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Abstract
The relative independence of the tropical cyclone track forecasts produced by regional and global numerical weather prediction models suggests that a simple ensemble average or consensus forecast derived from a combination of these models may be more accurate, on average, than the forecasts of the individual models. Forecast errors of a simple ensemble average of three models for the 1995–96 Atlantic hurricane seasons, and either three global models or two regional models for the western North Pacific during 1997, were compared with errors of the individual models. For the Atlantic, the mean errors for the joint ensemble were 120 km at 24 h, 194 km at 48 h, and 266 km at 72 h, which represent improvements of 16%, 20%, and 23% with respect to the best of the individual models. The joint ensemble also resulted in reduction in the standard deviation of the forecast error. The 95th percentile of forecast error for the ensemble was reduced 19%, 14%, and 23% with respect to the best of the individual models. The spread of the ensemble forecast was found to possess some potential for use by forecasters as a measure of confidence in the ensemble forecast. Similar results were found for the western North Pacific.
Abstract
The relative independence of the tropical cyclone track forecasts produced by regional and global numerical weather prediction models suggests that a simple ensemble average or consensus forecast derived from a combination of these models may be more accurate, on average, than the forecasts of the individual models. Forecast errors of a simple ensemble average of three models for the 1995–96 Atlantic hurricane seasons, and either three global models or two regional models for the western North Pacific during 1997, were compared with errors of the individual models. For the Atlantic, the mean errors for the joint ensemble were 120 km at 24 h, 194 km at 48 h, and 266 km at 72 h, which represent improvements of 16%, 20%, and 23% with respect to the best of the individual models. The joint ensemble also resulted in reduction in the standard deviation of the forecast error. The 95th percentile of forecast error for the ensemble was reduced 19%, 14%, and 23% with respect to the best of the individual models. The spread of the ensemble forecast was found to possess some potential for use by forecasters as a measure of confidence in the ensemble forecast. Similar results were found for the western North Pacific.
Abstract
The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.
Abstract
The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.
Abstract
Two assimilation schemes are described in which continuous indirect insertion of satellite-derived temperatures is performed, using a global primitive equation forecast model. Both schemes employ a relatively simple indirect insertion technique but utilize different methods (Noise Freezing Methods I and II) to control the noise induced within the forecast model by data insertion. Using data collected in February 1976 during NASA Data Systems Test 6, the effectiveness of these schemes is compared with that of a third scheme in which satellite-derived temperatures are assimilated using the same techniques that most operational forecast centers employ. After a 36 h start-up period, 48 h forecasts were produced using each assimilation scheme and root-mean-square errors computed for the differences between the forecast fields and upper-air observations of geopotential height. The forecasts of geopotential height made using the noise freezing methods are found to show substantial improvements over those made using conventional techniques. The forecasts produced using Noise Freezing Methods I and II are comparable with each other, and show average percent improvements over conventional forecasts ranging from 5 to 10% at 850 mb and from 10 to 15% at both 500 and 300 mb. Improvements of nearly 25% are observed for individual forecasts.
Abstract
Two assimilation schemes are described in which continuous indirect insertion of satellite-derived temperatures is performed, using a global primitive equation forecast model. Both schemes employ a relatively simple indirect insertion technique but utilize different methods (Noise Freezing Methods I and II) to control the noise induced within the forecast model by data insertion. Using data collected in February 1976 during NASA Data Systems Test 6, the effectiveness of these schemes is compared with that of a third scheme in which satellite-derived temperatures are assimilated using the same techniques that most operational forecast centers employ. After a 36 h start-up period, 48 h forecasts were produced using each assimilation scheme and root-mean-square errors computed for the differences between the forecast fields and upper-air observations of geopotential height. The forecasts of geopotential height made using the noise freezing methods are found to show substantial improvements over those made using conventional techniques. The forecasts produced using Noise Freezing Methods I and II are comparable with each other, and show average percent improvements over conventional forecasts ranging from 5 to 10% at 850 mb and from 10 to 15% at both 500 and 300 mb. Improvements of nearly 25% are observed for individual forecasts.
Abstract
In January of 1988, significant upgrades were made to the Navy Operational Global Atmospheric Prediction System (NOGAPS). Among these improvements was the implementation of a multivariate optimum interpolation analysis scheme. Since that time, this analysis scheme has been improved and expanded to satisfy almost all of the navy's atmospheric analysis requirements. In this paper, we describe the global database available for analysis, the techniques currently used to produce the NOGAPS analyzed fields, and the modification required for other applications.
Abstract
In January of 1988, significant upgrades were made to the Navy Operational Global Atmospheric Prediction System (NOGAPS). Among these improvements was the implementation of a multivariate optimum interpolation analysis scheme. Since that time, this analysis scheme has been improved and expanded to satisfy almost all of the navy's atmospheric analysis requirements. In this paper, we describe the global database available for analysis, the techniques currently used to produce the NOGAPS analyzed fields, and the modification required for other applications.
Abstract
A cross-spectral analysis method is developed to estimate the noise variance spectra of three or more independent measurement systems observing the same input. The noise is modeled using a first-order autoregressive process. Estimates of the two process parameters are used to determine confidence limits for system noise that can be placed on the observed data.
The method has been applied to dew-point data collected in aircraft intercomparison flights and a research flight in the National Hail Research Experiment. The six dew-point systems used were manufactured by the same company and operate by electrically cooling a metal mirror until a film of water vapor or frost is optically detected on the mirrored surface. The ratio of the signal to noise variance was found to vary between about 10:1 and 100:1 at the origin and decrease to zero between about 0.15 and 0.3 Hz, both properties dependent on atmospheric conditions and the structure of system noise. Since the data were collected once per second, appropriate filtering and decimation could be performed for archiving purposes with a 50% space savings and small loss of “information.” Ninety-five percent confidence limits on the filtered observed data with a cutoff at 0.2 Hz vary from ±0.5 to ±0.1°C, with the latter figure most representative of those computed.
Abstract
A cross-spectral analysis method is developed to estimate the noise variance spectra of three or more independent measurement systems observing the same input. The noise is modeled using a first-order autoregressive process. Estimates of the two process parameters are used to determine confidence limits for system noise that can be placed on the observed data.
The method has been applied to dew-point data collected in aircraft intercomparison flights and a research flight in the National Hail Research Experiment. The six dew-point systems used were manufactured by the same company and operate by electrically cooling a metal mirror until a film of water vapor or frost is optically detected on the mirrored surface. The ratio of the signal to noise variance was found to vary between about 10:1 and 100:1 at the origin and decrease to zero between about 0.15 and 0.3 Hz, both properties dependent on atmospheric conditions and the structure of system noise. Since the data were collected once per second, appropriate filtering and decimation could be performed for archiving purposes with a 50% space savings and small loss of “information.” Ninety-five percent confidence limits on the filtered observed data with a cutoff at 0.2 Hz vary from ±0.5 to ±0.1°C, with the latter figure most representative of those computed.
Abstract
In June 1990, the assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System (NOGAPS) was initiated at Fleet Numerical Oceanography Center (FNOC). These observations are derived directly from the information contained in the tropical cyclone warnings issued by the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center. This paper describes these synthetic observations, the evolution of their use at FNOC, and the details of their assimilation into NOGAPS. The results of a comprehensive evaluation of the 1991 NOGAPS tropical cyclone forecast performance in the western North Pacific are presented. NOGAPS analysis and forecast position errors were determined for all tropical circulations of tropical storm strength or greater. It was found that, after the assimilation of synthetic observations, the NOGAPS spectral forecast model consistently maintained the tropical circulations as evidenced by detection percentages of 96%, 90% and 87% for 24-, 48-, and 72-h forecasts, respectively. The average forecast position errors were 188, 299, and 434 km for the respective forecasts. The respective errors for the One-Way Influence Tropical Cyclone Model (OTCM), one of JTWC's primary track-forecasting aids, were 215, 364, and 529 km. In homogeneous comparisons the percent improvement of the NOGAPS 48- and 72-h forecasts was 14% and 12% over the OTCM and 31% and 33% over JTWC's operational Climatology–Persistence Model.
Abstract
In June 1990, the assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System (NOGAPS) was initiated at Fleet Numerical Oceanography Center (FNOC). These observations are derived directly from the information contained in the tropical cyclone warnings issued by the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center. This paper describes these synthetic observations, the evolution of their use at FNOC, and the details of their assimilation into NOGAPS. The results of a comprehensive evaluation of the 1991 NOGAPS tropical cyclone forecast performance in the western North Pacific are presented. NOGAPS analysis and forecast position errors were determined for all tropical circulations of tropical storm strength or greater. It was found that, after the assimilation of synthetic observations, the NOGAPS spectral forecast model consistently maintained the tropical circulations as evidenced by detection percentages of 96%, 90% and 87% for 24-, 48-, and 72-h forecasts, respectively. The average forecast position errors were 188, 299, and 434 km for the respective forecasts. The respective errors for the One-Way Influence Tropical Cyclone Model (OTCM), one of JTWC's primary track-forecasting aids, were 215, 364, and 529 km. In homogeneous comparisons the percent improvement of the NOGAPS 48- and 72-h forecasts was 14% and 12% over the OTCM and 31% and 33% over JTWC's operational Climatology–Persistence Model.
Abstract
A method to predict an anisotropic expected forecast error distribution for consensus forecasts of tropical cyclone (TC) tracks is presented. The method builds upon the Goerss predicted consensus error (GPCE), which predicts the isotropic radius of the 70% isopleth of expected TC track error. Consensus TC track forecasts are computed as the mean of a collection of TC track forecasts from different models and are basin dependent. A novel aspect of GPCE is that it uses not only the uncertainty in the collection of constituent models to predict expected error, but also other features of the predicted storm, including initial intensity, forecast intensity, and storm speed. The new method, called GPCE along–across (GPCE-AX), takes a similar approach but separates the predicted error into across-track and along-track components. GPCE-AX has been applied to consensus TC track forecasts in the Atlantic (CONU/TVCN, where CONU is consensus version U and TVCN is the track variable consensus) and in the western North Pacific (consensus version W, CONW). The results for both basins indicate that GPCE-AX either outperforms or is equal in quality to GPCE in terms of reliability (the fraction of time verification is bound by the 70% uncertainty isopleths) and sharpness (the area bound by the 70% isopleths). GPCE-AX has been implemented at both the National Hurricane Center and at the Joint Typhoon Warning Center for real-time testing and evaluation.
Abstract
A method to predict an anisotropic expected forecast error distribution for consensus forecasts of tropical cyclone (TC) tracks is presented. The method builds upon the Goerss predicted consensus error (GPCE), which predicts the isotropic radius of the 70% isopleth of expected TC track error. Consensus TC track forecasts are computed as the mean of a collection of TC track forecasts from different models and are basin dependent. A novel aspect of GPCE is that it uses not only the uncertainty in the collection of constituent models to predict expected error, but also other features of the predicted storm, including initial intensity, forecast intensity, and storm speed. The new method, called GPCE along–across (GPCE-AX), takes a similar approach but separates the predicted error into across-track and along-track components. GPCE-AX has been applied to consensus TC track forecasts in the Atlantic (CONU/TVCN, where CONU is consensus version U and TVCN is the track variable consensus) and in the western North Pacific (consensus version W, CONW). The results for both basins indicate that GPCE-AX either outperforms or is equal in quality to GPCE in terms of reliability (the fraction of time verification is bound by the 70% uncertainty isopleths) and sharpness (the area bound by the 70% isopleths). GPCE-AX has been implemented at both the National Hurricane Center and at the Joint Typhoon Warning Center for real-time testing and evaluation.
Abstract
Experimental wind datasets were derived for two time periods (13–20 July and 24 August–10 September 1995) from GOES-8 observations processed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW CIMSS). The first dataset was focused on Tropical Storm Chantal, and the second dataset was focused on the multiple-storm environment that included Hurricanes Humberto, Iris, and Luis. Both datasets feature a processing and quality control strategy designed to optimize the quantity and content of geostationary satellite-derived winds in the vicinity of tropical cyclones. Specifically, the winds were extracted from high-density targets obtained from multispectral imagery, which included three water vapor bands (6.7, 7.0, and 7.3 μm), infrared, and visible. The Navy Operational Global Atmospheric Prediction System (NOGAPS) was used as the vehicle to determine the impact of these winds upon tropical cyclone track forecasts. During the 1995 Atlantic hurricane season the NOGAPS forecasts were found to be quite skillful, displaying relative improvement of tropical cyclone position error with respect to CLIPER (climate and persistence) of 20% at 24 h, 35% at 48 h, and 33% at 72 h. The NOGAPS data assimilation system was run with and without the high-density GOES-8 winds for the two aforementioned time periods. The assimilation of these winds resulted in significant improvements in the NOGAPS forecasts for Tropical Storm Chantal and Hurricane Iris and mixed results for Hurricanes Humberto and Luis. Overall, for all four cyclones, the NOGAPS forecasts made with the use of the UW CIMSS winds displayed relative improvement of forecast position error with respect to those made without the use of the UW CIMSS winds of 14% at 24 h, and 12% at both 48 and 72 h.
Abstract
Experimental wind datasets were derived for two time periods (13–20 July and 24 August–10 September 1995) from GOES-8 observations processed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW CIMSS). The first dataset was focused on Tropical Storm Chantal, and the second dataset was focused on the multiple-storm environment that included Hurricanes Humberto, Iris, and Luis. Both datasets feature a processing and quality control strategy designed to optimize the quantity and content of geostationary satellite-derived winds in the vicinity of tropical cyclones. Specifically, the winds were extracted from high-density targets obtained from multispectral imagery, which included three water vapor bands (6.7, 7.0, and 7.3 μm), infrared, and visible. The Navy Operational Global Atmospheric Prediction System (NOGAPS) was used as the vehicle to determine the impact of these winds upon tropical cyclone track forecasts. During the 1995 Atlantic hurricane season the NOGAPS forecasts were found to be quite skillful, displaying relative improvement of tropical cyclone position error with respect to CLIPER (climate and persistence) of 20% at 24 h, 35% at 48 h, and 33% at 72 h. The NOGAPS data assimilation system was run with and without the high-density GOES-8 winds for the two aforementioned time periods. The assimilation of these winds resulted in significant improvements in the NOGAPS forecasts for Tropical Storm Chantal and Hurricane Iris and mixed results for Hurricanes Humberto and Luis. Overall, for all four cyclones, the NOGAPS forecasts made with the use of the UW CIMSS winds displayed relative improvement of forecast position error with respect to those made without the use of the UW CIMSS winds of 14% at 24 h, and 12% at both 48 and 72 h.
Abstract
We have compared analysis increments produced by the optimal interpolation scheme and initialization increments produced by the nonlinear normal-mode initialization scheme in the U.S. Navy Operational Global Atmospheric Prediction System. Results indicate that analysis increments of height in the tropics are partially removed by the subsequent initialization. Similar results are obtained for the field of horizontal velocity divergence within the extratropics as well as tropics. Consequently, for some fields in some areas, the initialized analyses are primarily defined by the model-produced background field, irrespective of the availability of observations or model error estimates.
Abstract
We have compared analysis increments produced by the optimal interpolation scheme and initialization increments produced by the nonlinear normal-mode initialization scheme in the U.S. Navy Operational Global Atmospheric Prediction System. Results indicate that analysis increments of height in the tropics are partially removed by the subsequent initialization. Similar results are obtained for the field of horizontal velocity divergence within the extratropics as well as tropics. Consequently, for some fields in some areas, the initialized analyses are primarily defined by the model-produced background field, irrespective of the availability of observations or model error estimates.
Abstract
The meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones is evaluated and it is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The evaluation was conducted during the 1990 operational testing of a procedure to improve the initial analysis or specification of tropical cyclones (TCs) in NOGAPS by the U.S. Navy Fleet Numerical Oceanography Center (FNOC). The NOGAPS TC analysis procedure generates synthetic TC observations based on operational vortex data (e.g., location and maximum surface wind speed) and then adds the observations to the observational data base with flags to force their assimilation. Results from the first year of testing were favorable, despite intermittent application of the procedure.
The meteorological characteristics of the NOGAPS tropical cyclone predictions were evaluated by examining the formation of low-level cyclone circulation systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. Analyzed circulations were found in the vicinity of developing TCs for nearly all cyclones during the operational test period. This finding implies that the model is “primed” for assimilating the synthetic observations and may be accurately simulating the large-scale environments favorable to TC formation. The analyzed TC circulations had greater than observed horizontal extent due to coarse grid spacing (δx∼ 160 km) in the global model; however, the vortices, in general, were vertically stacked and maintained during the forecast by realistic amounts of thermodynamic forcing from the cumulus parameterization. Despite the large size of the NOGAPS TC vortices, the track forecasts were not overly biased with regard to track or speed. The operational utility of the NOGAPS track forecasts was analyzed through a comparison with the real-time runs of a baseline climatology persistence aid and with the best dynamical model used by the Joint Typhoon Warning Center, Guam. To ensure a realistic comparison of the forecasts and to improve the appearance of the global model tracks, a postprocessing adjustment procedure was employed that accounts for the observed initial motion and position. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. In fact, NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones. Overall, the adjusted NOGAPS track forecasts were judged to be competitive with other aids used by the operational forecasters at JTWC and it is suggested that global models may make important contributions to improving TC forecasting in the future.
Abstract
The meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones is evaluated and it is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The evaluation was conducted during the 1990 operational testing of a procedure to improve the initial analysis or specification of tropical cyclones (TCs) in NOGAPS by the U.S. Navy Fleet Numerical Oceanography Center (FNOC). The NOGAPS TC analysis procedure generates synthetic TC observations based on operational vortex data (e.g., location and maximum surface wind speed) and then adds the observations to the observational data base with flags to force their assimilation. Results from the first year of testing were favorable, despite intermittent application of the procedure.
The meteorological characteristics of the NOGAPS tropical cyclone predictions were evaluated by examining the formation of low-level cyclone circulation systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. Analyzed circulations were found in the vicinity of developing TCs for nearly all cyclones during the operational test period. This finding implies that the model is “primed” for assimilating the synthetic observations and may be accurately simulating the large-scale environments favorable to TC formation. The analyzed TC circulations had greater than observed horizontal extent due to coarse grid spacing (δx∼ 160 km) in the global model; however, the vortices, in general, were vertically stacked and maintained during the forecast by realistic amounts of thermodynamic forcing from the cumulus parameterization. Despite the large size of the NOGAPS TC vortices, the track forecasts were not overly biased with regard to track or speed. The operational utility of the NOGAPS track forecasts was analyzed through a comparison with the real-time runs of a baseline climatology persistence aid and with the best dynamical model used by the Joint Typhoon Warning Center, Guam. To ensure a realistic comparison of the forecasts and to improve the appearance of the global model tracks, a postprocessing adjustment procedure was employed that accounts for the observed initial motion and position. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. In fact, NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones. Overall, the adjusted NOGAPS track forecasts were judged to be competitive with other aids used by the operational forecasters at JTWC and it is suggested that global models may make important contributions to improving TC forecasting in the future.
