Abstract
Seasonal forecasts of summer continental United States (CONUS) rainfall have relatively low skill, partly due to a lack of consensus about its sources of predictability. The East Asian monsoon (EAM) can excite a cross-Pacific Rossby wave train, also known as the Asia–North America (ANA) teleconnection. In this study, we analyze the ANA teleconnection in observations and model simulations from the Community Atmospheric Model, version 5 (CAM5), comparing experiments with prescribed climatological SSTs and prescribed observed SSTs. Observations indicate a statistically significant relationship between a strong EAM and increased probability of positive precipitation anomalies over the US west coast and the Plains-Midwest. The ANA teleconnection and CONUS rainfall patterns are improved in the CAM5 experiment with prescribed observed SSTs, suggesting that SST variability is necessary to simulate this teleconnection over CONUS. We find distinct ANA patterns between ENSO phases, with the La Niña-related patterns in CAM5 disagreeing with observations. Using linear steady-state quasi-geostrophic theory, we conclude that incorrect EAM forcing location greatly contributed to CAM5 biases, and jet stream disparities explained the ENSO-related biases. Finally, we compared EAM forcing experiments with different mean states using a simple dry nonlinear atmospheric general circulation model. Overall, the ANA pattern over CONUS and its modulation by ENSO forcing are well described by dry dynamics on seasonal-to-interannual timescales, including the constructive (destructive) interference between El Niño (La Niña) modulation and the ANA patterns over CONUS.
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References
Becker E, van den Dool H, Zhang Q (2014) Predictability and forecast skill in NMME. J Clim 27:5891–5906. https://doi.org/10.1175/JCLI-D-13-00597.1
Beverley JD, Woolnough SJ, Baker LH, Johnson SJ, Weisheimer A (2019) The northern hemisphere circumglobal teleconnection in a seasonal forecast model and its relationship to European summer forecast skill. Clim Dyn 52(5):3759–3771. https://doi.org/10.1007/s00382-018-4371-4
Beverley JD, Woolnough SJ, Baker LH, Johnson SJ, Weisheimer A, O’Reilly CH (2021) Dynamical mechanisms linking Indian monsoon precipitation and the circumglobal teleconnection. Clim Dyn 57(9):2615–2636. https://doi.org/10.1007/s00382-021-05825-6
Brenner S, Mitchell K (Kenneth Erwin), Yang C, U.S. Air Force Geophysics Laboratory, Atmospheric Sciences Division (1984) The AFGL global spectral model: expanded resolution baseline version. Hanscom AFB, Massachusetts: Air Force Geophysics Laboratory, Air Force Systems Command, United States Air Force. Retrieved from https://catalog.hathitrust.org/Record/102326036/Home. Accessed Feb 2021
Burgman RJ, Jang Y (2015) Simulated U.S. drought response to interannual and decadal Pacific SST variability. J Clim 28:4688–4705. https://doi.org/10.1175/JCLI-D-14-00247.1
Ciancarelli B, Castro CL, Woodhouse C, Dominguez F, Chang HI, Carrillo C, Griffin D (2014) Dominant patterns of US warm season precipitation variability in a fine resolution observational record, with focus on the southwest. Int J Climatol 34(3):687–707. https://doi.org/10.1002/joc.3716
DeAngelis AM, Wang H, Koster RD, Schubert SD, Chang Y, Marshak J (2020) Prediction skill of the 2012 U.S. Great Plains flash drought in subseasonal experiment (SubX) models. J Clim 33(14):6229–6253. https://doi.org/10.1175/JCLI-D-19-0863.1
Ding Q, Wang B (2005) Circumglobal teleconnection in the northern hemisphere summer. J Clim 18:3483–3505. https://doi.org/10.1175/JCLI3473.1
Ding Q, Wang B, Wallace JM, Branstator G (2011) Tropical–extratropical teleconnections in boreal summer: observed interannual variability. J Clim 24:1878–1896. https://doi.org/10.1175/2011JCLI3621.1
Dirmeyer PA, Fennessy MJ, Marx L (2003) Low skill in dynamical prediction of boreal summer climate: grounds for looking beyond sea surface temperature. J Clim 16:995–1002. https://doi.org/10.1175/1520-0442(2003)016%3c0995:LSIDPO%3e2.0.CO;2
Du Y, Li T, **e Z et al (2016) Interannual variability of the Asian subtropical westerly jet in boreal summer and associated with circulation and SST anomalies. Clim Dyn 46:2673. https://doi.org/10.1007/s00382-015-2723-x
Ha KJ, Seo YW, Lee JY, Kripalani RH, Yun KS (2018) Linkages between the South and East Asian summer monsoons: a review and revisit. Clim Dyn 51(11):4207–4227. https://doi.org/10.1007/s00382-017-3773-z
Hao Z, Singh VP, **a Y (2018) Seasonal drought prediction: advances, challenges, and future prospects. Rev Geophys 56:108–141. https://doi.org/10.1002/2016RG000549
Henderson SA, Maloney ED, Son S (2017) Madden–Julian oscillation Pacific teleconnections: the impact of the basic state and MJO representation in general circulation models. J Clim 30(12):4567–4587. https://doi.org/10.1175/JCLI-D-16-0789.1
Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J et al (2020) The ERA5 global reanalysis. Q J R Meteorol Soc 146(730):1999–2049. https://doi.org/10.1002/qj.3803
Hu Q, Feng S (2012) AMO- and ENSO-driven summertime circulation and precipitation variations in North America. J Clim 25:6477–6495. https://doi.org/10.1175/JCLI-D-11-00520.1
Hu ZZ, Kumar A, Jha B, Huang B (2020) How much of monthly mean precipitation variability over global land is associated with SST anomalies? Clim Dyn 54(1):701–712. https://doi.org/10.1007/s00382-019-05023-5
Huang B, Thorne PW, Banzon VF, Boyer T, Chepurin G, Lawrimore JH, Menne MJ, Smith TM, Vose RS, Zhang H (2017) 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
Islam S, Tang Y (2017) Simulation of different types of ENSO impacts on South Asian Monsoon in CCSM4. Clim Dyn 48(3–4):893–911. https://doi.org/10.1007/s00382-016-3117-4
Islam S, Tang Y, Jackson PL (2013) Asian monsoon simulations by Community Climate Models CAM4 and CCSM4. Clim Dyn 41(9–10):2617–2642. https://doi.org/10.1007/s00382-013-1752-6
Jha B, Kumar A, Hu ZZ (2019) An update on the estimate of predictability of seasonal mean atmospheric variability using North American Multi-Model Ensemble. Clim Dyn 53(12):7397–7409. https://doi.org/10.1007/s00382-016-3217-1
Jong B, Ting M, Seager R (2021) Assessing ENSO summer teleconnections, impacts, and predictability in North America. J Clim 34(9):3629–3643. https://doi.org/10.1175/JCLI-D-20-0761.1
Kim D, Lee S, Lopez H, Goes M (2020) Pacific mean-state control of Atlantic multidecadal oscillation–El Niño relationship. J Clim 33(10):4273–4291. https://doi.org/10.1175/JCLI-D-19-0398.1
Kirtman BP, Paolino DA, Kinter JL III, Straus DM (2001) Impact of tropical subseasonal SST variability on seasonal mean climate. Mon Weather Rev 129:853–868. https://doi.org/10.1175/1520-0493(2001)129%3c0853:IOTSSV%3e2.0.CO;2
Koster RD, Sud YC, Guo Z, Dirmeyer PA, Bonan G, Oleson KW et al (2006) GLACE: the global land–atmosphere coupling experiment. Part I: overview. J Hydrometeorol 7(4):590–610. https://doi.org/10.1175/JHM510.1
Lau W, Weng H (2002) Recurrent teleconnection patterns linking summertime precipitation variability over East Asia and North America. J Meteorol Soc Jpn 80:1309–1324. https://doi.org/10.2151/jmsj.80.1309
Lau K-M, Kim K-M, Lee J-Y (2004) Interannual variability, global teleconnection and potential predictability associated with the Asian summer monsoon. In: Chang CP (ed) East Asian monsoon. World Scientific, Singapore. https://doi.org/10.1142/9789812701411_0004
Lee S, Wang B (2016) Regional boreal summer intraseasonal oscillation over Indian Ocean and Western Pacific: comparison and predictability study. Clim Dyn 46:2213–2229. https://doi.org/10.1007/s00382-015-2698-7
Lee S, Wang C, Mapes BE (2009) A simple atmospheric model of the local and teleconnection responses to tropical heating anomalies. J Clim 22(2):272–284. https://doi.org/10.1175/2008JCLI2303.1
Lee JY, Wang B, Ding Q, Ha KJ, Ahn JB, Kumar A et al (2011) How predictable is the Northern Hemisphere summer upper-tropospheric circulation? Clim Dyn 37(5):1189–1203. https://doi.org/10.1007/s00382-010-0909-9
Li J, Ding R, Wu Z, Zhong Q, Li B, Li J (2019) Inter-decadal change in potential predictability of the East Asian summer monsoon. Theor Appl Climatol 136(1):403–415. https://doi.org/10.1007/s00704-018-2482-9
Li RKK, Tam CY, Lau NC, Sohn SJ, Ahn JB, O’Reilly C (2021) Forcing mechanism of the Silk Road pattern and the sensitivity of Rossby-wave source hotspots to mean-state winds. Q J R Meteorol Soc 47:2533–2546. https://doi.org/10.1002/qj.4039
Liu AZ, Ting M, Wang H (1998) Maintenance of circulation anomalies during the 1988 drought and 1993 floods over the United States. J Atmos Sci 55:2810–2832. https://doi.org/10.1175/1520-0469(1998)055%3c2810:MOCADT%3e2.0.CO;2
Liu F, Li T, Wang H, Deng L, Zhang Y (2016) Modulation of boreal summer intraseasonal oscillations over the western North Pacific by ENSO. J Clim 29(20):7189–7201. https://doi.org/10.1175/JCLI-D-15-0831.1
Liu Y, Ke Z, Ding Y (2019) Predictability of East Asian summer monsoon in seasonal climate forecast models. Int J Climatol 39(15):5688–5701. https://doi.org/10.1002/joc.6180
Lopez H, Lee S-K, Dong S, Goni G, Kirtman B, Atlas R, Kumar A (2019) East Asian Monsoon as a modulator of U.S. Great Plains heatwaves. J Geophys Res Atmos 124:6342–6358. https://doi.org/10.1029/2018JD030151
Mallakpour I, Villarini G (2016) Investigating the relationship between the frequency of flooding over the central United States and large-scale climate. Adv Water Resour 92:159–171. https://doi.org/10.1016/j.advwatres.2016.04.008
Malloy KM, Kirtman BP (2020) Predictability of midsummer Great Plains low-level jet and associated precipitation. Weather Forecast 35(1):215–235. https://doi.org/10.1175/WAF-D-19-0103.1
Mariotti A, Baggett C, Barnes EA, Becker E, Butler A, Collins DC, Dirmeyer PA, Ferranti L, Johnson NC, Jones J, Kirtman BP, Lang AL, Molod A, Newman M, Robertson AW, Schubert S, Waliser DE, Albers J (2021) Windows of opportunity for skillful forecasts subseasonal to seasonal and beyond. Bull Am Meteorol Soc 101(5):E608–E625. https://doi.org/10.1175/BAMS-D-18-0326.1
Moon JY, Wang B, Ha KJ, Lee JY (2013) Teleconnections associated with Northern Hemisphere summer monsoon intraseasonal oscillation. Clim Dyn 40(11–12):2761–2774. https://doi.org/10.1007/s00382-012-1394-0
Neale RB et al (2010) Description of the NCAR Community Atmosphere Model (CAM 5.0). NCAR technical note NCAR/TN-486+STR, National Center for Atmospheric Research, Boulder
O’Reilly CH, Woollings T, Zanna L, Weisheimer A (2018) The impact of tropical precipitation on summertime Euro-Atlantic circulation via a circumglobal wave train. J Clim 31:6481–6504. https://doi.org/10.1175/JCLI-D-17-0451.1
Pegion PJ, Kumar A (2010) Multimodel estimates of atmospheric response to modes of SST variability and implications for droughts. J Clim 23:4327–4341. https://doi.org/10.1175/2010JCLI3295.1
Schubert SD, Suarez MJ, Pegion PJ, Kistler MA, Kumar A (2002) Predictability of zonal means during boreal summer. J Clim 15:420–434. https://doi.org/10.1175/1520-0442(2002)015%3c0420:POZMDB%3e2.0.CO;2
Schubert SD, Suarez MJ, Pegion PJ, Koster RD, Bacmeister JT (2008) Potential predictability of long-term drought and pluvial conditions in the U.S. Great Plains. J Clim 21(4):802–816. https://doi.org/10.1175/2007JCLI1741.1
Schubert S, Wang H, Suarez M (2011) Warm season subseasonal variability and climate extremes in the Northern Hemisphere: the role of stationary Rossby waves. J Clim 24:4773–4792. https://doi.org/10.1175/JCLI-D-10-05035.1
Sheffield J, Camargo SJ, Fu R, Hu Q, Jiang X, Johnson N, Karnauskas KB, Kim ST, Kinter J, Kumar S, Langenbrunner B, Maloney E, Mariotti A, Meyerson JE, Neelin JD, Nigam S, Pan Z, Ruiz-Barradas A, Seager R, Serra YL, Sun D, Wang C, **e S, Yu J, Zhang T, Zhao M (2013) North American climate in CMIP5 experiments. Part II: evaluation of historical simulations of intraseasonal to decadal variability. J Clim 26:9247–9290. https://doi.org/10.1175/JCLI-D-12-00593.1
Slater LJ, Villarini G, Bradley AA (2016) Evaluation of the skill of North-American Multi-Model Ensemble (NMME) global climate models in predicting average and extreme precipitation and temperature over the continental USA. Clim Dyn. https://doi.org/10.1007/s00382-016-3286-1
Song F, Zhou T (2015) The crucial role of internal variability in modulating the decadal variation of the East Asian summer monsoon–ENSO relationship during the twentieth century. J Clim 28(18):7093–7107. https://doi.org/10.1175/JCLI-D-14-00783.1
Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A et al (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41(9–10):2711–2744. https://doi.org/10.1007/s00382-012-1607-6
Tian D, Wood EF, Yuan X (2017) CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States. Hydrol Earth Syst Sci 21(3):1477–1490. https://doi.org/10.5194/hess-21-1477-2017
Ting M, Wang H (1997) Summertime U.S. precipitation variability and its relation to Pacific sea surface temperature. J Clim 10:1853–1873. https://doi.org/10.1175/1520-0442(1997)010%3c1853:SUSPVA%3e2.0.CO;2
Trenberth KE, Branstator GW, Karoly D, Kumar A, Lau NC, Ropelewski C (1998) Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J Geophys Res 103(C7):14291–14324. https://doi.org/10.1029/97JC01444
Wang B, Wu R, Lau K (2001) Interannual variability of the Asian summer monsoon: contrasts between the Indian and the Western North Pacific–East Asian monsoons. J Clim 14:4073–4090. https://doi.org/10.1175/1520-0442(2001)014%3c4073:IVOTAS%3e2.0.CO;2
Wang B, Wu Z, Li J, Liu J, Chang CP, Ding Y, Wu G (2008) How to measure the strength of the East Asian summer monsoon. J Clim 21(17):4449–4463. https://doi.org/10.1175/2008JCLI2183.1
Wang J, Kim H, Kim D, Henderson SA, Stan C, Maloney ED (2020) MJO teleconnections over the PNA region in climate models. Part II: impacts of the MJO and basic state. J Clim 33(12):5081–5101. https://doi.org/10.1175/JCLI-D-19-0865.1
Weaver SJ, Schubert S, Wang H (2009) Warm season variations in the low-level circulation and precipitation over the Central United States in observations, AMIP simulations, and idealized SST experiments. J Clim 22:5401–5420. https://doi.org/10.1175/2009JCLI2984.1
Weaver SJ, Baxter S, Harnos K (2016) Regional changes in the interannual variability of U.S. warm season precipitation. J Clim 29:5157–5173. https://doi.org/10.1175/JCLI-D-14-00803.1
Wu B, Zhou T, Li T (2009) Contrast of rainfall–SST relationships in the Western North Pacific between the ENSO-develo** and ENSO-decaying summers. J Clim 22(16):4398–4405. https://doi.org/10.1175/2009JCLI2648.1
**e P, Arkin PA (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Am Meteorol Soc 78(11):2539–2558. https://doi.org/10.1175/1520-0477(1997)078%3c2539:GPAYMA%3e2.0.CO;2
Yang Y, Zhu Z, Li T, Yao M (2020) Effects of western Pacific intraseasonal convection on surface air temperature anomalies over North America. Int J Climatol 40(6):2913–2923. https://doi.org/10.1002/joc.6373
Zhao G, Huang G, Wu R, Tao W, Gong H, Qu X, Hu K (2015) A new upper-level circulation index for the East Asian summer monsoon variability. J Clim 28(24):9977–9996. https://doi.org/10.1175/JCLI-D-15-0272.1
Zhao S, Deng Y, Black RX (2018) An intraseasonal mode of atmospheric variability relevant to the U.S. hydroclimate in boreal summer: dynamic origin and East Asia connection. J Clim 31:9855–9868. https://doi.org/10.1175/JCLI-D-18-0206.1
Zhou S, L’Heureux M, Weaver S et al (2012) A composite study of the MJO influence on the surface air temperature and precipitation over the Continental United States. Clim Dyn 38:1459–1471. https://doi.org/10.1007/s00382-011-1001-9
Zhou F, Ren HL, Hu ZZ, Liu MH, Wu J, Liu CZ (2020) Seasonal predictability of primary East Asian summer circulation patterns by three operational climate prediction models. Q J R Meteorol Soc 146(727):629–646. https://doi.org/10.1002/qj.3697
Zhu Z, Li T (2016) A new paradigm for continental U.S. summer rainfall variability: Asia–North America teleconnection. J Clim 29:7313–7327. https://doi.org/10.1175/JCLI-D-16-0137.1
Zhu Z, Li T (2018) Amplified contiguous United States summer rainfall variability induced by East Asian monsoon interdecadal change. Clim Dyn 50:3523. https://doi.org/10.1007/s00382-017-3821-8
Zhu J, Huang B, Hu ZZ, Kinter JL, Marx L (2013) Predicting US summer precipitation using NCEP Climate Forecast System version 2 initialized by multiple ocean analyses. Clim Dyn 41(7–8):1941–1954. https://doi.org/10.1007/s00382-013-1785-x
Acknowledgements
The authors would like to thank the two anonymous reviewers for their insight and constructive feedback, which helped improve the manuscript. The authors acknowledge the National Center for Atmospheric Research for access to the Community Earth System Model to conduct the prescribed SST experiments. We also thank the University of Miami Institute for Data Science and Computing (IDSC) for computational resources to complete the dry nonlinear AGCM model experiments.
Funding
This work was supported through NOAA Grants NA15OAR4320064, NA16OAR4310141, N16OAR4310149 and NA20OAR430472 and DOE Grant DE-SC0019433.
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Malloy, K., Kirtman, B.P. The summer Asia–North America teleconnection and its modulation by ENSO in Community Atmosphere Model, version 5 (CAM5). Clim Dyn 59, 2213–2230 (2022). https://doi.org/10.1007/s00382-022-06205-4
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DOI: https://doi.org/10.1007/s00382-022-06205-4