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The East Asian Subtropical Jet Stream and Atlantic Tropical Cyclones

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The East Asian Subtropical Jet Stream and Atlantic Tropical Cyclones 1 The East Asian Subtropical Jet Stream and Atlantic Tropical 2 Cyclones 3 4 5 6 Wei Zhang1,*, Gabriele Villarini1, Gabriel A. Vecchi2,3 7 8 9 10 1IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, Iowa, USA 11 2Department of Geosciences, Princeton University, Princeton, NJ, USA 12 3Princeton Environmental Institute, Princeton University, Princeton, NJ, USA 13 Submitted to GRL 14 15 *Corresponding author: Wei Zhang, Ph.D., IIHR-Hydroscience & Engineering, The University 16 of Iowa, Iowa City, Iowa, USA. Email: [email protected] 17 18 19 20 21 22 1 23 Abstract 24 Atlantic tropical cyclones (TCs) can cause significant societal and economic impacts, as 2019’s 25 Dorian serves to remind us of these storms’ destructiveness. Decades of effort to understand and 26 predict Atlantic TC activity have improved seasonal forecast skill, but large uncertainties still 27 remain, in part due to an incomplete understanding of the drivers of TC variability. Here we 28 identify an association between the East Asian Subtropical Jet Stream (EASJ) during July-October 29 and the frequency of Atlantic TCs (wind speed ≥ 34 knot) and hurricanes (wind speed ≥ 64 knot) 30 during August-November based on observations for 1980-2018. This strong association is tied to 31 the impacts of EASJ on a stationary Rossby wave train emanating from East Asia and the tropical 32 Pacific to the North Atlantic, leading to changes in vertical wind shear in the Atlantic Main 33 Development Region (80°W-20°W, 10°N-20°N). 34 35 36 37 38 39 Plain Language Summary 40 Atlantic tropical cyclones (TCs) are responsible for significant societal and economic impacts in 41 terms of fatalities and property damage, as 2017's Harvey, Irma and Maria, 2018's Florence and 42 Matthew and 2019's Dorian serve to highlight. There are still large uncertainties in current seasonal 43 predictions for Atlantic TCs, which partly arise from our incomplete understanding of the drivers 44 of the variability and nature of such storms. Here we find an association between the East Asian 45 Subtropical Jet Stream (EASJ) during July-October and the frequency of Atlantic TCs during 46 August-November based on observations for 1980-2018, arising from the impacts of EASJ on the 47 propagation of Rossby wave trains from East Asia to the North Atlantic, leading to changes in 48 vertical wind shear over the Atlantic Main Development Region (MDR). 2 49 50 1. Introduction 51 Atlantic tropical cyclones (TCs) receive significant interest both from the scientific 52 community and the general public because of their large societal and economic impacts in terms 53 of fatalities and property damage [Czajkowski et al., 2011; 2017; Klotzbach et al., 2018; Pielke Jr 54 et al., 2008]. Understanding the association between climate drivers and Atlantic TCs represents 55 the fundamental basis for seasonal predictions of TC activity: improving this understanding is a 56 critical step towards prediction improvement [e.g., Elsner and Schmertmann, 1993; Emanuel, 57 2005; Gray, 1984; Gray et al., 1993; Keith and Xie, 2009; Klotzbach and Gray, 2009; Landsea et 58 al., 1998; Vecchi et al., 2010; 2014; Vecchi and Soden, 2007; Vecchi and Villarini, 2014; Villarini 59 et al., 2019]. 60 Numerous studies have explored the controls on variations of seasonal Atlantic TC 61 frequency, finding a strong linkage with African easterly waves [Gray et al., 1993], West Sahel 62 rainfall [Landsea and Gray, 1992], relative sea surface temperature (SST) [Vecchi and Soden, 63 2007], tropical mean SST [Latif et al., 2007], Atlantic Main Development Region (MDR; 80°W- 64 20°W, 10°N-20°N) SST [Saunders and Harris, 1997], Atlantic Meridional Mode [Kossin and 65 Vimont, 2007], and the El Niño Southern Oscillation (ENSO) [Goldenberg et al., 2001; Gray, 66 1984]. Much of the existing literature has focused on the association between these storms and 67 climate “modes” arising in the tropical oceans, which can impact atmospheric and oceanic 68 conditions in the North Atlantic, because of their potential as sources for seasonal prediction. For 69 example, ENSO and the Atlantic Meridional Mode have been shown to modulate Atlantic TCs. In 70 addition, local vertical wind shear [Aiyyer and Thorncroft, 2011; Latif et al., 2007] is a good 71 indicator for Atlantic TCs. Moreover, Caribbean 200-mb zonal winds and sea level pressures have 72 been used for forecasting hurricanes [Gray et al., 1994], though one must exercise caution in 3 73 interpreting causality from strong statistical agreement between seasonal lower-troposphere 74 atmospheric wind anomalies and hurricane activity [Swanson, 2008]. Nonetheless, little attention 75 has been paid to remote variations in extratropical atmospheric systems in the Pacific and Eurasia. 76 Jet streams meander around our planet’s atmosphere, affecting high-impact weather events 77 such as atmospheric rivers, heat waves, cold waves, flooding and extreme precipitation [Cohen et 78 al., 2014]. As a prominent component of the weather and climate system in the Asia–Pacific sector 79 [Thompson et al., 2003], the East Asian Subtropical Jet stream (EASJ) is associated with 80 precipitation and temperature in North America. For example, EASJ is tied to winter climate in 81 North America [Yang et al., 2002], atmospheric rivers making landfall over the western United 82 States [Zhang and Villarini, 2018], and the precipitation pattern of the continental United States 83 [Zhu and Li, 2016]. Moreover, stationary Rossby trains can be modulated by the EASJ, as Rossby 84 waves disperse energy along strong westerly jets [Hoskins and Ambrizzi, 1993] that tend to refract 85 the waves toward the core of the jet stream, and act as efficient waveguides [Branstator, 2002; 86 Held et al., 2002; Hoskins and Ambrizzi, 1993]. Mounting observational evidence has supported 87 the importance of the tropospheric jets as waveguides for teleconnections [Branstator, 2002; 88 Branstator and Teng, 2017; Chen, 2002; Hsu and Lin, 1992]. During boreal summer, because the 89 EASJ is shifted poleward, it cannot directly interact with the Rossby waves forced from the deep 90 tropics [Graf and Zanchettin, 2012; Zhu and Li, 2016]. However, the Rossby wave energy can be 91 trapped by the EASJ in East Asia, triggering the downstream development of a Rossby wave train 92 along the EASJ towards North America and the North Atlantic [Graf and Zanchettin, 2012; 93 Swanson et al., 1997; Zhu and Li, 2016]. Here we examine whether and the extent to which the 94 EASJ is associated with the frequency of Atlantic TCs and hurricanes. 4 95 The remainder of this manuscript is organized as follows. Section 2 presents data and 96 methodology. Section 3 discusses the results, followed by Section 4 that summarizes concluding 97 remarks. 98 99 2. Data and Methodology 100 We use four monthly reanalysis datasets to obtain information about the three-dimensional 101 structure of the atmosphere, including: the National Aeronautics and Space Administration 102 (NASA)’s Modern-Era Retrospective Analysis for Research and Applications, version 2 103 (MERRA-2) at 0.5° × 0.625° spatial resolution for 1980-present [Gelaro et al., 2017]; the 104 European Centre for Medium-Range Weather Forecasts (ECMWF)’s ERA-5 at 0.25° × 0.25° 105 spatial resolution (1979-present) [Hersbach et al., 2020]; the National Centers for Environmental 106 Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data at 2.5° 107 × 2.5° spatial resolution (1948-present); and the Japanese 55-year ReAnalysis (JRA-55, 1958- 108 present) at 1.25° × 1.25° spatial resolution [Kobayashi et al., 2015]. Our focus is on the period 109 1980-2018 which is the common period for the four reanalysis data sets. In terms of observed TC 110 information, we use the Atlantic hurricane database (HURDAT2) for observed basin-wide TCs 111 every six hours during the lifetime of the recorded TCs [Landsea and Franklin, 2013]. We only 112 consider TCs that reach the intensity level of tropical storm or above during August-November. 113 No lifetime constraint is considered for defining tropical storm and hurricane. 114 The Niño3.4 index was calculated based on the monthly SST data obtained from the Met 115 Office Hadley Center (HadISST1.1) at 1° × 1° resolution [Rayner et al., 2003]; it was computed 116 as the SST anomaly averaged over the domain (5°S-5°N, 120°E-170°W) using the base period 117 1981-2010. Vertical wind shear is defined as the magnitude of the differences in winds between 5 118 200 hPa and 850 hPa levels. We use the definition for the intensity of EASJ as the 200-hPa zonal 119 wind averaged within 30°-35°N and 130°E-180°E. The results based on EASJ defined in 130°- 120 170°E or 130°-160°E [Yang et al., 2002] are similar to but slightly weaker than those using 130°E- 121 180°E. 122 To quantify the development of Rossby waves, the Rossby wave source (RWS) is defined 123 as [Sardeshmukh and Hoskins, 1988]: 124 ��� = −(�∇ ∙ �� + �� ∙ ∇�) (1) 125 where � is the absolute vorticity and �� is the divergent (irrotational) wind component. The Rossby 126 wave source diagnostic has been widely used to analyze Rossby wave generation [Held et al., 127 2002; Renwick and Revell, 1999]. 128 The atmospheric general circulation model (AGCM) we use to gain a deeper insight into 129 the physical processes is constructed based on the dynamic core of the Geophysical Fluid 130 Dynamics Laboratory (GFDL) [Held and Suarez, 1994; Wang et al., 2003]. The AGCM is set up 131 with five sigma levels (an interval of 0.2, a top level at σ = 0, and a bottom level at σ = 1) and a 132 horizontal resolution of T42.
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