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, baroclinic waves and frontal systems provide strong lifting mechanisms and the Great Plains low-level jet (LLJ) provides anomalous moisture for favorable dynamical and thermodynamical environments for MCS development. In contrast, during summer, favorable environments featuring significantly weaker baroclinic lifting and thermodynamic instability suggest much lower predictability of MCSs compared to spring ( Song et al. 2019 ). Besides limitations in physics parameterizations, it is unclear if GCMs are
, baroclinic waves and frontal systems provide strong lifting mechanisms and the Great Plains low-level jet (LLJ) provides anomalous moisture for favorable dynamical and thermodynamical environments for MCS development. In contrast, during summer, favorable environments featuring significantly weaker baroclinic lifting and thermodynamic instability suggest much lower predictability of MCSs compared to spring ( Song et al. 2019 ). Besides limitations in physics parameterizations, it is unclear if GCMs are
subtropical jet are apparent in most of models shown. The subtropical jet in MRI-CGCM3, GFDL CM3, and MIROC5 extends too far east relative to reanalysis. Furthermore, a southward shift of the jet is apparent in MIROC5. NorESM1-M has the smallest mean zonal wind errors in the Pacific out of the models shown. Fig . 2. Mean 250-hPa zonal wind (contours) for (top left) reanalysis and the good MJO models during DJF. Contours are every 10 m s −1 beginning at 35 m s −1 . Color shading represents the deviation
subtropical jet are apparent in most of models shown. The subtropical jet in MRI-CGCM3, GFDL CM3, and MIROC5 extends too far east relative to reanalysis. Furthermore, a southward shift of the jet is apparent in MIROC5. NorESM1-M has the smallest mean zonal wind errors in the Pacific out of the models shown. Fig . 2. Mean 250-hPa zonal wind (contours) for (top left) reanalysis and the good MJO models during DJF. Contours are every 10 m s −1 beginning at 35 m s −1 . Color shading represents the deviation
/phenomena in the tropics (e.g., Neale et al. 2008 ; Lau and Waliser 2011 ; Jin et al. 2013 ; Zhang 2013 ; Kim et al. 2014b ) and the impact extends outside of the tropical region. Anomalous MJO-induced upper-level divergence can generate anomalous Rossby wave source (RWS) by producing divergent flow anomalies in the region of the strong absolute vorticity and its gradient associated with the midlatitude North Pacific westerly jet ( Sardeshmukh and Hoskins 1988 ). Rossby waves excited by the tropical
/phenomena in the tropics (e.g., Neale et al. 2008 ; Lau and Waliser 2011 ; Jin et al. 2013 ; Zhang 2013 ; Kim et al. 2014b ) and the impact extends outside of the tropical region. Anomalous MJO-induced upper-level divergence can generate anomalous Rossby wave source (RWS) by producing divergent flow anomalies in the region of the strong absolute vorticity and its gradient associated with the midlatitude North Pacific westerly jet ( Sardeshmukh and Hoskins 1988 ). Rossby waves excited by the tropical
models in recent years exhibit high skill in predicting ENSO from a month to 2 years in advance (e.g., Rosati et al. 1997 ; Jin et al. 2008 ; Luo et al. 2008 ; Kim et al. 2012 ). The NAO is the dominant mode of variability over the North Atlantic, characterized by a seesaw pattern in boreal winter sea level pressure between the Azores high and Icelandic low ( Hurrell et al. 2003 ). Both phases of the NAO are associated with the intensity and structure changes of the midlatitude jet over the North
models in recent years exhibit high skill in predicting ENSO from a month to 2 years in advance (e.g., Rosati et al. 1997 ; Jin et al. 2008 ; Luo et al. 2008 ; Kim et al. 2012 ). The NAO is the dominant mode of variability over the North Atlantic, characterized by a seesaw pattern in boreal winter sea level pressure between the Azores high and Icelandic low ( Hurrell et al. 2003 ). Both phases of the NAO are associated with the intensity and structure changes of the midlatitude jet over the North
, with the corresponding increase in height southward toward the Indian Ocean. A low-level westerly jet is seen in the area where the height gradient is strongest. There are also some differences with respect to ERA-Interim. AM4.0 exhibits stronger westerlies that extend farther eastward past the Philippines, and the geopotential height gradient is stronger. The difference in the westerly jet is further shown in Fig. 2 , along with moisture, precipitation, and its variability. Mean precipitation
, with the corresponding increase in height southward toward the Indian Ocean. A low-level westerly jet is seen in the area where the height gradient is strongest. There are also some differences with respect to ERA-Interim. AM4.0 exhibits stronger westerlies that extend farther eastward past the Philippines, and the geopotential height gradient is stronger. The difference in the westerly jet is further shown in Fig. 2 , along with moisture, precipitation, and its variability. Mean precipitation
have important implications for the subseasonal prediction of midlatitude weather extremes (e.g., Henderson et al. 2016 ; Mundhenk et al. 2018 ; Baggett et al. 2017 ). Henderson et al. (2017) developed diagnostics linking teleconnection biases to biases in the position and extent of the North Pacific jet. Figure 2 (from Henderson et al. 2017 ) contains two panels, each having MJO teleconnection performance during December–February on the y axis. In Fig. 2a , the x axis represents an MJO
have important implications for the subseasonal prediction of midlatitude weather extremes (e.g., Henderson et al. 2016 ; Mundhenk et al. 2018 ; Baggett et al. 2017 ). Henderson et al. (2017) developed diagnostics linking teleconnection biases to biases in the position and extent of the North Pacific jet. Figure 2 (from Henderson et al. 2017 ) contains two panels, each having MJO teleconnection performance during December–February on the y axis. In Fig. 2a , the x axis represents an MJO
.1175/1520-0469(1987)044<2418:OTROSS>2.0.CO;2 . 10.1175/1520-0469(1987)044<2418:OTROSS>2.0.CO;2 Liu , J.-W. , S.-P. Zhang , and S.-P. Xie , 2013 : Two types of surface wind response to the East China Sea Kuroshio Front . J. Climate , 26 , 8616 – 8627 , doi: 10.1175/JCLI-D-12-00092.1 . 10.1175/JCLI-D-12-00092.1 Liu , T. , and W. Tang , 1996 : Equivalent neutral wind. Jet Propulsion Laboratory Publ. 96-17, 22 pp. Masunaga , R. , H. Nakamura , T. Miyasaka , K. Nishii , and Y. Tanimoto , 2015
.1175/1520-0469(1987)044<2418:OTROSS>2.0.CO;2 . 10.1175/1520-0469(1987)044<2418:OTROSS>2.0.CO;2 Liu , J.-W. , S.-P. Zhang , and S.-P. Xie , 2013 : Two types of surface wind response to the East China Sea Kuroshio Front . J. Climate , 26 , 8616 – 8627 , doi: 10.1175/JCLI-D-12-00092.1 . 10.1175/JCLI-D-12-00092.1 Liu , T. , and W. Tang , 1996 : Equivalent neutral wind. Jet Propulsion Laboratory Publ. 96-17, 22 pp. Masunaga , R. , H. Nakamura , T. Miyasaka , K. Nishii , and Y. Tanimoto , 2015
. Sprenger , 2016 : On the relationship between extratropical cyclone precipitation and intensity . Geophys. Res. Lett. , 43 , 1752 – 1758 , https://doi.org/10.1002/2016GL068018 . 10.1002/2016GL068018 Pithan , F. , T. G. Shepherd , G. Zappa , and I. Sandu , 2016 : Climate model biases in jet streams, blocking and storm tracks resulting from missing orographic drag . Geophys. Res. Lett. , 43 , 7231 – 7240 , https://doi.org/10.1002/2016GL069551 . 10.1002/2016GL069551 Rudeva , I
. Sprenger , 2016 : On the relationship between extratropical cyclone precipitation and intensity . Geophys. Res. Lett. , 43 , 1752 – 1758 , https://doi.org/10.1002/2016GL068018 . 10.1002/2016GL068018 Pithan , F. , T. G. Shepherd , G. Zappa , and I. Sandu , 2016 : Climate model biases in jet streams, blocking and storm tracks resulting from missing orographic drag . Geophys. Res. Lett. , 43 , 7231 – 7240 , https://doi.org/10.1002/2016GL069551 . 10.1002/2016GL069551 Rudeva , I
. Jakob , and J. Catto , 2014 : The relationship between clouds and dynamics in Southern Hemisphere extratropical cyclones in the real world and a climate model . J. Geophys. Res. Atmos. , 119 , 6609 – 6628 , https://doi.org/10.1002/2013JD020699 . 10.1002/2013JD020699 Grise , K. M. , and B. Medeiros , 2016 : Understanding the varied influence of midlatitude jet position on clouds and cloud radiative effects in observations and global climate models . J. Climate , 29 , 9005 – 9025
. Jakob , and J. Catto , 2014 : The relationship between clouds and dynamics in Southern Hemisphere extratropical cyclones in the real world and a climate model . J. Geophys. Res. Atmos. , 119 , 6609 – 6628 , https://doi.org/10.1002/2013JD020699 . 10.1002/2013JD020699 Grise , K. M. , and B. Medeiros , 2016 : Understanding the varied influence of midlatitude jet position on clouds and cloud radiative effects in observations and global climate models . J. Climate , 29 , 9005 – 9025
most of the year, being negative only during March–May and positive during November–December. The map has negative values over the interior of the Arabian Sea, with positive values confined near coasts ( Fig. 5c ), a pattern that reflects the dominance of the southwest monsoon winds in the annual cycle. The bias is largest during the summer ( Fig. 5f ), because the low-level (Findlater) jet in the models is weaker than observed. (iv) Circulation The NAS circulation is complex, with a prominent
most of the year, being negative only during March–May and positive during November–December. The map has negative values over the interior of the Arabian Sea, with positive values confined near coasts ( Fig. 5c ), a pattern that reflects the dominance of the southwest monsoon winds in the annual cycle. The bias is largest during the summer ( Fig. 5f ), because the low-level (Findlater) jet in the models is weaker than observed. (iv) Circulation The NAS circulation is complex, with a prominent
