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Shu-Hsien Chou, Wenzhong Zhao, and Ming-Dah Chou

Abstract

The daily mean heat and momentum fluxes at the surface derived from the Special Sensor Microwave/Imager and Japan’s Geostationary Meteorological Satellite radiance measurements are used to study the temporal and spatial variability of the surface energy budgets and their relationship to the sea surface temperature during the Coupled Ocean–Atmosphere Response Experiment intensive observing period (IOP). For three time legs observed during the IOP, the retrieved surface fluxes compare reasonably well with those from the Improved Meteorological Instrument (IMET) buoy, RV Moana Wave, and RV Wecoma. The characteristics of surface heat and momentum fluxes are very different between the southern and northern warm pool. In the southern warm pool, the net surface heat flux is dominated by solar radiation, which is, in turn, modulated by the two Madden–Julian oscillations. The surface winds are generally weak, leading to a shallow ocean mixed layer. The solar radiation penetrating through the bottom of the mixed layer is significant, and the change in the sea surface temperature during the IOP does not follow the net surface heat flux. In the northern warm pool, the northeasterly trade wind is strong and undergoes strong seasonal variation. The variation of the net surface heat flux is dominated by evaporation. The two westerly wind bursts associated with the Madden–Julian oscillations seem to have little effect on the net surface heat flux. The ocean mixed layer is deep, and the solar radiation penetrating through the bottom of the mixed layer is small. As opposed to the southern warm pool, the trend of the sea surface temperature in the northern warm pool during the IOP is in agreement with the variation of the net heat flux at the surface.

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Anastasia Romanou, William B. Rossow, and Shu-Hsien Chou

Abstract

In the first part of the paper, a high space–time resolution (1° latitude/longitude and daily) dataset of the turbulent fluxes at the ocean surface is used to estimate and study the seasonal to annual near-global maps of the decorrelation scales of the latent and sensible heat fluxes. The decorrelation scales describe the temporal and spatial patterns that dominate the flux fields (within a bandpass window) and hence reveal the dominant variability in the air–sea interaction. Regional comparison to the decorrelation scales of the flux-related variables such as the wind stress, the humidity difference, and the SST identifies the main mechanism responsible for the variability in each flux field.

In the second part of the paper, the decorrelation scales are used to develop a method for filling missing values in the dataset that result from the incomplete satellite coverage. Weight coefficients in a linear regression function are determined from the spatial and temporal decorrelations and are functions of zonal and meridional distance and time. Therefore they account for all spatial and temporal patterns on scales greater than 1 day and 1° latitude/longitude and less than 1 yr and the ocean basin scale. The method is evaluated by simulating the missing-value distribution of the Goddard Satellite-Based Surface Turbulent Fluxes, version 2 (GSSTF2) dataset in the NCEP SST, the International Satellite Climatology Project (ISCCP)-FD (fluxes calculated using D1 series) surface radiation, and the Global Precipitation Climatology Project (GPCP) datasets and by comparing the filled datasets to the original ones. Main advantages of the method are that the decorrelation scales are unrestricted functions of space and time; only information internal to the flux field is used in the interpolation scheme, and the computation cost of the method is low enough to facilitate its use in similar large datasets.

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Shu-Hsien Chou, Eric Nelkin, Joe Ardizzone, and Robert M. Atlas

Abstract

The ocean surface latent heat flux (LHF) plays an essential role in global energy and water cycle variability. In this study, monthly LHF over global oceans during 1992–93 are compared among Goddard Satellite-Based Surface Turbulent Fluxes, version 2 (GSSTF2), Hamburg Ocean–Atmosphere Parameters and Fluxes from Satellite Data (HOAPS), NCEP–NCAR reanalysis (NCEP), and da Silva et al. (da Silva). To find the causes for discrepancies of LHF, monthly 10-m wind speed (U 10m), 10-m specific humidity (Q 10m), and sea–air humidity difference (Q SQ 10m) are also compared during the same period. The mean differences, standard deviations of differences, and temporal correlation of these monthly variables over global oceans during 1992–93 between GSSTF2 and each of the other three datasets are analyzed. The large-scale patterns of the 2-yr-mean fields for these variables are similar among these four datasets, but significant quantitative differences are found.

The temporal correlation is higher in the northern extratropics than in the south for all variables, with the contrast being especially large for da Silva as a result of more missing ship observations in the south. The da Silva dataset has extremely low temporal correlation and large differences with GSSTF2 for all variables in the southern extratropics, indicating that da Silva hardly produces a realistic variability in these variables. The NCEP has extremely low temporal correlation (0.27) and large spatial variations of differences with GSSTF2 for Q SQ 10m in the Tropics, which causes the low correlation for LHF. Over the Tropics, the HOAPS mean LHF is significantly smaller than GSSTF2 by ∼31% (37 W m−2), whereas the other two datasets are comparable to GSSTF2. This is because the HOAPS has systematically smaller LHF than GSSTF2 in space, while the other two datasets have very large spatial variations of large positive and negative LHF differences with GSSTF2 to cancel and to produce smaller regional-mean differences. Based on comparison with high-quality flux observations, we conclude that the GSSTF2 latent heat flux, surface air humidity, and winds are likely to be more realistic than the other three flux datasets examined, although those of GSSTF2 are still subject to regional biases.

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Shu-Hsien Chou, Ming-Dah Chou, Pui-King Chan, Po-Hsiung Lin, and Kung-Hwa Wang

Abstract

Seasonal to interannual variations of the net surface heating (F NET) and its relationship to sea surface temperature tendency (dT s/dt) in the tropical eastern Indian and western Pacific Oceans are studied for the period October 1997–September 2000. The surface heat fluxes are derived from the Special Sensor Microwave Imager and Japanese Geostationary Meteorological Satellite radiance measurements. It is found that the magnitude of solar heating is larger than that of evaporative cooling, but the spatial variation of the latter is significantly larger than the former. As a result, the spatial patterns of the seasonal and interannual variability of F NET are dominated by the variability of evaporative cooling. Seasonal variations of F NET and dT s/dt are significantly correlated, except for the equatorial western Pacific. The high correlation is augmented by the high negative correlation between solar heating and evaporative cooling.

The change of F NET between the 1997/98 El Niño and 1998/99 La Niña is significantly larger in the tropical eastern Indian Ocean than that in the tropical western Pacific. For the former region, reduced evaporative cooling arising from weakened winds during El Niño is generally associated with enhanced solar heating due to reduced cloudiness, leading to enhanced interannual variability of F NET. For the latter region, reduced evaporative cooling due to weakened winds is generally associated with reduced solar heating arising from increased cloudiness, and vice versa. Consequently, the interannual variability of F NET is reduced. The correlation between interannual variations of F NET and dT s/dt is weak in the tropical western Pacific and eastern Indian Oceans, indicating the importance of ocean dynamics in affecting the interannual SST variation.

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Shu-Hsien Chou, Eric Nelkin, Joe Ardizzone, Robert M. Atlas, and Chung-Lin Shie

Abstract

Information on the turbulent fluxes of momentum, latent heat, and sensible heat at the air–sea interface is essential in improving model simulations of climate variations and in climate studies. A 13.5-yr (July 1987–December 2000) dataset of daily surface turbulent fluxes over global oceans has been derived from the Special Sensor Microwave Imager (SSM/I) radiance measurements. This dataset, Goddard Satellite-based Surface Turbulent Fluxes, version 2 (GSSTF2), has a spatial resolution of 1° × 1° latitude–longitude and a temporal resolution of 1 day. Turbulent fluxes are derived from the SSM/I surface winds and surface air humidity, as well as the 2-m air and sea surface temperatures (SST) of the NCEP–NCAR reanalysis, using a bulk aerodynamic algorithm based on the surface layer similarity theory.

The GSSTF2 bulk flux model is validated by comparing hourly turbulent fluxes computed from ship data using the model with those observed fluxes of 10 field experiments over the tropical and midlatitude oceans during 1991–99. In addition, the GSSTF2 daily wind stress, latent heat flux, wind speed, surface air humidity, and SST compare reasonably well with those of the collocated measurements of the field experiments. The global distributions of 1988–2000 annual- and seasonal-mean turbulent fluxes show reasonable patterns related to the atmospheric general circulation and seasonal variations. Zonal averages of latent heat fluxes and input parameters over global oceans during 1992–93 have been compared among several flux datasets: GSSTF1 (version 1), GSSTF2, the Hamburg Ocean–Atmosphere Parameters and Fluxes from Satellite Data (HOAPS), NCEP–NCAR reanalysis, and one based on the Comprehensive Ocean–Atmosphere Data Set (COADS). Significant differences are found among the five. These analyses suggest that the GSSTF2 latent heat flux, surface air humidity, and winds are likely to be more realistic than the other four flux datasets examined, although those of GSSTF2 are still subject to regional biases. The GSSTF2 is useful for climate studies and has been submitted to the sea surface turbulent flux project (SEAFLUX) for intercomparison studies.

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