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The National Center for Atmospheric Research (NCAR), in a joint effort with the National Oceanic and Atmospheric Administration (NOAA) and the German Aerospace Research Establishment, has developed a dropwindsonde based on the Global Positioning System (GPS) satellite navigation. The NCAR GPS dropwindsonde represents a major advance in both accuracy and resolution for atmospheric measurements over data-sparse oceanic areas of the globe, providing wind accuracies of 0.5–2.0 m s−1 with a vertical resolution of ~5 m. One important advance over previous generations of sondes is the ability to measure surface (10 m) winds. The new dropwindsonde has already been used extensively in one major international research field experiment (Fronts and Atlantic Storm Track Experiment), in operational and research hurricane flights from NOAA's National Weather Service and Hurricane Research Division, during NCAR's SNOWBAND experiment, and in recent CALJET and NORPEX El Niño experiments. The sonde has been deployed from a number of different aircraft, including NOAA's WP-3Ds and new Gulf stream IV jet, the Air Force C-130s, NCAR's Electra, and a leased Lear-36. This paper describes the characteristics of the new dropwindsonde and its associated aircraft data system, details the accuracy of its measurements, and presents examples from its initial applications.
The National Center for Atmospheric Research (NCAR), in a joint effort with the National Oceanic and Atmospheric Administration (NOAA) and the German Aerospace Research Establishment, has developed a dropwindsonde based on the Global Positioning System (GPS) satellite navigation. The NCAR GPS dropwindsonde represents a major advance in both accuracy and resolution for atmospheric measurements over data-sparse oceanic areas of the globe, providing wind accuracies of 0.5–2.0 m s−1 with a vertical resolution of ~5 m. One important advance over previous generations of sondes is the ability to measure surface (10 m) winds. The new dropwindsonde has already been used extensively in one major international research field experiment (Fronts and Atlantic Storm Track Experiment), in operational and research hurricane flights from NOAA's National Weather Service and Hurricane Research Division, during NCAR's SNOWBAND experiment, and in recent CALJET and NORPEX El Niño experiments. The sonde has been deployed from a number of different aircraft, including NOAA's WP-3Ds and new Gulf stream IV jet, the Air Force C-130s, NCAR's Electra, and a leased Lear-36. This paper describes the characteristics of the new dropwindsonde and its associated aircraft data system, details the accuracy of its measurements, and presents examples from its initial applications.
In 1997, the Tropical Prediction Center (TPC) began operational Gulfstream-IV jet aircraft missions to improve the numerical guidance for hurricanes threatening the continental United States, Puerto Rico, and the Virgin Islands. During these missions, the new generation of Global Positioning System dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of the tropical cyclone to obtain profiles of wind, temperature, and humidity from flight level to the surface. The observations were ingested into the global model at the National Centers for Environmental Prediction, which subsequently serves as initial and boundary conditions to other numerical tropical cyclone models. Because of a lack of tropical cyclone activity in the Atlantic basin, only five such missions were conducted during the inaugural 1997 hurricane season.
Due to logistical constraints, sampling in all quadrants of the storm environment was accomplished in only one of the five cases during 1997. Nonetheless, the dropwindsonde observations improved mean track forecasts from the Geophysical Fluid Dynamics Laboratory hurricane model by as much as 32%, and the intensity forecasts by as much as 20% during the hurricane watch period (within 48 h of projected landfall). Forecasts from another dynamical tropical cyclone model (VICBAR) also showed modest improvements with the dropwindsonde observations. These improvements, if confirmed by a larger sample, represent a large step toward the forecast accuracy goals of TPC. The forecast track improvements are as large as those accumulated over the past 20–25 years, and those for forecast intensity provide further evidence that better synoptic-scale data can lead to more skillful dynamical tropical cyclone intensity forecasts.
In 1997, the Tropical Prediction Center (TPC) began operational Gulfstream-IV jet aircraft missions to improve the numerical guidance for hurricanes threatening the continental United States, Puerto Rico, and the Virgin Islands. During these missions, the new generation of Global Positioning System dropwindsondes were released from the aircraft at 150–200-km intervals along the flight track in the environment of the tropical cyclone to obtain profiles of wind, temperature, and humidity from flight level to the surface. The observations were ingested into the global model at the National Centers for Environmental Prediction, which subsequently serves as initial and boundary conditions to other numerical tropical cyclone models. Because of a lack of tropical cyclone activity in the Atlantic basin, only five such missions were conducted during the inaugural 1997 hurricane season.
Due to logistical constraints, sampling in all quadrants of the storm environment was accomplished in only one of the five cases during 1997. Nonetheless, the dropwindsonde observations improved mean track forecasts from the Geophysical Fluid Dynamics Laboratory hurricane model by as much as 32%, and the intensity forecasts by as much as 20% during the hurricane watch period (within 48 h of projected landfall). Forecasts from another dynamical tropical cyclone model (VICBAR) also showed modest improvements with the dropwindsonde observations. These improvements, if confirmed by a larger sample, represent a large step toward the forecast accuracy goals of TPC. The forecast track improvements are as large as those accumulated over the past 20–25 years, and those for forecast intensity provide further evidence that better synoptic-scale data can lead to more skillful dynamical tropical cyclone intensity forecasts.
Previous studies have identified statistically significant long-term improvements in forecasts issued by the National Hurricane Center (NHC) for Atlantic basin tropical cyclones. Recently, however, attention has been focused on the forecast accuracy of landfall location and timing, and the long-term improvement trends for this relatively small sample of forecasts were mixed. These results may lead some to conclude that the accuracy of NHC forecasts close to the United States has not improved over time.
A statistically robust dataset can be obtained by considering “landfall-threatening” storms, defined as one for which tropical cyclone watches or warnings are in effect for some portion of the continental United States. In this study, long-term trends in accuracy are determined for NHC forecasts issued during these periods of threat and compared to trends for the Atlantic basin overall. A second set of trends are determined for forecasts verifying during the periods of threat.
The analysis shows that NHC forecasts for land-threatening tropical cyclones are improving. These improvement trends are statistically significant, although the improvement rates for the land-threatening storms are smaller than those for the basin overall. Over the period 1970–2001, forecasts issued during the watch/warning stage improved at annual average rates of 0.7%, 1.6%, and 1.9% at 24,48, and 72 h, respectively.
Previous studies have identified statistically significant long-term improvements in forecasts issued by the National Hurricane Center (NHC) for Atlantic basin tropical cyclones. Recently, however, attention has been focused on the forecast accuracy of landfall location and timing, and the long-term improvement trends for this relatively small sample of forecasts were mixed. These results may lead some to conclude that the accuracy of NHC forecasts close to the United States has not improved over time.
A statistically robust dataset can be obtained by considering “landfall-threatening” storms, defined as one for which tropical cyclone watches or warnings are in effect for some portion of the continental United States. In this study, long-term trends in accuracy are determined for NHC forecasts issued during these periods of threat and compared to trends for the Atlantic basin overall. A second set of trends are determined for forecasts verifying during the periods of threat.
The analysis shows that NHC forecasts for land-threatening tropical cyclones are improving. These improvement trends are statistically significant, although the improvement rates for the land-threatening storms are smaller than those for the basin overall. Over the period 1970–2001, forecasts issued during the watch/warning stage improved at annual average rates of 0.7%, 1.6%, and 1.9% at 24,48, and 72 h, respectively.
Since 1982, the Hurricane Research Division (HRD) has conducted a series of experiments with research aircraft to enhance the number of observations in the environment and the core of hurricanes threatening the United States. During these experiments, the National Oceanic and Atmospheric Administration WP-3D aircraft crews release Omega dropwindsondes (ODWs) at 15–20-min intervals along the flight track to obtain profiles of wind, temperature, and humidity between flight level and the sea surface. Data from the ODWs are transmitted back to the aircraft and then sent via satellite to the Tropical Prediction Center and the National Centers for Environmental Prediction (NCEP), where the observations become part of the operational database.
This paper tests the hypothesis that additional observations improve the objective track forecast models that provide operational guidance to the hurricane forecasters. The testing evaluates differences in forecast tracks from models run with and without the ODW data in a research mode at HRD, NCEP, and the Geophysical Fluid Dynamics Laboratory. The middle- and lower-tropospheric ODW data produce statistically significant reductions in 12–60-h mean forecast errors. The error reductions, which range from 16% to 30%, are at least as large as the accumulated improvement in operational forecasts achieved over the last 20–25 years. This breakthrough provides strong experimental evidence that more comprehensive observations in the hurricane environment and core will lead to immediate improvements in operational forecast guidance.
Since 1982, the Hurricane Research Division (HRD) has conducted a series of experiments with research aircraft to enhance the number of observations in the environment and the core of hurricanes threatening the United States. During these experiments, the National Oceanic and Atmospheric Administration WP-3D aircraft crews release Omega dropwindsondes (ODWs) at 15–20-min intervals along the flight track to obtain profiles of wind, temperature, and humidity between flight level and the sea surface. Data from the ODWs are transmitted back to the aircraft and then sent via satellite to the Tropical Prediction Center and the National Centers for Environmental Prediction (NCEP), where the observations become part of the operational database.
This paper tests the hypothesis that additional observations improve the objective track forecast models that provide operational guidance to the hurricane forecasters. The testing evaluates differences in forecast tracks from models run with and without the ODW data in a research mode at HRD, NCEP, and the Geophysical Fluid Dynamics Laboratory. The middle- and lower-tropospheric ODW data produce statistically significant reductions in 12–60-h mean forecast errors. The error reductions, which range from 16% to 30%, are at least as large as the accumulated improvement in operational forecasts achieved over the last 20–25 years. This breakthrough provides strong experimental evidence that more comprehensive observations in the hurricane environment and core will lead to immediate improvements in operational forecast guidance.
The Joint Hurricane Testbed (JHT) is reviewed at the completion of its first decade. Views of the program by hurricane forecasters at the National Hurricane Center, the test bed's impact on forecast accuracy, and highlights of the top-rated projects are presented. Key concerns encountered by the test bed are identified as possible “lessons learned” for future research-to-operations efforts. The paper concludes with thoughts on the potential changing role of the JHT.
The Joint Hurricane Testbed (JHT) is reviewed at the completion of its first decade. Views of the program by hurricane forecasters at the National Hurricane Center, the test bed's impact on forecast accuracy, and highlights of the top-rated projects are presented. Key concerns encountered by the test bed are identified as possible “lessons learned” for future research-to-operations efforts. The paper concludes with thoughts on the potential changing role of the JHT.
Hurricane Andrew of 1992 caused unprecedented economic devastation along its path through the Bahamas, southeastern Florida, and Louisiana. Damage in the United States was estimated to be $26 billion (in 1992 dollars), making Andrew one of the most expensive natural disasters in U.S. history. This hurricane struck southeastern Florida with maximum 1-min surface winds estimated in a 1992 poststorm analysis at 125 kt (64 m s−1). This original assessment was primarily based on an adjustment of aircraft reconnaissance flight-level winds to the surface.
Based on recent advancements in the understanding of the eyewall wind structure of major hurricanes, the official intensity of Andrew was adjusted upward for five days during its track across the Atlantic Ocean and Gulf of Mexico by the National Hurricane Center Best Track Change Committee. In particular, Andrew is now assessed by the National Hurricane Center to be a Saffir–Simpson Hurricane Scale category-5 hurricane (the highest intensity category possible) at its landfall in southeastern Florida, with maximum 1-min winds of 145 kt (75 m s−1). This makes Andrew only the third category-5 hurricane to strike the United States since at least 1900. Implications for how this change impacts society's planning for such extreme events are discussed.
Hurricane Andrew of 1992 caused unprecedented economic devastation along its path through the Bahamas, southeastern Florida, and Louisiana. Damage in the United States was estimated to be $26 billion (in 1992 dollars), making Andrew one of the most expensive natural disasters in U.S. history. This hurricane struck southeastern Florida with maximum 1-min surface winds estimated in a 1992 poststorm analysis at 125 kt (64 m s−1). This original assessment was primarily based on an adjustment of aircraft reconnaissance flight-level winds to the surface.
Based on recent advancements in the understanding of the eyewall wind structure of major hurricanes, the official intensity of Andrew was adjusted upward for five days during its track across the Atlantic Ocean and Gulf of Mexico by the National Hurricane Center Best Track Change Committee. In particular, Andrew is now assessed by the National Hurricane Center to be a Saffir–Simpson Hurricane Scale category-5 hurricane (the highest intensity category possible) at its landfall in southeastern Florida, with maximum 1-min winds of 145 kt (75 m s−1). This makes Andrew only the third category-5 hurricane to strike the United States since at least 1900. Implications for how this change impacts society's planning for such extreme events are discussed.
The Hurricane Research Division (HRD) is NOAA's primary component for research on tropical cyclones. In accomplishing research goals, many staff members have developed analysis procedures and forecast models that not only help improve the understanding of hurricane structure, motion, and intensity change, but also provide operational support for forecasters at the National Hurricane Center (NHC). During the 1993 hurricane season, HRD demonstrated three important real-time capabilities for the first time. These achievements included the successful transmission of a series of color radar reflectivity images from the NOAA research aircraft to NHC, the operational availability of objective mesoscale streamline and isotach analyses of a hurricane surface wind field, and the transition of the experimental dropwindsonde program on the periphery of hurricanes to a technology capable of supporting operational requirements. Examples of these and other real-time capabilities are presented for Hurricane Emily.
The Hurricane Research Division (HRD) is NOAA's primary component for research on tropical cyclones. In accomplishing research goals, many staff members have developed analysis procedures and forecast models that not only help improve the understanding of hurricane structure, motion, and intensity change, but also provide operational support for forecasters at the National Hurricane Center (NHC). During the 1993 hurricane season, HRD demonstrated three important real-time capabilities for the first time. These achievements included the successful transmission of a series of color radar reflectivity images from the NOAA research aircraft to NHC, the operational availability of objective mesoscale streamline and isotach analyses of a hurricane surface wind field, and the transition of the experimental dropwindsonde program on the periphery of hurricanes to a technology capable of supporting operational requirements. Examples of these and other real-time capabilities are presented for Hurricane Emily.
