatial resolution between the models, are the main factors influencing the differences in forecasting the dust AODs in the Middle East.
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Kok JF, Adebiyi AA, Albani S, Balkanski Y, Checa-Garcia R, Chin M, Colarco PR, Hamilton DS, Huang Y, Ito A, Klose M, Leung DM, Li L, Mahowald NM, Miller RL, Obiso V, García-Pando CP, Rocha-Lima A, Wan JS, Whicker CA. Improved representation of the global dust cycle using observational constraints on dust properties and abundance. ATMOSPHERIC CHEMISTRY AND PHYSICS 2021; 21:8127-8167. [PMID: 37649640 PMCID: PMC10466066 DOI: 10.5194/acp-21-8127-2021] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.
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Affiliation(s)
- Jasper F. Kok
- Department of Atmospheric and Oceanic Sciences, University
of California, Los Angeles, CA 90095, USA
| | - Adeyemi A. Adebiyi
- Department of Atmospheric and Oceanic Sciences, University
of California, Los Angeles, CA 90095, USA
| | - Samuel Albani
- Department of Environmental and Earth Sciences, University
of Milano-Bicocca, Milano, Italy
- Laboratoire des Sciences du Climat et de
l’Environnement, CEA-CNRS-UVSQ-UPSaclay, Gif-sur-Yvette, France
| | - Yves Balkanski
- Laboratoire des Sciences du Climat et de
l’Environnement, CEA-CNRS-UVSQ-UPSaclay, Gif-sur-Yvette, France
| | - Ramiro Checa-Garcia
- Laboratoire des Sciences du Climat et de
l’Environnement, CEA-CNRS-UVSQ-UPSaclay, Gif-sur-Yvette, France
| | - Mian Chin
- Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard
Space Flight Center, Greenbelt, MD 20771, USA
| | - Peter R. Colarco
- Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard
Space Flight Center, Greenbelt, MD 20771, USA
| | - Douglas S. Hamilton
- Department of Earth and Atmospheric Sciences, Cornell
University, Ithaca, NY 14850, USA
| | - Yue Huang
- Department of Atmospheric and Oceanic Sciences, University
of California, Los Angeles, CA 90095, USA
| | - Akinori Ito
- Yokohama Institute for Earth Sciences, JAMSTEC, Yokohama,
Kanagawa 236-0001, Japan
| | - Martina Klose
- Barcelona Supercomputing Center (BSC), 08034 Barcelona,
Spain
| | - Danny M. Leung
- Department of Atmospheric and Oceanic Sciences, University
of California, Los Angeles, CA 90095, USA
| | - Longlei Li
- Department of Earth and Atmospheric Sciences, Cornell
University, Ithaca, NY 14850, USA
| | - Natalie M. Mahowald
- Department of Earth and Atmospheric Sciences, Cornell
University, Ithaca, NY 14850, USA
| | - Ron L. Miller
- NASA Goddard Institute for Space Studies, New York NY10025
USA
| | - Vincenzo Obiso
- Barcelona Supercomputing Center (BSC), 08034 Barcelona,
Spain
- NASA Goddard Institute for Space Studies, New York NY10025
USA
| | - Carlos Pérez García-Pando
- Barcelona Supercomputing Center (BSC), 08034 Barcelona,
Spain
- ICREA, Catalan Institution for Research and Advanced
Studies, 08010 Barcelona, Spain
| | - Adriana Rocha-Lima
- Physics Department, UMBC, Baltimore, Maryland, USA
- Joint Center Joint Center for Earth Systems Technology,
UMBC, Baltimore, Maryland, USA
| | - Jessica S. Wan
- Department of Earth and Atmospheric Sciences, Cornell
University, Ithaca, NY 14850, USA
| | - Chloe A. Whicker
- Department of Atmospheric and Oceanic Sciences, University
of California, Los Angeles, CA 90095, USA
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Yuan T, Yu H, Chin M, Remer LA, McGee D, Evan A. Anthropogenic Decline of African Dust: Insights From the Holocene Records and Beyond. GEOPHYSICAL RESEARCH LETTERS 2020; 47:e2020GL089711. [PMID: 33281243 PMCID: PMC7685148 DOI: 10.1029/2020gl089711] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 10/14/2020] [Accepted: 10/16/2020] [Indexed: 05/22/2023]
Abstract
African dust exhibits strong variability on a range of time scales. Here we show that the interhemispheric contrast in Atlantic SST (ICAS) drives African dust variability at decadal to millennial timescales, and the strong anthropogenic increase of the ICAS in the future will decrease African dust loading to a level never seen during the Holocene. We provide a physical framework to understand the relationship between the ICAS and African dust activity: positive ICAS anomalies push the Intertropical Convergence Zone (ITCZ) northward and decrease surface wind speed over African dust source regions, which reduces dust emission and transport. It provides a unified framework for and is consistent with relationships in the literature. We find strong observational and proxy-record support for the ICAS-ITCZ-dust relationship during the past 160 and 17,000 years. Model-projected anthropogenic increase of the ICAS will reduce African dust by as much as 60%, which has broad consequences.
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Affiliation(s)
- Tianle Yuan
- Earth Sciences DivisionNASA Goddard Space Flight CenterGreenbeltMDUSA
- Joint Center for Earth Systems TechnologyUniversity of Maryland at Baltimore CountyBaltimoreMDUSA
| | - Hongbin Yu
- Earth Sciences DivisionNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Mian Chin
- Earth Sciences DivisionNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Lorraine A. Remer
- Joint Center for Earth Systems TechnologyUniversity of Maryland at Baltimore CountyBaltimoreMDUSA
| | - David McGee
- Department of Earth, Atmosphere, and Planetary SciencesMassachusetts Institute of TechnologyBostonMAUSA
| | - Amato Evan
- Scrips Institute of OceanographyUniversity of CaliforniaSan DiegoCAUSA
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RANS Simulation of Local Strong Sandstorms Induced by a Cold Pool with Vorticity. ATMOSPHERE 2020. [DOI: 10.3390/atmos11040321] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Local strong sandstorms (LSSs) in northwestern China often occur suddenly in tens of minutes during the late afternoon and by dusk. Observations and theoretical studies have shown the trigger role of cold-air pools over desert areas for the occurrence of LSS. In this study, a numerical heat convection model was established to simulate an LSS that was induced by a single cold pool with vertical helicity to study the evolution process. The Reynolds averaged Navier–Stokes (RANS) method was used for the numerical calculation to illustrate different stages of the evolution process of an LSS. Results show that after the intrusion of a cold pool into the upper region of the surface convective mixing layer, descending of the cold air would lead to the downward transport of vorticity, enabling thermal convection cells in the mixing layer to become swirling convection cells. After LSS is fully developed, there occurs many subvortices (secondary vortices) in the convection field. The velocity at different altitudes over selected positions in the calculation domain is consistent with the "lobe" shape of an LSS. The secondary vortices cause quick and huge energy dissipation and the decay of the LSS. These results are consistent with observations and indicate the crucial effect of convection cells structure in the mixing layer and the cold pool in the upper layer on the formation of LSS.
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Pope RJ, Marsham JH, Knippertz P, Brooks ME, Roberts AJ. Identifying errors in dust models from data assimilation. GEOPHYSICAL RESEARCH LETTERS 2016; 43:9270-9279. [PMID: 27840459 PMCID: PMC5082526 DOI: 10.1002/2016gl070621] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Revised: 08/12/2016] [Accepted: 08/14/2016] [Indexed: 06/06/2023]
Abstract
Airborne mineral dust is an important component of the Earth system and is increasingly predicted prognostically in weather and climate models. The recent development of data assimilation for remotely sensed aerosol optical depths (AODs) into models offers a new opportunity to better understand the characteristics and sources of model error. Here we examine assimilation increments from Moderate Resolution Imaging Spectroradiometer AODs over northern Africa in the Met Office global forecast model. The model underpredicts (overpredicts) dust in light (strong) winds, consistent with (submesoscale) mesoscale processes lifting dust in reality but being missed by the model. Dust is overpredicted in the Sahara and underpredicted in the Sahel. Using observations of lighting and rain, we show that haboobs (cold pool outflows from moist convection) are an important dust source in reality but are badly handled by the model's convection scheme. The approach shows promise to serve as a useful framework for future model development.
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Affiliation(s)
- R. J. Pope
- Institute for Atmospheric and Climate ScienceUniversity of LeedsLeedsUK
- National Centre for Earth ObservationUniversity of LeedsLeedsUK
| | - J. H. Marsham
- Institute for Atmospheric and Climate ScienceUniversity of LeedsLeedsUK
- National Centre for Atmospheric ScienceUniversity of LeedsLeedsUK
| | - P. Knippertz
- Institute of Meteorology and Climate ResearchKarlsruhe Institute of TechnologyKarlsruheGermany
| | | | - A. J. Roberts
- Institute for Atmospheric and Climate ScienceUniversity of LeedsLeedsUK
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