Modeling the Influence of Upstream Land–Atmosphere Coupling on the 2017 Persistent Drought over Northeast China

Dingwen Zeng aSchool of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing, China
bKey Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
cKey Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, and Key Open Laboratory of Arid Climate Change and Disaster Reduction, Institute of Arid Meteorology, China Meteorological Administration, Lanzhou, China

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Xing Yuan aSchool of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing, China
bKey Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Abstract

Persistent drought events that cause serious damage to the economy and environment are usually intensified by the feedback between the land surface and atmosphere. Therefore, reasonably modeling land–atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling has focused on the amplification effect of land–atmosphere coupling on local anticyclonic circulation anomalies, while less attention has been paid to the nonlocal influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land–atmosphere coupling over the area south of Lake Baikal (ASLB) influences the drought events occurring over its downstream region [i.e., Northeast China (NEC)] by using the Weather Research and Forecasting (WRF) Model and a linear baroclinic model (LBM). When the ASLB region is artificially forced to be wet in the WRF simulations during March–May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May–July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May–July cannot be captured due to the upstream wetting in March–May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower-level heating instead of the upper-level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land–atmosphere coupling in capturing downstream persistent droughts.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-20-0650.s1.

© 2021 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: Xing Yuan, xyuan@nuist.edu.cn

Abstract

Persistent drought events that cause serious damage to the economy and environment are usually intensified by the feedback between the land surface and atmosphere. Therefore, reasonably modeling land–atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling has focused on the amplification effect of land–atmosphere coupling on local anticyclonic circulation anomalies, while less attention has been paid to the nonlocal influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land–atmosphere coupling over the area south of Lake Baikal (ASLB) influences the drought events occurring over its downstream region [i.e., Northeast China (NEC)] by using the Weather Research and Forecasting (WRF) Model and a linear baroclinic model (LBM). When the ASLB region is artificially forced to be wet in the WRF simulations during March–May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May–July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May–July cannot be captured due to the upstream wetting in March–May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower-level heating instead of the upper-level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land–atmosphere coupling in capturing downstream persistent droughts.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-20-0650.s1.

© 2021 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: Xing Yuan, xyuan@nuist.edu.cn

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  • Berg, A., B. Lintner, K. Findell, and A. Giannini, 2017: Soil moisture influence on seasonality and large-scale circulation in simulations of the West African monsoon. J. Climate, 30, 22952317, https://doi.org/10.1175/JCLI-D-15-0877.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berg, L. K., W. I. Gustafson Jr., E. I. Kassianov, and L. Deng, 2013: Evaluation of a modified scheme for shallow convection: Implementation of CuP and case studies. Mon. Wea. Rev., 141, 134147, https://doi.org/10.1175/MWR-D-12-00136.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, F., and Coauthors, 1996: Modeling of land-surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101, 72517268, https://doi.org/10.1029/95JD02165.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, M., P. Xie, and J. E. Janowiak, 2002: Global land precipitation: A 50-yr monthly analysis based on gauge observations. J. Hydrometeor., 3, 249266, https://doi.org/10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diasso, U., and B. J. Abiodun, 2017: Drought modes in West Africa and how well CORDEX RCMs simulate them. Theor. Appl. Climatol., 128, 223240, https://doi.org/10.1007/s00704-015-1705-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dole, R. M. P., and Coauthors, 2011: Was there a basis for anticipating the 2010 Russian heat wave? Geophys. Res. Lett., 38, L06702, https://doi.org/10.1029/2010GL046582.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duerinck, H. M., R. J. van der Ent, N. C. van de Giesen, G. Schoups, V. Babovic, and P. J.-F. Yeh , 2016: Observed soil moisture–precipitation feedback in Illinois: A systematic analysis over different scales. J. Hydrometeor., 17, 16451660, https://doi.org/10.1175/JHM-D-15-0032.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Entin, J. K., A. Robock, K. Y. Vinnikov, S. E. Hollinger, S. Liu, and A. Namkhai, 2000: Temporal and spatial scales of observed soil moisture variations in the extratropics. J. Geophys. Res., 105, 11 86511 877, https://doi.org/10.1029/2000JD900051.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fischer, E. M., S. I. Seneviratne, D. Lüthi, and C. Schär, 2007a: Contribution of land–atmosphere coupling to recent European summer heat waves. Geophys. Res. Lett., 34, L06707, https://doi.org/10.1029/2006GL029068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fischer, E. M., S. I. Seneviratne, P. L. Vidale, D. Lüthi, and C. Schär, 2007b: Soil moisture–atmosphere interactions during the 2003 European summer heat wave. J. Climate, 20, 50815099, https://doi.org/10.1175/JCLI4288.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gochis, D., W. Shuttleworth, and Z. L. Yang, 2002: Sensitivity of the modeled North American monsoon regional climate to convective parameterization. Mon. Wea. Rev., 130, 12821298, https://doi.org/10.1175/1520-0493(2002)130<1282:SOTMNA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grell, G. A., and D. Dévényi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693, https://doi.org/10.1029/2002GL015311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grell, G. A., and S. R. Freitas, 2014: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmos. Chem. Phys., 14, 52335250, https://doi.org/10.5194/acp-14-5233-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Han, J., and H. L. Pan, 2011: Revision of convection and vertical diffusion schemes in the NCEP Global Forecast System. Wea. Forecasting, 26, 520533, https://doi.org/10.1175/WAF-D-10-05038.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Han, T., H. Chen, and H. Wang, 2015: Recent changes in summer precipitation in Northeast China and the background circulation. Int. J. Climatol., 35, 42104219, https://doi.org/10.1002/joc.4280.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Han, T., H. Wang, and J. Sun, 2017: Strengthened relationship between eastern ENSO and summer precipitation over northeastern China. J. Climate, 30, 44974512, https://doi.org/10.1175/JCLI-D-16-0551.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirschi, M., and Coauthors, 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nat. Geosci., 4, 1721, https://doi.org/10.1038/ngeo1032.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S. Y., Y. Noh, and J. Dudhia, 2006a: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S. Y., J. H. Kim, J. O. Lim, and J. Dudhia, 2006b: The WRF single moment microphysics scheme (WSM). J. Korean Meteor. Soc., 42, 129151.

    • Search Google Scholar
    • Export Citation
  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jankov, I., W. A. Gallus Jr., M. Segal, B. Shaw, and S. E. Koch, 2005: The impact of different WRF model physical parameterizations and their interactions on warm season MCS rain. Wea. Forecasting, 20, 10481060, https://doi.org/10.1175/WAF888.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140, https://doi.org/10.1126/science.1100217.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., Y. Chang, H. Wang, and S. Schubert, 2016: Impacts of local soil moisture anomalies on the atmospheric circulation and on remote surface meteorological fields during boreal summer: A comprehensive analysis over North America. J. Climate, 29, 73457364, https://doi.org/10.1175/JCLI-D-16-0192.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lau, W. K. M., and K.-M. Kim, 2012: The 2010 Pakistan flood and Russian heat wave: Teleconnection of hydrometeorological extremes. J. Hydrometeor., 13, 392403, https://doi.org/10.1175/JHM-D-11-016.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, H., H. Chen, H. Wang, J. Sun, and J. Ma, 2018: Can Barents Sea ice decline in spring enhance summer hot drought events over northeastern China? J. Climate, 31, 47054725, https://doi.org/10.1175/JCLI-D-17-0429.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, K., J. Zhang, K. Yang, and L. Wu, 2019: The role of soil moisture feedbacks in future summer temperature change over East Asia. J. Geophys. Res. Atmos., 124, 12 03412 056, https://doi.org/10.1029/2018JD029670.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, W., W. Guo, Y. Xue, C. Fu, and B. Qiu, 2015: Sensitivity of a regional climate model to land surface parameterization schemes for East Asian summer monsoon simulation. Climate Dyn., 47, 22932308, https://doi.org/10.1007/s00382-015-2964-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, X., W. Zhou, and Y. D. Chen, 2015: Assessment of regional drought trend and risk over China: A drought climate division perspective. J. Climate, 28, 70257037, https://doi.org/10.1175/JCLI-D-14-00403.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liang, M., and X. Yuan, 2021: Critical role of soil moisture memory in predicting 2012 central USA flash drought. Front. Earth Sci., 9, 615969, https://doi.org/10.3389/feart.2021.615969.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liang, X.-Z., and Coauthors, 2012: Regional climate—Weather Research and Forecasting Model. Bull. Amer. Meteor. Soc., 93, 13631387, https://doi.org/10.1175/BAMS-D-11-00180.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lu, J., T. Feng, J. Li, Z. Cai, X. Xu, L. Li, and J. Li, 2019: Impact of assimilating Himawari-8-derived layered precipitable water with varying cumulus and microphysics parameterization schemes on the simulation of Typhoon Hato. J. Geophys. Res. Atmos., 124, 30503071, https://doi.org/10.1029/2018JD029364.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miralles, D. G., A. J. Teuling, C. C. van Heerwaarden, and J. Vilà-Guerau de Arellano, 2014: Mega heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci., 7, 345349, https://doi.org/10.1038/ngeo2141.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miralles, D. G., P. Gentine, S. I. Seneviatne, and A. J. Teuling, 2019: Land–atmospheric feedbacks during droughts and heatwaves: State of the science and current challenges. Ann. N. Y. Acad. Sci., 1436, 1935, https://doi.org/10.1111/nyas.13912.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • PaiMazumder, D., and J. M. Done, 2016: Potential predictability sources of the 2012 U.S. drought in observations and a regional model ensemble. J. Geophys. Res. Atmos., 121, 12 58112 592, https://doi.org/10.1002/2016JD025322.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Powers, J. G., and Coauthors, 2017: The Weather Research and Forecasting (WRF) Model: Overview, system efforts, and future directions. Bull. Amer. Meteor. Soc., 98, 17171737, https://doi.org/10.1175/BAMS-D-15-00308.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ren, X., D. Yang, and X. Yang, 2015: Characteristics and mechanisms of the subseasonal eastward extension of the South Asian high. J. Climate, 28, 67996822, https://doi.org/10.1175/JCLI-D-14-00682.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roundy, J. K., C. R. Ferguson, and E. F. Wood, 2013: Temporal variability of land–atmosphere coupling and its implications for drought over the Southeast United States. J. Hydrometeor., 14, 622635, https://doi.org/10.1175/JHM-D-12-090.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2014: The NCEP Climate Forecast System version 2. J. Climate, 27, 21852208, https://doi.org/10.1175/JCLI-D-12-00823.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schubert, S. D., H. Wang, and M. Suarez, 2011: Warm season subseasonal variability and climate extremes in the Northern Hemisphere: The role of stationary Rossby waves. J. Climate, 24, 47734792, https://doi.org/10.1175/JCLI-D-10-05035.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schubert, S. D., H. Wang, R. D. Koster, M. J. Suarez, and P. Ya. Groisman, 2014: Northern Eurasian heat waves and droughts. J. Climate, 27, 31693207, https://doi.org/10.1175/JCLI-D-13-00360.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schumacher, D. L., and Coauthors, 2019: Amplification of mega-heatwaves through heat torrents fuelled by upwind drought. Nat. Geosci., 12, 712717, https://doi.org/10.1038/s41561-019-0431-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Small, R. J. O., S. P. D. Szoeke, and S. P. Xie, 2007: The Central American midsummer drought: Regional aspects and large-scale forcing. J. Climate, 20, 48534873, https://doi.org/10.1175/JCLI4261.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., and H. Wang, 2006: Regional difference of summer air temperature in Northeast China and its relationship to atmospheric general circulation and sea surface temperature (in Chinese). Chin. J. Geophys., 49, 588598, https://doi.org/10.1002/cjg2.872.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., and H. Wang, 2012: Changes of the connection between the summer North Atlantic Oscillation and the East Asian summer rainfall. J. Geophys. Res., 117, D08110, https://doi.org/10.1029/2012JD017482.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Teuling, A. J., and Coauthors, 2013: Evapotranspiration amplifies European summer drought. Geophys. Res. Lett., 40, 20712075, https://doi.org/10.1002/grl.50495.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vaidya, S. S., and S. S. Singh, 2000: Applying the Betts–Miller–Janjic scheme of convection in prediction of the Indian monsoon. Wea. Forecasting, 15, 349356, https://doi.org/10.1175/1520-0434(2000)015<0349:ATBMJS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Hailan, S. D. Schubert, R. D. Koster, and Y. Chang, 2019: Phase locking of the boreal summer atmospheric response to dry land surface anomalies in the Northern Hemisphere. J. Climate, 32, 10811099, https://doi.org/10.1175/JCLI-D-18-0240.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Huijun, and S. He, 2015: The North China/northeastern Asia severe summer drought in 2014. J. Climate, 28, 66676681, https://doi.org/10.1175/JCLI-D-15-0202.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, S., X. Yuan, and R. Wu, 2019: Attribution of the persistent spring–summer hot and dry extremes over Northeast China in 2017. Bull. Amer. Meteor. Soc., 100, S85S89, https://doi.org/10.1175/BAMS-D-18-0120.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Z. Q., A. M. Duan, and G. X. Wu, 2014: Impacts of boundary layer parameterization schemes and air–sea coupling on WRF simulation of the East Asian summer monsoon. Sci. China Earth Sci., 44, 14801493, https://doi.org/10.1007/s11430-013-4801-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and F.-F. Jin, 2003: A moist linear baroclinic model: Coupled dynamical–convective response to El Niño. J. Climate, 16, 11211139, https://doi.org/10.1175/1520-0442(2003)16<1121:AMLBMC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., R. Vasic, Z. Janjić, Y. M. Liu, and P. C. Chu, 2012: The impact of spring subsurface soil temperature anomaly in the western U.S. on North American summer precipitation: A case study using regional climate model downscaling. J. Geophys. Res., 117, D11103, https://doi.org/10.1029/2012JD017692.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., and Coauthors, 2016: Spring land temperature anomalies in northwestern US and the summer drought over Southern Plains and adjacent areas. Environ. Res. Lett., 11, 044018, https://doi.org/10.1088/1748-9326/11/5/059502.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., and Coauthors, 2018: Spring land surface and subsurface temperature anomalies and subsequent downstream late spring–summer droughts/floods in North America and East Asia. J. Geophys. Res. Atmos., 123, 50015019, https://doi.org/10.1029/2017JD028246.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yanai, M., and T. Tomita, 1998: Seasonal and interannual variability of atmospheric heat sources and moisture sinks as determined from NCEP–NCAR reanalysis. J. Climate, 11, 463482, https://doi.org/10.1175/1520-0442(1998)011<0463:SAIVOA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, M., Q. Li, M. J. Hayes, M. D. Svoboda, and R. R. Heim, 2014: Are droughts becoming more frequent or severe in China based on the standardized precipitation evapotranspiration index: 1951–2010? Int. J. Climatol., 34, 545558, https://doi.org/10.1002/joc.3701.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuan, X., and E. F. Wood, 2013: Multimodel seasonal forecasting of global drought onset. Geophys. Res. Lett., 40, 49004905, https://doi.org/10.1002/grl.50949.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuan, X., X. Z. Liang, and E. F. Wood, 2012: WRF ensemble downscaling seasonal forecasts of China winter precipitation during 1982–2008. Climate Dyn., 39, 20412058, https://doi.org/10.1007/s00382-011-1241-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuan, X., L. Wang, P. Wu, P. Ji, J. Sheffield, and M. Zhang, 2019: Anthropogenic shift towards higher risk of flash drought over China. Nat. Commun., 10, 4661, https://doi.org/10.1038/s41467-019-12692-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuan, X., F. Ma, H. Li, and S. Chen, 2020: A review on multi-scale drought processes and prediction under global change (in Chinese). Trans. Atmos. Sci., 43, 225237.

    • Search Google Scholar
    • Export Citation
  • Zaitchik, B. F., J. A. Santanello, S. V. Kumar, and C. D. Peters-Lidard, 2013: Representation of soil moisture feedbacks during drought in NASA Unified WRF (NU-WRF). J. Hydrometeor., 14, 360367, https://doi.org/10.1175/JHM-D-12-069.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zeng, D., and X. Yuan, 2018: Multi-scale land–atmosphere coupling and its application in assessing subseasonal forecasts over East Asia. J. Hydrometeor., 19, 745760, https://doi.org/10.1175/JHM-D-17-0215.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zeng, D., X. Yuan, and J. K. Roundy, 2019: Effect of teleconnected land–atmosphere coupling on Northeast China persistent drought in spring–summer of 2017. J. Climate, 32, 74037420, https://doi.org/10.1175/JCLI-D-19-0175.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhai, J., B. Su, V. Krysanova, T. Vetter, C. Gao, and T. Jiang, 2010: Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of China. J. Climate, 23, 649663, https://doi.org/10.1175/2009JCLI2968.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, C., and Y. Wang, 2017: Projected future changes of tropical cyclone activity over the western North and South Pacific in a 20-km-mesh regional climate model. J. Climate, 30, 59235941, https://doi.org/10.1175/JCLI-D-16-0597.1.

    • Crossref
    • 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, R., and Z. Zuo, 2011: Impact of spring soil moisture on surface energy balance and summer monsoon circulation over East Asia and precipitation in East China. J. Climate, 24, 33093322, https://doi.org/10.1175/2011JCLI4084.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zheng, Y., K. Alapaty, J. A. Herwehe, A. D. Del Genio, and D. Niyogi, 2016: Improving high-resolution weather forecasts using the Weather Research and Forecasting (WRF) model with an updated Kain–Fritsch scheme. Mon. Wea. Rev., 144, 833860, https://doi.org/10.1175/MWR-D-15-0005.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhong, Z., Y. Hu, J. Min, and H. Xu, 2007: Numerical experiments on the spin-up time for seasonal-scale regional climate modeling. J. Meteor. Res., 21, 409419.

    • Search Google Scholar
    • Export Citation
  • Zhou, S., and Coauthors, 2019: Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity. Proc. Natl. Acad. Sci. USA, 116, 18 84818 853, https://doi.org/10.1073/pnas.1904955116.

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