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Il-Ju Moon, Tetsu Hara, Isaac Ginis, Stephen E. Belcher, and Hendrik L. Tolman

Abstract

The effect of surface waves on air–sea momentum exchange over mature and growing seas is investigated by combining ocean wave models and a wave boundary layer model. The combined model estimates the wind stress by explicitly calculating the wave-induced stress. In the frequency range near the spectral peak, the NOAA/ NCEP surface wave model WAVEWATCH-III is used to estimate the spectra, while the spectra in the equilibrium range are determined by an analytical model. This approach allows for the estimation of the drag coefficient and the equivalent surface roughness for any surface wave fields. Numerical experiments are performed for constant winds from 10 to 45 m s−1 to investigate the effect of mature and growing seas on air–sea momentum exchange. For mature seas, the Charnock coefficient is estimated to be about 0.01 ∼ 0.02 and the drag coefficient increases as wind speed increases, both of which are within the range of previous observational data. With growing seas, results for winds less than 30 m s−1 show that the drag coefficient is larger for younger seas, which is consistent with earlier studies. For winds higher than 30 m s−1, however, results show a different trend; that is, very young waves yield less drag. This is because the wave-induced stress due to very young waves makes a small contribution to the total wind stress in very high wind conditions.

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Brodie C. Pearson, Alan L. M. Grant, Jeff A. Polton, and Stephen E. Belcher

Abstract

This study uses large-eddy simulation to investigate the structure of the ocean surface boundary layer (OSBL) in the presence of Langmuir turbulence and stabilizing surface heat fluxes. The OSBL consists of a weakly stratified layer, despite a surface heat flux, above a stratified thermocline. The weakly stratified (mixed) layer is maintained by a combination of a turbulent heat flux produced by the wave-driven Stokes drift and downgradient turbulent diffusion. The scaling of turbulence statistics, such as dissipation and vertical velocity variance, is only affected by the surface heat flux through changes in the mixed layer depth. Diagnostic models are proposed for the equilibrium boundary layer and mixed layer depths in the presence of surface heating. The models are a function of the initial mixed layer depth before heating is imposed and the Langmuir stability length. In the presence of radiative heating, the models are extended to account for the depth profile of the heating.

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Natasha S. Lucas, Alan L. M. Grant, Tom P. Rippeth, Jeff A. Polton, Matthew R. Palmer, Liam Brannigan, and Stephen E. Belcher

Abstract

Understanding the processes that control the evolution of the ocean surface boundary layer (OSBL) is a prerequisite for obtaining accurate simulations of air–sea fluxes of heat and trace gases. Observations of the rate of dissipation of turbulent kinetic energy (ε), temperature, salinity, current structure, and wave field over a period of 9.5 days in the northeast Atlantic during the Ocean Surface Mixing, Ocean Submesoscale Interaction Study (OSMOSIS) are presented. The focus of this study is a storm that passed over the observational area during this period. The profiles of ε in the OSBL are consistent with profiles from large-eddy simulation (LES) of Langmuir turbulence. In the transition layer (TL), at the base of the OSBL, ε was found to vary periodically at the local inertial frequency. A simple bulk model of the OSBL and a parameterization of shear driven turbulence in the TL are developed. The parameterization of ε is based on assumptions about the momentum balance of the OSBL and shear across the TL. The predicted rate of deepening, heat budget, and the inertial currents in the OSBL were in good agreement with the observations, as is the agreement between the observed value of ε and that predicted using the parameterization. A previous study reported spikes of elevated dissipation related to enhanced wind shear alignment at the base of the OSBL after this storm. The spikes in dissipation are not predicted by this new parameterization, implying that they are not an important source of dissipation during the storm.

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Adam A. Scaife, Elizabeth Good, Ying Sun, Zhongwei Yan, Nick Dunstone, Hong-Li Ren, Chaofan Li, Riyu Lu, Peili Wu, Zongjian Ke, Zhuguo Ma, Kalli Furtado, Tongwen Wu, Tianjun Zhou, Tyrone Dunbar, Chris Hewitt, Nicola Golding, Peiqun Zhang, Rob Allan, Kirstine Dale, Fraser C. Lott, Peter A. Stott, Sean Milton, Lianchun Song, and Stephen Belcher

Abstract

We present results from the first 6 years of this major U.K. government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between U.K. and Chinese climate scientists, and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modeling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over 300 peer reviewed studies generated jointly by U.K. and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skillful predictions of important aspects of Chinese climate such as East Asian summer monsoon rainfall. In addition, the development of improved modeling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real-time climate services. Participation of dozens of institutes through subprojects in this program, which is governed by the Met Office Hadley Centre, the China Meteorological Administration, and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services.

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Curtis R. Wood, Samantha J. Arnold, Ahmed A. Balogun, Janet F. Barlow, Stephen E. Belcher, Rex E. Britter, Hong Cheng, Adrian Dobre, Justin J. N. Lingard, Damien Martin, Marina K. Neophytou, Fredrik K. Petersson, Alan G. Robins, Dudley E. Shallcross, Robert J. Smalley, James E. Tate, Alison S. Tomlin, and Iain R. White

In the event of a release of toxic gas in the center of London, emergency services personnel would need to determine quickly the extent of the area contaminated. The transport of pollutants by turbulent flow within the complex streets and building architecture of London, United Kingdom, is not straightforward, and we might wonder whether it is at all possible to make a scientifically reasoned decision. Here, we describe recent progress from a major U.K. project, Dispersion of Air Pollution and its Penetration into the Local Environment (DAPPLE; information online at www.dapple.org.uk). In DAPPLE, we focus on the movement of airborne pollutants in cities by developing a greater understanding of atmospheric flow and dispersion within urban street networks. In particular, we carried out full-scale dispersion experiments in central London from 2003 through 2008 to address the extent of the dispersion of tracers following their release at street level. These measurements complemented previous studies because 1) our focus was on dispersion within the first kilometer from the source, when most of the material was expected to remain within the street network rather than being mixed into the boundary layer aloft; 2) measurements were made under a wide variety of meteorological conditions; and 3) central London represents a European, rather than North American, city geometry. Interpretation of the results from the full-scale experiments was supported by extensive numerical and wind tunnel modeling, which allowed more detailed analysis under idealized and controlled conditions. In this article, we review the full-scale DAPPLE methodologies and show early results from the analysis of the 2007 field campaign data.

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