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Kubota, Masahisa; Iwasaka, Naoto; Kizu, Shoichi; Konda, Masanori; Kutsuwada, Kunio

doi:10.1023/a:1015845321836

Cited by 168 publications

(29 citation statements)

References 32 publications

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“…For instance, data collected by the Special Sensor Microwave Imager (SSM/I) on board the Defense Meteorological Satellite Program satellites have been used to retrieve near-surface air humidity and winds over the ocean, and have been the basis of various satellite-based LHF products. These products include the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF) data set [Chou et al, 1997;Chou et al, 2003], the Japanese Ocean Flux data sets with Use of Remote Sensing Observations (J-OFURO) [Kubota et al, 2002] and the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) [Grassl et al, 2000]. LHF estimates from Objectively Analyzed air-sea Fluxes (OAFlux) data set [Yu and Weller, 2007] are also made available by merging satellite and reanalysis data.…”

Section: Datamentioning

confidence: 99%

Trends and variations of ocean surface latent heat flux: Results from GSSTF2c data set

Chiu

Shie

2013

Geophysical Research Letters

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Trends and variations of Goddard Satellite‐based Surface Turbulent Fluxes (GSSTF) version 2c (GSSTF2c) latent heat flux (LHF) are examined. This version of LHF takes account of the correction in Earth incidence angle. The trend of global mean LHF for GSSTF2c is much reduced relative to GSSTF version 2b Set 1 and Set 2 for the same period 1988–2008. Temporal increase of GSSTF2c LHF in the two decades is 11.0%, in which 3.1%, 5.8%, and 2.1% are attributed to the increase in wind, the increase in sea surface saturated air humidity, and the decrease in near‐surface air humidity, respectively. The first empirical orthogonal function of LHF is a conventional El Niño Southern Oscillation (ENSO) mode. However, the trends in LHF are independent of conventional ENSO phenomena. After removing ENSO signal, the pattern of LHF trends is primarily determined by the pattern of air‐sea humidity difference trends.

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Section: Datamentioning

confidence: 99%

Trends and variations of ocean surface latent heat flux: Results from GSSTF2c data set

Chiu

Shie

2013

Geophysical Research Letters

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“…Comparisons of the NCEPR and ERA40 near-surface winds with satellite, buoy, research-vessel and land station winds showed that reanalysis near-surface winds were biased low, particularly in tropical latitudes and for high wind speeds (Swail and Cox, 2000;Smith et al, 2001;Kubota et al, 2002;Caires and Sterl, 2003;Goswami and Sengupta, 2003;Wu and Xie, 2003;Yuan, 2004;Jiang et al, 2005).…”

Section: Ncep-ncar and Ecmwf Reanalysis (Ncepr And Era40) Windsmentioning

confidence: 99%

Trends in ship wind speeds adjusted for observation method and height

Thomas

Kent

Swail

et al. 2007

Intl Journal of Climatology

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Globally averaged wind speeds from archived ship reports show an increasing trend since the 1940s, which previous studies attributed to the gradual shift from visually estimated to anemometer-measured winds, and an increase in mean anemometer height. To test this hypothesis, adjustments to account for these changes were applied to individual ship wind observations in the International Comprehensive Ocean-Atmosphere Data Set (ICOADS). Annual means calculated from adjusted reports were compared to reanalysis near-surface winds in consistently well-sampled regions for the period 1958-2002.The adjustments to individual ship wind reports for known biases improve the homogeneity over the entire period and remove trends, prior to the early 1980s. However, for the 21-year period 1982-2002, trends remain in the annual mean spatially averaged adjusted winds, of 0.4 ms −1 decade −1 (6% decade −1 ) for estimated speeds, and of 0.2 ms −1 decade −1 (3% decade −1 ) for measured speeds. In contrast, co-located reanalysis near-surface wind speeds show little change, 1% decade −1 or less. Anemometers were installed on increasing numbers of ships during the period of study, even as many of these ships continued to report estimated winds. Part of the trend in estimated wind speeds is probably spurious, most likely a result of observers being increasingly influenced by readings from anemometers located well above 10-m. This influence is indicated by the gradual reduction in the tendency to underestimate nighttime marine winds. Results confirm earlier findings that reanalysis near-surface winds were biased low. The paper summarizes methods that could be employed to account for remaining inhomogeneities and thereby improve the quality of the marine wind climate record.

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“…To determine Q net , we used daily mean datasets from Japanese Ocean Flux Datasets with Use of Remote Sensing Observations version 2 (J-OFURO2; Kubota et al 2002;Tomita et al 2010a) to extract gridded datasets of turbulent sensible and latent heat fluxes at the ocean surface.…”

Section: Methodsmentioning

confidence: 99%

Impact of downward heat penetration below the shallow seasonal thermocline on the sea surface temperature

et al. 2015

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model during the warming season. Seasonal changes in the HPD indicate that the thermal effects of Q net gradually penetrate below the shallow seasonal thermocline due to vertical eddy diffusivity. Downward heat penetration into the layer below the shallow seasonal thermocline occurs widely throughout the North Pacific, and two-thirds of Q net penetrates below the ML. In a hypothetical analysis of the case where the observed Q net accumulates only within the ML, the change in SST is unrealistically larger than that of the observed SST. These results indicate that heat penetration plays a crucial role in climate variations during the warming season.

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Untitled

Cited by 168 publications

References 32 publications

Trends and variations of ocean surface latent heat flux: Results from GSSTF2c data set

Trends and variations of ocean surface latent heat flux: Results from GSSTF2c data set

Trends in ship wind speeds adjusted for observation method and height

Impact of downward heat penetration below the shallow seasonal thermocline on the sea surface temperature

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