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. Climatol. , 47 , 3170 – 3187 , doi: 10.1175/2008JAMC1893.1 . Liu , W. T. , and W. Tang , 1996 : Equivalent neutral wind. Jet Propulsion Laboratory Publ. 96-17, 16 pp. [Available online at http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19970010322.pdf .] Mapes , B. , R. Milliff , and J. Morzel , 2009 : Composite life cycle of maritime tropical mesoscale convective systems in scatterometer and microwave satellite observations . J. Atmos. Sci. , 66 , 199 – 208 , doi: 10
. Climatol. , 47 , 3170 – 3187 , doi: 10.1175/2008JAMC1893.1 . Liu , W. T. , and W. Tang , 1996 : Equivalent neutral wind. Jet Propulsion Laboratory Publ. 96-17, 16 pp. [Available online at http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19970010322.pdf .] Mapes , B. , R. Milliff , and J. Morzel , 2009 : Composite life cycle of maritime tropical mesoscale convective systems in scatterometer and microwave satellite observations . J. Atmos. Sci. , 66 , 199 – 208 , doi: 10
, 2008 : Comparison of upper tropospheric water vapor observations from the Microwave Limb Sounder and Atmospheric Infrared Sounder . J. Geophys. Res. , 113 , D22110 , doi: 10.1029/2008JD010000 . Frankignoul , C. , N. Sennechael , Y.-O. Kwon , and M. A. Alexander , 2011 : Influence of the meridional shifts of the Kuroshio and the Oyashio Extensions on the atmospheric circulation . J. Climate , 24 , 762 – 777 , doi: 10.1175/2010JCLI3731.1 . Hashizume , H. , S. P. Xie , M
, 2008 : Comparison of upper tropospheric water vapor observations from the Microwave Limb Sounder and Atmospheric Infrared Sounder . J. Geophys. Res. , 113 , D22110 , doi: 10.1029/2008JD010000 . Frankignoul , C. , N. Sennechael , Y.-O. Kwon , and M. A. Alexander , 2011 : Influence of the meridional shifts of the Kuroshio and the Oyashio Extensions on the atmospheric circulation . J. Climate , 24 , 762 – 777 , doi: 10.1175/2010JCLI3731.1 . Hashizume , H. , S. P. Xie , M
circulation model (AGCM) suggest that these two mechanisms can be operative comparably over the KE in January (cf. Shimada and Minobe 2011 ). Samelson et al. (2006) argued that the positive correlations between SST and surface wind stress away from the immediate vicinity of oceanic fronts may be attributable to the deeper MABL over the warmer SST. Recent high-resolution satellite observations and numerical experiments have suggested mesoscale influences of SST on clouds and precipitation systems
circulation model (AGCM) suggest that these two mechanisms can be operative comparably over the KE in January (cf. Shimada and Minobe 2011 ). Samelson et al. (2006) argued that the positive correlations between SST and surface wind stress away from the immediate vicinity of oceanic fronts may be attributable to the deeper MABL over the warmer SST. Recent high-resolution satellite observations and numerical experiments have suggested mesoscale influences of SST on clouds and precipitation systems
1. Introduction Recent high-resolution satellite observations have significantly advanced the understanding of how the ocean and atmosphere interact on monthly or longer time scales. These observations have revealed that the divergence and curl 1 of near-surface horizontal wind exhibit remarkable structures over large-scale sea surface temperature (SST) fronts, where the SST significantly changes within several tens or hundreds of kilometers [see Xie (2004) , Chelton et al. (2004) , Small
1. Introduction Recent high-resolution satellite observations have significantly advanced the understanding of how the ocean and atmosphere interact on monthly or longer time scales. These observations have revealed that the divergence and curl 1 of near-surface horizontal wind exhibit remarkable structures over large-scale sea surface temperature (SST) fronts, where the SST significantly changes within several tens or hundreds of kilometers [see Xie (2004) , Chelton et al. (2004) , Small
correlation? Do the scales of variability in the model match observations? The paper is organized as follows: Section 2 describes the model and observed product data, and the methods of analysis, including latent heat flux (LHF) decomposition and feedback parameter. LHF is focused on because of its dominance of the net heat flux term response to SST (see section 2 below). Section 3 describes the variability and covariability of SST and LHF in models and data, and then section 4 presents two
correlation? Do the scales of variability in the model match observations? The paper is organized as follows: Section 2 describes the model and observed product data, and the methods of analysis, including latent heat flux (LHF) decomposition and feedback parameter. LHF is focused on because of its dominance of the net heat flux term response to SST (see section 2 below). Section 3 describes the variability and covariability of SST and LHF in models and data, and then section 4 presents two
boundary current regimes takes place at frontal scale and mesoscale where until recently available observations and numerical modeling tools have been inadequate to resolve these small-scale dynamical processes. As a result, detailed mechanisms governing air–sea interaction along western boundary current regimes are still lacking. Many recent studies on extratropical active air–sea feedback draw attention to the influence of the strong SST gradient in western boundary regimes on lower
boundary current regimes takes place at frontal scale and mesoscale where until recently available observations and numerical modeling tools have been inadequate to resolve these small-scale dynamical processes. As a result, detailed mechanisms governing air–sea interaction along western boundary current regimes are still lacking. Many recent studies on extratropical active air–sea feedback draw attention to the influence of the strong SST gradient in western boundary regimes on lower
. More recently, O’Reilly and Czaja (2015) produced a more accurate KE index derived from a maximum covariance analysis between SST and SSH gradient observations, but SST observations with high spatial resolution were only available since June 2002, so that a longer KE index (1992–2011) was obtained by projecting the 2002–11 SSH spatial pattern onto the full SSH record. It is thus of interest to use data with higher temporal resolution that describe the KE variability over a longer duration, so
. More recently, O’Reilly and Czaja (2015) produced a more accurate KE index derived from a maximum covariance analysis between SST and SSH gradient observations, but SST observations with high spatial resolution were only available since June 2002, so that a longer KE index (1992–2011) was obtained by projecting the 2002–11 SSH spatial pattern onto the full SSH record. It is thus of interest to use data with higher temporal resolution that describe the KE variability over a longer duration, so
observations shows a distinct SLP trough along the KE ( Tanimoto et al. 2011 ). Enhanced surface wind convergence due to the vertical mixing effect and/or hydrostatic effect can locally strengthen upward motion, which can reach the midtroposphere in many occasions, enhancing cloud formation and precipitation ( Minobe et al. 2008 , 2010 ; Tokinaga et al. 2009 ; Frenger et al. 2013 ; Masunaga et al. 2015 ). Westward-propagating wind-forced oceanic Rossby waves are shown to play an important role in
observations shows a distinct SLP trough along the KE ( Tanimoto et al. 2011 ). Enhanced surface wind convergence due to the vertical mixing effect and/or hydrostatic effect can locally strengthen upward motion, which can reach the midtroposphere in many occasions, enhancing cloud formation and precipitation ( Minobe et al. 2008 , 2010 ; Tokinaga et al. 2009 ; Frenger et al. 2013 ; Masunaga et al. 2015 ). Westward-propagating wind-forced oceanic Rossby waves are shown to play an important role in
