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Abstract
The GFDL hurricane modeling system, initiated in the 1970s, has progressed from a research tool to an operational system over four decades. This system is still in use today in research and operations, and its evolution will be briefly described. This study used an idealized version of the 2014 GFDL model to test its sensitivity across a wide range of three environmental factors that are often identified as key factors in tropical cyclone (TC) evolution: SST, atmospheric stability (upper-air thermal anomalies), and vertical wind shear (westerly through easterly). A wide range of minimum central pressure intensities resulted (905–980 hPa). The results confirm that a scenario (e.g., global warming) in which the upper troposphere warms relative to the surface will have less TC intensification than one with a uniform warming with height. The TC rainfall is also investigated for the SST–stability parameter space. Rainfall increases for combinations of SST increase and increasing stability similar to global warming scenarios, consistent with climate change TC downscaling studies with the GFDL model. The forecast system’s sensitivity to vertical shear was also investigated. The idealized model simulations showed weak disturbances dissipating under strong easterly and westerly shear of 10 m s−1. A small bias for greater intensity under easterly sheared versus westerly sheared environments was found at lower values of SST. The impact of vertical shear on intensity was different when a strong vortex was used in the simulations. In this case, none of the initial disturbances weakened, and most intensified to some extent.
Abstract
The GFDL hurricane modeling system, initiated in the 1970s, has progressed from a research tool to an operational system over four decades. This system is still in use today in research and operations, and its evolution will be briefly described. This study used an idealized version of the 2014 GFDL model to test its sensitivity across a wide range of three environmental factors that are often identified as key factors in tropical cyclone (TC) evolution: SST, atmospheric stability (upper-air thermal anomalies), and vertical wind shear (westerly through easterly). A wide range of minimum central pressure intensities resulted (905–980 hPa). The results confirm that a scenario (e.g., global warming) in which the upper troposphere warms relative to the surface will have less TC intensification than one with a uniform warming with height. The TC rainfall is also investigated for the SST–stability parameter space. Rainfall increases for combinations of SST increase and increasing stability similar to global warming scenarios, consistent with climate change TC downscaling studies with the GFDL model. The forecast system’s sensitivity to vertical shear was also investigated. The idealized model simulations showed weak disturbances dissipating under strong easterly and westerly shear of 10 m s−1. A small bias for greater intensity under easterly sheared versus westerly sheared environments was found at lower values of SST. The impact of vertical shear on intensity was different when a strong vortex was used in the simulations. In this case, none of the initial disturbances weakened, and most intensified to some extent.
Abstract
The hurricane project at the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL) was established in 1970. By the mid-1970s pioneering research had led to the development of a new hurricane model. As the reputation of the model grew, GFDL was approached in 1986 by the director of the National Meteorological Center about establishing a collaboration between the two federal organizations to transition the model into an operational modeling system. After a multiyear effort by GFDL scientists to develop a system that could support rigorous requirements of operations, and multiyear testing had demonstrated its superior performance compared to existing guidance products, operational implementation was made in 1995. Through collaboration between GFDL and the U.S. Navy, the model was also made operational at Fleet Numerical Meteorology and Oceanography Center in 1996. GFDL scientists continued to support and improve the model during the next two decades by collaborating with other scientists at GFDL, the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), 1 the National Hurricane Center, the U.S. Navy, the University of Rhode Island (URI), Old Dominion University, and the NOAA Hurricane Research Division. Scientists at GFDL, URI, and EMC collaborated to transfer key components of the GFDL model to the NWS new Hurricane Weather Research and Forecasting Model (HWRF) that became operational in 2007. The purpose of the article is to highlight the critical role of these collaborations. It is hoped that the experiences of the authors will serve as an example of how such collaboration can benefit the nation with improved weather guidance products.
Abstract
The hurricane project at the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory (GFDL) was established in 1970. By the mid-1970s pioneering research had led to the development of a new hurricane model. As the reputation of the model grew, GFDL was approached in 1986 by the director of the National Meteorological Center about establishing a collaboration between the two federal organizations to transition the model into an operational modeling system. After a multiyear effort by GFDL scientists to develop a system that could support rigorous requirements of operations, and multiyear testing had demonstrated its superior performance compared to existing guidance products, operational implementation was made in 1995. Through collaboration between GFDL and the U.S. Navy, the model was also made operational at Fleet Numerical Meteorology and Oceanography Center in 1996. GFDL scientists continued to support and improve the model during the next two decades by collaborating with other scientists at GFDL, the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), 1 the National Hurricane Center, the U.S. Navy, the University of Rhode Island (URI), Old Dominion University, and the NOAA Hurricane Research Division. Scientists at GFDL, URI, and EMC collaborated to transfer key components of the GFDL model to the NWS new Hurricane Weather Research and Forecasting Model (HWRF) that became operational in 2007. The purpose of the article is to highlight the critical role of these collaborations. It is hoped that the experiences of the authors will serve as an example of how such collaboration can benefit the nation with improved weather guidance products.
Abstract
The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean–wave (Modular Ocean Model 6–WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2–3 × 10−3 for wind speeds of 25–55 m s−1. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 45°, a feature that is underestimated by current models of sea state–dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state–dependent parameterizations of the drag coefficient in tropical cyclone conditions.
Abstract
The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean–wave (Modular Ocean Model 6–WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2–3 × 10−3 for wind speeds of 25–55 m s−1. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 45°, a feature that is underestimated by current models of sea state–dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state–dependent parameterizations of the drag coefficient in tropical cyclone conditions.
Abstract
Based on a large-eddy simulation approach, this study investigates the response of the ocean surface boundary layer (OSBL) and Langmuir turbulence (LT) to extreme wind and complex wave forcing under tropical cyclones (TCs). The Stokes drift vector that drives LT is determined from spectral wave simulations. During maximum TC winds, LT substantially enhances the entrainment of cool water, causing rapid OSBL deepening. This coincides with relatively strong wave forcing, weak inertial currents, and shallow OSBL depth 
Abstract
Based on a large-eddy simulation approach, this study investigates the response of the ocean surface boundary layer (OSBL) and Langmuir turbulence (LT) to extreme wind and complex wave forcing under tropical cyclones (TCs). The Stokes drift vector that drives LT is determined from spectral wave simulations. During maximum TC winds, LT substantially enhances the entrainment of cool water, causing rapid OSBL deepening. This coincides with relatively strong wave forcing, weak inertial currents, and shallow OSBL depth
Abstract
This paper describes a forecasting configuration of the Geophysical Fluid Dynamics Laboratory (GFDL) High-resolution Atmospheric Model (HiRAM). HiRAM represents an early attempt in unifying, within a global modeling framework, the capabilities of GFDL’s low-resolution climate models for Intergovernmental Panel on Climate Change (IPCC) type climate change assessments and high-resolution limited-area models for hurricane predictions. In this study, the potential of HiRAM as a forecasting tool is investigated by applying the model to the near-term and intraseasonal hindcasting of tropical cyclones (TCs) in the Atlantic basin from 2006 to 2009. Results demonstrate that HiRAM provides skillful near-term forecasts of TC track and intensity relative to their respective benchmarks from t = 48 h through t = 144 h. At the intraseasonal time scale, a simple HiRAM ensemble provides skillful forecasts of 21-day Atlantic basin TC activity at a 2-day lead time. It should be noted that the methodology used to produce these hindcasts is applicable in a real-time forecasting scenario. While the initial experimental results appear promising, the HiRAM forecasting system requires various improvements in order to be useful in an operational setting. These modifications are currently under development and include a data assimilation system for forecast initialization, increased horizontal resolution to better resolve the vortex structure, 3D ocean model coupling, and wave model coupling. An overview of these ongoing developments is provided, and the specifics of each will be described in subsequent papers.
Abstract
This paper describes a forecasting configuration of the Geophysical Fluid Dynamics Laboratory (GFDL) High-resolution Atmospheric Model (HiRAM). HiRAM represents an early attempt in unifying, within a global modeling framework, the capabilities of GFDL’s low-resolution climate models for Intergovernmental Panel on Climate Change (IPCC) type climate change assessments and high-resolution limited-area models for hurricane predictions. In this study, the potential of HiRAM as a forecasting tool is investigated by applying the model to the near-term and intraseasonal hindcasting of tropical cyclones (TCs) in the Atlantic basin from 2006 to 2009. Results demonstrate that HiRAM provides skillful near-term forecasts of TC track and intensity relative to their respective benchmarks from t = 48 h through t = 144 h. At the intraseasonal time scale, a simple HiRAM ensemble provides skillful forecasts of 21-day Atlantic basin TC activity at a 2-day lead time. It should be noted that the methodology used to produce these hindcasts is applicable in a real-time forecasting scenario. While the initial experimental results appear promising, the HiRAM forecasting system requires various improvements in order to be useful in an operational setting. These modifications are currently under development and include a data assimilation system for forecast initialization, increased horizontal resolution to better resolve the vortex structure, 3D ocean model coupling, and wave model coupling. An overview of these ongoing developments is provided, and the specifics of each will be described in subsequent papers.
Abstract
The performance of the wave model WAVEWATCH III under a very strong, category 5, tropical cyclone wind forcing is investigated with different drag coefficient parameterizations and ocean current inputs. The model results are compared with field observations of the surface wave spectra from an airborne scanning radar altimeter, National Data Buoy Center (NDBC) time series, and satellite altimeter measurements in Hurricane Ivan (2004). The results suggest that the model with the original drag coefficient parameterization tends to overestimate the significant wave height and the dominant wavelength and produces a wave spectrum with narrower directional spreading. When an improved drag parameterization is introduced and the wave–current interaction is included, the model yields an improved forecast of significant wave height, but underestimates the dominant wavelength. When the hurricane moves over a preexisting mesoscale ocean feature, such as the Loop Current in the Gulf of Mexico or a warm- and cold-core ring, the current associated with the feature can accelerate or decelerate the wave propagation and significantly modulate the wave spectrum.
Abstract
The performance of the wave model WAVEWATCH III under a very strong, category 5, tropical cyclone wind forcing is investigated with different drag coefficient parameterizations and ocean current inputs. The model results are compared with field observations of the surface wave spectra from an airborne scanning radar altimeter, National Data Buoy Center (NDBC) time series, and satellite altimeter measurements in Hurricane Ivan (2004). The results suggest that the model with the original drag coefficient parameterization tends to overestimate the significant wave height and the dominant wavelength and produces a wave spectrum with narrower directional spreading. When an improved drag parameterization is introduced and the wave–current interaction is included, the model yields an improved forecast of significant wave height, but underestimates the dominant wavelength. When the hurricane moves over a preexisting mesoscale ocean feature, such as the Loop Current in the Gulf of Mexico or a warm- and cold-core ring, the current associated with the feature can accelerate or decelerate the wave propagation and significantly modulate the wave spectrum.
Abstract
Tropical cyclones are fueled by the air–sea heat flux, which is reduced when the ocean surface cools due to mixed layer deepening and upwelling. Wave-driven Langmuir turbulence can significantly modify these processes. This study investigates the impact of sea-state-dependent Langmuir turbulence on the three-dimensional ocean response to a tropical cyclone in coupled wave–ocean simulations. The Stokes drift is computed from the simulated wave spectrum using the WAVEWATCH III wave model and passed to the three-dimensional Princeton Ocean Model. The Langmuir turbulence impact is included in the vertical mixing of the ocean model by adding the Stokes drift to the shear of the vertical mean current and by including Langmuir turbulence enhancements to the K-profile parameterization (KPP) scheme. Results are assessed by comparing simulations with explicit (sea-state dependent) and implicit (independent of sea state) Langmuir turbulence parameterizations, as well as with turbulence driven by shear alone. The results demonstrate that the sea-state-dependent Langmuir turbulence parameterization significantly modifies the three-dimensional ocean response to a tropical cyclone. This is due to the reduction of upwelling and horizontal advection where the near-surface currents are reduced by Langmuir turbulence. The implicit scheme not only misses the impact of sea-state dependence on the surface cooling, but it also misrepresents the impact of the Langmuir turbulence on the Eulerian advection. This suggests that explicitly resolving the sea-state-dependent Langmuir turbulence will lead to increased accuracy in predicting the ocean response in coupled tropical cyclone–ocean models.
Abstract
Tropical cyclones are fueled by the air–sea heat flux, which is reduced when the ocean surface cools due to mixed layer deepening and upwelling. Wave-driven Langmuir turbulence can significantly modify these processes. This study investigates the impact of sea-state-dependent Langmuir turbulence on the three-dimensional ocean response to a tropical cyclone in coupled wave–ocean simulations. The Stokes drift is computed from the simulated wave spectrum using the WAVEWATCH III wave model and passed to the three-dimensional Princeton Ocean Model. The Langmuir turbulence impact is included in the vertical mixing of the ocean model by adding the Stokes drift to the shear of the vertical mean current and by including Langmuir turbulence enhancements to the K-profile parameterization (KPP) scheme. Results are assessed by comparing simulations with explicit (sea-state dependent) and implicit (independent of sea state) Langmuir turbulence parameterizations, as well as with turbulence driven by shear alone. The results demonstrate that the sea-state-dependent Langmuir turbulence parameterization significantly modifies the three-dimensional ocean response to a tropical cyclone. This is due to the reduction of upwelling and horizontal advection where the near-surface currents are reduced by Langmuir turbulence. The implicit scheme not only misses the impact of sea-state dependence on the surface cooling, but it also misrepresents the impact of the Langmuir turbulence on the Eulerian advection. This suggests that explicitly resolving the sea-state-dependent Langmuir turbulence will lead to increased accuracy in predicting the ocean response in coupled tropical cyclone–ocean models.
Improving the forecasts of the intensity of tropical cyclones (TCs) remains a major challenge. One possibility for improvement is consideration of the effects that aerosols have on tropical clouds and cyclones. The authors have been pursuing this under the Hurricane Aerosol and Microphysics Program, supported by the U.S. Department of Homeland Security. This was done through observations of aerosols and resulting cloud microphysical structure within tropical cyclones and simulating their effects using high-resolution TC models that treat cloud internal processes explicitly. In addition to atmospheric aerosols, special attention was given also to the impact of the intense sea-spray-generated aerosols and convective rolls in the hurricane boundary layer (BL) under hurricane- force winds.
The results of simulations and observations show that TC ingestion of aerosols that serve as cloud condensation nuclei can lead to significant reductions in their intensities. This is caused by redistribution of the precipitation and latent heating to more vigorous convection in the storm periphery that cools the low levels and interferes with the inflow of energy to the eyewall, hence making the eye larger and the maximum winds weaker. The microphysical effects of the pollution and dust aerosols occur mainly at the peripheral clouds. Closer to the circulation center, the hurricane-force winds raise intense sea spray that is lifted efficiently in the roll vortices that form in the BL and coalesce into rain of mostly seawater already at cloud base, which dominates the microstructure and affects the dynamics of the inner convective cloud bands.
Improving the forecasts of the intensity of tropical cyclones (TCs) remains a major challenge. One possibility for improvement is consideration of the effects that aerosols have on tropical clouds and cyclones. The authors have been pursuing this under the Hurricane Aerosol and Microphysics Program, supported by the U.S. Department of Homeland Security. This was done through observations of aerosols and resulting cloud microphysical structure within tropical cyclones and simulating their effects using high-resolution TC models that treat cloud internal processes explicitly. In addition to atmospheric aerosols, special attention was given also to the impact of the intense sea-spray-generated aerosols and convective rolls in the hurricane boundary layer (BL) under hurricane- force winds.
The results of simulations and observations show that TC ingestion of aerosols that serve as cloud condensation nuclei can lead to significant reductions in their intensities. This is caused by redistribution of the precipitation and latent heating to more vigorous convection in the storm periphery that cools the low levels and interferes with the inflow of energy to the eyewall, hence making the eye larger and the maximum winds weaker. The microphysical effects of the pollution and dust aerosols occur mainly at the peripheral clouds. Closer to the circulation center, the hurricane-force winds raise intense sea spray that is lifted efficiently in the roll vortices that form in the BL and coalesce into rain of mostly seawater already at cloud base, which dominates the microstructure and affects the dynamics of the inner convective cloud bands.
Abstract
Numerical simulation of sea surface directional wave spectra under hurricane wind forcing was carried out using a high-resolution wave model. The simulation was run for four days as Hurricane Bonnie (1998) approached the U.S. East Coast. The results are compared with buoy observations and NASA Scanning Radar Altimeter (SRA) data, which were obtained on 24 August 1998 in the open ocean and on 26 August when the storm was approaching the shore. The simulated significant wave height in the open ocean reached 14 m, agreeing well with the SRA and buoy observations. It gradually decreased as the hurricane approached the shore. In the open ocean, the dominant wavelength and wave direction in all four quadrants relative to the storm center were simulated very accurately. For the landfall case, however, the simulated dominant wavelength displays noticeable overestimation because the wave model cannot properly simulate shoaling processes. Direct comparison of the model and SRA directional spectra in all four quadrants of the hurricane shows excellent agreement in general. In some cases, the model produces smoother spectra with narrower directional spreading than do the observations. The spatial characteristics of the spectra depend on the relative position from the hurricane center, the hurricane translation speed, and bathymetry. Attempts are made to provide simple explanations for the misalignment between local wind and wave directions and for the effect of hurricane translation speed on wave spectra.
Abstract
Numerical simulation of sea surface directional wave spectra under hurricane wind forcing was carried out using a high-resolution wave model. The simulation was run for four days as Hurricane Bonnie (1998) approached the U.S. East Coast. The results are compared with buoy observations and NASA Scanning Radar Altimeter (SRA) data, which were obtained on 24 August 1998 in the open ocean and on 26 August when the storm was approaching the shore. The simulated significant wave height in the open ocean reached 14 m, agreeing well with the SRA and buoy observations. It gradually decreased as the hurricane approached the shore. In the open ocean, the dominant wavelength and wave direction in all four quadrants relative to the storm center were simulated very accurately. For the landfall case, however, the simulated dominant wavelength displays noticeable overestimation because the wave model cannot properly simulate shoaling processes. Direct comparison of the model and SRA directional spectra in all four quadrants of the hurricane shows excellent agreement in general. In some cases, the model produces smoother spectra with narrower directional spreading than do the observations. The spatial characteristics of the spectra depend on the relative position from the hurricane center, the hurricane translation speed, and bathymetry. Attempts are made to provide simple explanations for the misalignment between local wind and wave directions and for the effect of hurricane translation speed on wave spectra.
Abstract
Numerical simulation of sea surface directional wave spectra under hurricane wind forcing was carried out using a high-resolution wave model. The simulation was run for four days as Hurricane Bonnie (1998) approached the U.S. East Coast. The results are compared with buoy observations and NASA Scanning Radar Altimeter (SRA) data, which were obtained on 24 August 1998 in the open ocean and on 26 August when the storm was approaching the shore. The simulated significant wave height in the open ocean reached 14 m, agreeing well with the SRA and buoy observations. It gradually decreased as the hurricane approached the shore. In the open ocean, the dominant wavelength and wave direction in all four quadrants relative to the storm center were simulated very accurately. For the landfall case, however, the simulated dominant wavelength displays noticeable overestimation because the wave model cannot properly simulate shoaling processes. Direct comparison of the model and SRA directional spectra in all four quadrants of the hurricane shows excellent agreement in general. In some cases, the model produces smoother spectra with narrower directional spreading than do the observations. The spatial characteristics of the spectra depend on the relative position from the hurricane center, the hurricane translation speed, and bathymetry. Attempts are made to provide simple explanations for the misalignment between local wind and wave directions and for the effect of hurricane translation speed on wave spectra.
Abstract
Numerical simulation of sea surface directional wave spectra under hurricane wind forcing was carried out using a high-resolution wave model. The simulation was run for four days as Hurricane Bonnie (1998) approached the U.S. East Coast. The results are compared with buoy observations and NASA Scanning Radar Altimeter (SRA) data, which were obtained on 24 August 1998 in the open ocean and on 26 August when the storm was approaching the shore. The simulated significant wave height in the open ocean reached 14 m, agreeing well with the SRA and buoy observations. It gradually decreased as the hurricane approached the shore. In the open ocean, the dominant wavelength and wave direction in all four quadrants relative to the storm center were simulated very accurately. For the landfall case, however, the simulated dominant wavelength displays noticeable overestimation because the wave model cannot properly simulate shoaling processes. Direct comparison of the model and SRA directional spectra in all four quadrants of the hurricane shows excellent agreement in general. In some cases, the model produces smoother spectra with narrower directional spreading than do the observations. The spatial characteristics of the spectra depend on the relative position from the hurricane center, the hurricane translation speed, and bathymetry. Attempts are made to provide simple explanations for the misalignment between local wind and wave directions and for the effect of hurricane translation speed on wave spectra.
