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Peter Gaube, Dudley B. Chelton, Roger M. Samelson, Michael G. Schlax, and Larry W. O’Neill

is based on the bulk flux formulation from the Coupled Ocean–Atmosphere Response Experiment, version 3.0 (COARE 3.0; Fairall et al. 2003 ). Surface stresses computed by the COARE 3.0 algorithm are about 15% larger than those computed by the Large et al. (1994) algorithm (see Fig. B2 of Risien and Chelton 2008 ), but the conclusions of this study are not significantly dependent on the choice of C D . The surface stress τ , stress components τ x and τ y , and vector winds were calculated

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Yi-Hui Wang and W. Timothy Liu

Abstract

This study investigates the regional atmospheric response to the Kuroshio Extension (KE) using a combination of multiple satellite observations and reanalysis data from boreal winter over a period of at least a decade. The goal is to understand the relationship between KE variations and atmospheric responses at low frequencies. A climate index is used to measure the interannual to decadal KE variability, which leaves remarkable imprints on the mesoscale sea surface temperature (SST). Clear spatial coherence between the SST signals and frontal-scale atmospheric variables, including surface wind convergence, vertical velocity, precipitation, and clouds, is identified by linear regression analysis. Consistent with previous studies, the penetrating effect of the KE variability on the free atmosphere is found. The westward tilt of the atmospheric response above the KE near 500 hPa is revealed. The difference in the associations of frontal-scale air temperature and geopotential height with the KE variability between the satellite observations and the reanalysis data suggests an imperfect interpretation of frontal-scale oceanic forcing on the overlying atmosphere in the reanalysis assimilation system.

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Shusaku Sugimoto

Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) bulk flux algorithm 3.0 ( Fairall et al. 2003 ), based on the so-called aerodynamic bulk formulas as follows: where Q E and Q H are the latent and sensible heat fluxes, respectively; ρ a is the air density; L is the latent heat of vaporization of water; c p is the specific heat of air at constant pressure; U a is WND; q s is the saturated specific humidity; q a is Qa; T a is SAT; T s is SST; and C E and

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Larry W. O’Neill, Tracy Haack, and Theodore Durland

.DAAC ( SeaPAC 2014 ). JPL has recently reprocessed most of the QuikSCAT data record with several algorithm updates. The improvements compared to previous versions include the following: a correction to rain-contaminated winds using an autonomous neural network–based technique ( Stiles and Dunbar 2010 ), which significantly improves the accuracy of vector wind retrievals in rain; a procedure to minimize cross-track biases of retrieved wind speeds; adjustments to the DIR threshold, which reduces grid

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Atsuhiko Isobe, Shin’ichiro Kako, and Shinsuke Iwasaki

cyclones off the East Asian coast . Mon. Wea. Rev. , 120 , 3029 – 3035 , doi: 10.1175/1520-0493(1992)120<3029:COECOT>2.0.CO;2 . Chin , T. M. , J. Vazquez , E. M. Armstrong , and A. J. Mariano , 2010 : Algorithm theoretical basis document: Multi-scale, motion-compensated analysis of sea surface temperature, version 1.1. NASA Measures Algorithm Theoretical Basis Doc., 17 pp. [Available online at ftp://mariana.jpl.nasa.gov/mur_sst/tmchin/docs/ATBD/atbd_1.1actual.pdf .] Dudhia , J. , D

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R. Justin Small, Frank O. Bryan, Stuart P. Bishop, Sarah Larson, and Robert A. Tomas

monthly mean output. The dataset is derived solely from satellite data except for 2 m air temperature taken from NCEP–DOE reanalysis ( Kanamitsu et al. 2002 ). Daily averaged SST is an ensemble median of multiple satellite data sources and of Reynolds et al. (2007) SST. The fluxes are computed using the COARE 3.0 bulk flux algorithm ( Fairall et al. 2003 ). We use the latter years 2002–13 when more satellite data were available. Full details of the dataset are given in Tomita et al. (2019) . The J

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Ryusuke Masunaga, Hisashi Nakamura, Takafumi Miyasaka, Kazuaki Nishii, and Bo Qiu

Aqua . The product is available on a 1.0° × 1.0° grid for the period from July 2002 to August 2012. Objectively analyzed air–sea fluxes (OAFlux) are used for monthly mean fluxes of sensible and latent heat at the sea surface ( Yu et al. 2008 ), available on a 1.0° × 1.0° grid since January 1958. The data are constructed through the COARE 3.0 flux algorithm ( Fairall et al. 2003 ) from data measured by several satellites, including OISST and wind products derived from AMSR-E and QuikSCAT and

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R. Justin Small, Frank O. Bryan, Stuart P. Bishop, and Robert A. Tomas

temperature taken from the NCEP–DOE reanalysis ( Kanamitsu et al. 2002 ). Daily averaged SST is an ensemble median of multiple satellite data sources and of Reynolds et al. 2007 OISST. The fluxes are computed using the COARE 3.0 bulk flux algorithm ( Fairall et al. 2003 ). We use the latter years 2002–13 when more satellite data was available. Full details of the dataset are given in Tomita et al. (2019) . The Objectively Analyzed Air–Sea Fluxes (OAFlux) product ( Yu and Weller 2007 ) uses variational

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Kazutoshi Sato, Atsuyoshi Manda, Qoosaku Moteki, Kensuke K. Komatsu, Koto Ogata, Hatsumi Nishikawa, Miki Oshika, Yuriko Otomi, Shiori Kunoki, Hisao Kanehara, Takashi Aoshima, Kenichi Shimizu, Jun Uchida, Masako Shimoda, Mitsuharu Yagi, Shoshiro Minobe, and Yoshihiro Tachibana

analyses. Precipitation intensity in the mesoscale analysis was underestimated relative to the radar observation ( Figs. 5 , 10 , and 11 ). The TRMM data also underestimated this intensity ( Figs. 5 , 6 , and 11 ). These findings indicate the need for further validation and improvement of the numerical model used in the mesoscale analysis and retrieval algorithm for the TRMM dataset, although this was beyond the scope of the present study. In addition, latent heat flux was underestimated in the

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Ayumu Miyamoto, Hisashi Nakamura, and Takafumi Miyasaka

– 3401 , https://doi.org/10.1175/2010JCLI3910.1 . 10.1175/2010JCLI3910.1 Hubanks , P. , S. Platnick , M. King , and B. Ridgway , 2016 : MODIS Atmosphere L3 Gridded Product Algorithm Theoretical Basis Document (ATBD) and Users Guide. NASA GSFC, MODIS Tech. Doc. ATBD-MOD-30, 122 pp., https://modis-images.gsfc.nasa.gov/_docs/L3_ATBD_C6.pdf . Hwang , Y.-T. , and D. M. W. Frierson , 2013 : Link between the double-Intertropical Convergence Zone problem and cloud biases over the Southern

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