Zhou Chunhong, Rao Xiaoqin, Sheng Li, et al. Application of scale-adaptive dust emission scheme to CMA-CUACE/Dust. J Appl Meteor Sci, 2024, 35(4): 400-413. DOI:  10.11898/1001-7313.20240402.
Citation: Zhou Chunhong, Rao Xiaoqin, Sheng Li, et al. Application of scale-adaptive dust emission scheme to CMA-CUACE/Dust. J Appl Meteor Sci, 2024, 35(4): 400-413. DOI:  10.11898/1001-7313.20240402.

Application of Scale-adaptive Dust Emission Scheme to CMA-CUACE/Dust

DOI: 10.11898/1001-7313.20240402
  • Received Date: 2024-04-01
  • Rev Recd Date: 2024-06-12
  • Publish Date: 2024-07-31
  • Sand and dust storms are significant natural disasters which affect East Asia and China in spring, occurring from March to May. Performances of CMA-CUACE/Dust, an operational Asian sand and dust storm numerical forecasting system of CMA since 2006, are analyzed. It’s found that the model overestimates in Central Asia, underestimates in northern Mongolia, and diffuses too quickly in downwind areas far away from the source area, especially in Northern China, Korean Peninsula and Japan, resulting in low peak values or less lingering time there for very extreme sand and dust storm events. A scale-adaptive dust emission scheme is applied by resolving the mean wind speed of the model grid into sectional one which can account for values larger than the mean value by Weibull integration function. This significant aspect is crucial because the dust emission is the third power of the wind in the dust emission scheme. New wind erosion database is also adopted which consists of the updated desertification by using twenty-year surface data and new parameters deduced from site observations in the heart of Gobi Desert, determining the size distribution of the emitted dust together with the soil texture data sampling from main deserts in China.After evaluation for the strongest sand and dust episode of 13-17 in March 2021 in East Asia in the past decade, and the consistent run in the same operational environment from 1 March to 31 May in 2023, it is found that the updated CMA-CUACE/Dust effectively improves disadvantages such as overestimation in Central Asia, underestimation in northern Mongolia, and rapid dissipation in China. The predicted peak dust concentration of the extreme episode closely matches observations in China both in the source area and in Shanghai after a 4-day transportation. Threat score (TS) of three-month forecast run also indicates that the improved model shows good consistency and continuity in forecast results across various forecast lengths. TS for 1-5 days with different forecast lengths is significantly higher than that of the previous operational system and surpasses those of Korean dust model—ADAM (the Asian Dust Aerosol Model). Furthermore, the missing rate is significantly reduced, while the false alarm rate remains almost unchanged. TS for episodes beyond the level of sand and storms are all above 0.3, with some exceeding 0.5. All these findings show that the improved model performs much better than the previous one.
  • Fig. 1  Forecasted dust concentration(the shaded) by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observation(the mark) at 1400 BT 14 Mar and 1400 BT 15 Mar in 2021

    Fig. 1  Forecasted dust concentration(the shaded) by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observation(the mark) at 1400 BT 14 Mar and 1400 BT 15 Mar in 2021

    Fig. 2  Forecasted dust concentration(the shaded) by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observation(the mark) at 0800 BT 17 Mar 2021

    Fig. 2  Forecasted dust concentration(the shaded) by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observation(the mark) at 0800 BT 17 Mar 2021

    Fig. 3  Forecasted dust concentration by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observation in Beijing and Shanghai from 0800 BT 13 Mar to 0200 BT 18 Mar in 2021

    Fig. 3  Forecasted dust concentration by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observation in Beijing and Shanghai from 0800 BT 13 Mar to 0200 BT 18 Mar in 2021

    Fig. 4  Thread score, missing rate and false rate for CMA-CUACE/Dust V1.0, CMA-CUACE/Dust V1.5 and ADAM from Mar to May in 2023

    Fig. 4  Thread score, missing rate and false rate for CMA-CUACE/Dust V1.0, CMA-CUACE/Dust V1.5 and ADAM from Mar to May in 2023

    Fig. 5  Threat score, missing rate and false rate of five episodes of sand and dust storms in spring of 2023 for CMA-CUACE/Dust V1.0, CMA-CUACE/Dust V1.5 and ADAM

    Fig. 5  Threat score, missing rate and false rate of five episodes of sand and dust storms in spring of 2023 for CMA-CUACE/Dust V1.0, CMA-CUACE/Dust V1.5 and ADAM

    Fig. 6  Forecasted PM10 concentration(the shaded) in onset stage of sand and dust storm event from 19 Mar to 24 Mar in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 6  Forecasted PM10 concentration(the shaded) in onset stage of sand and dust storm event from 19 Mar to 24 Mar in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 7  Forecasted PM10 concentration(the shaded) in transportation stage of sand and dust storm event from 19 Mar to 24 Mar in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 7  Forecasted PM10 concentration(the shaded) in transportation stage of sand and dust storm event from 19 Mar to 24 Mar in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 8  Forecasted dust concentration(the shaded) of sand and dust storm event from 9 Apr to 13 Apr in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 8  Forecasted dust concentration(the shaded) of sand and dust storm event from 9 Apr to 13 Apr in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 9  Forecasted dust concentration(the shaded) in onset and transportation stages of sand and dust event from 18 May to 21 May in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Fig. 9  Forecasted dust concentration(the shaded) in onset and transportation stages of sand and dust event from 18 May to 21 May in 2023 by CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5 with observed phenomena(the mark)

    Table  1  Geometric mean diameter(d), geometric standard deviation(σ) and binding energy(e) of three modes of dust released in MBA scheme in CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5

    分布参数 模态Ⅰ 模态Ⅱ 模态Ⅲ
    V1.0 V1.5 V1.0 V1.5 V1.0 V1.5
    d/μm 1.50 5.75 6.70 13.75 14.2 27.5
    σ 1.7 1.7 1.6 1.6 1.5 1.5
    e/(g·cm2·s-2) 3.61 3.61 3.52 3.52 3.42 3.42
    DownLoad: Download CSV

    Table  1  Geometric mean diameter(d), geometric standard deviation(σ) and binding energy(e) of three modes of dust released in MBA scheme in CMA-CUACE/Dust V1.0 and CMA-CUACE/Dust V1.5

    分布参数 模态Ⅰ 模态Ⅱ 模态Ⅲ
    V1.0 V1.5 V1.0 V1.5 V1.0 V1.5
    d/μm 1.50 5.75 6.70 13.75 14.2 27.5
    σ 1.7 1.7 1.6 1.6 1.5 1.5
    e/(g·cm2·s-2) 3.61 3.61 3.52 3.52 3.42 3.42
    DownLoad: Download CSV

    Table  2  Thresholds of PM10 concentration(unit:μg·m-3) for spring dust intensity in China

    地区 扬沙或浮尘 沙尘暴 强沙尘暴 特强沙尘暴
    新疆地区 [245, 4890] [4891, 12388] [12389, 16235] 不低于16236
    西北地区 [408, 6031] [6032, 8150] 不低于8151
    东北地区 [408, 3260] [3261, 7824] 不低于7825
    其余地区 [408, 4727] [4728, 7172] 不低于7173
    DownLoad: Download CSV

    Table  2  Thresholds of PM10 concentration(unit:μg·m-3) for spring dust intensity in China

    地区 扬沙或浮尘 沙尘暴 强沙尘暴 特强沙尘暴
    新疆地区 [245, 4890] [4891, 12388] [12389, 16235] 不低于16236
    西北地区 [408, 6031] [6032, 8150] 不低于8151
    东北地区 [408, 3260] [3261, 7824] 不低于7825
    其余地区 [408, 4727] [4728, 7172] 不低于7173
    DownLoad: Download CSV

    Table  3  Processes above sand and dust storm from Mar to May in 2023

    编号 起止时间 级别 主要影响系统
    202306 03-19—03-24 强沙尘暴 地面冷锋、蒙古气旋
    202308 04-09—04-13 沙尘暴 蒙古气旋及冷锋
    202310 04-18—04-21 强沙尘暴 蒙古气旋及冷锋
    202312 04-27—04-29 沙尘暴 冷锋
    202314 05-18—05-21 沙尘暴 蒙古气旋、冷锋
    DownLoad: Download CSV

    Table  3  Processes above sand and dust storm from Mar to May in 2023

    编号 起止时间 级别 主要影响系统
    202306 03-19—03-24 强沙尘暴 地面冷锋、蒙古气旋
    202308 04-09—04-13 沙尘暴 蒙古气旋及冷锋
    202310 04-18—04-21 强沙尘暴 蒙古气旋及冷锋
    202312 04-27—04-29 沙尘暴 冷锋
    202314 05-18—05-21 沙尘暴 蒙古气旋、冷锋
    DownLoad: Download CSV
  • [1]
    Li Y, Wang G F. Design and implementation of Meteorological Disaster Risk Management System. J Appl Meteor Sci, 2022, 33(5): 628-640. doi:  10.11898/1001-7313.20220510
    [2]
    Wu X T, Wang X Y, Zheng D, et al. Effects of different aerosols on cloud-to-ground lightning activity in the Yangtze River Delta. J Appl Meteor Sci, 2023, 34(5): 608-618. doi:  10.11898/1001-7313.20230509
    [3]
    Xiao H X, Zhang F, Wang Y Q, et al. Nowcasting of cloud images based on generative adversarial network and satellite data. J Appl Meteor Sci, 2023, 34(2): 220-233. doi:  10.11898/1001-7313.20230208
    [4]
    Li R J, Huang M Y, Ding D P, et al. Warm cloud size distribution experiment based on 70 m3 expansion cloud chamber. J Appl Meteor Sci, 2023, 34(5): 540-551. doi:  10.11898/1001-7313.20230503
    [5]
    Ginoux P, Prospero J M, Gill T E, et al. Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Rev Geophys, 2012, 50(3). DOI:  10.1029/2012RG000388.
    [6]
    Jugder D, Gantsetseg B, Davaanyam E, et al. Developing a soil erodibility map across Mongolia. Nat Hazards, 2018, 92(1): 71-94.
    [7]
    Zhou C H, Gui H, Hu J, et al. Detection of new dust source in Central/East Asia and their impact on simulations of a severe sand and dust storm. J Geophys Res, 2019, 124: 10232-10247. doi:  10.1029/2019JD030753
    [8]
    Prospero J M, Ginoux P, Torres O, et al. Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 total ozone mapping spectrometer(TOMS) absorbing aerosol product. Rev Geophys, 2002, 40(1). DOI:  10.1029/2000rg000095.
    [9]
    Huang L P, Deng L T, Wang R C, et al. Key technologies of CMA-MESO and application to operational forecast. J Appl Meteor Sci, 2022, 33(6): 641-654. doi:  10.11898/1001-7313.20220601
    [10]
    Zhou Z J, Wang X W, Niu R Y. Climate characteristics of sandstorm in China in recent 47 years. Q J Appl Meteor, 2002, 13(2): 193-200. http://qikan.camscma.cn/article/id/20020225
    [11]
    Ma J Y, He Q, Yang X H, et al. Characteristics analysis of regional and local sandstorm over the hinterland of Taklimakan Desert: Taking Tazhong as example. Desert Oasis Meteor, 2016, 10(2): 36-42. https://www.cnki.com.cn/Article/CJFDTOTAL-XJQX201602007.htm
    [12]
    Fang Z Y, Wang W. Characteristic analysis of China dust storm in 2002. Q J Appl Meteor, 2003, 14(5): 513-521. doi:  10.3969/j.issn.1001-7313.2003.05.001
    [13]
    Yumimoto K, Kajino M, Tanaka T Y, et al. Dust vortex in the Taklimakan Desert by Himawari-8 high frequency and resolution observation. Sci Rep, 2019, 9(1). DOI:  10.1038/s41598-018-37861-4.
    [14]
    Chen S Y, Huang J P, Li J X, et al. Comparison of dust emissions, transport, and deposition between the Taklimakan Desert and Gobi Desert from 2007 to 2011. Sci China Earth Sci, 2017, 60(7): 1338-1355. doi:  10.1007/s11430-016-9051-0
    [15]
    Tian Y H, Ji Z K, Liu H Y. Main climatic factors and land cover effects on sandstorms in the central part of Inner Mongolia Plateau. Q J Appl Meteor, 2005, 16(4): 476-483. doi:  10.3969/j.issn.1001-7313.2005.04.008
    [16]
    Li X, Liu Y. Assessment of two aerosol modules of CAM5. J Appl Meteor Sci, 2013, 24(1): 75-86. http://qikan.camscma.cn/article/id/20130108
    [17]
    Westphal D L, Toon O B, Carlson T N. A two-dimensional numerical investigation of the dynamics and microphysics of Saharan dust storms. J Geophys Res, 1987, 92(D3): 3027-3049. doi:  10.1029/JD092iD03p03027
    [18]
    Iversen J D, White B R. Saltation threshold on Earth, Mars and Venus. Sedimentology, 1982, 29(1): 111-119. doi:  10.1111/j.1365-3091.1982.tb01713.x
    [19]
    Tegen I, Fung I. Modeling of mineral dust in the atmosphere: Sources, transport, and optical thickness. J Geophys Res, 1994, 99(D11): 22897-22914.
    [20]
    Alfaro S C, Gomes L. Modeling mineral aerosol production by wind erosion: Emission intensities and aerosol size distributions in source areas. J Geophys Res, 2001, 106(D16): 18075-18084.
    [21]
    Shao Y P. A model for mineral dust emission. J Geophys Res, 2001, 106(D17): 20239-20254.
    [22]
    Marticorena B, Bergametti G. Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme. J Geophys Res, 1995, 100(D8): 16415-16430.
    [23]
    Kok J F. A scaling theory for the size distribution of emitted dust aerosols suggests climate models underestimate the size of the global dust cycle. PNAS, 2011, 108(3): 1016-1021.
    [24]
    Dubovik O, Sinyuk A, Lapyonok T, et al. Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. J Geophys Res Atmos, 2006, 111(D11). DOI:  10.1029/2005JD006619.
    [25]
    Nakajima T, Tonna G, Rao R, et al. Use of sky brightness measurements from ground for remote sensing of particulate polydispersions. Appl Opt, 1996, 35(15): 2672-2686.
    [26]
    Zhang X Y, Wang Y Q, Niu T, et al. Atmospheric aerosol compositions in China: Spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols. Atmos Chem Phys, 2012, 12(2): 779-799.
    [27]
    Che H Z, Zhang X Y, Chen H B, et al. Instrument calibration and aerosol optical depth validation of the China Aerosol Remote Sensing Network. J Geophys Res, 2009, 114(D3). DOI:  10.1029/2008JD011030.
    [28]
    Zhou C H, Gong S L, Zhang X Y, et al. Development and evaluation of an operational SDS forecasting system for East Asia: CUACE/Dust. Atmos Chem Phys, 2008, 8(4): 787-798.
    [29]
    Zhou C H, Zhang X C, Zhang J, et al. Representations of dynamics size distributions of mineral dust over East Asia by a regional sand and dust storm model. Atmos Res, 2021, 250. DOI:  10.1016/j.atmosres.2020.105403.
    [30]
    Gong S L, Barrie L A, Blanchet J P, et al. Canadian Aerosol Module: A size-segregated simulation of atmospheric aerosol processes for climate and air quality models 1. Module development. J Geophys Res, 2003, 108(D1). DOI:  10.1029/2001JD002002.
    [31]
    Zhou C H, Shen X J, Liu Z R, et al. Simulating aerosol size distribution and mass concentration with simultaneous nucleation, condensation/coagulation, and deposition with the GRAPES-CUACE. J Meteor Res, 2018, 32(2): 265-278.
    [32]
    Marticorena B, Bergametti G, Aumont B, et al. Modeling the atmospheric dust cycle: 2. Simulation of Saharan dust sources. J Geophys Res, 1997, 102(D4): 4387-4404.
    [33]
    Alfaro S C, Gaudichet A, Gomes L, et al. Modeling the size distribution of a soil aerosol produced by sandblasting. J Geophys Res, 1997, 102(D10): 11239-11249.
    [34]
    Guggenheim S, Martin R T. Definition of clay and clay mineral: Joint report of the AIPEA nomenclature and CMS nomenclature committees. Clays Clay Miner, 1995, 43(2): 255-256.
    [35]
    Alfaro S C, Gaudichet A, Gomes L, et al. Mineral aerosol production by wind erosion: Aerosol particle sizes and binding energies. Geophys Res Lett, 1998, 25(7): 991-994.
    [36]
    Gong S L, Zhang X Y, Zhao T L, et al. Characterization of soil dust aerosol in China and its transport and distribution during 2001 ACE-Asia: 2. Model simulation and validation. J Geophys Res, 2003, 108(D9). DOI: 10.1029/2002JD002632.
  • 加载中
  • -->

Catalog

    Figures(18)  / Tables(6)

    Article views (288) PDF downloads(56) Cited by()
    • Received : 2024-04-01
    • Accepted : 2024-06-12
    • Published : 2024-07-31

    /

    DownLoad:  Full-Size Img  PowerPoint