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- Author or Editor: N. E. Huang x
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Abstract
The probability density function and the first three statistical moments of velocity, acceleration and pressure of a gravity wave field, for points in the vicinity of still water level, are obtained taking into consideration the effects of free surface fluctuation and using the second-order Stokes wave model. These results reduce to those obtained previously by Tung using linear wave theory.
Abstract
The probability density function and the first three statistical moments of velocity, acceleration and pressure of a gravity wave field, for points in the vicinity of still water level, are obtained taking into consideration the effects of free surface fluctuation and using the second-order Stokes wave model. These results reduce to those obtained previously by Tung using linear wave theory.
Abstract
The effect of wave breaking on the wave energy spectral shape is examined. The Stokes wave-breaking criterion is first extended to random waves and a breaking wave model is established in which the elevation of breaking waves is expressed in terms of that of the original ideal waves, which are assumed to be stationary and Gaussian. Based on this model, a simple but approximate expression for the spectrum of breaking waves is derived and applied to the case in which a deep water unidirectional wave train enters a region of adverse current steady in time and uniformly distributed in depth.
Abstract
The effect of wave breaking on the wave energy spectral shape is examined. The Stokes wave-breaking criterion is first extended to random waves and a breaking wave model is established in which the elevation of breaking waves is expressed in terms of that of the original ideal waves, which are assumed to be stationary and Gaussian. Based on this model, a simple but approximate expression for the spectrum of breaking waves is derived and applied to the case in which a deep water unidirectional wave train enters a region of adverse current steady in time and uniformly distributed in depth.
Abstract
As part of the Grand Banks Experiment in May 1979, airborne laser profilometer measurements of the ocean wave field were made across a large cold-water extrusion situated over the Newfoundland Ridge. The feature is actually an extension of the Labrador Current which is bordered on the west side by the Gulf Stream and on the east side by the North Atlantic Current. Star-shaped flight patterns were flown over the fronts on each side of the cold-water feature. A graphic technique was applied to the apparent wavenumber spectra in order to determine the changes in wave energy, wavelength and direction of propagation of the dominant wind-wave and swell components as they move across the fronts. At the western front, the sea state increased abruptly and the results indicate that wave-current interactions were the most important mechanism for wave modification although boundary-layer effects were present and increased wave breaking was observed. At the eastern front, changes in the swell are compared to theoretical predictions and are in very close agreement.
Abstract
As part of the Grand Banks Experiment in May 1979, airborne laser profilometer measurements of the ocean wave field were made across a large cold-water extrusion situated over the Newfoundland Ridge. The feature is actually an extension of the Labrador Current which is bordered on the west side by the Gulf Stream and on the east side by the North Atlantic Current. Star-shaped flight patterns were flown over the fronts on each side of the cold-water feature. A graphic technique was applied to the apparent wavenumber spectra in order to determine the changes in wave energy, wavelength and direction of propagation of the dominant wind-wave and swell components as they move across the fronts. At the western front, the sea state increased abruptly and the results indicate that wave-current interactions were the most important mechanism for wave modification although boundary-layer effects were present and increased wave breaking was observed. At the eastern front, changes in the swell are compared to theoretical predictions and are in very close agreement.
Abstract
A methodology is proposed for estimating the parameters of a gamma raindrop size distribution model from radar measurements of Z h , Z dr, and K dp at S band. Previously developed algorithms by Gorgucci et al. are extended to cover low rain-rate events where both Z dr and K dp are noisy. Polarimetric data from the S-band Dual-Polarization Doppler Radar (S-Pol) during the Tropical Rainfall Measuring Mission (TRMM)/Brazil campaign are analyzed; specifically, the gamma parameters are retrieved for samples of convective and trailing stratiform rain during the 15 February 1999 squall-line event. Histograms of N w and D o are retrieved from radar for each rain type and compared with related statistics reported in the literature. The functional behavior of N w and D o versus rain rate retrieved from radar is compared against samples of 2D-video and RD-69 disdrometer data obtained during the campaign. The time variation of N w , D o , and μ averaged over a 5 km × 5 km area (within which a network of gauges and a profiler were situated) is shown to illustrate temporal changes associated with the gamma parameters as the squall line passed over the network. The gauge-derived areal rainfall over the network is compared against radar using the areal Φdp method, and the concept of an effective slope of a linear axis ratio versus diameter model is shown to significantly reduce the bias in radar-derived rainfall accumulation.
Abstract
A methodology is proposed for estimating the parameters of a gamma raindrop size distribution model from radar measurements of Z h , Z dr, and K dp at S band. Previously developed algorithms by Gorgucci et al. are extended to cover low rain-rate events where both Z dr and K dp are noisy. Polarimetric data from the S-band Dual-Polarization Doppler Radar (S-Pol) during the Tropical Rainfall Measuring Mission (TRMM)/Brazil campaign are analyzed; specifically, the gamma parameters are retrieved for samples of convective and trailing stratiform rain during the 15 February 1999 squall-line event. Histograms of N w and D o are retrieved from radar for each rain type and compared with related statistics reported in the literature. The functional behavior of N w and D o versus rain rate retrieved from radar is compared against samples of 2D-video and RD-69 disdrometer data obtained during the campaign. The time variation of N w , D o , and μ averaged over a 5 km × 5 km area (within which a network of gauges and a profiler were situated) is shown to illustrate temporal changes associated with the gamma parameters as the squall line passed over the network. The gauge-derived areal rainfall over the network is compared against radar using the areal Φdp method, and the concept of an effective slope of a linear axis ratio versus diameter model is shown to significantly reduce the bias in radar-derived rainfall accumulation.
Abstract
A wave sensor, consisting of parallel, evenly spaced capacitance wires, whose output is the sum of the water surface deflections at the wires, has been built and tested in a wave tank. The probe output simulates Bragg scattering of electromagnetic waves from a water surface with waves; it can be used to simulate electromagnetic probing of the sea surface by radar. Our study establishes that the wave probe, called the “Harp” for short, will simulate Bragg scattering, and that it can also be used to study nonlinear wave processes.
Abstract
A wave sensor, consisting of parallel, evenly spaced capacitance wires, whose output is the sum of the water surface deflections at the wires, has been built and tested in a wave tank. The probe output simulates Bragg scattering of electromagnetic waves from a water surface with waves; it can be used to simulate electromagnetic probing of the sea surface by radar. Our study establishes that the wave probe, called the “Harp” for short, will simulate Bragg scattering, and that it can also be used to study nonlinear wave processes.
Abstract
Altimeter data obtained from GEOS-3 during the three year period 1975–78 for a region of the western North Atlantic which includes a portion of the Gulf Stream system and part of the open ocean area of the subtropical gyre are analyzed by a new technique which utilizes all the points along the satellite tracks. The physical phenomenon studied are the time-variable but almost geostrophic currents, or mesoscale eddies, so that geoid errors contaminate the scientific signal minimally and the dynamical interpretation is direct. Results presented include the spatial distribution of geostrophic eddy kinetic energy and examples of a synoptic map of the eddy field (April 1977) and of a time series at a point. These results are compared to and synthesized with a diverse and selected set of existing measurements and observations obtained in situ by a variety of instrumental techniques. The agreement is generally good, and the altimeter data analyzed provides new information on features in the map of mean eddy kinetic energy. The implications are that satellite altimetry will serve as a powerful quantitative tool in eddy current research and that even presently archived data contains further useful scientific information.
Abstract
Altimeter data obtained from GEOS-3 during the three year period 1975–78 for a region of the western North Atlantic which includes a portion of the Gulf Stream system and part of the open ocean area of the subtropical gyre are analyzed by a new technique which utilizes all the points along the satellite tracks. The physical phenomenon studied are the time-variable but almost geostrophic currents, or mesoscale eddies, so that geoid errors contaminate the scientific signal minimally and the dynamical interpretation is direct. Results presented include the spatial distribution of geostrophic eddy kinetic energy and examples of a synoptic map of the eddy field (April 1977) and of a time series at a point. These results are compared to and synthesized with a diverse and selected set of existing measurements and observations obtained in situ by a variety of instrumental techniques. The agreement is generally good, and the altimeter data analyzed provides new information on features in the map of mean eddy kinetic energy. The implications are that satellite altimetry will serve as a powerful quantitative tool in eddy current research and that even presently archived data contains further useful scientific information.
This paper gives a general overview of two ocean wave experiments. The experimental goals of the Surface Wave Processes Program (SWAPP) and of the Surface Wave Dynamics Experiment (SWADE) are quite different but complementary. In general terms, SWAPP is focused on local processes: principally wave breaking, upper mixed layer dynamics, and microwave and acoustic signatures of wave breaking. SWADE, on the other hand, is concerned primarily with the evolution of the directional wave spectrum in both time and space, improved understanding of wind forcing and wave dissipation, the effect of waves on the air-sea coupling mechanisms, and the radar response of the surface. Both programs acknowledge that wave dissipation is the weakest link in our understanding of wave evolution on the ocean. SWAPP takes a closer look at wave dissipation processes directly, while SWADE, with the use of fully non-linear (third generation) wave models and carefully measured wind forcing, provides an opportunity to study the effect of dissipation on spectral evolution. Both programs involve many research platforms festooned with instruments and large teams of scientists and engineers gathering and analyzing huge datasets. The success of SWAPP and SWADE will be measured in the degree to which the results can be integrated into a far more complete picture than we have had heretofore of interfacial physics, wave evolution, and mixed layer dynamics.
This paper gives a general overview of two ocean wave experiments. The experimental goals of the Surface Wave Processes Program (SWAPP) and of the Surface Wave Dynamics Experiment (SWADE) are quite different but complementary. In general terms, SWAPP is focused on local processes: principally wave breaking, upper mixed layer dynamics, and microwave and acoustic signatures of wave breaking. SWADE, on the other hand, is concerned primarily with the evolution of the directional wave spectrum in both time and space, improved understanding of wind forcing and wave dissipation, the effect of waves on the air-sea coupling mechanisms, and the radar response of the surface. Both programs acknowledge that wave dissipation is the weakest link in our understanding of wave evolution on the ocean. SWAPP takes a closer look at wave dissipation processes directly, while SWADE, with the use of fully non-linear (third generation) wave models and carefully measured wind forcing, provides an opportunity to study the effect of dissipation on spectral evolution. Both programs involve many research platforms festooned with instruments and large teams of scientists and engineers gathering and analyzing huge datasets. The success of SWAPP and SWADE will be measured in the degree to which the results can be integrated into a far more complete picture than we have had heretofore of interfacial physics, wave evolution, and mixed layer dynamics.
Abstract
Dry conditions in 2013–16 in much of the western United States were responsible for severe drought and led to an exceptional fire season in the Pacific Northwest in 2015. Winter 2015/16 was forecasted to relieve drought in the southern portion of the region as a result of increased precipitation due to a very strong El Niño signal. A student forecasting challenge is summarized in which forecasts of winter hydroclimate across the western United States were made on 1 January 2016 for the winter hydroclimate using several dynamical and statistical forecast methods. They show that the precipitation forecasts had a large spread and none were skillful, while anomalously high observed temperatures were forecasted with a higher skill and precision. The poor forecast performance, particularly for precipitation, is traceable to high uncertainty in the North American Multi-Model Ensemble (NMME) forecast, which appears to be related to the inability of the models to predict an atmospheric blocking pattern over the region. It is found that strong El Niño sensitivities in dynamical models resulted in an overprediction of precipitation in the southern part of the domain. The results suggest the need for a more detailed attribution study of the anomalous meteorological patterns of the 2015/16 El Niño event compared to previous major events.
Abstract
Dry conditions in 2013–16 in much of the western United States were responsible for severe drought and led to an exceptional fire season in the Pacific Northwest in 2015. Winter 2015/16 was forecasted to relieve drought in the southern portion of the region as a result of increased precipitation due to a very strong El Niño signal. A student forecasting challenge is summarized in which forecasts of winter hydroclimate across the western United States were made on 1 January 2016 for the winter hydroclimate using several dynamical and statistical forecast methods. They show that the precipitation forecasts had a large spread and none were skillful, while anomalously high observed temperatures were forecasted with a higher skill and precision. The poor forecast performance, particularly for precipitation, is traceable to high uncertainty in the North American Multi-Model Ensemble (NMME) forecast, which appears to be related to the inability of the models to predict an atmospheric blocking pattern over the region. It is found that strong El Niño sensitivities in dynamical models resulted in an overprediction of precipitation in the southern part of the domain. The results suggest the need for a more detailed attribution study of the anomalous meteorological patterns of the 2015/16 El Niño event compared to previous major events.
Abstract
This analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s–1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s–2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.
Abstract
This analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s–1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s–2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.
Abstract
Promising new opportunities to apply artificial intelligence (AI) to the Earth and environmental sciences are identified, informed by an overview of current efforts in the community. Community input was collected at the first National Oceanic and Atmospheric Administration (NOAA) workshop on “Leveraging AI in the Exploitation of Satellite Earth Observations and Numerical Weather Prediction” held in April 2019. This workshop brought together over 400 scientists, program managers, and leaders from the public, academic, and private sectors in order to enable experts involved in the development and adaptation of AI tools and applications to meet and exchange experiences with NOAA experts. Paths are described to actualize the potential of AI to better exploit the massive volumes of environmental data from satellite and in situ sources that are critical for numerical weather prediction (NWP) and other Earth and environmental science applications. The main lessons communicated from community input via active workshop discussions and polling are reported. Finally, recommendations are presented for both scientists and decision-makers to address some of the challenges facing the adoption of AI across all Earth science.
Abstract
Promising new opportunities to apply artificial intelligence (AI) to the Earth and environmental sciences are identified, informed by an overview of current efforts in the community. Community input was collected at the first National Oceanic and Atmospheric Administration (NOAA) workshop on “Leveraging AI in the Exploitation of Satellite Earth Observations and Numerical Weather Prediction” held in April 2019. This workshop brought together over 400 scientists, program managers, and leaders from the public, academic, and private sectors in order to enable experts involved in the development and adaptation of AI tools and applications to meet and exchange experiences with NOAA experts. Paths are described to actualize the potential of AI to better exploit the massive volumes of environmental data from satellite and in situ sources that are critical for numerical weather prediction (NWP) and other Earth and environmental science applications. The main lessons communicated from community input via active workshop discussions and polling are reported. Finally, recommendations are presented for both scientists and decision-makers to address some of the challenges facing the adoption of AI across all Earth science.
