Description: Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 43 (2013): 1589–1610, doi:10.1175/JPO-D-12-0173.1.

Description: This study investigates the exchange of momentum between the atmosphere and ocean using data collected from four oceanic field experiments. Direct covariance estimates of momentum fluxes were collected in all four experiments and wind profiles were collected during three of them. The objective of the investigation is to improve parameterizations of the surface roughness and drag coefficient used to estimate the surface stress from bulk formulas. Specifically, the Coupled Ocean–Atmosphere Response Experiment (COARE) 3.0 bulk flux algorithm is refined to create COARE 3.5. Oversea measurements of dimensionless shear are used to investigate the stability function under stable and convective conditions. The behavior of surface roughness is then investigated over a wider range of wind speeds (up to 25 m s−1) and wave conditions than have been available from previous oversea field studies. The wind speed dependence of the Charnock coefficient α in the COARE algorithm is modified to , where m = 0.017 m−1 s and b = −0.005. When combined with a parameterization for smooth flow, this formulation gives better agreement with the stress estimates from all of the field programs at all winds speeds with significant improvement for wind speeds over 13 m s−1. Wave age– and wave slope–dependent parameterizations of the surface roughness are also investigated, but the COARE 3.5 wind speed–dependent formulation matches the observations well without any wave information. The available data provide a simple reason for why wind speed–, wave age–, and wave slope–dependent formulations give similar results—the inverse wave age varies nearly linearly with wind speed in long-fetch conditions for wind speeds up to 25 m s−1.

Description: This work was funded by the National Science Foundation Grant OCE04-24536 as part of the CLIVAR Mode Water Dynamics Experiment (CLIMODE) and the Office of Naval Research Grant N00014-05-1-0139 as part of the CBLAST-LOW program.

Description: 2014-02-01

Description: Author Posting. © American Meteorological Society 2006. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 19 (2006): 6153–6169, doi:10.1175/JCLI3970.1.

Description: The present study used a new net surface heat flux (Qnet) product obtained from the Objective Analyzed Air–Sea Fluxes (OAFlux) project and the International Satellite Cloud Climatology Project (ISCCP) to examine two specific issues—one is to which degree Qnet controls seasonal variations of sea surface temperature (SST) in the tropical Atlantic Ocean (20°S–20°N, east of 60°W), and the other is whether the physical relation can serve as a measure to evaluate the physical representation of a heat flux product. To better address the two issues, the study included the analysis of three additional heat flux products: the Southampton Oceanographic Centre (SOC) heat flux analysis based on ship reports, and the model fluxes from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). The study also uses the monthly subsurface temperature fields from the World Ocean Atlas to help analyze the seasonal changes of the mixed layer depth (hMLD). The study showed that the tropical Atlantic sector could be divided into two regimes based on the influence level of Qnet. SST variability poleward of 5°S and 10°N is dominated by the annual cycle of Qnet. In these regions the warming (cooling) of the sea surface is highly correlated with the increased (decreased) Qnet confined in a relatively shallow (deep) hMLD. The seasonal evolution of SST variability is well predicted by simply relating the local Qnet with a variable hMLD. On the other hand, the influence of Qnet diminishes in the deep Tropics within 5°S and 10°N and ocean dynamic processes play a dominant role. The dynamics-induced changes in SST are most evident along the two belts, one of which is located on the equator and the other off the equator at about 3°N in the west, which tilts to about 10°N near the northwestern African coast. The study also showed that if the degree of consistency between the correlation relationships of Qnet, hMLD, and SST variability serves as a measure of the quality of the Qnet product, then the Qnet from OAFlux + ISCCP and ERA-40 are most physically representative, followed by SOC. The NCEP–NCAR Qnet is least representative. It should be noted that the Qnet from OAFlux + ISCCP and ERA-40 have a quite different annual mean pattern. OAFlux + ISCCP agrees with SOC in that the tropical Atlantic sector gains heat from the atmosphere on the annual mean basis, where the ERA-40 and the NCEP–NCAR model reanalyses indicate that positive Qnet occurs only in the narrow equatorial band and in the eastern portion of the tropical basin. Nevertheless, seasonal variances of the Qnet from OAFlux + ISCCP and ERA-40 are very similar once the respective mean is removed, which explains why the two agree with each other in accounting for the seasonal variability of SST. In summary, the study suggests that an accurate estimation of surface heat flux is crucially important for understanding and predicting SST fluctuations in the tropical Atlantic Ocean. It also suggests that future emphasis on improving the surface heat flux estimation should be placed more on reducing the mean bias.

Description: This study is support by the NOAA CLIVAR Atlantic under Grant NA06GP0453 and NOAA Climate observations and Climate Change and Data Detection under Grant NA17RJ1223.

Description: Author Posting. © American Meteorological Society, 2007. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 20 (2007): 3190-3209, doi:10.1175/JCLI4163.1.

Description: This study investigated the accuracy and physical representation of air–sea surface heat flux estimates for the Indian Ocean on annual, seasonal, and interannual time scales. Six heat flux products were analyzed, including the newly developed latent and sensible heat fluxes from the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project and net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP), the heat flux analysis from the Southampton Oceanography Centre (SOC), the National Centers for Environmental Prediction reanalysis 1 (NCEP1) and reanalysis-2 (NCEP2) datasets, and the European Centre for Medium-Range Weather Forecasts operational (ECMWF-OP) and 40-yr Re-Analysis (ERA-40) products. This paper presents the analysis of the six products in depicting the mean, the seasonal cycle, and the interannual variability of the net heat flux into the ocean. Two time series of in situ flux measurements, one taken from a 1-yr Arabian Sea Experiment field program and the other from a 1-month Joint Air–Sea Monsoon Interaction Experiment (JASMINE) field program in the Bay of Bengal were used to evaluate the statistical properties of the flux products over the measurement periods. The consistency between the six products on seasonal and interannual time scales was investigated using a standard deviation analysis and a physically based correlation analysis. The study has three findings. First of all, large differences exist in the mean value of the six heat flux products. Part of the differences may be attributable to the bias in the numerical weather prediction (NWP) models that underestimates the net heat flux into the Indian Ocean. Along the JASMINE ship tracks, the four NWP modeled mean fluxes all have a sign opposite to the observations, with NCEP1 being underestimated by 53 W m−2 (the least biased) and ECMWF-OP by 108 W m−2 (the most biased). At the Arabian Sea buoy site, the NWP mean fluxes also have an underestimation bias, with the smallest bias of 26 W m−2 (ERA-40) and the largest bias of 69 W m−2 (NCEP1). On the other hand, the OAFlux+ISCCP has the best comparison at both measurement sites. Second, the bias effect changes with the time scale. Despite the fact that the mean is biased significantly, there is no major bias in the seasonal cycle of all the products except for ECMWF-OP. The latter does not have a fixed mean due to the frequent updates of the model platform. Finally, among the four products (OAFlux+ISCCP, ERA-40, NCEP1, and NCEP2) that can be used for studying interannual variability, OAFlux+ISCCP and ERA-40 Qnet have good consistency as judged from both statistical and physical measures. NCEP1 shows broad agreement with the two products, with varying details. By comparison, NCEP2 is the least representative of the Qnet variabilities over the basin scale.

Description: This work is supported by the NOAA Office of Climate Observation and the Office of Climate Change and Data Detection under Grant NA17RJ1223.

Description: Author Posting. © American Meteorological Society, 2009. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 22 (2009): 5527–5540, doi:10.1175/2009JCLI2961.1.

Description: A 5-yr climatology of the meteorology, including boundary layer cloudiness, for the southeast Pacific region is presented using observations from a buoy located at 20°S, 85°W. The sea surface temperature and surface air temperature exhibit a sinusoidal seasonal cycle that is negatively correlated with surface pressure. The relative humidity, wind speed, and wind direction show little seasonal variability. But the advection of cold and dry air from the southeast varies seasonally and is highly correlated with the latent heat flux variations. A simple model was used to estimate the monthly cloud fraction using the observed surface downwelling longwave radiative flux and surface meteorological parameters. The annual cycle of cloud fraction is highly correlated to that of S. A. Klein: lower-tropospheric stability parameter (0.87), latent heat flux (−0.59), and temperature and moisture advection (0.60). The derived cloud fraction compares poorly with the International Satellite Cloud Climatology Project (ISCCP)-derived low-cloud cover but compares well (0.86 correlation) with ISCCP low- plus middle-cloud cover. The monthly averaged diurnal variations in cloud fraction show marked seasonal variability in the amplitude and temporal structure. The mean annual cloud fraction is lower than the mean annual nighttime cloud fraction by about 9%. Annual and diurnal cycles of surface longwave and shortwave cloud radiative forcing were also estimated. The longwave cloud radiative forcing is about 45 W m−2 year-round, but, because of highly negative shortwave cloud radiative forcing, the net cloud radiative forcing is always negative with an annual mean of −50 W m−2.

Description: This research was supported by the Climate Prediction Program for the Americas (CPPA) of NOAA’s Climate Program Office. The Stratus Ocean Reference Station at 20°S, 85°W is supported by NOAA’s Climate Observation Program.

Description: Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Atmospheric and Oceanic Technology 39 (2013): 450–469, doi:10.1175/JTECH-D-12-00078.1.

Description: A surface mooring was deployed in the Gulf Stream for 15 months to investigate the role of air–sea interaction in mode water formation and other processes. The accuracies of the near-surface meteorological and oceanographic measurements are investigated. In addition, the impacts of these measurement errors on the estimation and study of the air–sea fluxes in the Gulf Stream are discussed. Pre- and postdeployment calibrations together with in situ comparison between shipboard and moored sensors supported the identification of biases due to sensor drifts, sensor electronics, and calibration errors. A postdeployment field study was used to further investigate the performance of the wind sensors. The use of redundant sensor sets not only supported the filling of data gaps but also allowed an examination of the contribution of random errors. Air–sea fluxes were also analyzed and computed from both Coupled Ocean–Atmosphere Response Experiment (COARE) bulk parameterization and using direct covariance measurements. The basic conclusion is that the surface buoy deployed in the Gulf Stream to support air–sea interaction research was successful, providing an improved 15-month record of surface meteorology, upper-ocean variability, and air–sea fluxes with known accuracies. At the same time, the coincident deployment of mean meteorological and turbulent flux sensors proved to be a successful strategy to certify the validity of the bulk formula fluxes over the midrange of wind speeds and to support further work to address the present shortcomings of the bulk formula methods at the low and high wind speeds.

Description: The National Science Foundation (Grant OCE04-24536) funded this work, as part of the CLIVAR Mode Water Dynamics Experiment (CLIMODE). The Vetlesen Foundation is also acknowledged for the early support of S. Bigorre.

Description: 2013-09-01

Description: Author Posting. © American Meteorological Society, 2014. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 44 (2014): 2569–2587, doi:10.1175/JPO-D-14-0026.1.

Description: This paper describes the occurrence of diurnal restratification events found in the southeast trade wind regime off northern Chile. This is a region where persistent marine stratus clouds are found and where there is a less than complete understanding of the dynamics that govern the maintenance of the sea surface temperature. A surface mooring deployed in the region provides surface meteorological, air–sea flux, and upper-ocean temperature, salinity, and velocity data. In the presence of steady southeast trade winds and strong evaporation, a warm, salty surface mixed layer is found in the upper ocean. During the year, these trade winds, at times, drop dramatically and surface heating leads to the formation of shallow, warm diurnal mixed layers over one to several days. At the end of such a low wind period, mean sea surface temperature is warmer. Though magnitudes of the individual diurnal warming events are consistent with local forcing, as judged by running a one-dimensional model, the net warming at the end of a low wind event is more difficult to predict. This is found to stem from differences between the observed and predicted near-inertial shear and the depths over which the warmed water is distributed. As a result, the evolution of SST has a dependency on these diurnal restratification events and on near-surface processes that govern the depth over which the heat gained during such events is distributed.

Description: RAW was supported by the NOAA Climate Program Office. SM and AT were supported by NASA Grant NNX12AD47G,ONR Grant N000140910196, and NSF-OCE 0928138 RAW.

Description: 2015-03-01

Description: Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 117 (2012): C03017, doi:10.1029/2011JC007267.

Description: Frequency spectra from deep-ocean near-bottom acoustic measurements obtained contemporaneously with wind, wave, and seismic data are described and used to determine the correlations among these data and to discuss possible causal relationships. Microseism energy appears to originate in four distinct regions relative to the hydrophone: wind waves above the sensors contribute microseism energy observed on the ocean floor; a fraction of this local wave energy propagates as seismic waves laterally, and provides a spatially integrated contribution to microseisms observed both in the ocean and on land; waves in storms generate microseism energy in deep water that travels as seismic waves to the sensor; and waves reflected from shorelines provide opposing waves that add to the microseism energy. Correlations of local wind speed with acoustic and seismic spectral time series suggest that the local Longuet-Higgins mechanism is visible in the acoustic spectrum from about 0.4 Hz to 80 Hz. Wind speed and acoustic levels at the hydrophone are poorly correlated below 0.4 Hz, implying that the microseism energy below 0.4 Hz is not typically generated by local winds. Correlation of ocean floor acoustic energy with seismic spectra from Oahu and with wave spectra near Oahu imply that wave reflections from Hawaiian coasts, wave interactions in the deep ocean near Hawaii, and storms far from Hawaii contribute energy to the seismic and acoustic spectra below 0.4 Hz. Wavefield directionality strongly influences the acoustic spectrum at frequencies below about 2 Hz, above which the acoustic levels imply near-isotropic surface wave directionality.

Description: Funding for the ALOHA Cabled Observatory was provided by the National Science Foundation and the State of Hawaii through the School of Ocean and Earth Sciences and Technology at the University of Hawaii-Manoa (F. Duennebier, PI). Donations from AT&T and TYCOM and the cooperation of the U.S. Navy made this project possible. The WHOI-Hawaii Ocean Time series Station (WHOTS) mooring is maintained by Woods Hole Oceanographic Institution (PIs R. Weller and A. Plueddemann) with funding from the NOAA Climate Program Office/Climate Observation Division. NSF grant OCE- 0926766 supported R. Lukas (co-PI) to augment and collaborate on the maintenance of WHOTS. Lukas was also supported during this analysis by The National Ocean Partnership Program “Advanced Coupled Atmosphere-Wave-Ocean Modeling for Improving Tropical Cyclone Prediction Models” under contract N00014-10-1-0154 to the University of Rhode Island (I. Ginis, PI).

Description: 2012-09-10