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The net energy budget at the ocean‐atmosphere interface of the “Cold Tongue” region
Author(s) -
Pinker Rachel T.,
Bentamy Abderrahim,
Zhang Banglin,
Chen Wen,
Ma Yingtao
Publication year - 2017
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1002/2016jc012581
Subject(s) - buoy , climatology , atmosphere (unit) , satellite , environmental science , sea surface temperature , energy budget , standard deviation , flux (metallurgy) , latent heat , atmospheric sciences , meteorology , geology , geography , oceanography , physics , mathematics , statistics , materials science , astronomy , metallurgy , thermodynamics
Pacific “Cold Tongue” (PCT) sea surface temperature (SST) experiences significant (>0.5°C) interannual variations forced by the El‐Nino Southern Oscillations (ENSO) with global impacts on the Earth climate. In this study, we estimate the PCT net heat budget known to be difficult to derive using numerical models. The main goal is to determine how accurately the net heat flux across the surface/atmosphere interface can currently be determined primarily, from satellite observations; these are first evaluated against the nearest available observations inside and outside the PCT of the Tropical Pacific Ocean, using buoy arrays such as the Tropical Atmosphere Ocean/Triangle Trans‐Ocean Buoy Network (TAO/TRITON). It was found that the satellite‐based estimates of both turbulent and radiative fluxes are in better agreement with the observations than similar estimates from leading numerical models. The monthly mean satellite estimates of PCT SW↓ during January/July 2009 were 273.07/170.14, for LW↓, latent heat and sensible heat they were 378.79/365.54, 95.52/130.31, 9.89/20.67, respectively (all in W/m 2 ). The estimated standard deviations for PCT SW↓ were in the range of 7.2–7.8% of the mean and in the range of 2.0–2.5% for LW↓, at daily time scale. Satellite estimates of both PCT LHF and SHF exhibit much higher variability, characterized by standard deviations of 50% from the mean values.