• Abdi, H., and L. J. Williams, 2010: Principal component analysis. Wiley Interdiscip. Rev.: Comput. Stat., 2, 433459, https://doi.org/10.1002/wics.101.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ali, Z., I. Hussain, M. Faisal, E. E. Elashkar, S. Gani, and M. A. Shehzad, 2019: Selection of appropriate time scale with Boruta algorithm for regional drought monitoring using multi-scaler drought index. Tellus, 71A, 1–16, https://doi.org/10.1080/16000870.2019.1604057.

  • Ashok, K., S. K. Behera, S. A. Rao, H. Weng, and T. Yamagata, 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res., 112, C11007, https://doi.org/10.1029/2006JC003798.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ault, T. R., 2020: On the essentials of drought in a changing climate. Science, 368, 256260, https://doi.org/10.1126/science.aaz5492.

  • Barreto, N. J. C., M. S. Mesquita, D. Mendes, M. H. C. Spyrides, G. U. Pedra, and P. S. Lucio, 2017: Maximum covariance analysis to identify intraseasonal oscillations over tropical Brazil. Climate Dyn., 49, 15831596, https://doi.org/10.1007/s00382-016-3401-3.

    • Search Google Scholar
    • Export Citation
  • Bonsal, B. R., E. E. Wheaton, A. C. Chipanshi, C. Lin, D. J. Sauchyn, and L. Wen, 2011: Drought research in Canada: A review. Atmos.–Ocean, 49, 303319, https://doi.org/10.1080/07055900.2011.555103.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data. J. Climate, 5, 541560, https://doi.org/10.1175/1520-0442(1992)005<0541:AIOMFF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Capotondi, A., and Coauthors, 2015: Understanding ENSO diversity. Bull. Amer. Meteor. Soc., 96, 921938, https://doi.org/10.1175/BAMS-D-13-00117.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carvalho, M. J., P. Melo-Gonçalves, J. C. Teixeira, and A. Rocha, 2016: Regionalization of Europe based on a K-means cluster analysis of the climate change of temperatures and precipitation. Phys. Chem. Earth, 94, 2228, https://doi.org/10.1016/j.pce.2016.05.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cash, B. A., X. Rodó, and J. L. Kinter III, 2008: Links between tropical Pacific SST and the regional climate of Bangladesh: Role of the western tropical and central extratropical Pacific. J. Climate, 21, 46474663, https://doi.org/10.1175/2007JCLI2001.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chang, C.-P., Z. Wang, J. Ju, and T. Li, 2004: On the relationship between western Maritime Continent monsoon rainfall and ENSO during northern winter. J. Climate, 17, 665672, https://doi.org/10.1175/1520-0442(2004)017<0665:OTRBWM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chang, C.-P., Z. Wang, J. McBride, and C.-H. Liu, 2005: Annual cycle of Southeast Asia–Maritime Continent rainfall and the asymmetric monsoon transition. J. Climate, 18, 287301, https://doi.org/10.1175/JCLI-3257.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chikamoto, Y., and Y. Tanimoto, 2005: Role of specific humidity anomalies in Caribbean SST response to ENSO. J. Meteor. Soc. Japan, 83, 959975, https://doi.org/10.2151/jmsj.83.959.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, M., and Coauthors, 2013: Long-term climate change: Projections, commitments and irreversibility. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 1029–1136.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, B. I., J. S. Mankin, K. Marvel, A. P. Williams, J. E. Smerdon, and K. J. Anchukaitis, 2020: Twenty-first century drought projections in the CMIP6 forcing scenarios. Earth’s Future, 8, e2019EF001461, https://doi.org/10.1029/2019EF001461.

    • Crossref
    • Export Citation
  • Dai, A., 2011: Drought under global warming: A review. Wiley Interdiscip. Rev. Climate Change, 2, 4565, https://doi.org/10.1002/wcc.81.

  • Dai, A., 2013: Increasing drought under global warming in observations and models. Nat. Climate Change, 3, 5258, https://doi.org/10.1038/nclimate1633.

    • Search Google Scholar
    • Export Citation
  • D’Arrigo, R., and Coauthors, 2006: Monsoon drought over Java, Indonesia, during the past two centuries. Geophys. Res. Lett., 33, L04709, https://doi.org/10.1029/2005GL025465.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • ESCAP, 2020: Ready for the dry years: Building resilience to drought in South-East Asia. Economic and Social Commission for Asia and the Pacific (ESCAP), United Nations, 68 pp., https://www.unescap.org/sites/default/files/publications/Ready%20for%20the%20Dry%20Years.pdf.

    • Search Google Scholar
    • Export Citation
  • Feng, J., L. Wang, W. Chen, S. K. Fong, and K. C. Leong, 2010: Different impacts of two types of Pacific Ocean warming on Southeast Asian rainfall during boreal winter. J. Geophys. Res., 115, D24122, https://doi.org/10.1029/2010JD014761.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., and M.-Y. C. Fovell, 1993: Climate zones of the conterminous United States defined using cluster analysis. J. Climate, 6, 21032135, https://doi.org/10.1175/1520-0442(1993)006<2103:CZOTCU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fung, K. F., Y. F. Huang, and C. H. Koo, 2020: Assessing drought conditions through temporal pattern, spatial characteristic and operational accuracy indicated by SPI and SPEI: Case analysis for Peninsular Malaysia. Nat. Hazards, 103, 20712101, https://doi.org/10.1007/s11069-020-04072-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ge, Y., T. Apurv, and X. Cai, 2016: Spatial and temporal patterns of drought in the continental U.S. during the past century. Geophys. Res. Lett., 43, 62946303, https://doi.org/10.1002/2016GL069660.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Glantz, M. H., and I. J. Ramirez, 2020: Reviewing the Oceanic Niño Index (ONI) to enhance societal readiness for El Niño’s impacts. Int. J. Disaster Risk Sci., 11, 394403, https://doi.org/10.1007/s13753-020-00275-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gocic, M., and S. Trajkovic, 2014: Spatiotemporal characteristics of drought in Serbia. J. Hydrol., 510, 110123, https://doi.org/10.1016/j.jhydrol.2013.12.030.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guerreiro, S. B., R. J. Dawson, C. Kilsby, E. Lewis, and A. Ford, 2018: Future heat-waves, droughts and floods in 571 European cities. Environ. Res. Lett., 13, 034009, https://doi.org/10.1088/1748-9326/aaaad3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hamid, E. Y., Z.-I. Kawasaki, and R. Mardiana, 2001: Impact of the 1997–98 El Niño event on lightning activity over Indonesia. Geophys. Res. Lett., 28, 147150, https://doi.org/10.1029/2000GL011374.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hanel, M., O. Rakovec, Y. Markonis, P. Máca, L. Samaniego, J. Kysely, and R. Kumar, 2018: Revisiting the recent European droughts from a long-term perspective. Sci. Rep., 8, 9499, https://doi.org/10.1038/s41598-018-27464-4.

    • Search Google Scholar
    • Export Citation
  • Harris, I., T. J. Osborn, P. Jones, and D. Lister, 2020: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., 2016: Introduction to the climate system. Global Physical Climatology, 2nd ed., Elsevier, 1–23.

  • Hasan, H. H., S. F. Mohd Razali, N. S. Muhammad, and A. Ahmad, 2021: Hydrological drought across Peninsular Malaysia: Implication of drought index. Nat. Hazards Earth Syst. Sci., preprint, https://doi.org/10.5194/nhess-2021-176.

    • Crossref
    • Export Citation
  • Haslinger, K., and G. Blöschl, 2017: Space-time patterns of meteorological drought events in the European greater alpine region over the past 210 years. Water Resour. Res., 53, 98079823, https://doi.org/10.1002/2017WR020797.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hernandez, M., C. C. Ummenhofer, and K. J. Anchukaitis, 2015: Multi-scale drought and ocean-atmosphere variability in monsoon Asia. Environ. Res. Lett., 10, 074010, https://doi.org/10.1088/1748-9326/10/7/074010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirahara, S., M. Ishii, and Y. Fukuda, 2014: Centennial-scale sea surface temperature analysis and its uncertainty. J. Climate, 27, 5775, https://doi.org/10.1175/JCLI-D-12-00837.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jim, C. Y., 1999: The forest fires in Indonesia 1997–98: Possible causes and pervasive consequences. Geography, 84, 251260, https://doi.org/10.2307/40573309.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Juneng, L., and F. T. Tangang, 2005: Evolution of ENSO-related rainfall anomalies in Southeast Asia region and its relationship with atmosphere–ocean variations in Indo-Pacific sector. Climate Dyn., 25, 337350, https://doi.org/10.1007/s00382-005-0031-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Juneng, L., and F. T. Tangang, 2010: Long-term trends of winter monsoon synoptic circulations over the Maritime Continent: 1962–2007. Atmos. Sci. Lett., 11, 199203, https://doi.org/10.1002/asl.272.

    • Search Google Scholar
    • Export Citation
  • Juneng, L., and Coauthors, 2016: Sensitivity of Southeast Asia rainfall simulations to cumulus and air–sea flux parameterizations in RegCM4. Climate Res., 69, 59–77, https://doi.org/10.3354/cr01386.

    • Crossref
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437472, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311644, https://doi.org/10.1175/BAMS-83-11-1631.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kang, H., and V. Sridhar, 2021: A near-term drought assessment using hydrological and climate forecasting in the Mekong River Basin. Int. J. Climatol., 41 (Suppl. 1), E2497E2516, https://doi.org/10.1002/joc.6860.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kaspar, F., A. Andersson, M. Ziese, and R. Hollmann, 2022: Contributions to the improvement of climate data availability and quality for sub-Saharan Africa. Front. Climate, 3, 815043, https://doi.org/10.3389/fclim.2021.815043.

    • Search Google Scholar
    • Export Citation
  • Kendall, M. G., 1970: Rank Correlation Methods. 4th ed. Charles Griffin 202 pp.

    • Crossref
    • Export Citation
  • Kumar, K. N., M. Rajeevan, D. S. Pai, A. K. Srivastava, and B. Preethi, 2013: On the observed variability of monsoon droughts over India. Wea. Climate Extremes, 1, 4250, https://doi.org/10.1016/j.wace.2013.07.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kurniadi, A., E. Weller, S. K. Min, and M. G. Seong, 2021: Independent ENSO and IOD impacts on rainfall extremes over Indonesia. Int. J. Climatol., 41, 36403656, https://doi.org/10.1002/joc.7040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuswanto, H., A. W. Puspa, I. S. Ahmad, and F. Hibatullah, 2021: Drought analysis in East Nusa Tenggara (Indonesia) using regional frequency analysis. Sci. World J., 2021, 6626102, https://doi.org/10.1155/2021/6626102.

    • Crossref
    • Export Citation
  • Lau, N. C., and M. J. Nath, 2003: Atmosphere–ocean variations in the Indo-Pacific sector during ENSO episodes. J. Climate, 16, 320, https://doi.org/10.1175/1520-0442(2003)016<0003:AOVITI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le, P. V. V., T. Phan-Van, K. V. Mai, and D. Q. Tran, 2019: Space–time variability of drought over Vietnam. Int. J. Climatol., 39, 54375451, https://doi.org/10.1002/joc.6164.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, S. Y., and J. L. McBride, 2016: The progression of the boreal winter monsoon through the western Maritime Continent as differentiated by ENSO phase. Adv. Geosci., 42, 5160, https://doi.org/10.5194/adgeo-42-51-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lima, C. H. R., and A. AghaKouchak, 2017: Droughts in Amazonia: Spatiotemporal variability, teleconnections, and seasonal predictions. Water Resour. Res., 53, 10 82410 840, https://doi.org/10.1002/2016WR020086.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mallya, G., V. Mishra, D. Niyogi, S. Tripathi, and R. S. Govindaraju, 2016: Trends and variability of droughts over the Indian monsoon region. Wea. Climate Extremes, 12, 4368, https://doi.org/10.1016/j.wace.2016.01.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mann, H. B., 1945: Nonparametric tests against trend. Econometrica, 13, 245259, https://doi.org/10.2307/1907187.

  • McKee, T. B., N. J. Doesken, and J. Kleist, 1993: The relationship of drought frequency and duration to time scales. Eighth Conf. on Applied Climatology, Anaheim, CA, Amer. Meteor. Soc., 179184.

    • Crossref
    • Export Citation
  • Miao, L., S. Li, F. Zhang, T. Chen, Y. Shan, and Y. Zhang, 2020: Future drought in the drylands of Asia under the 1.5°C and 2.0°C warming scenarios. Earth’s Future, 8, e2019EF001337, doi:10.1029/2019ef001337.

    • Crossref
    • Export Citation
  • Mishra, A. K., and V. P. Singh, 2010: A review of drought concepts. J. Hydrol., 391, 202216, https://doi.org/10.1016/j.jhydrol.2010.07.012.

  • Misra, V., and S. DiNapoli, 2013: The variability of the Southeast Asian summer monsoon. Int. J. Climatol., 34, 893901, https://doi.org/10.1002/joc.3735.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mo, R., 2003: Efficient algorithms for maximum covariance analysis of datasets with many variables and fewer realizations: A revisit. J. Atmos. Oceanic Technol., 20, 18041809, https://doi.org/10.1175/1520-0426(2003)020<1804:EAFMCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mursidi, A., and A. D. P. Sari, 2017: Management of drought disaster in Indonesia. J. Terapan Manajemen Bisnis, 3, 165–171, https://pdfs.semanticscholar.org/9ef3/eca3ce4249340fd8401f025abc517260611b.pdf.

    • Crossref
    • Export Citation
  • Naumann, G., and Coauthors, 2018: Global changes in drought conditions under different levels of warming. Geophys. Res. Lett., 45, 32853296, https://doi.org/10.1002/2017GL076521.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nguyen, P.-L., S.-K. Min, and Y.-H. Kim, 2020: Combined impacts of the El Niño–Southern Oscillation and Pacific Decadal Oscillation on global droughts assessed using the standardized precipitation evapotranspiration index. Int. J. Climatol., 41 (Suppl. 1), E1645–E1662, https://doi.org/10.1002/joc.6796.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nguyen-Ngoc-Bich, P., and Coauthors, 2021: Projected evolution of drought characteristics in Vietnam based on CORDEX-SEA downscaled CMIP5 data. Int. J. Climatol., 41, 57335751, https://doi.org/10.1002/joc.7150.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oñate-Valdivieso, F., V. Uchuari, and A. Oñate-Paladines, 2020: Large-scale climate variability patterns and drought: A case of study in South America. Water Resour. Manage., 34, 20612079, https://doi.org/10.1007/s11269-020-02549-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, J. H., J. S. Kug, S. I. An, and T. Li, 2019: Role of the western hemisphere warm pool in climate variability over the western North Pacific. Climate Dyn., 53, 27432755, https://doi.org/10.1007/s00382-019-04652-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poli, P., and Coauthors, 2017: Recent advances in satellite data rescue. Bull. Amer. Meteor. Soc., 98, 14711484, https://doi.org/10.1175/BAMS-D-15-00194.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pratiwi, N. A. H., M. Karuniasa, and D. S. Abi Suroso, 2018: Exploring historical and projection of drought periods in Cirebon Regency, Indonesia. E3S Web Conf., Vol. 68, Palembang, Indonesia, EDP Sciences, 02007.

    • Crossref
    • Export Citation
  • Qian, J. H., A. W. Robertson, and V. Moron, 2010: Interactions among ENSO, the monsoon, and diurnal cycle in rainfall variability over Java, Indonesia. J. Atmos. Sci., 67, 35093524, https://doi.org/10.1175/2010JAS3348.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qiu, S., W. Zhou, M. Y.-T. Leung, and X. Li, 2017: Regional moisture budget associated with drought/flood events over China. Prog. Earth Planet. Sci., 4, 36, https://doi.org/10.1186/s40645-017-0148-3.

    • Search Google Scholar
    • Export Citation
  • Räsänen, T. A., V. Lindgren, J. H. A. Guillaume, B. M. Buckley, and M. Kummu, 2016: On the spatial and temporal variability of ENSO precipitation and drought teleconnection in mainland Southeast Asia. Climate Past, 12, 18891905, https://doi.org/10.5194/cp-12-1889-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Riaz, S. M. F., M. J. Iqbal, and M. J. Baig, 2017: Influence of Siberian high on temperature variability over northern areas of South Asia. Meteor. Atmos. Phys., 130, 441457, https://doi.org/10.1007/s00703-017-0531-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rousseeuw, P. J., 1987: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math., 20, 5365, https://doi.org/10.1016/0377-0427(87)90125-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salimun, E., F. Tangang, L. Juneng, S. K. Behera, and W. Yu, 2014: Differential impacts of conventional El Niño versus El Niño Modoki on Malaysian rainfall anomaly during winter monsoon. Int. J. Climatol., 34, 27632774, https://doi.org/10.1002/joc.3873.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salinger, M. J., M. L. Shrestha, W. Dong, J. L. McGregor, and S. Wang, 2014: Climate in Asia and the Pacific: Climate variability and change. Climate in Asia and the Pacific, Springer, 17–57.

    • Crossref
    • Export Citation
  • Salvacion, A. R., 2021: Mapping meteorological drought hazard in the Philippines using SPI and SPEI. Spat. Inf. Res., 29, 949–960, https://doi.org/10.1007/s41324-021-00402-9.

    • Crossref
    • Export Citation
  • Sam, T. T., D. N. Khoi, N. T. T. Thao, P. T. T. Nhi, N. T. Quan, N. X. Hoan, and V. T. Nguyen, 2019: Impact of climate change on meteorological, hydrological and agricultural droughts in the Lower Mekong River Basin: A case study of the Srepok Basin, Vietnam. Water Environ. J., 33, 547559, https://doi.org/10.1111/wej.12424.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmitz, J. T., and S. L. Mullen, 1996: Water vapor transport associated with the summertime North American monsoon as depicted by ECMWF analyses. J. Climate, 9, 16211634, https://doi.org/10.1175/1520-0442(1996)009<1621:WVTAWT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, E. Rustemeier, and M. Ziese, 2020: GPCC full data monthly product version 2020 at 0.25°: Monthly land-surface precipitation from rain-gauges built on GTS-based and historical data. Accessed 2021, https://doi.org/10.5676/DWD_GPCC/FD_M_V2020_025.

    • Crossref
    • Export Citation
  • Sen, P. K., 1968: Estimates of the regression coefficient based on Kendall’s tau. J. Amer. Stat. Assoc., 63, 13791389, https://doi.org/10.1080/01621459.1968.10480934.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Setiawan, A. M., W.-S. Lee, and J. Rhee, 2017: Spatio-temporal characteristics of Indonesian drought related to El Niño events and its predictability using the multi-model ensemble. Int. J. Climatol., 37, 47004719, https://doi.org/10.1002/joc.5117.

    • Search Google Scholar
    • Export Citation
  • Sheffield, J., K. M. Andreadis, E. F. Wood, and D. P. Lettenmaier, 2009: Global and continental drought in the second half of the twentieth century: Severity–area–duration analysis and temporal variability of large-scale events. J. Climate, 22, 19621981, https://doi.org/10.1175/2008JCLI2722.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sheffield, J., E. F. Wood, and M. L. Roderick, 2012: Little change in global drought over the past 60 years. Nature, 491, 435438, https://doi.org/10.1038/nature11575.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Spinoni, J., T. Antofie, P. Barbosa, Z. Bihari, M. Lakatos, S. Szalai, T. Szentimrey, and J. Vogt, 2013: An overview of drought events in the Carpathian region in 1961–2010. Adv. Sci. Res., 10, 2132, https://doi.org/10.5194/asr-10-21-2013.

    • Search Google Scholar
    • Export Citation
  • Spinoni, J., G. Naumann, H. Carrao, P. Barbosa, and J. Vogt, 2014: World drought frequency, duration, and severity for 1951–2010. Int. J. Climatol., 34, 2792–2804, https://doi.org/10.1002/joc.3875.

  • Spinoni, J., G. Naumann, and J. V. Vogt, 2017: Pan-European seasonal trends and recent changes of drought frequency and severity. Global Planet. Change, 148, 113130, https://doi.org/10.1016/j.gloplacha.2016.11.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steinley, D., 2006: K-means clustering: A half-century synthesis. Br. J. Math. Stat. Psychol., 59, 134, https://doi.org/10.1348/000711005X48266.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stojanovic, M., and Coauthors, 2020: Trends and extremes of drought episodes in Vietnam sub-regions during 1980–2017 at different timescales. Water, 12, 813, https://doi.org/10.3390/w12030813.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Supari, F. T., E. Salimun, E. Aldrian, A. Sopaheluwakan, and L. Juneng, 2017: ENSO modulation of seasonal rainfall and extremes in Indonesia. Climate Dyn., 51, 25592580, https://doi.org/10.1007/s00382-017-4028-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Supharatid, S., and J. Nafung, 2021: Projected drought conditions by CMIP6 multimodel ensemble over Southeast Asia. J. Water Climate Change, 12, 33303354, https://doi.org/10.2166/wcc.2021.308.

    • Search Google Scholar
    • Export Citation
  • Suroso, D. Nadhilah, Ardiansyah, and E. Aldrian, 2021: Drought detection in Java Island based on Standardized Precipitation and Evapotranspiration Index (SPEI). J. Water Climate Change, 12, 2734–2752, https://doi.org/10.2166/wcc.2021.022.

    • Search Google Scholar
    • Export Citation
  • Tangang, F., and Coauthors, 2020: Projected future changes in rainfall in Southeast Asia based on CORDEX-SEA multi-model simulations. Climate Dyn., 55, 12471267, https://doi.org/10.1007/s00382-020-05322-2.

    • Search Google Scholar
    • Export Citation
  • Thilakarathne, M., and V. Sridhar, 2017: Characterization of future drought conditions in the lower Mekong River basin. Wea. Climate Extremes, 17, 4758, https://doi.org/10.1016/j.wace.2017.07.004.

    • Search Google Scholar
    • Export Citation
  • Thirumalai, K., P. N. DiNezio, Y. Okumura, and C. Deser, 2017: Extreme temperatures in Southeast Asia caused by El Niño and worsened by global warming. Nat. Comm., 8, 15531. https://doi.org/10.1038/ncomms15531.

  • Thornthwaite, C. W., 1948: An approach toward a rational classification of climate. Geogr. Rev., 38, 5594, https://doi.org/10.2307/210739.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., A. Dai, G. Van Der Schrier, P. D. Jones, J. Barichivich, K. R. Briffa, and J. Sheffield, 2014: Global warming and changes in drought. Nat. Climate Change, 4, 1722, https://doi.org/10.1038/nclimate2067.

    • Search Google Scholar
    • Export Citation
  • Ummenhofer, C. C., R. D. D’Arrigo, K. J. Anchukaitis, B. M. Buckley, and E. R. Cook, 2013: Links between Indo-Pacific climate variability and drought in the Monsoon Asia Drought Atlas. Climate Dyn., 40, 13191334, https://doi.org/10.1007/s00382-012-1458-1.

    • Search Google Scholar
    • Export Citation
  • Uttaruk, Y., and T. Laosuwan, 2019: Drought analysis using satellite-based data and spectral index in upper northeastern Thailand. Pol. J. Environ. Stud., 28, 44474454, https://doi.org/10.15244/pjoes/94998.

    • Search Google Scholar
    • Export Citation
  • Vicente-Serrano, S. M., S. Beguería, and J. I. López-Moreno, 2010: A multiscalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 16961718, https://doi.org/10.1175/2009JCLI2909.1.

    • Search Google Scholar
    • Export Citation
  • Wang, B., R. Wu, and T. I. M. Li, 2003: Atmosphere–warm ocean interaction and its impacts on Asian-Australian monsoon variation. J. Climate, 16, 11951211, https://doi.org/10.1175/1520-0442(2003)16<1195:AOIAII>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, C., 2019: 2019: Three-ocean interactions and climate variability: A review and perspective. Climate Dyn., 53, 51195136, https://doi.org/10.1007/s00382-019-04930-x.

    • Search Google Scholar
    • Export Citation
  • Wang, W., Y. Zhu, R. Xu, and J. Liu, 2015: Drought severity change in China during 1961–2012 indicated by SPI and SPEI. Nat. Hazards, 75, 24372451, https://doi.org/10.1007/s11069-014-1436-5.

    • Search Google Scholar
    • Export Citation
  • Warren, J. F., 2013: Climate change and the impact of drought on human affairs and human history in the Philippines, 1582 to 2009. Working paper 174, Murdoch University.

  • Wei, J., H. Su, and Z.-L. Yang, 2016: Impact of moisture flux convergence and soil moisture on precipitation: A case study for the southern United States with implications for the globe. Climate Dyn., 46, 467481, https://doi.org/10.1007/s00382-015-2593-2.

    • Search Google Scholar
    • Export Citation
  • Wilhite, D. A., and M. H. Glantz, 1985: Understanding the drought phenomenon: The role of definitions. Water Int., 10, 111120, https://doi.org/10.1080/02508068508686328.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. Vol. 91, Academic Press, 627 pp.

  • WMO, 2006: Drought monitoring and early warning: Concepts, progress and future challenges. WMO 1006, 24 pp., http://www.wamis.org/agm/pubs/brochures/WMO1006e.pdf.

  • Yao, J., D. Tuoliewubieke, J. Chen, W. Huo, and W. Hu, 2019: Identification of drought events and correlations with large-scale ocean–atmospheric patterns of variability: A case study in Xinjiang, China. Atmosphere, 10, 94, https://doi.org/10.3390/atmos10020094.

    • Search Google Scholar
    • Export Citation
  • Zhang, L., and T. Zhou, 2015: Drought over East Asia: A review. J. Climate, 28, 33753399, https://doi.org/10.1175/JCLI-D-14-00259.1.

  • Zhang, L., W. Song, and W. Song, 2020: Assessment of agricultural drought risk in the Lancang-Mekong Region, South East Asia. Int. J. Environ. Res. Public Health, 17, 6153, https://doi.org/10.3390/ijerph17176153.

    • Search Google Scholar
    • Export Citation
  • Zhang, W., F.-F. Jin, J.-X. Zhao, L. Qi, and H.-L. Ren, 2013: The possible influence of a nonconventional El Niño on the severe autumn drought of 2009 in Southwest China. J. Climate, 26, 83928405, https://doi.org/10.1175/JCLI-D-12-00851.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 272 272 272
Full Text Views 73 73 71
PDF Downloads 61 61 61

Drought over Southeast Asia and Its Association with Large-Scale Drivers

View More View Less
  • 1 aFaculty of Meteorology, Hydrology and Oceanography, VNU University of Science, Vietnam National University, Hanoi, Vietnam
  • | 2 bREMOSAT Laboratory, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, Hanoi, Vietnam
  • | 3 cGlenn Department of Civil Engineering, Clemson University, Clemson, South Carolina
  • | 4 dDepartment of Infrastructure and Urban Development Strategies, Vietnam Institute for Development Strategies, Ministry of Planning and Investment, Hanoi, Vietnam
  • | 5 eDepartment of Civil and Environmental Engineering, University of California, Irvine, Irvine, California
Restricted access

Abstract

In this study, the spatiotemporal variability of drought over the entire Southeast Asia (SEA) region and its associations with the large-scale climate drivers during the period 1960–2019 are investigated for the first time. The 12-month Standardized Precipitation Evapotranspiration Index (SPEI) was computed based on the monthly Global Precipitation Climatology Centre (GPCC) precipitation and the monthly Climate Research Unit (CRU) 2-m temperature. The relationships between drought and large-scale climate drivers were examined using the principal component analysis (PCA) and maximum covariance analysis (MCA) techniques. Results showed that the spatiotemporal variability of drought characteristics over SEA is significantly different between mainland Indochina and the Maritime Continent and the difference has been increased substantially in recent decades. Moreover, the entire SEA is divided into four homogeneous drought subregions. Drought over SEA is strongly associated with oceanic and atmospheric large-scale drivers, particularly El Niño–Southern Oscillation (ENSO), following by other remote factors such as the variability of sea surface temperature (SST) over the tropical Atlantic, the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IOD). In addition, there exists an SST anomaly dipole over the Pacific Ocean, which modulates the atmospheric circulations and consequently precipitation over SEA, affecting drought conditions in the study region.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Tan Phan-Van, phanvantan@hus.edu.vn

Abstract

In this study, the spatiotemporal variability of drought over the entire Southeast Asia (SEA) region and its associations with the large-scale climate drivers during the period 1960–2019 are investigated for the first time. The 12-month Standardized Precipitation Evapotranspiration Index (SPEI) was computed based on the monthly Global Precipitation Climatology Centre (GPCC) precipitation and the monthly Climate Research Unit (CRU) 2-m temperature. The relationships between drought and large-scale climate drivers were examined using the principal component analysis (PCA) and maximum covariance analysis (MCA) techniques. Results showed that the spatiotemporal variability of drought characteristics over SEA is significantly different between mainland Indochina and the Maritime Continent and the difference has been increased substantially in recent decades. Moreover, the entire SEA is divided into four homogeneous drought subregions. Drought over SEA is strongly associated with oceanic and atmospheric large-scale drivers, particularly El Niño–Southern Oscillation (ENSO), following by other remote factors such as the variability of sea surface temperature (SST) over the tropical Atlantic, the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IOD). In addition, there exists an SST anomaly dipole over the Pacific Ocean, which modulates the atmospheric circulations and consequently precipitation over SEA, affecting drought conditions in the study region.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Tan Phan-Van, phanvantan@hus.edu.vn

Supplementary Materials

    • Supplemental Materials (PDF 7.09 MB)
Save