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Abstract
Though operational tropical cyclone synoptic surveillance generally leads to smaller track forecast errors in the National Oceanic and Atmospheric Administration Global Forecasting System (GFS) than would occur otherwise, not every case is improved. Very large GFS forecast degradations due to surveillance are investigated. Small perturbations to model initial conditions may have a large impact locally or downstream in a short time. In these cases, the perturbations are due either to erroneous data assimilated into the models or to issues with the complex data assimilation system itself, and may have caused the forecast degradations. Investigation of forecast and observing system failures can lead to procedural changes that may eliminate some causes of future large forecast errors.
Abstract
Though operational tropical cyclone synoptic surveillance generally leads to smaller track forecast errors in the National Oceanic and Atmospheric Administration Global Forecasting System (GFS) than would occur otherwise, not every case is improved. Very large GFS forecast degradations due to surveillance are investigated. Small perturbations to model initial conditions may have a large impact locally or downstream in a short time. In these cases, the perturbations are due either to erroneous data assimilated into the models or to issues with the complex data assimilation system itself, and may have caused the forecast degradations. Investigation of forecast and observing system failures can lead to procedural changes that may eliminate some causes of future large forecast errors.
The suite of tropical cyclone track forecast models in the Atlantic basin from the 1976 to 2000 hurricane seasons are treated as a forecast ensemble. The 12-h ensemble mean forecast, adjusted for forecast difficulty, has improved at a rate of just under 1% per year, and the improvement rate increases to almost 2.4% per year for the 72-h forecasts. The average size of the 72-h (48-h) error in 1976 is less than the average size of the 48-h (36-h) error in 2000. The average 36-h forecast error in 2000 is comparable to the 24-h forecast error in 1976. The ensemble currently spans the true path of the tropical cyclone in the cross-track direction more than 90% of the time and in the alongtrack direction between 60% and 90% of the time depending on the forecast lead time. The ensemble spread is unable to provide estimates of individual forecast reliability, likely making probabilistic landfall forecasts from this ensemble unreliable. The reliability of the spread in the cross-track direction suggests the possibility of limiting hurricane watch and warning regions depending upon the ensemble spread at landfall.
The suite of tropical cyclone track forecast models in the Atlantic basin from the 1976 to 2000 hurricane seasons are treated as a forecast ensemble. The 12-h ensemble mean forecast, adjusted for forecast difficulty, has improved at a rate of just under 1% per year, and the improvement rate increases to almost 2.4% per year for the 72-h forecasts. The average size of the 72-h (48-h) error in 1976 is less than the average size of the 48-h (36-h) error in 2000. The average 36-h forecast error in 2000 is comparable to the 24-h forecast error in 1976. The ensemble currently spans the true path of the tropical cyclone in the cross-track direction more than 90% of the time and in the alongtrack direction between 60% and 90% of the time depending on the forecast lead time. The ensemble spread is unable to provide estimates of individual forecast reliability, likely making probabilistic landfall forecasts from this ensemble unreliable. The reliability of the spread in the cross-track direction suggests the possibility of limiting hurricane watch and warning regions depending upon the ensemble spread at landfall.
The important role of the correct use of statistics in the atmnospheric sciences literature is once again emphasized. Despite previous work on this topic, statistical techniques, even very simple ones, continue to be misused or altogether neglected, with the inevitable result of misleading or erroneous conclusions. An example concerning the impact of global climate change and hurricane activity is presented.
The important role of the correct use of statistics in the atmnospheric sciences literature is once again emphasized. Despite previous work on this topic, statistical techniques, even very simple ones, continue to be misused or altogether neglected, with the inevitable result of misleading or erroneous conclusions. An example concerning the impact of global climate change and hurricane activity is presented.
Abstract
In 1997, the National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the U.S. Virgin Islands, and Hawaii. During the first 10 yr, 176 such missions were conducted. Global Positioning System dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of each tropical cyclone to obtain wind, temperature, and humidity profiles from flight level (about 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and sent to the National Centers for Environmental Prediction and the Global Telecommunications System to be ingested into the Global Forecast System, which serves as initial and boundary conditions for regional numerical models that also forecast tropical cyclone track and intensity. The results of an observing system experiment using these data are presented.
Abstract
In 1997, the National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the U.S. Virgin Islands, and Hawaii. During the first 10 yr, 176 such missions were conducted. Global Positioning System dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of each tropical cyclone to obtain wind, temperature, and humidity profiles from flight level (about 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and sent to the National Centers for Environmental Prediction and the Global Telecommunications System to be ingested into the Global Forecast System, which serves as initial and boundary conditions for regional numerical models that also forecast tropical cyclone track and intensity. The results of an observing system experiment using these data are presented.
Abstract
Since 1997, the Tropical Prediction Center and the Hurricane Research Division have conducted operational synoptic surveillance missions with a Gulfstream IV-SP jet aircraft to improve numerical forecast guidance. Due to limited aircraft resources, optimal observing strategies for these missions must be developed. In the current study, the most rapidly growing modes are represented by areas of large forecast spread in the NCEP bred-vector ensemble forecasting system. The sampling strategy requires sampling of the entire target region with regularly spaced dropwindsonde observations.
Three dynamical models were employed in testing the targeting and sampling strategies. With the assimilation into the numerical guidance of all the observations gathered during the surveillance missions, only the 12-h Geophysical Fluid Dynamics Laboratory Hurricane Model forecast showed statistically significant improvement. Assimilation of only the subset of data from the subjectively found fully sampled target regions produced a statistically significant reduction of the track forecast errors of up to 25% within the critical first 2 days of the forecast. This is comparable with the cumulative business-as-usual improvement expected over 18 yr.
Abstract
Since 1997, the Tropical Prediction Center and the Hurricane Research Division have conducted operational synoptic surveillance missions with a Gulfstream IV-SP jet aircraft to improve numerical forecast guidance. Due to limited aircraft resources, optimal observing strategies for these missions must be developed. In the current study, the most rapidly growing modes are represented by areas of large forecast spread in the NCEP bred-vector ensemble forecasting system. The sampling strategy requires sampling of the entire target region with regularly spaced dropwindsonde observations.
Three dynamical models were employed in testing the targeting and sampling strategies. With the assimilation into the numerical guidance of all the observations gathered during the surveillance missions, only the 12-h Geophysical Fluid Dynamics Laboratory Hurricane Model forecast showed statistically significant improvement. Assimilation of only the subset of data from the subjectively found fully sampled target regions produced a statistically significant reduction of the track forecast errors of up to 25% within the critical first 2 days of the forecast. This is comparable with the cumulative business-as-usual improvement expected over 18 yr.
Abstract
Four aircraft released dropwindsondes in and around tropical cyclones in the west Pacific during The Observing System Research and Predictability Experiment (THORPEX) Pacific Area Regional Campaign (T-PARC) in 2008 and the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR); multiple aircraft concurrently participated in similar missions in the Atlantic. Previous studies have treated each region separately and have focused on the tropical cyclones whose environments were sampled. The large number of missions and tropical cyclones in both regions, and additional tropical cyclones in the east Pacific and Indian Oceans, allows for the global impact of these observations on tropical cyclone track forecasts to be studied.
The study shows that there are unintended global consequences to local changes in initial conditions, in this case due to the assimilation of dropwindsonde data in tropical cyclone environments. These global impacts are mainly due to the spectral nature of the model system. These differences should be small and slightly positive, since improved local initial conditions should lead to small global forecast improvements. However, the impacts on tropical cyclones far removed from the data are shown to be as large and positive as those on the tropical cyclones specifically targeted for improved track forecasts. Causes of this unexpected result are hypothesized, potentially providing operational forecasters tools to identify when large remote impacts from surveillance missions might occur.
Abstract
Four aircraft released dropwindsondes in and around tropical cyclones in the west Pacific during The Observing System Research and Predictability Experiment (THORPEX) Pacific Area Regional Campaign (T-PARC) in 2008 and the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR); multiple aircraft concurrently participated in similar missions in the Atlantic. Previous studies have treated each region separately and have focused on the tropical cyclones whose environments were sampled. The large number of missions and tropical cyclones in both regions, and additional tropical cyclones in the east Pacific and Indian Oceans, allows for the global impact of these observations on tropical cyclone track forecasts to be studied.
The study shows that there are unintended global consequences to local changes in initial conditions, in this case due to the assimilation of dropwindsonde data in tropical cyclone environments. These global impacts are mainly due to the spectral nature of the model system. These differences should be small and slightly positive, since improved local initial conditions should lead to small global forecast improvements. However, the impacts on tropical cyclones far removed from the data are shown to be as large and positive as those on the tropical cyclones specifically targeted for improved track forecasts. Causes of this unexpected result are hypothesized, potentially providing operational forecasters tools to identify when large remote impacts from surveillance missions might occur.
Abstract
Statistical analyses of the most recent 40 yr of hurricane tracks (1956–95) are presented, leading to a version of the North Atlantic climatology and persistence (CLIPER) model that exhibits much smaller forecast biases but similar forecast errors compared to the previously used version. Changes to the model involve the inclusion of more accurate historical tropical cyclone track data and a simpler derivation of the regression equations. Nonlinear systems analysis shows that the predictability timescale in which the average errors increase by a factor e is approximately 2.5 days in the Atlantic basin, which is larger than that found by similar methods near Australia. This suggests that 5-day tropical cyclone track forecasts may have some benefit, and therefore a version of CLIPER extended to 5 days to be used as a baseline to measure this skill is needed.
Abstract
Statistical analyses of the most recent 40 yr of hurricane tracks (1956–95) are presented, leading to a version of the North Atlantic climatology and persistence (CLIPER) model that exhibits much smaller forecast biases but similar forecast errors compared to the previously used version. Changes to the model involve the inclusion of more accurate historical tropical cyclone track data and a simpler derivation of the regression equations. Nonlinear systems analysis shows that the predictability timescale in which the average errors increase by a factor e is approximately 2.5 days in the Atlantic basin, which is larger than that found by similar methods near Australia. This suggests that 5-day tropical cyclone track forecasts may have some benefit, and therefore a version of CLIPER extended to 5 days to be used as a baseline to measure this skill is needed.
Abstract
Linear multiple regression and discriminant analyses provide estimates of the errors of track forecasts from a nested barotropic hurricane track forecast model (VICBAR), which was run in the North Atlantic Basin during the 1989–94 hurricane seasons. Predictors are determined from the synoptic situation, the magnitude of atmospheric changes in the environment of the tropical cyclone, the consistency between current and past predictions, and the past performance of the model for each particular storm. This technique distinguishes cases in which VICBAR performs well from those for which it performs poorly and can provide skillful operational predictions of model performance to forecasters.
Abstract
Linear multiple regression and discriminant analyses provide estimates of the errors of track forecasts from a nested barotropic hurricane track forecast model (VICBAR), which was run in the North Atlantic Basin during the 1989–94 hurricane seasons. Predictors are determined from the synoptic situation, the magnitude of atmospheric changes in the environment of the tropical cyclone, the consistency between current and past predictions, and the past performance of the model for each particular storm. This technique distinguishes cases in which VICBAR performs well from those for which it performs poorly and can provide skillful operational predictions of model performance to forecasters.
Abstract
The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a contingency table with all other forecasts is presented. Skill scores and probabilities are calculated. Forecast verifications with the currently used technique have shown a slight improvement in intensity forecasts. The new technique, taking into account all forecasts, suggests that the probability of a forecast having a large (>30 kt) error is decreasing, and the likelihood of the error being less than about 10 kt is increasing in time, at all forecast lead times except 12 h when the forecasts are already quite good.
Abstract
The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a contingency table with all other forecasts is presented. Skill scores and probabilities are calculated. Forecast verifications with the currently used technique have shown a slight improvement in intensity forecasts. The new technique, taking into account all forecasts, suggests that the probability of a forecast having a large (>30 kt) error is decreasing, and the likelihood of the error being less than about 10 kt is increasing in time, at all forecast lead times except 12 h when the forecasts are already quite good.
Abstract
In 1997, the National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the Virgin Islands, and Hawaii. During the first two years, 24 missions were conducted. Global positioning system dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of each tropical cyclone to obtain profiles of wind, temperature, and humidity from flight level (nearly 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and sent to NCEP to be ingested into the Global Data Assimilation System, which subsequently served as initial and boundary conditions for a number of numerical models that forecast the track and intensity of tropical cyclones. The current study is an attempt to mimic this process to assess the impact of these operational missions on the numerical guidance. Although the small number of missions flown in 1997 showed error reductions of as much as 32%, the improvements seen in the 2-yr sample are not promising. The additional dropwindsonde data from the synoptic surveillance missions provided statistically significant improvements in the GFDL forecasts only at 12 h. The “VBAR” and Global Forecast System (AVN) forecasts were not significantly improved at any forecast time. Further examination suggests that the AVN synthetic vortex procedure, combined with difficulty in the quantification of the current storm-motion vector operationally, may have caused the mediocre improvements. Forecast improvements of 14%–24% in GFDL forecasts are shown in the subset of cases in which the synthetic vortex data do not seem to be a problem. Improvements in the landfall forecasts are also seen in this subset of cases. A reassessment of tropical cyclone vortex initialization schemes used by forecast centers and numerical modelers may be necessary.
Abstract
In 1997, the National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the Virgin Islands, and Hawaii. During the first two years, 24 missions were conducted. Global positioning system dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of each tropical cyclone to obtain profiles of wind, temperature, and humidity from flight level (nearly 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and sent to NCEP to be ingested into the Global Data Assimilation System, which subsequently served as initial and boundary conditions for a number of numerical models that forecast the track and intensity of tropical cyclones. The current study is an attempt to mimic this process to assess the impact of these operational missions on the numerical guidance. Although the small number of missions flown in 1997 showed error reductions of as much as 32%, the improvements seen in the 2-yr sample are not promising. The additional dropwindsonde data from the synoptic surveillance missions provided statistically significant improvements in the GFDL forecasts only at 12 h. The “VBAR” and Global Forecast System (AVN) forecasts were not significantly improved at any forecast time. Further examination suggests that the AVN synthetic vortex procedure, combined with difficulty in the quantification of the current storm-motion vector operationally, may have caused the mediocre improvements. Forecast improvements of 14%–24% in GFDL forecasts are shown in the subset of cases in which the synthetic vortex data do not seem to be a problem. Improvements in the landfall forecasts are also seen in this subset of cases. A reassessment of tropical cyclone vortex initialization schemes used by forecast centers and numerical modelers may be necessary.
