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VOL. 10, NO. 4 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY AUGUST 1993Tracking Hurricane Claudette with the U.S. Air Force Over-the-Horizon Radar T. M. GEORGES NOAA Wave Propagation Laboratory, Boulder, Colorado J. A. HARLAN CIRES, University of Colorado, Boulder, Colorado L. R. MEYER General Electric Company, Bangor, Maine
VOL. 10, NO. 4 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY AUGUST 1993Tracking Hurricane Claudette with the U.S. Air Force Over-the-Horizon Radar T. M. GEORGES NOAA Wave Propagation Laboratory, Boulder, Colorado J. A. HARLAN CIRES, University of Colorado, Boulder, Colorado L. R. MEYER General Electric Company, Bangor, Maine
hydrodynamics lead to further errors in the predictions of water quality and biological parameters. One way to improve model performance is through continued model development and increases in grid resolution and the accuracy of forcing fields and parameterization schemes. Another way, which we apply here, is to integrate data from existing observing networks into the model through data assimilation, thereby making the model results more realistic. Oceanographic data assimilation has been performed for many
hydrodynamics lead to further errors in the predictions of water quality and biological parameters. One way to improve model performance is through continued model development and increases in grid resolution and the accuracy of forcing fields and parameterization schemes. Another way, which we apply here, is to integrate data from existing observing networks into the model through data assimilation, thereby making the model results more realistic. Oceanographic data assimilation has been performed for many
A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Cloudsthese effects requires detailed knowledge of atmospheric variability, which in turn requires an expanded environmental database beyond the typical deterministic or “standard” atmospheres utilized by many modern radiative transfer models. To this end, the Air Force Institute of Technology (AFIT) has produced an atmospheric characterization and radiative transfer code, the Laser Environmental Effects Definition and Reference (LEEDR; Fiorino et al. 2014 ). LEEDR is a verified and validated atmospheric
these effects requires detailed knowledge of atmospheric variability, which in turn requires an expanded environmental database beyond the typical deterministic or “standard” atmospheres utilized by many modern radiative transfer models. To this end, the Air Force Institute of Technology (AFIT) has produced an atmospheric characterization and radiative transfer code, the Laser Environmental Effects Definition and Reference (LEEDR; Fiorino et al. 2014 ). LEEDR is a verified and validated atmospheric
520 $OURNAL O,F ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME9The Effect of a CO2 Laser Pulse Shape on the Accuracy of DIAL Measurements AVISHAI BEN-DAVIDScience and Technology Corporation, Edgewood, Maryland ALAN P. FORCE, FRANCIS M. D'AMICO, AND SILVIO L. EMERYU.S. Army Chemical Research, Development, and Engineering Center. Aberdeen Proving Ground, Maryland (Manuscript received 5 March 1991
520 $OURNAL O,F ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME9The Effect of a CO2 Laser Pulse Shape on the Accuracy of DIAL Measurements AVISHAI BEN-DAVIDScience and Technology Corporation, Edgewood, Maryland ALAN P. FORCE, FRANCIS M. D'AMICO, AND SILVIO L. EMERYU.S. Army Chemical Research, Development, and Engineering Center. Aberdeen Proving Ground, Maryland (Manuscript received 5 March 1991
1. Introduction The interactions of aerosols with clouds represent a leading source of uncertainty in quantifying anthropogenic radiative forcing of climate globally since preindustrial times ( Solomon et al. 2007 ). Clouds are also reported to constitute the largest source of uncertainty in climate sensitivity to radiative forcing in current coupled ocean–atmosphere climate models ( Soden and Held 2006 ). In the tropics, differences in the predicted sensitivity of marine boundary layer clouds
1. Introduction The interactions of aerosols with clouds represent a leading source of uncertainty in quantifying anthropogenic radiative forcing of climate globally since preindustrial times ( Solomon et al. 2007 ). Clouds are also reported to constitute the largest source of uncertainty in climate sensitivity to radiative forcing in current coupled ocean–atmosphere climate models ( Soden and Held 2006 ). In the tropics, differences in the predicted sensitivity of marine boundary layer clouds
Clouds and the Earth’s Radiant Energy System (CERES) FluxByCldTyp Edition 4 Data Product1. Introduction One of the greatest challenges in climate model projections of warming in response to anthropogenic forcing is the representation of clouds and their interactions with Earth’s radiation budget in climate models ( Boucher et al. 2013 ). Cloud processes occur over a range of time and space scales, which makes them difficult to model. Climate models agree that feedbacks collectively amplify the surface temperature response to external forcing, but the strengths of the
1. Introduction One of the greatest challenges in climate model projections of warming in response to anthropogenic forcing is the representation of clouds and their interactions with Earth’s radiation budget in climate models ( Boucher et al. 2013 ). Cloud processes occur over a range of time and space scales, which makes them difficult to model. Climate models agree that feedbacks collectively amplify the surface temperature response to external forcing, but the strengths of the
VOL. 10, NO. 3 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY JUNEI993An 1 1-cm Coherent Polarimetric Radar for Meteorological Research JAMES I. METCALF, ALEXANDER W. BISHOP,* RICHARD C. CHANLEY,* TIMOTHY C. HIETT, AND PIO J. PETROCCHIAtmospheric Sciences Division, Geophysics Directorate, Phillips Laboratory, Hanscom Air Force Base, Massachusetts (Manuscript received 17 January 1992, in final form I September
VOL. 10, NO. 3 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY JUNEI993An 1 1-cm Coherent Polarimetric Radar for Meteorological Research JAMES I. METCALF, ALEXANDER W. BISHOP,* RICHARD C. CHANLEY,* TIMOTHY C. HIETT, AND PIO J. PETROCCHIAtmospheric Sciences Division, Geophysics Directorate, Phillips Laboratory, Hanscom Air Force Base, Massachusetts (Manuscript received 17 January 1992, in final form I September
Performance Evaluation of Force Transducer for the Observation of Sediment Entrainment in Rapidly Varied Flowscritical shear stress and the critical velocity. Incipient motion and wave energy dissipation are traditionally predicted by bed shear stresses. For noncohesive sediments, the critical Shields number or the well-known Shields curve is widely used in practice and was initially proposed by Shields (1936) , who examined the forces exerted on a single grain at incipient motion under steady flows. The results suggested that sediment motion results from the destabilizing force of the shear stress exceeding
critical shear stress and the critical velocity. Incipient motion and wave energy dissipation are traditionally predicted by bed shear stresses. For noncohesive sediments, the critical Shields number or the well-known Shields curve is widely used in practice and was initially proposed by Shields (1936) , who examined the forces exerted on a single grain at incipient motion under steady flows. The results suggested that sediment motion results from the destabilizing force of the shear stress exceeding
data. A well-defined altimeter NRCS decrease with increasing QuikSCAT wind speed is observed up to hurricane force winds, but matchup data are lacking above this level. The dashed curve in Fig. 1 represents the Young (1993) model. It is clear this linear Geosat model lies near the data but slightly underestimates the NRCS saturation at highest winds. The proposed new high-wind altimeter model function branch, also shown in Fig. 1 , is again a linear model relating NRCS to 10-m wind speeds
data. A well-defined altimeter NRCS decrease with increasing QuikSCAT wind speed is observed up to hurricane force winds, but matchup data are lacking above this level. The dashed curve in Fig. 1 represents the Young (1993) model. It is clear this linear Geosat model lies near the data but slightly underestimates the NRCS saturation at highest winds. The proposed new high-wind altimeter model function branch, also shown in Fig. 1 , is again a linear model relating NRCS to 10-m wind speeds
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
