Articles | Volume 22, issue 17
https://doi.org/10.5194/acp-22-11255-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-22-11255-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Sep 2022
Research article |
| 02 Sep 2022
| 02 Sep 2022
What caused the interdecadal shift in the El Niño–Southern Oscillation (ENSO) impact on dust mass concentration over northwestern South Asia?
Lamei Shi
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
College of Earth and Planetary Sciences, University of Chinese
Academy of Sciences, Beijing 101407, China
Jiahua Zhang
CORRESPONDING AUTHOR
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
College of Earth and Planetary Sciences, University of Chinese
Academy of Sciences, Beijing 101407, China
Da Zhang
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
College of Earth and Planetary Sciences, University of Chinese
Academy of Sciences, Beijing 101407, China
Jingwen Wang
Key Laboratory of Digital Earth Science, Aerospace Information
Research Institute, Chinese Academy of Sciences, Beijing 100094, China
College of Earth and Planetary Sciences, University of Chinese
Academy of Sciences, Beijing 101407, China
Xianglei Meng
College of Earth and Planetary Sciences, University of Chinese
Academy of Sciences, Beijing 101407, China
Yuqin Liu
Key Laboratory of Urban Environment and Health, Institute of Urban
Environment, Chinese Academy of Sciences, Xiamen 361021, China
Fengmei Yao
College of Earth and Planetary Sciences, University of Chinese
Academy of Sciences, Beijing 101407, China
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Cited articles
Abish, B. and Mohanakumar, K.: Absorbing aerosol variability over the Indian
subcontinent and its increasing dependence on ENSO, Glob. Planet. Change,
106, 13–19, https://doi.org/10.1016/j.gloplacha.2013.02.007, 2013.
Ashok, K., Behera, S. K., Rao, S. A., Weng, H., and Yamagata, T.: El Nino
Modoki and its possible teleconnection, J. Geophys. Res., 112, C11007, https://doi.org/10.1029/2006JC003798, 2007.
Avila, A.: The chemical composition of dust transported in red rains – its
contribution to the biogeochemical cycle of a holm oak forest in Catalonia
(Spain), Atmos. Environ., 32, 179–191, https://doi.org/10.1016/S1352-2310(97)00286-0, 1998.
Babu, S. S., Manoj, M. R., Moorthy, K. K., Gogoi, M. M., Nair, V. S.,
Kompalli, S. K., Satheesh, S. K., Niranjan, K., Ramagopal, K., Bhuyan, P.
K., and Singh, D.: Trends in aerosol optical depth over Indian region:
Potential causes and impact indicators, J. Geophys. Res.-Atmos., 118,
11794–11806, https://doi.org/10.1002/2013JD020507, 2013.
Banerjee, P. and Kumar, S. P.: ENSO modulation of interannual variability of
dust aerosols over the northwest Indian Ocean, J. Clim., 29, 1391–1415,
https://doi.org/10.1175/JCLI-D-15-0039.1, 2016.
Banerjee, P., Satheesh, S. K., Moorthy, K. K., Nanjundiah, R. S., and Nair,
V. S.: Long-range transport of mineral dust to the northeast Indian Ocean:
Regional versus remote sources and the implications, J. Clim., 32,
1525–1549, https://doi.org/10.1175/JCLI-D-18-0403.1, 2019.
Behrooz, R. D., Esmaili-Sari, A., Bahramifar, N., and Kaskaoutis, D. G.:
Analysis of the TSP, PM10 concentrations and water-soluble ionic species in airborne samples over Sistan, Iran during the summer dusty period, Atmos.
Pollut. Res., 8, 403–417, https://doi.org/10.1016/j.apr.2016.11.001, 2017.
Bollasina, M. A., Ming, Y., and Ramaswamy, V.: Anthropogenic aerosols and
the weakening of the south asian summer monsoon, Science, 334,
502–505, https://doi.org/10.1126/science.1204994, 2011.
Bozlaker, A., Prospero, J. M., Fraser, M. P., and Chellam, S.: Quantifying
the contribution of long-range saharan dust transport on particulate matter
concentrations in Houston, Texas, using detailed elemental analysis,
Environ. Sci. Technol., 47, 10179–10187, https://doi.org/10.1021/es4015663,
2013.
Buchard, V., Randles, C. A., da Silva, A. M., Darmenov, A., Colarco, P. R.,
Govindaraju, R., Ferrare, R., Hair, J., Beyersdorf, A. J., Ziemba, L. D.,
and Yu, H.: The MERRA-2 aerosol reanalysis, 1980 onward. Part II: Evaluation
and case studies, J. Clim., 30, 6851–6872,
https://doi.org/10.1175/JCLI-D-16-0613.1, 2017.
Cai, W., Borlace, S., Lengaigne, M., Van Rensch, P., Collins, M., Vecchi,
G., Timmermann, A., Santoso, A., Mcphaden, M. J., Wu, L., England, M. H.,
Wang, G., Guilyardi, E., and Jin, F. F.: Increasing frequency of extreme El
Niño events due to greenhouse warming, Nat. Clim. Chang., 4, 111–116,
https://doi.org/10.1038/nclimate2100, 2014.
Chauhan, S. S.: Desertification control and management of land degradation
in the Thar desert of India, Environmentalist, 23, 219–227,
https://doi.org/10.1023/B:ENVR.0000017366.67642.79, 2003.
Chen, Y.-S., Sheen, P.-C., Chen, E.-R., Liu, Y.-K., Wu, T.-N., and Yang,
C.-Y.: Effects of Asian dust storm events on daily mortality in Taipei,
Taiwan, Environ. Res., 95, 151–155,
https://doi.org/10.1016/j.envres.2003.08.008, 2004.
Cherchi, A. and Navarra, A.: Influence of ENSO and of the Indian Ocean
Dipole on the Indian summer monsoon variability, Clim. Dyn., 41, 81–103,
https://doi.org/10.1007/s00382-012-1602-y, 2013.
Clark, C. O., Cole, J. E., and Webster, P. J.: Indian Ocean SST and Indian
summer rainfall: Predictive relationships and their decadal variability, J.
Clim., 13, 2503–2519, https://doi.org/10.1175/1520-0442(2000)013<2503:IOSAIS>2.0.CO;2, 2000.
Dong, B., Dai, A., Vuille, M., and Timm, O. E.: Asymmetric modulation of
ENSO teleconnections by the interdecadal Pacific oscillation, J. Clim., 31,
7337–7361, https://doi.org/10.1175/JCLI-D-17-0663.1, 2018.
Du, Y., Xie, S. P., Huang, G., and Hu, K.: Role of air-sea interaction in
the long persistence of El Niño-induced north Indian Ocean warming, J.
Clim., 22, 2023–2038, https://doi.org/10.1175/2008JCLI2590.1, 2009.
Easterling, D. R. and Wehner, M. F.: Is the climate warming or cooling?,
Geophys. Res. Lett., 36, 4–6, https://doi.org/10.1029/2009GL037810, 2009.
Erel, Y., Dayan, U., Rabi, R., Rudich, Y., and Stein, M.: Trans boundary
transport of pollutants by atmospheric mineral dust, Environ. Sci. Technol.,
40, 2996–3005, https://doi.org/10.1021/es051502l, 2006.
Fyfe, J. C., Merryfield, W. J., Kharin, V., Boer, G. J., Lee, W. S., and Von
Salzen, K.: Skillful predictions of decadal trends in global mean surface
temperature, Geophys. Res. Lett., 38, 1–5,
https://doi.org/10.1029/2011GL049508, 2011.
Fyfe, J. C., Gillett, N. P., and Zwiers, F. W.: Overestimated global warming
over the past 20 years, Nat. Clim. Chang., 3, 767–769,
https://doi.org/10.1038/nclimate1972, 2013.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan,
K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A.,
da Silva, A. M., Gu, W., Kim, G. K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M.,
Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The modern-era retrospective
analysis for research and applications, version 2 (MERRA-2), J. Clim., 30,
5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Global Modeling and Assimilation Office (GMAO): MERRA-2, NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://disc.gsfc.nasa.gov/, last access: 1 February 2021.
Graham, N. E.: Decadal-scale climate variability in the tropical and North
Pacific during the 1970s and 1980s: observations and model results, Clim.
Dyn., 10, 135–162, https://doi.org/10.1007/BF00210626, 1994.
Guo, H., Wang, X., and Gao, Z.: Uncertain linear regression model and its
application, J. Intell. Manuf., 28, 559–564,
https://doi.org/10.1007/s10845-014-1022-4, 2017.
Hansen, J. E., Sato, M., and Ruedy, R.: Radiative forcing and climate
response, J. Geophys. Res.-Atmos., 102, 6831–6864, https://doi.org/10.1029/96JD03436, 1997.
He, L., Lin, A., Chen, X., Zhou, H., Zhou, Z., and He, P.: Assessment of
MERRA-2 Surface PM2.5 over the Yangtze River Basin: Ground-based
verification, spatiotemporal distribution and meteorological dependence,
Remote Sens., 11, 460, https://doi.org/10.3390/rs11040460, 2019.
He, S. and Wang, H.: Oscillating relationship between the East Asian Winter
Monsoon and ENSO, J. Clim., 26, 9819–9838,
https://doi.org/10.1175/JCLI-D-13-00174.1, 2013.
Hirahara, S., Ishii, M., and Fukuda, Y.: Centennial-scale sea surface
temperature analysis and its uncertainty, J. Clim., 27, 57–75,
https://doi.org/10.1175/JCLI-D-12-00837.1, 2014.
Hu, S. and Fedorov, A. V.: The extreme El Niño of 2015–2016 and the end
of global warming hiatus, Geophys. Res. Lett., 44, 3816–3824,
https://doi.org/10.1002/2017GL072908, 2017.
Huang, B., Thorne, P. W., Banzon, V. F., Boyer, T., Chepurin, G., Lawrimore, J. H., Menne, M. J., Smith, T. M., Vose, R. S., and Zhang, H. M.: Extended reconstructed Sea surface temperature, Version 5 (ERSSTv5): Upgrades, validations, and intercomparisons, J. Clim., 30, 8179–8205, https://doi.org/10.1175/JCLI-D-16-0836.1, 2017.
Huang, X., Zhou, T., Turner, A., Dai, A., Chen, X., Clark, R., Jiang, J.,
Man, W., Murphy, J., Rostron, J., Wu, B., Zhang, L., Zhang, W., and Zou, L.:
The recent decline and recovery of Indian summer monsoon rainfall: Relative
roles of external forcing and internal variability, J. Clim., 33,
5035–5060, https://doi.org/10.1175/JCLI-D-19-0833.1, 2020.
Jin, Q. and Wang, C.: The greening of Northwest Indian subcontinent and
reduction of dust abundance resulting from Indian summer monsoon revival,
Sci. Rep., 8, 1–9, https://doi.org/10.1038/s41598-018-23055-5, 2018.
Jin, Q., Wei, J., Pu, B., Yang, Z. L., and Parajuli, S. P.: High Summertime
Aerosol Loadings Over the Arabian Sea and Their Transport Pathways, J.
Geophys. Res.-Atmos., 123, 10568–10590,
https://doi.org/10.1029/2018JD028588, 2018.
Jin, Q., Wei, J., Lau, W. K. M., Pu, B., and Wang, C.: Interactions of Asian
mineral dust with Indian summer monsoon: Recent advances and challenges,
Earth-Sci. Rev., 215, 103562,
https://doi.org/10.1016/j.earscirev.2021.103562, 2021.
Kaiser, J. and Granmar, M.: Mounting Evidence Indicts Fine-Particle
Pollution, Science, 307, 1858–1861, https://doi.org/10.1126/science.307.5717.1858a, 2005.
Kinter, I. L., Miyakoda, K., and Yang, S.: Recent change in the connection
from the Asian monsoon to ENSO, J. Clim., 15, 1203–1215,
https://doi.org/10.1175/1520-0442(2002)015<1203:RCITCF>2.0.CO;2, 2002.
Krishnamurthy, L. and Krishnamurthy, V.: Influence of PDO on South Asian
summer monsoon and monsoon-ENSO relation, Clim. Dyn., 42, 2397–2410,
https://doi.org/10.1007/s00382-013-1856-z, 2014.
Krishnamurthy, V. and Kirtman, B. P.: Variability of the Indian Ocean:
Relation to monsoon and ENSO, Q. J. R. Meteorol. Soc., 129, 1623–1646,
https://doi.org/10.1256/qj.01.166, 2003.
Kucharski, F., Bracco, A., Yoo, J. H., and Molteni, F.: Low-frequency
variability of the Indian monsoon-ENSO relationship and the tropical
Atlantic: The “weakening” of the 1980s and 1990s, J. Clim., 20,
4255–4266, https://doi.org/10.1175/JCLI4254.1, 2007.
Kug, J. S., An, S. Il, Jin, F. F., and Kang, I. S.: Preconditions for El
Niño and La Niña onsets and their relation to the Indian Ocean,
Geophys. Res. Lett., 32, 1–5, https://doi.org/10.1029/2004GL021674, 2005.
Kumar, K. K., Rajagopalan, B., and Cane, M. A.: On the weakening
relationship between the indian monsoon and ENSO, Science, 284,
2156–2159, https://doi.org/10.1126/science.284.5423.2156, 1999.
Lakshmi, N. B., Nair, V. S., and Suresh Babu, S.: Vertical structure of
aerosols and mineral dust over the Bay of Bengal from multisatellite
observations, J. Geophys. Res.-Atmos., 122, 12845–12861,
https://doi.org/10.1002/2017JD027643, 2017.
Lakshmi, N. B., Babu, S. S., and Nair, V. S.: Recent Regime Shifts in
Mineral Dust Trends over South Asia from Long-Term CALIPSO Observations,
IEEE Trans. Geosci. Remote Sens., 57, 4485–4489,
https://doi.org/10.1109/TGRS.2019.2891338, 2019.
Lee, Y. G., Kim, J., Ho, C. H., An, S. Il, Cho, H. K., Mao, R., Tian, B.,
Wu, D., Lee, J. N., Kalashnikova, O., Choi, Y., and Yeh, S. W.: The effects
of ENSO under negative AO phase on spring dust activity over northern China:
An observational investigation, Int. J. Climatol., 35, 935–947,
https://doi.org/10.1002/joc.4028, 2015.
Liu, J., Wu, D., Liu, G., Mao, R., Chen, S., Ji, M., Fu, P., Sun, Y., Pan,
X., Jin, H., Zhou, Y., and Wang, X.: Impact of Arctic amplification on
declining spring dust events in East Asia, Clim. Dyn., 54, 1913–1935,
https://doi.org/10.1007/s00382-019-05094-4, 2020.
Mahowald, N., Albani, S., Kok, J. F., Engelstaeder, S., Scanza, R., Ward, D.
S., and Flanner, M. G.: The size distribution of desert dust aerosols and
its impact on the Earth system, Aeolian Res., 15, 53–71,
https://doi.org/10.1016/j.aeolia.2013.09.002, 2014.
Mahowald, N. M., Yoshioka, M., Collins, W. D., Conley, A. J., Fillmore, D.
W., and Coleman, D. B.: Climate response and radiative forcing from mineral
aerosols during the last glacial maximum, pre-industrial, current and
doubled-carbon dioxide climates, Geophys. Res. Lett., 332, 382–385, https://doi.org/10.1029/2006GL026126, 2006.
Mahowald, N. M., Kloster, S., Engelstaedter, S., Moore, J. K., Mukhopadhyay, S., McConnell, J. R., Albani, S., Doney, S. C., Bhattacharya, A., Curran, M. A. J., Flanner, M. G., Hoffman, F. M., Lawrence, D. M., Lindsay, K., Mayewski, P. A., Neff, J., Rothenberg, D., Thomas, E., Thornton, P. E., and Zender, C. S.: Observed 20th century desert dust variability: impact on climate and biogeochemistry, Atmos. Chem. Phys., 10, 10875–10893, https://doi.org/10.5194/acp-10-10875-2010, 2010.
Miller, R. L. and Tegen, I.: Climate response to soil dust aerosols, J.
Clim., 11, 3247–3267, https://doi.org/10.1175/1520-0442(1998)011<3247:CRTSDA>2.0.CO;2, 1998.
National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR): Atmospheric reanalysis dataset, Physical Sciences Laboratory (PSL) [data set],
https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html, last access: 1 March 2021.
Nitta, T. and Yamada, S.: Recent warming of tropical sea surface temperature
and its relationship to the Northern Hemisphere circulation, J. Meteorol.
Soc. Japan, 67, 375–383, https://doi.org/10.2151/jmsj1965.67.3_375, 1989.
NOAA/CPC: Climate indices: monthly atmospheric and ocean time series, Climate Prediction Center of the National Oceanic and Atmospheric Administration (NOAA/CPC), Physical Sciences Laboratory (PSL) [data set], https://psl.noaa.gov/data/climateindices/list/, last access: 1 February 2021.
Osborn, T. J., Jones, P. D., Lister, D. H., Morice, C. P., Simpson, I. R.,
Winn, J. P., Hogan, E., and Harris, I. C.: Land Surface Air Temperature
Variations Across the Globe Updated to 2019: The CRUTEM5 Data Set, J.
Geophys. Res.-Atmos., 126, e2019JD032352, https://doi.org/10.1029/2019JD032352, 2021.
Pallikari, F.: On the false hypothesis of psi-mediated shift of statistical average in tests with random number generators, in: The Parapsychological Association Convention 2004, 5–8 August 2004, Vienna University, 157–171,
https://doi.org/10.13140/2.1.4054.5289, 2004.
Parker, D. J., Willetts, P., Birch, C., Turner, A. G., Marsham, J. H.,
Taylor, C. M., Kolusu, S., and Martin, G. M.: The interaction of moist
convection and mid-level dry air in the advance of the onset of the Indian
monsoon, Q. J. R. Meteorol. Soc., 142, 2256–2272,
https://doi.org/10.1002/qj.2815, 2016.
Poulsen, O. M., Breum, N. O., Ebbehoj, N., Hansen, A. M., Ivens, U. I., van
Lelieveld, D., Malmros, P., Matthiasen, L., Nielsen, B. H., and Nielsen, E.
M.: Sorting and recycling of domestic waste. Review of occupational health
problems and their possible causes, Sci. Total Environ., 168, 33–56, https://doi.org/10.1016/0048-9697(95)04521-2, 1995.
Prospero, J. M. and Nees, R. T.: Impact of the North African drought and El
Niño on mineral dust in the Barbados trade winds, Nature, 320, 735–738,
https://doi.org/10.1038/320735a0, 1986.
Randles, C. A., Sliva, A. M. da, Buchard, V., Colarco, P., Armenov, A., and
Govindaraju, R.: The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System
Description and Data Assimilation Evaluation, J. Clim., 30, 6823–6850,
https://doi.org/10.1175/JCLI-D-16-0609.1, 2017.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L.
V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea
surface temperature, sea ice, and night marine air temperature since the
late nineteenth century, J. Geophys. Res.-Atmos., 108, 4407,
https://doi.org/10.1029/2002jd002670, 2003.
Razakov, R. M. and Kosnazarov, K. A.: Dust and salt transfer from the
exposed bed of the Aral Sea and measures to decrease its environmental
impact, in: The Aral Sea Basin, edited by: Micklin, P. P. and Williams, W.
D., Springer, Berlin, Heidelberg, 95–102, https://doi.org/10.1007/978-3-642-61182-7_9, 1996.
Richon, C., Dutay, J.-C., Dulac, F., Wang, R., and Balkanski, Y.: Modeling the biogeochemical impact of atmospheric phosphate deposition from desert dust and combustion sources to the Mediterranean Sea, Biogeosciences, 15, 2499–2524, https://doi.org/10.5194/bg-15-2499-2018, 2018.
Sabeerali, C. T., Ajayamohan, R. S., Bangalath, H. K., and Chen, N.:
Atlantic Zonal Mode: An Emerging Source of Indian Summer Monsoon Variability
in a Warming World, Geophys. Res. Lett., 46, 4460–4467,
https://doi.org/10.1029/2019GL082379, 2019.
Sanchez de la Campa, A., Garcia-Salamanca, A., Solano, J., de la Rosa, J.,
and Ramos, J.-L.: Chemical and microbiological characterization of
atmospheric particulate matter during an intense African dust event in
Southern Spain., Environ. Sci. Technol., 47, 3630–3638,
https://doi.org/10.1021/es3051235, 2013.
Schulz, M., Prospero, J. M., Baker, A. R., Dentener, F., Ickes, L., Liss, P.
S., Mahowald, N. M., Nickovic, S., García-Pando, C. P., Rodríguez,
S., Sarin, M., Tegen, I., and Duce, R. A.: Atmospheric Transport and
Deposition of Mineral Dust to the Ocean: Implications for Research Needs,
Environ. Sci. Technol., 46, 10390–10404, https://doi.org/10.1021/es300073u, 2012.
Singh, R. P., Prasad, A. K., Kayetha, V. K., and Kafatos, M.: Enhancement of
oceanic parameters associated with dust storms using satellite data, J.
Geophys. Res., 113, C11008, https://doi.org/10.1029/2008JC004815, 2008.
Srivastava, G., Chakraborty, A., and Nanjundiah, R. S.: Multidecadal see-saw
of the impact of ENSO on Indian and West African summer monsoon rainfall,
Clim. Dyn., 52, 6633–6649, https://doi.org/10.1007/s00382-018-4535-2, 2019.
Tegen, I., Lacis, A. A., and Fung, I.: The influence on climate forcing of
mineral aerosols from disturbed soils, Nature, 380, 419–422, https://doi.org/10.1038/380419a0, 1996.
Tokinaga, H., Richter, I., and Kosaka, Y.: ENSO Influence on the Atlantic
Niño, Revisited: Multi-Year versus Single-Year ENSO Events, J. Clim.,
32, 4585–4600, https://doi.org/10.1175/JCLI-D-18-0683.1, 2019.
Trenberth, K. E. and Hurrell, J. W.: Decadal atmosphere-ocean variations in
the Pacific, Clim. Dyn., 9, 303–319, https://doi.org/10.1007/BF00204745, 1994.
Trenberth, K. E., Dai, A., Van Der Schrier, G., Jones, P. D., Barichivich,
J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought,
Nat. Clim. Chang., 4, 17–22, https://doi.org/10.1038/nclimate2067, 2014.
Veselovskii, I., Goloub, P., Podvin, T., Tanre, D., da Silva, A., Colarco, P., Castellanos, P., Korenskiy, M., Hu, Q., Whiteman, D. N., Pérez-Ramírez, D., Augustin, P., Fourmentin, M., and Kolgotin, A.: Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations, Atmos. Meas. Tech., 11, 949–969, https://doi.org/10.5194/amt-11-949-2018, 2018.
von Storch, H. and Zwiers, F. W.: Statistical Analysis in Climate Research,
Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9780511612336, 1999.
Wang, B., Wu, R., and Li, T.: Atmosphere-warm ocean interaction and its
impacts on Asian-Australian monsoon variation, J. Clim., 16, 1195–1211,
https://doi.org/10.1175/1520-0442(2003)16<1195:AOIAII>2.0.CO;2, 2003.
Wang, L., Chen, W., and Huang, R.: Interdecadal modulation of PDO on the
impact of ENSO on the east Asian winter monsoon, Geophys. Res. Lett., 35, L20702, https://doi.org/10.1029/2008GL035287, 2008.
Wang, S., Huang, J., He, Y., and Guan, Y.: Combined effects of the Pacific
Decadal Oscillation and El Niño-Southern Oscillation on Global Land
Dry-Wet Changes, Sci. Rep., 4, 6651, https://doi.org/10.1038/srep06651, 2014.
Watanabe, M. and Jin, F. F.: Role of Indian Ocean warming in the development
of Philippine Sea anticyclone during ENSO, Geophys. Res. Lett., 29,
1161–1164, https://doi.org/10.1029/2001gl014318, 2002.
Weare, B. C., Navato, A. R., and Newell, R. E.: Empirical orthogonal
analysis of Pacific sea surface temperatures, J. Phys. Oceanogr., 6,
671–678, https://doi.org/10.1175/1520-0485(1976)006<0671:EOAOPS>2.0.CO;2, 1976.
Weng, H., Ashok, K., Behera, S. K., Rao, S. A., and Yamagata, T.: Impacts of
recent El Niño Modoki on dry/wet conditions in the Pacific rim during
boreal summer, Clim. Dyn., 29, 113–129, https://doi.org/10.1007/s00382-007-0234-0, 2007.
Wu, R. and Kirtman, B. P.: Understanding the impacts of the Indian ocean on
ENSO variability in a coupled GCM, J. Clim., 17, 4019–4031,
https://doi.org/10.1175/1520-0442(2004)017<4019:UTIOTI>2.0.CO;2, 2004.
Wu, X., Liu, J., Wu, Y., Wang, X., Yu, X., Shi, J., and Bi, J.: Aerosol
optical absorption coefficients at a rural site in Northwest China: The
great contribution of dust particles, Atmos. Environ., 189, 145–152,
https://doi.org/10.1016/j.atmosenv.2018.07.002, 2018.
Xi, X. and Sokolik, I. N.: Dust interannual variability and trend in Central
Asia from 2000 to 2014 and their climatic linkages, J. Geophys. Res.-Atmos.,
120, 12175–12191, https://doi.org/10.1038/175238c0, 2016.
Yang, S. and Jiang, X.: Prediction of Eastern and Central Pacific ENSO
Events and Their Impacts on East Asian Climate by the NCEP Climate Forecast
System, J. Clim., 27, 4451–4472, https://doi.org/10.1175/JCLI-D-13-00471.1,
2014.
Yang, X. and Huang, P.: Restored relationship between ENSO and Indian summer
monsoon rainfall around 1999/2000, Innov., 2, 100102,
https://doi.org/10.1016/j.xinn.2021.100102, 2021.
Yu, J. and Kao, H.: Decadal changes of ENSO persistence barrier in SST and
ocean heat content indices: 1958–2001, J. Geophys. Res., 112, 1–10,
https://doi.org/10.1029/2006JD007654, 2007.
Yu, J.-Y., Mechoso, C. R., McWilliams, J. C., and Arakawa, A.: Impacts of
the Indian Ocean on the ENSO cycle, Geophys. Res. Lett., 29, 1204, https://doi.org/10.1029/2001GL014098, 2002.
Yu, Y., Notaro, M., Liu, Z., Wang, F., Alkolibi, F., Fadda, E., and Bakhrjy,
F.: Climatic controls on the interannual to decadal variability in Saudi
Arabian dust activity: Toward the development of a seasonal dust prediction
model, J. Geophys. Res.-Atmos., 120, 1739–1758,
https://doi.org/10.1002/jgrc.20224, 2015.
Yuan, Y. and Yang, S.: Impacts of Different Types of El Niño on the East
Asian Climate: Focus on ENSO Cycles, J. Clim., 25, 7702–7722, https://doi.org/10.1175/JCLI-D-11-00576.1, 2012.
Short summary
Dust impacts climate and human life. Analyzing the interdecadal change in dust activity and its influence factors is crucial for disaster mitigation. Based on a linear regression method, this study revealed the interdecadal variability of relationships between ENSO and dust over northwestern South Asia from 1982 to 2014 and analyzed the effects of atmospheric factors on this interdecadal variability. The result sheds new light on numerical simulation involving the interdecadal variation of dust.
Dust impacts climate and human life. Analyzing the interdecadal change in dust activity and its...
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