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Hua Zhang, Feng Zhang, Qiang Fu, Zhongping Shen, and Peng Lu

1. Introduction Photochemical processes in the atmosphere are driven by solar radiation, which dissociates certain molecules into reactive atoms or free radicals. Models that simulate the chemistry of the atmosphere must accurately simulate the radiation processes that initiate photodissociation. The photodissociation rate is proportional to the actinic flux. In addition, for some biological applications such as exposure of small “bodies” suspended in air or in water (e.g., phytoplankton in the

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Noboru Nakamura

diffusivity diagnosed in the equivalent latitude coordinate ( Nakamura 1996 ; Haynes and Shuckburgh 2000a ) and its relationship to the flux and the decay rate of the tracer, we will examine the effects of the spatiotemporal variations of the barrier properties on the global mixing. The next section introduces the 1D model and addresses the role of a barrier under various model configurations. Section 3 describes the results of the isentropic transport calculations in the UTLS region. The final section

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Maithili Sharan and Piyush Srivastava

1. Introduction Monin and Obukhov similarity (MOS) theory ( Monin and Obukhov 1954 ) is widely used to estimate the stability parameter (= z / L , where z is the height above the ground, and L is the Obukhov length) and surface fluxes in atmospheric models for weather forecasting as well as for air quality and climate modeling ( Arya 1988 ; Beljaars and Holtslag 1991 ; Garratt 1994 ; Oleson et al. 2008 ; Skamarock et al. 2008 ; Jimenez et al. 2012 ; Giorgi et al. 2012 ; Pielke 2013

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Piyush Srivastava and Maithili Sharan

1. Introduction A major source of uncertainty in the predictive capability of the atmospheric models is associated with the inadequate parameterization of turbulent fluxes in the models. Almost all the numerical models of atmosphere utilize the Monin–Obukhov similarity theory (MOST; Monin and Obukhov 1954 ) for parameterization of surface fluxes ( Stull 1988 ). The bulk algorithm for parameterization of surface fluxes based on MOST requires wind, temperature, and humidity measurements at two

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Chin-Hsuan Peng and Chun-Chieh Wu

Schubert 2009 ) and leading to the apparent import of absolute angular momentum under continuous diabatic heating inside the RMW (e.g., Smith and Montgomery 2015 ), which is favorable for further intensification of the vortex. As for the energy source of TC intensification, Riehl (1950) highlighted that sea surface heat fluxes play a crucial role in TC development. This concept was formally proposed in the context of the wind-induced surface heat exchange (WISHE) mechanism ( Emanuel 1986 , 1989

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Vickal V. Kumar, Christian Jakob, Alain Protat, Christopher R. Williams, and Peter T. May

and Rajopadhyaya 1999 ). In general circulation models (GCMs) convection cannot be represented by modeling individual convective clouds. Instead, simple representations of the collective effects of a cumulus cloud ensemble existing in a model grid box are applied. Among the most widespread of these cumulus parameterization approaches is the so-called mass-flux approach [see Arakawa (2004) for an overview]. Here, the vertical transport by the cloud ensemble is directly related to the mass flux

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P. Baas, G. J. Steeneveld, B. J. H. van de Wiel, and A. A. M. Holtslag

1. Introduction Flux–gradient relationships are used to relate gradients of mean atmospheric profiles to turbulent fluxes. The concept of flux–gradient relationships has proven to be very useful in estimating surface fluxes both in atmospheric models and from observed profiles. The relevant quantities to relate fluxes and gradients are obtained from dimensional analysis. Consequently, the functional form of the flux–gradient relationships must be found by experiment. Some of the current

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Tomas Chor, James C. McWilliams, and Marcelo Chamecki

1. Introduction In the atmospheric sciences community, eddy diffusivity models have been invaluable when representing turbulent fluxes ( Ghannam et al. 2017 ). The premise in these models is that the action of eddies can be parameterized as a diffusive process via a flow-dependent eddy diffusivity. This approach [hereafter referred to as gradient transport models (GTM) but also known as K theory; Stull 1988 ] can be written as (1) 〈 w ′ c ′ 〉 = − K ⁡ ( z )   ∂ 〈 C 〉 ∂ z , where C is the

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David H. Richter and Peter P. Sullivan

1. Introduction For predicting the intensity of tropical cyclones, detailed knowledge of the exchanges of heat, moisture, and momentum at the air–sea interface is essential. While the flux of latent and sensible heat from the ocean provides fuel for the storm, drag on the surface can act to weaken it, and thus a better understanding of the balance between these processes is required if hurricane intensity forecasts are to be improved ( Emanuel 1995 ; NOAA Science Advisory Board 2006 ). Because

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Li-Zhi Shen, Chun-Chieh Wu, and Falko Judt

1. Introduction Intensity and size are the two main characteristics used to describe the damage potential of tropical cyclones (TCs; Marks et al. 1998 ; Wang and Wu 2004 ; Cheng and Wu 2018 , 2020 ). The energy source of TCs is surface heat fluxes ( Riehl 1950 ; Zhang and Emanuel 2016 ), an idea that was cast into a theory called the wind-induced surface heat exchange (WISHE) mechanism ( Emanuel 1986 , 1989 ), which highlights the positive feedback between surface heat fluxes and storm

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