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Abstract
Numerical simulations with a primitive equation model which includes parameterized physics are conducted to study the effects of an island mountain range on translating tropical cyclones. The idealized topography with a 200 m peak is introduced over a 12 h growth period. The initial state contains a nonlinearly balanced vortex embedded in a uniform, unsheared, tropical easterly flow.
Many orographic effects are produced similar to those observed for typhoons passing over mountain ranges. The storm tends to translate at about twice the speed of the basic flow near the mountain, while its intensity is reduced. Air flows mostly around the mountain range instead of over it, forming a ridge on the windside and a trough on the leeside slopes. The tropical cyclone's passage induces a mean cyclonic circulation around the mountain with strongest amplitudes at low levels. As a result, the model tropical cyclone makes a cyclonic curvature in its path around the north end of the island mountain.
Further numerical experiments suggest that cumulus heating which maintains the tropical cyclone forces the cyclonic circulation around the mountain. In the experiment with an unforced, quasi-barotropic vortex we found that the lower level circulation is blocked by the mountain range. As the original low-level center fails to pass the mountain range, a secondary low-level circulation center forms in the induced lee trough. The secondary low-level center develops as the upper level center comes into phase.
A vorticity budget is performed for the 700 mb airflow prior to landfall and confirms the importance of diabatic processes in producing the observed orographic effects. Diabatic processes generate convergence to maintain the vorticity of the tropical cyclone. The horizontal advection of positive vorticity in conjunction with the leeside vortex stretching, results in the mean positive vorticity around the mountain.
Abstract
Numerical simulations with a primitive equation model which includes parameterized physics are conducted to study the effects of an island mountain range on translating tropical cyclones. The idealized topography with a 200 m peak is introduced over a 12 h growth period. The initial state contains a nonlinearly balanced vortex embedded in a uniform, unsheared, tropical easterly flow.
Many orographic effects are produced similar to those observed for typhoons passing over mountain ranges. The storm tends to translate at about twice the speed of the basic flow near the mountain, while its intensity is reduced. Air flows mostly around the mountain range instead of over it, forming a ridge on the windside and a trough on the leeside slopes. The tropical cyclone's passage induces a mean cyclonic circulation around the mountain with strongest amplitudes at low levels. As a result, the model tropical cyclone makes a cyclonic curvature in its path around the north end of the island mountain.
Further numerical experiments suggest that cumulus heating which maintains the tropical cyclone forces the cyclonic circulation around the mountain. In the experiment with an unforced, quasi-barotropic vortex we found that the lower level circulation is blocked by the mountain range. As the original low-level center fails to pass the mountain range, a secondary low-level circulation center forms in the induced lee trough. The secondary low-level center develops as the upper level center comes into phase.
A vorticity budget is performed for the 700 mb airflow prior to landfall and confirms the importance of diabatic processes in producing the observed orographic effects. Diabatic processes generate convergence to maintain the vorticity of the tropical cyclone. The horizontal advection of positive vorticity in conjunction with the leeside vortex stretching, results in the mean positive vorticity around the mountain.
Abstract
A planetary boundary-layer (PBL) parameterization based on the generalized similarity theory (GST) was tested in tropical cyclone models. This parameterization, with only one layer, is desired in modeling tropical cyclones for computational speed. The momentum, sensible heat and moisture fluxes are mutually dependent in this parameterization through nondimensional gradient equations. The internal structure of the PBL is determined implicitly through universal functions.
In comparison with a complex, one-dimensional, multilayer PBL model, the GST parameterization yields accurate moisture fluxes, but slightly overestimates the momentum flux and underestimates the sensible heal flux. The GST parameterization produces very realistic dynamics, energetics and thermal structure in an axisymmetric tropical cyclone model. This GST parameterization, although unable to treat the diffusion across the PBL inversion, is judged superior to drag coefficient parameterization and is a good alternative to the more expensive, multilayer parameterization.
Abstract
A planetary boundary-layer (PBL) parameterization based on the generalized similarity theory (GST) was tested in tropical cyclone models. This parameterization, with only one layer, is desired in modeling tropical cyclones for computational speed. The momentum, sensible heat and moisture fluxes are mutually dependent in this parameterization through nondimensional gradient equations. The internal structure of the PBL is determined implicitly through universal functions.
In comparison with a complex, one-dimensional, multilayer PBL model, the GST parameterization yields accurate moisture fluxes, but slightly overestimates the momentum flux and underestimates the sensible heal flux. The GST parameterization produces very realistic dynamics, energetics and thermal structure in an axisymmetric tropical cyclone model. This GST parameterization, although unable to treat the diffusion across the PBL inversion, is judged superior to drag coefficient parameterization and is a good alternative to the more expensive, multilayer parameterization.
Abstract
The impact of satellite-sensed winds on the intensity forecasts of tropical cyclones is evaluated by a simulation study with an axisymmetric numerical model. The parameterized physics in the forecast model are deliberately made different from those in the model that generates the observation. Model-generated “observations” are assimilated into forecasts by 12 h dynamic initialization.
A series of 24 h forecasts with and without assimilation of satellite-sensed winds are conducted and compared with the observations. Results indicate that assimilation with marine surface (or low-level) wind alone does not improve intensity forecasts appreciably, that a strong relaxation coefficient in the initialization scheme causes model rejection of the assimilation, and that an attenuating relaxation coefficient is recommended. However, when wind observations at the outflow level are included in the assimilation, forecasts improve substantially. The best forecasts are achieved when observations over the entire lower troposphere are assimilated.
Additional experiments indicate the errors in the satellite observations contaminate the forecast. But the assimilation of inflow and outflow winds still improve the intensity forecast if the satellite observation errors are less than or about the same magnitude of those in the initial wind field.
Abstract
The impact of satellite-sensed winds on the intensity forecasts of tropical cyclones is evaluated by a simulation study with an axisymmetric numerical model. The parameterized physics in the forecast model are deliberately made different from those in the model that generates the observation. Model-generated “observations” are assimilated into forecasts by 12 h dynamic initialization.
A series of 24 h forecasts with and without assimilation of satellite-sensed winds are conducted and compared with the observations. Results indicate that assimilation with marine surface (or low-level) wind alone does not improve intensity forecasts appreciably, that a strong relaxation coefficient in the initialization scheme causes model rejection of the assimilation, and that an attenuating relaxation coefficient is recommended. However, when wind observations at the outflow level are included in the assimilation, forecasts improve substantially. The best forecasts are achieved when observations over the entire lower troposphere are assimilated.
Additional experiments indicate the errors in the satellite observations contaminate the forecast. But the assimilation of inflow and outflow winds still improve the intensity forecast if the satellite observation errors are less than or about the same magnitude of those in the initial wind field.
Abstract
An axisymmetric, multilayer, numerical tropical cyclone model with a well-resolved planetary boundary layer is used to test the response of local, instantaneous changes of sea surface temperature (SST). One experiment shows that the storm's intensity is steadily decreased as the SST in the inner 300 km is instantaneously cooled by 2°C. However, in the second experiment, in which the SST is cooled by 2°C outside the radius of 300 km, the storm shows no immediate and appreciable weakening. The intensity of the tropical cyclone in this case is maintained by enhanced evaporation in the inner 300 km and increased baroclinicity.
Abstract
An axisymmetric, multilayer, numerical tropical cyclone model with a well-resolved planetary boundary layer is used to test the response of local, instantaneous changes of sea surface temperature (SST). One experiment shows that the storm's intensity is steadily decreased as the SST in the inner 300 km is instantaneously cooled by 2°C. However, in the second experiment, in which the SST is cooled by 2°C outside the radius of 300 km, the storm shows no immediate and appreciable weakening. The intensity of the tropical cyclone in this case is maintained by enhanced evaporation in the inner 300 km and increased baroclinicity.
Abstract
The interactions between atmospheric vortex pairs are simulated and studied with a nondivergent barotropic model and a three-dimensional tropical cyclone model.
Numerical experiments with nondivergent barotropic vortex pairs show that the relative movements of the vortices are sensitive to the separation distance and the characteristics of the swirling wind of the vortex. No mutual attraction is found in any of the nondivergent barotropic vortex pairs tested.
Results from the three-dimensional tropical cyclone model show that on a constant ƒ-plane with no mean wind, the movements of the two interacting tropical cyclones consist of a mutual cyclonic rotation, attraction and eventual merging, in agreement with Fujiwhara's description. The displacement of one interacting storm in the mutual rotation is proportional to the combined strength of the binary system, but inversely proportional to the size of the storm and to the square of the separation distance. The rate of merging is related to the development of a mean secondary circulation on the radial–vertical plane, and is quite independent of the strength of the two tropical cyclones.
The latitudinal variation of the Coriolis parameter adds a northwest beta drift to the trajectories. Depending on their relative strength and location, the beta drift either speeds up the merging process or separates the two interacting tropical cyclones.
Abstract
The interactions between atmospheric vortex pairs are simulated and studied with a nondivergent barotropic model and a three-dimensional tropical cyclone model.
Numerical experiments with nondivergent barotropic vortex pairs show that the relative movements of the vortices are sensitive to the separation distance and the characteristics of the swirling wind of the vortex. No mutual attraction is found in any of the nondivergent barotropic vortex pairs tested.
Results from the three-dimensional tropical cyclone model show that on a constant ƒ-plane with no mean wind, the movements of the two interacting tropical cyclones consist of a mutual cyclonic rotation, attraction and eventual merging, in agreement with Fujiwhara's description. The displacement of one interacting storm in the mutual rotation is proportional to the combined strength of the binary system, but inversely proportional to the size of the storm and to the square of the separation distance. The rate of merging is related to the development of a mean secondary circulation on the radial–vertical plane, and is quite independent of the strength of the two tropical cyclones.
The latitudinal variation of the Coriolis parameter adds a northwest beta drift to the trajectories. Depending on their relative strength and location, the beta drift either speeds up the merging process or separates the two interacting tropical cyclones.
Abstract
Numerical experiments were conducted to assess the impact of Omega dropwindsonde (ODW) data and Special Sensor Microwave/Imager (SSM/I) rain rates in the analysis and prediction of Hurricane Florence (1988). The ODW data were used to enhance the initial analysis that was based on the National Meteorological Center/Regional Analysis and Forecast System (NMC/RAFS) 2.5° analysis at 0000 UTC 9 September 1988. The SSM/I rain rates at 0000 and 1200 UTC 9 September 1988 were assimilated into the Naval Research Laboratory's limited-area model during model integration.
Results show that the numerical prediction with the ODW-enhanced initial analysis was superior to the control without ODW data. The 24-h intensity forecast error is reduced by about 75%, landfall location by about 95% (reduced from 294 to 15 km), and landfall time by about 5 h (from 9 to 4 h) when the ODW data were included. Results also reveal that the assimilation of SSM/I-retrieved rain rates reduce the critical landfall location forecast error by about 43% (from 294 to 169 km) and the landfall time forecast error by about 7 h (from 9 to 2 h) when the NMC/RAFS 2.5° initial analysis was not enhanced by the ODW data. The assimilation of SSM/I rain rates further improved the forecast error of the landfall time by 4 h (from 4 to 0 h) when the ODW data were used. This study concludes that numerical predictions of tropical cyclone can benefit from assimilations of ODW data and SSM/I-retrieved rain rates.
Abstract
Numerical experiments were conducted to assess the impact of Omega dropwindsonde (ODW) data and Special Sensor Microwave/Imager (SSM/I) rain rates in the analysis and prediction of Hurricane Florence (1988). The ODW data were used to enhance the initial analysis that was based on the National Meteorological Center/Regional Analysis and Forecast System (NMC/RAFS) 2.5° analysis at 0000 UTC 9 September 1988. The SSM/I rain rates at 0000 and 1200 UTC 9 September 1988 were assimilated into the Naval Research Laboratory's limited-area model during model integration.
Results show that the numerical prediction with the ODW-enhanced initial analysis was superior to the control without ODW data. The 24-h intensity forecast error is reduced by about 75%, landfall location by about 95% (reduced from 294 to 15 km), and landfall time by about 5 h (from 9 to 4 h) when the ODW data were included. Results also reveal that the assimilation of SSM/I-retrieved rain rates reduce the critical landfall location forecast error by about 43% (from 294 to 169 km) and the landfall time forecast error by about 7 h (from 9 to 2 h) when the NMC/RAFS 2.5° initial analysis was not enhanced by the ODW data. The assimilation of SSM/I rain rates further improved the forecast error of the landfall time by 4 h (from 4 to 0 h) when the ODW data were used. This study concludes that numerical predictions of tropical cyclone can benefit from assimilations of ODW data and SSM/I-retrieved rain rates.
Abstract
Special Sensor Microwave/Imager (SSM/I) retrieved rainfall rates were assimilated into a limited-area numerical prediction model in an attempt to improve the initial analysis and forecast of a tropical cyclone. Typhoon Flo of 1990, which was observed in an intensive observation period of the Tropical Cyclone Motion Experiment-1990, was chosen for this study. The SSM/I retrieved rainfall rates within 888 km (8° latitude) of the storm center were incorporated into the initial fields by a reversed Kuo cumulus parameterization. In the procedure used here, the moisture field in the model is adjusted so that the model generates the SSM/I-observed rainfall rates. This scheme is applied through two different assimilation methods. The first method is based on a dynamic initialization in which the prediction model is integrated backward adiabatically to t = −6 h and then forward diabatically for 6 h to the initial time. During the diabatic forward integration, the SSM/I rainfall rates are incorporated using the reversed Kuo cumulus parameterization. The second method is a forward data assimilation integration starting from t = −12 h. From t = −6 h to t = 0, the SSM/I rainfall rates are incorporated, also using the reversed Kuo scheme. During this period, the momentum fields are relaxed to the initial (t = 0) analysis to reduce the initial position error generated during the preforecast integration. Five cases for which SSM/I overpasses were available were tested, including two cases before and three after Flo's recurvature. Forecasts at 48 h are compared with the actual storm track and intensifies estimated by the Joint Typhoon Warning Center. For the five cases tested, the assimilation of SSM/I retrieved rainfall rates reduced the average 48-h forecast distance error from 239 km in the control runs to 81 km in the assimilation experiments. It is postulated that the large positive impact was a consequence of the improved forecast intensity and speed of the typhoon when the SSM/I rain-rate data were assimilated.
Abstract
Special Sensor Microwave/Imager (SSM/I) retrieved rainfall rates were assimilated into a limited-area numerical prediction model in an attempt to improve the initial analysis and forecast of a tropical cyclone. Typhoon Flo of 1990, which was observed in an intensive observation period of the Tropical Cyclone Motion Experiment-1990, was chosen for this study. The SSM/I retrieved rainfall rates within 888 km (8° latitude) of the storm center were incorporated into the initial fields by a reversed Kuo cumulus parameterization. In the procedure used here, the moisture field in the model is adjusted so that the model generates the SSM/I-observed rainfall rates. This scheme is applied through two different assimilation methods. The first method is based on a dynamic initialization in which the prediction model is integrated backward adiabatically to t = −6 h and then forward diabatically for 6 h to the initial time. During the diabatic forward integration, the SSM/I rainfall rates are incorporated using the reversed Kuo cumulus parameterization. The second method is a forward data assimilation integration starting from t = −12 h. From t = −6 h to t = 0, the SSM/I rainfall rates are incorporated, also using the reversed Kuo scheme. During this period, the momentum fields are relaxed to the initial (t = 0) analysis to reduce the initial position error generated during the preforecast integration. Five cases for which SSM/I overpasses were available were tested, including two cases before and three after Flo's recurvature. Forecasts at 48 h are compared with the actual storm track and intensifies estimated by the Joint Typhoon Warning Center. For the five cases tested, the assimilation of SSM/I retrieved rainfall rates reduced the average 48-h forecast distance error from 239 km in the control runs to 81 km in the assimilation experiments. It is postulated that the large positive impact was a consequence of the improved forecast intensity and speed of the typhoon when the SSM/I rain-rate data were assimilated.
Abstract
A series of observing system simulation experiments (OSSE) and real data assimilation experiments were conducted to assess the impact of assimilating Special Sensor Microwave/Imager (SSM/I)-estimated rainfall rates on limited-area model predictions of intense winter cyclones.
For the OSSE, the slow-moving, fronto- and cyclogenesis along the cast coast of United States during the second intensive observation period (IOP 2) of the Genesis of Atlantic Lows Experiment (GALE) (26-28 January 1986) was selected as the test case. The perfect “observed” rainfall rates were obtained by an integration of a version of the Naval Research Laboratory (NRL) limited-area model, whereas the “forecast” was generated by a degraded version of the NRL model. A number of OSSEs were conducted in which the “observed” rainfall rates were assimilated into the “forecast” model. Rainfall rates of various data frequencies, different vertical beating profiles, various assimilation windows, and prescribed systematic errors were assimilated to test the sensitivity of the impact. It was found that assimilation of rainfall rates, in general, improves the forecast in terms of sea level pressure S1 scores when either the “observed” or model-determined vertical beating profiles were used. The improvement was insensitive to the error in rainfall magnitude estimates but was sensitive to errors in geographic locations of the precipitation. More frequent observations (additional sensors in orbits) had positive but gradually diminishing benefits.
Real SSM/I-measured rainfall rates were assimilated for the rapid-moving, intense marine cyclone of IOP 4 of the Experiment on Rapidly Intensifying Cyclones over the Atlantic (ERICA) (4–5 January 1989), which started from an initial offshore disturbance with a minimum pressure of 998 mb at 0000 UTC 4 January and developed into a very intense storm of 937 mb 24 h later. The NRL model simulated a well-behaved but less intense cyclogenesis episode based on the RAFS (Regional Analysis and Forecast System) initial analysis, reaching a minimum sea level pressure of 952 mb at 24 h. The first SSM/I aboard a DMSP (Defense Meteorological Satellite Program) satellite flew over the marine cyclone at 0000, 0930, and 2200 UTC 4 January and measured rainfall rates over portions of the warm and cold fronts associated with the cyclone. The SSM/I rainfall rates at 0000 and 0930 UTC were assimilated into the model as latent heating functions in ±3-h windows with model-determined vertical profiles. Two different methods were used to define the latent heating rates for the model in the assimilation experiments: 1) the model heating rates were defined by the maximum of the model computed and the SSM/I measured, and 2) the model beating rates were replaced by the SSM/I-measured rainfall rates within the SSM/I swath. Results of the assimilation experiments indicated that the assimilation in general leads to better intensity forecasts. The best forecast with assimilation predicted a 24-h minimum surface pressure of 943 mb, cutting the forecast error of the “no sat” forecast by 50%. This most efficient assimilation was carried out with assimilations of two-time SSM/I observations using the swath method. Further analysis indicated that the assimilation also resulted in better track and structure forecasts.
Abstract
A series of observing system simulation experiments (OSSE) and real data assimilation experiments were conducted to assess the impact of assimilating Special Sensor Microwave/Imager (SSM/I)-estimated rainfall rates on limited-area model predictions of intense winter cyclones.
For the OSSE, the slow-moving, fronto- and cyclogenesis along the cast coast of United States during the second intensive observation period (IOP 2) of the Genesis of Atlantic Lows Experiment (GALE) (26-28 January 1986) was selected as the test case. The perfect “observed” rainfall rates were obtained by an integration of a version of the Naval Research Laboratory (NRL) limited-area model, whereas the “forecast” was generated by a degraded version of the NRL model. A number of OSSEs were conducted in which the “observed” rainfall rates were assimilated into the “forecast” model. Rainfall rates of various data frequencies, different vertical beating profiles, various assimilation windows, and prescribed systematic errors were assimilated to test the sensitivity of the impact. It was found that assimilation of rainfall rates, in general, improves the forecast in terms of sea level pressure S1 scores when either the “observed” or model-determined vertical beating profiles were used. The improvement was insensitive to the error in rainfall magnitude estimates but was sensitive to errors in geographic locations of the precipitation. More frequent observations (additional sensors in orbits) had positive but gradually diminishing benefits.
Real SSM/I-measured rainfall rates were assimilated for the rapid-moving, intense marine cyclone of IOP 4 of the Experiment on Rapidly Intensifying Cyclones over the Atlantic (ERICA) (4–5 January 1989), which started from an initial offshore disturbance with a minimum pressure of 998 mb at 0000 UTC 4 January and developed into a very intense storm of 937 mb 24 h later. The NRL model simulated a well-behaved but less intense cyclogenesis episode based on the RAFS (Regional Analysis and Forecast System) initial analysis, reaching a minimum sea level pressure of 952 mb at 24 h. The first SSM/I aboard a DMSP (Defense Meteorological Satellite Program) satellite flew over the marine cyclone at 0000, 0930, and 2200 UTC 4 January and measured rainfall rates over portions of the warm and cold fronts associated with the cyclone. The SSM/I rainfall rates at 0000 and 0930 UTC were assimilated into the model as latent heating functions in ±3-h windows with model-determined vertical profiles. Two different methods were used to define the latent heating rates for the model in the assimilation experiments: 1) the model heating rates were defined by the maximum of the model computed and the SSM/I measured, and 2) the model beating rates were replaced by the SSM/I-measured rainfall rates within the SSM/I swath. Results of the assimilation experiments indicated that the assimilation in general leads to better intensity forecasts. The best forecast with assimilation predicted a 24-h minimum surface pressure of 943 mb, cutting the forecast error of the “no sat” forecast by 50%. This most efficient assimilation was carried out with assimilations of two-time SSM/I observations using the swath method. Further analysis indicated that the assimilation also resulted in better track and structure forecasts.
Abstract
The principles of variational analysis are reviewed in a symbolic manner, with emphasis on the error introduced by a failure to use an exact constraint. A technique to approximate a nonlinear exact constraint is suggested, with the object of avoiding error magnification in regions of good data, in the process of analyzing slow mode amplitudes for nonlinear mode initialization. The technique amounts to subtractingall fast modes from the data fields that form the input to the variational analysis. The analysis procedure is then focused on only the analysis of slow mode fields. These general considerations are demonstrated by computations with the vortex model of Tribbia, and show how nonlinear mode techniques can improve initial analyses in a more significant way than the mere elimination of noise. A review of the relative merits and weaknesses of optimum interpolation and variational analysis suggests a logical way to use both techniques in an operational analysis system.
Abstract
The principles of variational analysis are reviewed in a symbolic manner, with emphasis on the error introduced by a failure to use an exact constraint. A technique to approximate a nonlinear exact constraint is suggested, with the object of avoiding error magnification in regions of good data, in the process of analyzing slow mode amplitudes for nonlinear mode initialization. The technique amounts to subtractingall fast modes from the data fields that form the input to the variational analysis. The analysis procedure is then focused on only the analysis of slow mode fields. These general considerations are demonstrated by computations with the vortex model of Tribbia, and show how nonlinear mode techniques can improve initial analyses in a more significant way than the mere elimination of noise. A review of the relative merits and weaknesses of optimum interpolation and variational analysis suggests a logical way to use both techniques in an operational analysis system.
