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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
– 112 , doi: 10.1007/BF00232256 . Kunoki , S. , and Coauthors , 2015 : Oceanic influence on the Baiu frontal zone in the East China Sea . J. Geophys. Res. Atmos. , 120 , 449 – 463 , doi: 10.1002/2014JD022234 . Kurihara , Y. , T. Sakurai , and T. Kuragano , 2006 : Global daily sea surface temperature analysis using data from satellite microwave radiometer, satellite infrared radiometer and in-situ observations (in Japanese) . Wea. Bull. , 73 , s1 – s18 . Kushnir , Y. , W. A
– 112 , doi: 10.1007/BF00232256 . Kunoki , S. , and Coauthors , 2015 : Oceanic influence on the Baiu frontal zone in the East China Sea . J. Geophys. Res. Atmos. , 120 , 449 – 463 , doi: 10.1002/2014JD022234 . Kurihara , Y. , T. Sakurai , and T. Kuragano , 2006 : Global daily sea surface temperature analysis using data from satellite microwave radiometer, satellite infrared radiometer and in-situ observations (in Japanese) . Wea. Bull. , 73 , s1 – s18 . Kushnir , Y. , W. A
from the smoothed background wind field u bg alone [i.e., for stress from (9) with u o = 0 everywhere] is O (1) cm day −1 . e. Estimation of SST-induced Ekman pumping The SST fields used in this study are the optimally interpolated SST analyses produced by the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center. Microwave and infrared satellite observations were combined with in situ measurements of SST to obtain daily, global fields on a ¼° × ¼° grid
from the smoothed background wind field u bg alone [i.e., for stress from (9) with u o = 0 everywhere] is O (1) cm day −1 . e. Estimation of SST-induced Ekman pumping The SST fields used in this study are the optimally interpolated SST analyses produced by the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center. Microwave and infrared satellite observations were combined with in situ measurements of SST to obtain daily, global fields on a ¼° × ¼° grid
daily zonal and meridional sea surface wind components of Quick Scatterometer (QuikSCAT) version 4 ( Ricciardulli et al. 2011 ) and 3-day running mean of Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) SST version 7 ( Wentz et al. 2014 ). Both are provided by Remote Sensing Systems (RSS) on a 0.25° × 0.25° latitude–longitude grid. For estimating transfer functions, rain-flagged observations are excluded. Data missing regions including the landmasses are filled with
daily zonal and meridional sea surface wind components of Quick Scatterometer (QuikSCAT) version 4 ( Ricciardulli et al. 2011 ) and 3-day running mean of Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) SST version 7 ( Wentz et al. 2014 ). Both are provided by Remote Sensing Systems (RSS) on a 0.25° × 0.25° latitude–longitude grid. For estimating transfer functions, rain-flagged observations are excluded. Data missing regions including the landmasses are filled with
). This map was constructed from 10 years of QuikSCAT wind observations spanning the time period November 1999–October 2009, as described in section 2a . Since both raining and rain-free conditions are included in this mean, it is referred to as the all-weather (AW) mean. The band of time-mean convergence—the GSCZ—overlies the approximate position of the Gulf Stream, from the Charleston Bump off the coast of South Carolina, separating from the shelf near Cape Hatteras, extending to the northeast
). This map was constructed from 10 years of QuikSCAT wind observations spanning the time period November 1999–October 2009, as described in section 2a . Since both raining and rain-free conditions are included in this mean, it is referred to as the all-weather (AW) mean. The band of time-mean convergence—the GSCZ—overlies the approximate position of the Gulf Stream, from the Charleston Bump off the coast of South Carolina, separating from the shelf near Cape Hatteras, extending to the northeast
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
