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1. Introduction More than two decades after the first comprehensive observations of the atmospheric kinetic energy spectrum ( Nastrom and Gage 1985 ), the dynamics of the mesoscale portion remain actively debated. At synoptic scales, where the flow is predominantly quasigeostrophic (QG), the horizontal wavenumber energy spectrum follows a k −3 power law (henceforth a −3 spectrum), agreeing with theoretical predictions for QG turbulence ( Charney 1971 ; Boer and Shepherd 1983 ). At scales
1. Introduction More than two decades after the first comprehensive observations of the atmospheric kinetic energy spectrum ( Nastrom and Gage 1985 ), the dynamics of the mesoscale portion remain actively debated. At synoptic scales, where the flow is predominantly quasigeostrophic (QG), the horizontal wavenumber energy spectrum follows a k −3 power law (henceforth a −3 spectrum), agreeing with theoretical predictions for QG turbulence ( Charney 1971 ; Boer and Shepherd 1983 ). At scales
, radar reflectivity, and kinetic energy (KE) flux. Some of these quantities can be measured more accurately with specialized instruments (e.g., measuring rainfall with rain gauges of modern design). However, the currently achievable precisions of the KE flux measurements in rainfall are still quite limited (see the brief literature review below). While different techniques for more accurate and more affordable DSD monitoring are under continuous development (e.g., Henson et al. 2004 ), there is also
, radar reflectivity, and kinetic energy (KE) flux. Some of these quantities can be measured more accurately with specialized instruments (e.g., measuring rainfall with rain gauges of modern design). However, the currently achievable precisions of the KE flux measurements in rainfall are still quite limited (see the brief literature review below). While different techniques for more accurate and more affordable DSD monitoring are under continuous development (e.g., Henson et al. 2004 ), there is also
TC kinetic energy have significant differences in terms of interannual variation, which is modulated by the anomalous environmental conditions associated with ENSO. Camargo and Sobel (2005) used the accumulated cyclone energy (ACE) index to examine the relationship between ENSO and TC activity over the WNP, suggesting that more intense and longer-lived TCs appear in warm years than in cold years. ACE, as a continuous variable, can be used to represent the interannual variability of TC intensity
TC kinetic energy have significant differences in terms of interannual variation, which is modulated by the anomalous environmental conditions associated with ENSO. Camargo and Sobel (2005) used the accumulated cyclone energy (ACE) index to examine the relationship between ENSO and TC activity over the WNP, suggesting that more intense and longer-lived TCs appear in warm years than in cold years. ACE, as a continuous variable, can be used to represent the interannual variability of TC intensity
1. Introduction Interactions between thermal and kinetic energy changes have been historically investigated in the literature under available potential energy, for example, by Margules (1910) and Lorenz (1955) . The focus of available potential energy is mainly on the hydrostatically balanced atmosphere so far. Zilitinkevich et al. (2007) proposed the idea of total turbulent energy conservation by considering interactions between turbulent kinetic energy (TKE) and turbulent potential
1. Introduction Interactions between thermal and kinetic energy changes have been historically investigated in the literature under available potential energy, for example, by Margules (1910) and Lorenz (1955) . The focus of available potential energy is mainly on the hydrostatically balanced atmosphere so far. Zilitinkevich et al. (2007) proposed the idea of total turbulent energy conservation by considering interactions between turbulent kinetic energy (TKE) and turbulent potential
waves have a nearly horizontal group velocity and, thus, can propagate energy long distances without encountering the ocean surface or bottom ( Garrett 2001 ). However, wave–wave interactions can lead to energy fluxes into and/or out of the near-inertial frequency band, and dissipation can occur, which acts as a sink for near-inertial energy. In this paper, we investigate the seasonality of near-inertial internal waves at a site in the western North Atlantic Ocean and examine a localized kinetic
waves have a nearly horizontal group velocity and, thus, can propagate energy long distances without encountering the ocean surface or bottom ( Garrett 2001 ). However, wave–wave interactions can lead to energy fluxes into and/or out of the near-inertial frequency band, and dissipation can occur, which acts as a sink for near-inertial energy. In this paper, we investigate the seasonality of near-inertial internal waves at a site in the western North Atlantic Ocean and examine a localized kinetic
hence artificial constraints were always introduced in close proximity to the mean water level. Therefore, measurements in the water, but above the wave troughs and certainly within the wave crests, are critical for such practical applications, but are most challenging. A classical wall (surface) layer similarity scaling for turbulence in a boundary layer gives an interpretation of the dissipation rate of turbulence kinetic energy , where is friction velocity, κ is the Von Kármán constant, and
hence artificial constraints were always introduced in close proximity to the mean water level. Therefore, measurements in the water, but above the wave troughs and certainly within the wave crests, are critical for such practical applications, but are most challenging. A classical wall (surface) layer similarity scaling for turbulence in a boundary layer gives an interpretation of the dissipation rate of turbulence kinetic energy , where is friction velocity, κ is the Von Kármán constant, and
commonly referred to as the Somali jet. The Somali jet possesses high kinetic energy (KE), per unit mass, with values sometimes exceeding 300 m 2 s −2 ( Krishnamurti and Ramanathan 1982 ). This highly energetic jet transports moisture from the ocean, driving convection and leading to high monsoon rainfall ( Saha 1970 ). The presence of the jet is an important factor for monsoon onset over India, and it is well known that the onset of the Somali jet precedes the onset of monsoon rainfall over the
commonly referred to as the Somali jet. The Somali jet possesses high kinetic energy (KE), per unit mass, with values sometimes exceeding 300 m 2 s −2 ( Krishnamurti and Ramanathan 1982 ). This highly energetic jet transports moisture from the ocean, driving convection and leading to high monsoon rainfall ( Saha 1970 ). The presence of the jet is an important factor for monsoon onset over India, and it is well known that the onset of the Somali jet precedes the onset of monsoon rainfall over the
1. Introduction The atmospheric kinetic energy (KE) spectrum has a canonical structure depicted schematically in Fig. 1 . With KE plotted as a function of horizontal wavenumber, the spectrum is characterized by a shallow-sloped region at low wavenumbers and global scales, a steeper-sloped power-law region at intermediate wavenumbers corresponding to wavelengths of baroclinic cyclones, followed by the mesoscale region with a shallower slope, close to − , that leads to fully three
1. Introduction The atmospheric kinetic energy (KE) spectrum has a canonical structure depicted schematically in Fig. 1 . With KE plotted as a function of horizontal wavenumber, the spectrum is characterized by a shallow-sloped region at low wavenumbers and global scales, a steeper-sloped power-law region at intermediate wavenumbers corresponding to wavelengths of baroclinic cyclones, followed by the mesoscale region with a shallower slope, close to − , that leads to fully three
( Moncrieff 2004 ; Majda 2007a , b ), recharge–discharge (e.g., Blade and Hartmann 1993 ; Hu and Randall 1995 ; Kemball-Cook and Weare 2001 ; Sobel and Gildor 2003 ), feedbacks with surface heat fluxes and radiation (e.g., Emanuel 1987 ; Neelin et al. 1987 ; Raymond 2001 ; Sobel et al. 2008 , 2010 ), and interactions with synoptic scales ( Biello and Majda 2005 ; Biello et al. 2007 ). In this study, we examine the MJO from the point of view of the kinetic energy budget, constructed from
( Moncrieff 2004 ; Majda 2007a , b ), recharge–discharge (e.g., Blade and Hartmann 1993 ; Hu and Randall 1995 ; Kemball-Cook and Weare 2001 ; Sobel and Gildor 2003 ), feedbacks with surface heat fluxes and radiation (e.g., Emanuel 1987 ; Neelin et al. 1987 ; Raymond 2001 ; Sobel et al. 2008 , 2010 ), and interactions with synoptic scales ( Biello and Majda 2005 ; Biello et al. 2007 ). In this study, we examine the MJO from the point of view of the kinetic energy budget, constructed from
influence their Re– X relationship and the resulting values for V t and kinetic energies. For those reasons, and as previously noted for graupel and hail mass, the size-dependent relationships developed here are presented in ranges of percentiles in Table 2 . Although the data are based on relatively small sample sizes, nonetheless, it is important to show variability in this way. The relationships shown in italic text in Table 2 compose a more extensive dataset as they are based on the median
influence their Re– X relationship and the resulting values for V t and kinetic energies. For those reasons, and as previously noted for graupel and hail mass, the size-dependent relationships developed here are presented in ranges of percentiles in Table 2 . Although the data are based on relatively small sample sizes, nonetheless, it is important to show variability in this way. The relationships shown in italic text in Table 2 compose a more extensive dataset as they are based on the median
