• Amaya, D. J., 2019: The Pacific Meridional Mode and ENSO: A review. Curr. Climate Change Rep., 5, 296307, https://doi.org/10.1007/s40641-019-00142-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baggett, C. F., E. A. Barnes, E. D. Maloney, and B. D. Mundhenk, 2017: Advancing atmospheric river forecasts into subseasonal-to-seasonal time scales. Geophys. Res. Lett., 44, 75287536, https://doi.org/10.1002/2017GL074434.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berg, N., and A. Hall, 2015: Increased interannual precipitation extremes over California under climate change. J. Climate, 28, 63246334, https://doi.org/10.1175/JCLI-D-14-00624.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blackport, R., and J. A. Screen, 2019: Influence of Arctic sea ice loss in autumn compared to that in winter on the atmospheric circulation. Geophys. Res. Lett., 46, 22132221, https://doi.org/10.1029/2018GL081469.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cayan, D. R., and J. O. Roads, 1984: Local relationships between United States West Coast precipitation and monthly mean circulation parameters. Mon. Wea. Rev., 112, 12761282, https://doi.org/10.1175/1520-0493(1984)112<1276:LRBUSW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, M., and A. Kumar, 2018: Winter 2015/16 atmospheric and precipitation anomalies over North America: El Niño response and the role of noise. Mon. Wea. Rev., 146, 909927, https://doi.org/10.1175/MWR-D-17-0116.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chiang, J. C. H., and D. J. Vimont, 2004: Analogous Pacific and Atlantic meridional modes of tropical atmosphere–ocean variability. J. Climate, 17, 41434158, https://doi.org/10.1175/JCLI4953.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, J., K. Pfeiffer, and J. A. Francis, 2018: Warm Arctic episodes linked with increased frequency of extreme winter weather in the United States. Nat. Commun., 9, 869, https://doi.org/10.1038/s41467-018-02992-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Compo, G. P., and Coauthors, 2011: The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc., 137, 128, https://doi.org/10.1002/qj.776.

  • Conil, S., and A. Hall, 2006: Local regimes of atmospheric variability: A case study of Southern California. J. Climate, 19, 43084325, https://doi.org/10.1175/JCLI3837.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, B. I., A. P. Williams, J. S. Mankin, R. Seager, J. E. Smerdon, and D. Singh, 2018: Revisiting the leading drivers of Pacific coastal drought variability in the contiguous United States. J. Climate, 31, 2543, https://doi.org/10.1175/JCLI-D-17-0172.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cvijanovic, I., B. D. Santer, C. Bonfils, D. D. Lucas, J. C. H. Chiang, and S. Zimmerman, 2017: Future loss of Arctic sea-ice cover could drive a substantial decrease in California’s rainfall. Nat. Commun., 8, 1947, https://doi.org/10.1038/s41467-017-01907-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davini, P., C. Cagnazzo, S. Gualdi, and A. Navarra, 2012: Bidimensional diagnostics, variability, and trends of Northern Hemisphere blocking. J. Climate, 25, 64966509, https://doi.org/10.1175/JCLI-D-12-00032.1.

    • 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
  • DeFlorio, M. J., D. E. Waliser, B. Guan, D. A. Lavers, F. M. Ralph, and F. Vitart, 2018: Global assessment of atmospheric river prediction skill. J. Hydrometeor., 19, 409426, https://doi.org/10.1175/JHM-D-17-0135.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeFlorio, M. J., D. E. Waliser, B. Guan, F. M. Ralph, and F. Vitart, 2019: Global evaluation of atmospheric river subseasonal prediction skill. Climate Dyn., 52, 30393060, https://doi.org/10.1007/s00382-018-4309-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., I. R. Simpson, K. A. McKinnon, and A. S. Phillips, 2017: The Northern Hemisphere extratropical atmospheric circulation response to ENSO: How well do we know it and how do we evaluate models accordingly? J. Climate, 30, 50595082, https://doi.org/10.1175/JCLI-D-16-0844.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M. D., 2013: Atmospheric rivers as drought busters on the U.S. West Coast. J. Hydrometeor., 14, 17211732, https://doi.org/10.1175/JHM-D-13-02.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M. D., 2016: Historical and future relations between large storms and droughts in California. San Francisco Estuary Watershed Sci., 14, 121, https://doi.org/10.15447/sfews.2016v14iss2art1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M. D., F. M. Ralph, T. Das, P. J. Neiman, and D. R. Cayan, 2011: Atmospheric rivers, floods and the water resources of California. Water, 3, 445478, https://doi.org/10.3390/w3020445.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dole, R. M., 1986: Persistent anomalies of the extratropical Northern Hemisphere wintertime circulation: Structure. Mon. Wea. Rev., 114, 178207, https://doi.org/10.1175/1520-0493(1986)114<0178:PAOTEN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dong, L., L. R. Leung, and F. Song, 2018: Future changes of subseasonal precipitation variability in North America during winter under global warming. Geophys. Res. Lett., 45, 12 46712 476, https://doi.org/10.1029/2018GL079900.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garfinkel, C. I., A. H. Butler, D. W. Waugh, M. M. Hurwitz, and L. M. Polvani, 2012: Why might stratospheric sudden warmings occur with similar frequency in El Niño and La Niña winters? J. Geophys. Res., 117, D19106, https://doi.org/10.1029/2012JD017777.

    • Search Google Scholar
    • Export Citation
  • Gelaro, R., and Coauthors, 2017: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). J. Climate, 30, 54195454, https://doi.org/10.1175/JCLI-D-16-0758.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gibson, P. B., S. E. Perkins-Kirkpatrick, P. Uotila, A. S. Pepler, and L. V. Alexander, 2017: On the use of self-organizing maps for studying climate extremes. J. Geophys. Res. Atmos., 122, 38913903, https://doi.org/10.1002/2016JD026256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gibson, P. B., D. E. Waliser, H. Lee, B. Tian, and E. Massoud, 2019: Climate model evaluation in the presence of observational uncertainty: Precipitation indices over the contiguous United States. J. Hydrometeor., 20, 13391357, https://doi.org/10.1175/JHM-D-18-0230.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, B., and D. E. Waliser, 2015: Detection of atmospheric rivers: Evaluation and application of an algorithm for global studies. J. Geophys. Res. Atmos., 120, 12 51412 535, https://doi.org/10.1002/2015JD024257.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, B., D. E. Waliser, N. P. Molotch, E. J. Fetzer, and P. J. Neiman, 2012: Does the Madden–Julian Oscillation influence wintertime atmospheric rivers and snowpack in the Sierra Nevada? Mon. Wea. Rev., 140, 325342, https://doi.org/10.1175/MWR-D-11-00087.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guan, B., N. P. Molotch, D. E. Waliser, E. J. Fetzer, and P. J. Neiman, 2013: The 2010/2011 snow season in California’s Sierra Nevada: Role of atmospheric rivers and modes of large-scale variability. Water Resour. Res., 49, 67316743, https://doi.org/10.1002/wrcr.20537.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guirguis, K., A. Gershunov, R. E. S. Clemesha, T. Shulgina, A. C. Subramanian, and F. M. Ralph, 2018: Circulation drivers of atmospheric rivers at the North American west coast. Geophys. Res. Lett., 45, 12 57612 584, https://doi.org/10.1029/2018GL079249.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guirguis, K., A. Gershunov, T. Shulgina, R. E. S. Clemesha, and F. M. Ralph, 2019: Atmospheric rivers impacting Northern California and their modulation by a variable climate. Climate Dyn., 52, 65696583, https://doi.org/10.1007/S00382-018-4532-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hayes, M. J., M. D. Svoboda, D. A. Wilhite, and O. V. Vanyarkho, 1999: Monitoring the 1996 drought using the standardized precipitation index. Bull. Amer. Meteor. Soc., 80, 429438, https://doi.org/10.1175/1520-0477(1999)080<0429:MTDUTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henderson, S. A., E. D. Maloney, and E. A. Barnes, 2016: The influence of the Madden–Julian oscillation on Northern Hemisphere winter blocking. J. Climate, 29, 45974616, https://doi.org/10.1175/JCLI-D-15-0502.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hendon, H. H., 1986: Streamfunction and velocity potential representation of equatorially trapped waves. J. Atmos. Sci., 43, 30383042, https://doi.org/10.1175/1520-0469(1986)043<3038:SAVPRO>2.0.CO;2.

    • 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
  • Horton, D. E., N. C. Johnson, D. Singh, D. L. Swain, B. Rajaratnam, and N. S. Diffenbaugh, 2015: Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature, 522, 465469, https://doi.org/10.1038/nature14550.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoskins, B., and K. Hodges, 2019: The annual cycle of Northern Hemisphere storm tracks. Part I: Seasons. J. Climate, 32, 17431760, https://doi.org/10.1175/JCLI-D-17-0870.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, H., F. Dominguez, Z. Wang, D. A. Lavers, G. Zhang, and F. M. Ralph, 2017: Linking atmospheric river hydrological impacts on the U.S. West Coast to Rossby wave breaking. J. Climate, 30, 33813399, https://doi.org/10.1175/JCLI-D-16-0386.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, B., and Coauthors, 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 81798205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jenney, A. M., K. M. Nardi, E. A. Barnes, and D. A. Randall, 2019: The seasonality and regionality of MJO impacts on North American temperature. Geophys. Res. Lett., 46, 91939202, https://doi.org/10.1029/2019GL083950.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jong, B.-T., M. Ting, R. Seager, N. Henderson, and D. E. Lee, 2018: Role of equatorial Pacific SST forecast error in the late winter California precipitation forecast for the 2015/16 El Niño. J. Climate, 31, 839852, https://doi.org/10.1175/JCLI-D-17-0145.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulkarni, A., and H. von Storch, 1995: Monte Carlo experiments on the effect of serial correlation on the Mann-Kendall test of trend. Meteor. Z., 4, 8285, https://doi.org/10.1127/metz/4/1992/82.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, S. K., H. Lopez, E. S. Chung, P. DiNezio, S. W. Yeh, and A. T. Wittenberg, 2018: On the fragile relationship between El Niño and California rainfall. Geophys. Res. Lett., 45, 907915, https://doi.org/10.1002/2017GL076197.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lehner, F., C. Deser, I. R. Simpson, and L. Terray, 2018: Attributing the U.S. Southwest’s recent shift into drier conditions. Geophys. Res. Lett., 45, 62516261, https://doi.org/10.1029/2018GL078312.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, P., and Coauthors, 2018: Climatology of tracked persistent maxima of 500-hPa geopotential height. Climate Dyn., 51, 701717, https://doi.org/10.1007/s00382-017-3950-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Masato, G., B. J. Hoskins, and T. Woollings, 2013: Wave-breaking characteristics of Northern Hemisphere winter blocking: A two-dimensional approach. J. Climate, 26, 45354549, https://doi.org/10.1175/JCLI-D-12-00240.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., C. T. Y. Chung, J. M. Arblaster, M. M. Holland, and C. M. Bitz, 2018: Tropical decadal variability and the rate of Arctic sea ice decrease. Geophys. Res. Lett., 45, 11 32611 333, https://doi.org/10.1029/2018GL079989.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morss, R. E., J. K. Lazo, B. G. Brown, H. E. Brooks, P. T. Ganderton, and B. N. Mills, 2008: Societal and economic research and applications for weather forecasts: Priorities for the North American THORPEX program. Bull. Amer. Meteor. Soc., 89, 335346, https://doi.org/10.1175/BAMS-89-3-335.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mundhenk, B. D., E. A. Barnes, E. D. Maloney, and K. M. Nardi, 2016: Modulation of atmospheric rivers near Alaska and the U.S. West Coast by Northeast Pacific height anomalies. J. Geophys. Res. Atmos., 121, 12 75112 765, https://doi.org/10.1002/2016jd025350.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mundhenk, B. D., E. A. Barnes, E. D. Maloney, and C. F. Baggett, 2018: Skillful empirical subseasonal prediction of landfalling atmospheric river activity using the Madden–Julian Oscillation and quasi-biennial oscillation. npj Climate Atmos. Sci., 1, 20177, https://doi.org/10.1038/S41612-017-0008-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Myers, T. A., C. R. Mechoso, G. V. Cesana, M. J. DeFlorio, and D. E. Waliser, 2018: Cloud feedback key to marine heatwave off Baja California. Geophys. Res. Lett., 45, 43454352, https://doi.org/10.1029/2018GL078242.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, M., and P. D. Sardeshmukh, 1998: The impact of the annual cycle on the North Pacific/North American response to remote low-frequency forcing. J. Atmos. Sci., 55, 13361353, https://doi.org/10.1175/1520-0469(1998)055<1336:TIOTAC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pandey, G. R., D. R. Cayan, and K. P. Georgakakos, 1999: Precipitation structure in the Sierra Nevada of California during winter. J. Geophys. Res., 104, 12 01912 030, https://doi.org/10.1029/1999JD900103.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Parsons, S., J. A. Renwick, and A. J. McDonald, 2016: An assessment of future Southern Hemisphere blocking using CMIP5 projections from four GCMs. J. Climate, 29, 75997611, https://doi.org/10.1175/JCLI-D-15-0754.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, P., A. Kumar, M. Chen, Z.-Z. Hu, and B. Jha, 2019: Was the North American extreme climate in winter 2013/14 a SST forced response? Climate Dyn., 52, 30993110, https://doi.org/10.1007/S00382-018-4314-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pfahl, S., C. Schwierz, M. Croci-Maspoli, C. M. Grams, and H. Wernli, 2015: Importance of latent heat release in ascending air streams for atmospheric blocking. Nat. Geosci., 8, 610614, https://doi.org/10.1038/ngeo2487.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rayner, S., D. Lach, and H. Ingram, 2005: Weather forecasts are for wimps: Why water resource managers do not use climate forecasts. Climatic Change, 69, 197227, https://doi.org/10.1007/s10584-005-3148-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reichle, R. H., Q. Liu, R. D. Koster, C. S. Draper, S. P. P. Mahanama, and G. S. Partyka, 2017: Land surface precipitation in MERRA-2. J. Climate, 30, 16431664, https://doi.org/10.1175/JCLI-D-16-0570.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Renwick, J. A., 2005: Persistent positive anomalies in the Southern Hemisphere circulation. Mon. Wea. Rev., 133, 977988, https://doi.org/10.1175/MWR2900.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Riddle, E. E., A. H. Butler, J. C. Furtado, J. L. Cohen, and A. Kumar, 2013: CFSv2 ensemble prediction of the wintertime Arctic Oscillation. Climate Dyn., 41, 10991116, https://doi.org/10.1007/s00382-013-1850-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., and Coauthors, 2014: Skillful long-range prediction of European and North American winters. Geophys. Res. Lett., 41, 25142519, https://doi.org/10.1002/2014GL059637.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., and N. Henderson, 2016: On the role of tropical ocean forcing of the persistent North American West Coast ridge of winter 2013/14. J. Climate, 29, 80278049, https://doi.org/10.1175/JCLI-D-16-0145.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., N. Harnik, W. A. Robinson, Y. Kushnir, M. Ting, H.-P. Huang, and J. Velez, 2005: Mechanisms of ENSO-forcing of hemispherically symmetric precipitation variability. Quart. J. Roy. Meteor. Soc., 131, 15011527, https://doi.org/10.1256/qj.04.96.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., and Coauthors, 2015: Causes of the 2011–14 California drought. J. Climate, 28, 69977024, https://doi.org/10.1175/JCLI-D-14-00860.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Singh, D., M. Ting, A. A. Scaife, and N. Martin, 2018: California winter precipitation predictability: Insights from the anomalous 2015–2016 and 2016–2017 seasons. Geophys. Res. Lett., 45, 99729980, https://doi.org/10.1029/2018GL078844.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Swain, D. L., 2015: A tale of two California droughts: Lessons amidst record warmth and dryness in a region of complex physical and human geography. Geophys. Res. Lett., 42, 999910 003, https://doi.org/10.1002/2015GL066628.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Swain, D. L., M. Tsiang, M. Haugen, D. Singh, A. Charland, B. Rajaratnam, and N. S. Diffenbaugh, 2014: The extraordinary California drought of 2013/2014: Character, context, and the role of climate change [in “Explaining Extremes of 2013 from a Climate Perspective”]. Bull. Amer. Meteor. Soc., 95 (9), S3S7, https://doi.org/10.1175/1520-0477-95.9.S1.1.

    • Search Google Scholar
    • Export Citation
  • Swain, D. L., D. E. Horton, D. Singh, and N. S. Diffenbaugh, 2016: Trends in atmospheric patterns conducive to seasonal precipitation and temperature extremes in California. Sci. Adv., 2, e1501344, https://doi.org/10.1126/sciadv.1501344.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Swain, D. L., D. Singh, D. E. Horton, J. S. Mankin, T. C. Ballard, and N. S. Diffenbaugh, 2017: Remote linkages to anomalous winter atmospheric ridging over the northeastern Pacific. J. Geophys. Res. Atmos., 122, 12 19412 209, https://doi.org/10.1002/2017JD026575.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Swain, D. L., B. Langenbrunner, J. D. Neelin, and A. Hall, 2018: Increasing precipitation volatility in twenty-first-century California. Nat. Climate Change, 8, 427433, https://doi.org/10.1038/s41558-018-0140-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Takaya, K., and H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608627, https://doi.org/10.1175/1520-0469(2001)058<0608:AFOAPI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Teng, H., and G. Branstator, 2017: Causes of extreme ridges that induce California droughts. J. Climate, 30, 14771492, https://doi.org/10.1175/JCLI-D-16-0524.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett., 25, 12971300, https://doi.org/10.1029/98GL00950.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thornton, P. E., M. M. Thornton, B. W. Mayer, Y. Wei, R. Devarakonda, R. S. Vose, and R. B. Cook, 2016: Daymet: daily surface weather data on a 1-km grid for North America, version 3. Oak Ridge National Laboratory Distributed Active Archive Center, accessed 5 April 2019, https://doi.org/10.3334/ORNLDAAC/1328.

    • Crossref
    • Export Citation
  • Ting, M., R. Seager, C. Li, H. Liu, and N. Henderson, 2018: Mechanism of future spring drying in the Southwestern United States in CMIP5 models. J. Climate, 31, 42654279, https://doi.org/10.1175/JCLI-D-17-0574.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Titchner, H. A., and N. A. Rayner, 2014: The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations. J. Geophys. Res. Atmos., 119, 28642889, https://doi.org/10.1002/2013JD020316.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tseng, K.-C., E. A. Barnes, and E. D. Maloney, 2018: Prediction of the midlatitude response to strong Madden–Julian Oscillation events on S2S time scales. Geophys. Res. Lett., 45, 463470, https://doi.org/10.1002/2017GL075734.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vitart, F., and Coauthors, 2017: The Subseasonal to Seasonal (S2S) prediction project database. Bull. Amer. Meteor. Soc., 98, 163173, https://doi.org/10.1175/BAMS-D-16-0017.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vose, R., and Coauthors, 2014: Gridded 5km GHCN-daily temperature and precipitation dataset (nCLIMGRID), version 1.0. NOAA National Centers for Environmental Information, accessed 16 January 2019, https://doi.org/10.7289/V5SX6B56.

    • Crossref
    • Export Citation
  • Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 19171932, https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2016: “The stippling shows statistically significant grid points”: How research results are routinely overstated and overinterpreted, and what to do about it. Bull. Amer. Meteor. Soc., 97, 22632273, https://doi.org/10.1175/BAMS-D-15-00267.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woollings, T., B. Hoskins, M. Blackburn, and P. Berrisford, 2008: A new Rossby wave–breaking interpretation of the North Atlantic Oscillation. J. Atmos. Sci., 65, 609626, https://doi.org/10.1175/2007JAS2347.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woollings, T., and Coauthors, 2018: Blocking and its response to climate change. Curr. Climate Change Rep., 4, 287300, https://doi.org/10.1007/s40641-018-0108-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yue, S., P. Pilon, B. Phinney, and G. Cavadias, 2002: The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol. Processes, 16, 18071829, https://doi.org/10.1002/hyp.1095.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, Y., and H.-M. Kim, 2018: Prediction of atmospheric rivers over the North Pacific and its connection to ENSO in the North American Multi-Model Ensemble (NMME). Climate Dyn., 16231637, https://doi.org/10.1007/S00382-017-3973-6.

    • Crossref
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Ridging Associated with Drought across the Western and Southwestern United States: Characteristics, Trends, and Predictability Sources

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  • 1 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California
  • 2 Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, California
  • 3 Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California
  • 4 Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, California, and Capacity Center for Climate and Weather Extremes, National Center for Atmospheric Research, Boulder, Colorado, and Nature Conservancy of California, San Francisco, California
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Abstract

Persistent winter ridging events are a consistent feature of meteorological drought across the western and southwestern United States. In this study, a ridge detection algorithm is developed and applied on daily geopotential height anomalies to track and quantify the diversity of individual ridge characteristics (e.g., position, frequency, magnitude, extent, and persistence). Three dominant ridge types are shown to play important, but differing, roles for influencing the location of landfalling atmospheric rivers (ARs), precipitation, and subsequently meteorological drought. For California, a combination of these ridge types is important for influencing precipitation deficits on daily through seasonal time scales, indicating the various pathways by which ridging can induce drought. Furthermore, both the frequency of ridge types and reduced AR activity are necessary features for explaining drought variability on seasonal time scales across the western and southwestern regions. The three ridge types are found to be associated in different ways with various remote drivers and modes of variability, highlighting possible sources of subseasonal-to-seasonal (S2S) predictability. A comparison between ridge types shows that anomalously large and persistent ridging events relate to different Rossby wave trains across the Pacific with different preferential upstream locations of tropical heating. For the “South-ridge” type, centered over the Southwest, a positive trend is found in both the frequency and persistence of these events across recent decades, likely contributing to observed regional drying. These results illustrate the utility of feature tracking for characterizing a wider range of ridging features that collectively influence precipitation deficits and drought.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0439.s1.

© 2020 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: Peter B. Gibson, pgibson@ucsd.edu

Abstract

Persistent winter ridging events are a consistent feature of meteorological drought across the western and southwestern United States. In this study, a ridge detection algorithm is developed and applied on daily geopotential height anomalies to track and quantify the diversity of individual ridge characteristics (e.g., position, frequency, magnitude, extent, and persistence). Three dominant ridge types are shown to play important, but differing, roles for influencing the location of landfalling atmospheric rivers (ARs), precipitation, and subsequently meteorological drought. For California, a combination of these ridge types is important for influencing precipitation deficits on daily through seasonal time scales, indicating the various pathways by which ridging can induce drought. Furthermore, both the frequency of ridge types and reduced AR activity are necessary features for explaining drought variability on seasonal time scales across the western and southwestern regions. The three ridge types are found to be associated in different ways with various remote drivers and modes of variability, highlighting possible sources of subseasonal-to-seasonal (S2S) predictability. A comparison between ridge types shows that anomalously large and persistent ridging events relate to different Rossby wave trains across the Pacific with different preferential upstream locations of tropical heating. For the “South-ridge” type, centered over the Southwest, a positive trend is found in both the frequency and persistence of these events across recent decades, likely contributing to observed regional drying. These results illustrate the utility of feature tracking for characterizing a wider range of ridging features that collectively influence precipitation deficits and drought.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0439.s1.

© 2020 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: Peter B. Gibson, pgibson@ucsd.edu

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