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1. Introduction Measurements of flow properties in the atmospheric surface layer over natural wind-generated waves have been made with varying degrees of accuracy over the last few decades. Generally speaking such measurements have been motivated by one of three goals: (i) estimation of interfacial fluxes of momentum, heat, and mass; (ii) exploration of the rate of wave generation by wind; and (iii) investigation of the transmission of electromagnetic radiation in the turbulent near
1. Introduction Measurements of flow properties in the atmospheric surface layer over natural wind-generated waves have been made with varying degrees of accuracy over the last few decades. Generally speaking such measurements have been motivated by one of three goals: (i) estimation of interfacial fluxes of momentum, heat, and mass; (ii) exploration of the rate of wave generation by wind; and (iii) investigation of the transmission of electromagnetic radiation in the turbulent near
610 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 13An Airborne Millimeter-Wave Imaging Radiometer for Cloud,Precipitation, and Atmospheric Water Vapor Studies P. RACETTE, R. F. AOLER, J. R. WAnGNASA/Goddard Space Flight Center, Greenbelt, Maryland A. J. GAS~EWSK~ ~D D. M. JAXSONDepartment of Electrical Engineering, Georgia Institute of Technology, Atlanta, Georgia D. S. ZAC
610 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 13An Airborne Millimeter-Wave Imaging Radiometer for Cloud,Precipitation, and Atmospheric Water Vapor Studies P. RACETTE, R. F. AOLER, J. R. WAnGNASA/Goddard Space Flight Center, Greenbelt, Maryland A. J. GAS~EWSK~ ~D D. M. JAXSONDepartment of Electrical Engineering, Georgia Institute of Technology, Atlanta, Georgia D. S. ZAC
The Use of Ship-Launched Fixed-Wing UAVs for Measuring the Marine Atmospheric Boundary Layer and Ocean Surface Processes1. Introduction Measurements of sea state and air–sea fluxes have historically been made from ships, buoys, and other platforms, but these essentially fixed-point measurements, over the time scales of surface wave and atmospheric processes, provide no observations of the spatial evolution and distribution of surface fluxes and the wave field. Aircraft-based measurements are an effective means to sample atmospheric and oceanic phenomena over a wide range of conditions and locations, and are also
1. Introduction Measurements of sea state and air–sea fluxes have historically been made from ships, buoys, and other platforms, but these essentially fixed-point measurements, over the time scales of surface wave and atmospheric processes, provide no observations of the spatial evolution and distribution of surface fluxes and the wave field. Aircraft-based measurements are an effective means to sample atmospheric and oceanic phenomena over a wide range of conditions and locations, and are also
An Evaluation of the Parallel Ensemble Empirical Mode Decomposition Method in Revealing the Role of Downscaling Processes Associated with African Easterly Waves in Tropical Cyclone Genesis1. Introduction Recent intense tropical storms have caused substantial financial damage to human societies and have threatened human life (e.g., Shen et al. 2006 , 2013a , b ). Therefore, improving our understanding of tropical cyclone (TC) genesis and prediction is an active topic in atmospheric research. The association of TCs with tropical waves has now been studied for several decades (e.g., Landsea 1993 ; Frank and Roundy 2006 ). Landsea (1993) indicated that over 85% of intense
1. Introduction Recent intense tropical storms have caused substantial financial damage to human societies and have threatened human life (e.g., Shen et al. 2006 , 2013a , b ). Therefore, improving our understanding of tropical cyclone (TC) genesis and prediction is an active topic in atmospheric research. The association of TCs with tropical waves has now been studied for several decades (e.g., Landsea 1993 ; Frank and Roundy 2006 ). Landsea (1993) indicated that over 85% of intense
emphasized the roles of wind speed, atmospheric stability, and terrain height in establishing flow streamlines and mountain wave features. Corby (1954) offers a review of early studies of mountain waves. As air is forced over terrain, the restoring force resulting from the difference between an air parcel’s density and that of the ambient environment at the same level will accelerate the air parcel back toward an equilibrium level. The oscillation of disturbed flow in a stable environment has been
emphasized the roles of wind speed, atmospheric stability, and terrain height in establishing flow streamlines and mountain wave features. Corby (1954) offers a review of early studies of mountain waves. As air is forced over terrain, the restoring force resulting from the difference between an air parcel’s density and that of the ambient environment at the same level will accelerate the air parcel back toward an equilibrium level. The oscillation of disturbed flow in a stable environment has been
1. Introduction Meteorological radars normally measure atmospheric targets that lie in the far-field or Fraunhofer region where r ≥ r f . The far-field distance, r f , is defined as r f = 2 D 2 / λ. (1) Here D is antenna diameter and λ is the radar wavelength. The r f is sometimes referred to as the Rayleigh distance ( Clarke and Brown 1980 ) and it approximately represents the transition between the Fresnel region and the far field. Millimeter-wave (MMW) cloud
1. Introduction Meteorological radars normally measure atmospheric targets that lie in the far-field or Fraunhofer region where r ≥ r f . The far-field distance, r f , is defined as r f = 2 D 2 / λ. (1) Here D is antenna diameter and λ is the radar wavelength. The r f is sometimes referred to as the Rayleigh distance ( Clarke and Brown 1980 ) and it approximately represents the transition between the Fresnel region and the far field. Millimeter-wave (MMW) cloud
directions). b. Example of observation Figure 11 shows an example of the observation from 0000 Japan standard time (JST) 25 April to 2200 JST 26 April 1998. The cos 2 s ( θ w /2) model [ Eq. (9) ] is used to estimate wave distributions, because the accuracy of the wave direction estimation for this model is better than that for the sech 2 ( γθ w ) model [ Eq. (21) ]. An atmospheric front passed over the observation area on 25 April 1998 ( Hisaki 2002 ), and the wind turned southeastward ( Fig. 11c
directions). b. Example of observation Figure 11 shows an example of the observation from 0000 Japan standard time (JST) 25 April to 2200 JST 26 April 1998. The cos 2 s ( θ w /2) model [ Eq. (9) ] is used to estimate wave distributions, because the accuracy of the wave direction estimation for this model is better than that for the sech 2 ( γθ w ) model [ Eq. (21) ]. An atmospheric front passed over the observation area on 25 April 1998 ( Hisaki 2002 ), and the wind turned southeastward ( Fig. 11c
Surface Wave Impact When Simulating Midlatitude Storm Developmentcoefficient over the ocean is expressed as where κ is the von Kármán constant and is the roughness length. The Charnock formula ( Charnock 1955 ) is used in nearly all atmospheric models, that is, , where α is the Charnock coefficient, g is the acceleration due to gravity, and is the friction velocity. The Charnock coefficient α is generally assumed to lie between 0.015 and 0.035, corresponding to the range reported in observational studies ( Powell et al. 2003 ). Surface gravity waves
coefficient over the ocean is expressed as where κ is the von Kármán constant and is the roughness length. The Charnock formula ( Charnock 1955 ) is used in nearly all atmospheric models, that is, , where α is the Charnock coefficient, g is the acceleration due to gravity, and is the friction velocity. The Charnock coefficient α is generally assumed to lie between 0.015 and 0.035, corresponding to the range reported in observational studies ( Powell et al. 2003 ). Surface gravity waves
processed using a marine atmospheric boundary layer model ( Smith 1988 ) to generate surface layer profiles, adjust meteorological measurements to common reference elevations, and compute atmospheric stability parameters and wind stress ( Hanson and White 1991 ). Output quantities were averaged to form 30-min values that coincide with the surface wave observations. Vector-averaged wind speed estimates at 10-m height ( U 10 ) are used for the results reported here. These observations compared well with
processed using a marine atmospheric boundary layer model ( Smith 1988 ) to generate surface layer profiles, adjust meteorological measurements to common reference elevations, and compute atmospheric stability parameters and wind stress ( Hanson and White 1991 ). Output quantities were averaged to form 30-min values that coincide with the surface wave observations. Vector-averaged wind speed estimates at 10-m height ( U 10 ) are used for the results reported here. These observations compared well with
1. Introduction Close to the coast the interaction between wind, waves, and tides becomes most complex but also most critical. Storms are particularly important at the coast as these events can lead to high waves, storm surges, inundation, and erosion in populated areas. The motivation for this paper is to explore ways of improving coastal surge and wave forecasting by improving the atmospheric forcing. Here, we specifically examine the issue of atmospheric model resolution. Storm surges are
1. Introduction Close to the coast the interaction between wind, waves, and tides becomes most complex but also most critical. Storms are particularly important at the coast as these events can lead to high waves, storm surges, inundation, and erosion in populated areas. The motivation for this paper is to explore ways of improving coastal surge and wave forecasting by improving the atmospheric forcing. Here, we specifically examine the issue of atmospheric model resolution. Storm surges are
