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- Author or Editor: Michael C. Kruk x
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Abstract
Numerous agencies around the world perform postseason analysis of tropical cyclone position and intensity, a process described as “best tracking.” However, this process is temporally and spatially inhomogeneous because data availability, operational techniques, and knowledge have changed over time and differ among agencies. The net result is that positions and intensities often vary for any given storm for different agencies. In light of these differences, it is imperative to analyze and document the interagency differences in tropical cyclone intensities. To that end, maximum sustained winds from different agencies were compared using data from the International Best Track Archive for Climate Stewardship (IBTrACS) global tropical cyclone dataset. Comparisons were made for a recent 5-yr period to investigate the current differences, where linear systematic differences were evident. Time series of the comparisons also showed temporal changes in the systematic differences, which suggest changes in operational procedures. Initial attempts were made to normalize maximum sustained winds by correcting for known changes in operational procedures. The result was mixed, in that the adjustments removed some but not all of the systematic differences. This suggests that more details on operational procedures are needed and that a complete reanalysis of tropical cyclone intensities should be performed.
Abstract
Numerous agencies around the world perform postseason analysis of tropical cyclone position and intensity, a process described as “best tracking.” However, this process is temporally and spatially inhomogeneous because data availability, operational techniques, and knowledge have changed over time and differ among agencies. The net result is that positions and intensities often vary for any given storm for different agencies. In light of these differences, it is imperative to analyze and document the interagency differences in tropical cyclone intensities. To that end, maximum sustained winds from different agencies were compared using data from the International Best Track Archive for Climate Stewardship (IBTrACS) global tropical cyclone dataset. Comparisons were made for a recent 5-yr period to investigate the current differences, where linear systematic differences were evident. Time series of the comparisons also showed temporal changes in the systematic differences, which suggest changes in operational procedures. Initial attempts were made to normalize maximum sustained winds by correcting for known changes in operational procedures. The result was mixed, in that the adjustments removed some but not all of the systematic differences. This suggests that more details on operational procedures are needed and that a complete reanalysis of tropical cyclone intensities should be performed.
Abstract
Best track data generally consist of the positions and intensities during the life cycle of a tropical cyclone. Despite the widespread interest in the distribution, frequency, and intensity of tropical cyclones worldwide, no publicly available central repository of global best track data from international agencies has been in existence. While there are numerous international centers that forecast tropical cyclones and archive best track data for their defined regions, most researchers traditionally use best track data from a very small subset of centers to construct global datasets and climatologies. This practice results in tropical cyclones that are either missed and/or misrepresented. While the process of combining positions and intensities from disparate data sources can be arduous, it is worthwhile and necessary in light of their importance. The nature of historical best track data is that they are prone to issues with intensity (maximum surface wind and minimum central pressure), especially in the presatellite era. This study is not a reanalysis effort and makes no attempt to correct any longstanding debates about the accuracy of the historical data. Rather, it simply and objectively combines all of the best track data from each of the regional forecast centers that provided best tracks into one single point for distribution, and the methods used to construct the dataset are the focus of this work. Processes are therefore described herein that detail the combining of tropical cyclone best track data with the techniques used to assess the quality of the minimum central pressure and maximum sustained wind speed of each reported tropical cyclone. The result is a comprehensive global best track compilation dataset that contains information on all documented tropical cyclones: the International Best Track Archive for Climate Stewardship (IBTrACS).
Abstract
Best track data generally consist of the positions and intensities during the life cycle of a tropical cyclone. Despite the widespread interest in the distribution, frequency, and intensity of tropical cyclones worldwide, no publicly available central repository of global best track data from international agencies has been in existence. While there are numerous international centers that forecast tropical cyclones and archive best track data for their defined regions, most researchers traditionally use best track data from a very small subset of centers to construct global datasets and climatologies. This practice results in tropical cyclones that are either missed and/or misrepresented. While the process of combining positions and intensities from disparate data sources can be arduous, it is worthwhile and necessary in light of their importance. The nature of historical best track data is that they are prone to issues with intensity (maximum surface wind and minimum central pressure), especially in the presatellite era. This study is not a reanalysis effort and makes no attempt to correct any longstanding debates about the accuracy of the historical data. Rather, it simply and objectively combines all of the best track data from each of the regional forecast centers that provided best tracks into one single point for distribution, and the methods used to construct the dataset are the focus of this work. Processes are therefore described herein that detail the combining of tropical cyclone best track data with the techniques used to assess the quality of the minimum central pressure and maximum sustained wind speed of each reported tropical cyclone. The result is a comprehensive global best track compilation dataset that contains information on all documented tropical cyclones: the International Best Track Archive for Climate Stewardship (IBTrACS).
Abstract
This study analyzes 25 years of Special Sensor Microwave Imager (SSM/I) retrievals of rain rate and wind speed to assess changes in storminess over the open water of the Pacific Ocean. Changes in storminess are characterized by combining trends in both the statistically derived 95th percentile exceedance frequencies of rain rate and wind speed (i.e., extremes). Storminess is computed annually and seasonally, with further partitioning done by phase of the El Niño–Southern Oscillation (ENSO) index and the Pacific decadal oscillation (PDO) index. Overall, rain-rate exceedance frequencies of 6–8 mm h−1 cover most of the western and central tropical Pacific, with higher values present around the Philippines, Japan, Mexico, and the northwest coast of Australia. Wind speed exceedance frequencies are a strong function of latitude, with values less (greater) than 12 m s−1 equatorward (poleward) of 30°N/S. Statistically significant increasing trends in rain rate were found in the western tropical Pacific near the Caroline Islands and the Solomon Islands, and in the extratropics from the Aleutian Islands down the coast along British Columbia and Washington State. Statistically significant increasing trends in wind speed are present in the equatorial central Pacific near Kiribati and the Republic of the Marshall Islands (RMI), and in the extratropics along the west coast of the United States and Canada. Thus, while extreme rain and winds are both increasing across large areas of the Pacific, these areas are modulated according to the phase of ENSO and the PDO, and their intersection takes aim at specific locations.
Abstract
This study analyzes 25 years of Special Sensor Microwave Imager (SSM/I) retrievals of rain rate and wind speed to assess changes in storminess over the open water of the Pacific Ocean. Changes in storminess are characterized by combining trends in both the statistically derived 95th percentile exceedance frequencies of rain rate and wind speed (i.e., extremes). Storminess is computed annually and seasonally, with further partitioning done by phase of the El Niño–Southern Oscillation (ENSO) index and the Pacific decadal oscillation (PDO) index. Overall, rain-rate exceedance frequencies of 6–8 mm h−1 cover most of the western and central tropical Pacific, with higher values present around the Philippines, Japan, Mexico, and the northwest coast of Australia. Wind speed exceedance frequencies are a strong function of latitude, with values less (greater) than 12 m s−1 equatorward (poleward) of 30°N/S. Statistically significant increasing trends in rain rate were found in the western tropical Pacific near the Caroline Islands and the Solomon Islands, and in the extratropics from the Aleutian Islands down the coast along British Columbia and Washington State. Statistically significant increasing trends in wind speed are present in the equatorial central Pacific near Kiribati and the Republic of the Marshall Islands (RMI), and in the extratropics along the west coast of the United States and Canada. Thus, while extreme rain and winds are both increasing across large areas of the Pacific, these areas are modulated according to the phase of ENSO and the PDO, and their intersection takes aim at specific locations.
Abstract
Tropical cyclones pose a significant threat to life and property along coastal regions of the United States. As these systems move inland and dissipate, they can also pose a threat to life and property, through heavy rains, high winds, and other severe weather such as tornadoes. While many studies have focused on the impacts from tropical cyclones on coastal counties of the United States, this study goes beyond the coast and examines the impacts caused by tropical cyclones on inland locations. Using geographical information system software, historical track data are used in conjunction with the radial maximum extent of the maximum sustained winds at 34-, 50-, and 64-kt (1 kt ≈ 0.5 m s−1) thresholds for all intensities of tropical cyclones and overlaid on a 30-km equal-area grid that covers the eastern half of the United States. The result is a series of maps with frequency distributions and an estimation of return intervals for inland tropical storm– and hurricane-force winds. Knowing where the climatologically favored areas are for tropical cyclones, combined with a climatological expectation of the inland penetration frequency of these storms, can be of tremendous value to forecasters, emergency managers, and the public.
Abstract
Tropical cyclones pose a significant threat to life and property along coastal regions of the United States. As these systems move inland and dissipate, they can also pose a threat to life and property, through heavy rains, high winds, and other severe weather such as tornadoes. While many studies have focused on the impacts from tropical cyclones on coastal counties of the United States, this study goes beyond the coast and examines the impacts caused by tropical cyclones on inland locations. Using geographical information system software, historical track data are used in conjunction with the radial maximum extent of the maximum sustained winds at 34-, 50-, and 64-kt (1 kt ≈ 0.5 m s−1) thresholds for all intensities of tropical cyclones and overlaid on a 30-km equal-area grid that covers the eastern half of the United States. The result is a series of maps with frequency distributions and an estimation of return intervals for inland tropical storm– and hurricane-force winds. Knowing where the climatologically favored areas are for tropical cyclones, combined with a climatological expectation of the inland penetration frequency of these storms, can be of tremendous value to forecasters, emergency managers, and the public.
Abstract
Within the realm of climate and environmental sciences, stakeholder engagement has traditionally been given a relative low priority in favor of generating tools, products, and services following the longstanding practice of pushing out information in the hopes users will pull it into their decision toolkits. However, the landscape is gradually shifting away from that paradigm and toward one in which the stakeholder community is more directly involved in the production of products and services with the scientific organization. This mutual learning arrangement, referred to as the coproduction of knowledge, has been applied to two user engagement activities within the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) and the NOAA Office of Coastal Management (OCM) Coral Reef Conservation Program (CRCP). The iterative nature of such dialogues helped scientists within NCEI and OCM to better understand user requirements and as a result generate climate information that was locally relevant and regionally applicable. The recent engagement activities exemplified the benefits of a robust and sustained relationship between climate scientists and the user community. They demonstrate that the interactions between the two led to the empowerment of the local community to shape and mold climate information products as well as further enhancing user buy in of these products and services with which local agriculture and food security, disaster risk reduction, energy, health, and water decisions are being made. This coproduction of knowledge model for user engagement activities also serves to build trust between the scientific and user communities.
Abstract
Within the realm of climate and environmental sciences, stakeholder engagement has traditionally been given a relative low priority in favor of generating tools, products, and services following the longstanding practice of pushing out information in the hopes users will pull it into their decision toolkits. However, the landscape is gradually shifting away from that paradigm and toward one in which the stakeholder community is more directly involved in the production of products and services with the scientific organization. This mutual learning arrangement, referred to as the coproduction of knowledge, has been applied to two user engagement activities within the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) and the NOAA Office of Coastal Management (OCM) Coral Reef Conservation Program (CRCP). The iterative nature of such dialogues helped scientists within NCEI and OCM to better understand user requirements and as a result generate climate information that was locally relevant and regionally applicable. The recent engagement activities exemplified the benefits of a robust and sustained relationship between climate scientists and the user community. They demonstrate that the interactions between the two led to the empowerment of the local community to shape and mold climate information products as well as further enhancing user buy in of these products and services with which local agriculture and food security, disaster risk reduction, energy, health, and water decisions are being made. This coproduction of knowledge model for user engagement activities also serves to build trust between the scientific and user communities.
Abstract
There are more than 2,000 islands across Hawaii and the U.S.-Affiliated Pacific Islands (USAPI), where freshwater resources are heavily dependent upon rainfall. Many of the islands experience dramatic variations in precipitation during the different phases of the El Niño–Southern Oscillation (ENSO). Traditionally, forecasters in the region relied on ENSO climatologies based on spatially limited in situ data to inform their seasonal precipitation outlooks. To address this gap, a unique NOAA/NASA collaborative project updated the ENSO-based rainfall climatology for the Exclusive Economic Zones (EEZs) encompassing Hawaii and the USAPI using NOAA’s PERSIANN Climate Data Record (CDR). The PERSIANN-CDR provides a 30-yr record of global daily precipitation at 0.25° resolution (∼750 km2 near the equator). This project took place over a 10- week NASA DEVELOP National Program term and resulted in a 478-page climatic reference atlas. This atlas is based on a 30-yr period from 1 January 1985 through 31 December 2014 and complements station data by offering an enhanced spatial representation of rainfall averages.
Regional and EEZ-specific maps throughout the atlas illustrate the percent departure from average for each season based on the Oceanic Niño Index (ONI) for different ENSO phases. To facilitate intercomparisons across locations, this percentage-based climatology was provided to regional climatologists, forecasters, and outreach experts within the region. Anomalous wet and dry maps for each ENSO phase are used by the regional constituents to better understand precipitation patterns across their regions and to produce more accurate forecasts to inform adaptation, conservation, and mitigation options for drought and f looding events.
Abstract
There are more than 2,000 islands across Hawaii and the U.S.-Affiliated Pacific Islands (USAPI), where freshwater resources are heavily dependent upon rainfall. Many of the islands experience dramatic variations in precipitation during the different phases of the El Niño–Southern Oscillation (ENSO). Traditionally, forecasters in the region relied on ENSO climatologies based on spatially limited in situ data to inform their seasonal precipitation outlooks. To address this gap, a unique NOAA/NASA collaborative project updated the ENSO-based rainfall climatology for the Exclusive Economic Zones (EEZs) encompassing Hawaii and the USAPI using NOAA’s PERSIANN Climate Data Record (CDR). The PERSIANN-CDR provides a 30-yr record of global daily precipitation at 0.25° resolution (∼750 km2 near the equator). This project took place over a 10- week NASA DEVELOP National Program term and resulted in a 478-page climatic reference atlas. This atlas is based on a 30-yr period from 1 January 1985 through 31 December 2014 and complements station data by offering an enhanced spatial representation of rainfall averages.
Regional and EEZ-specific maps throughout the atlas illustrate the percent departure from average for each season based on the Oceanic Niño Index (ONI) for different ENSO phases. To facilitate intercomparisons across locations, this percentage-based climatology was provided to regional climatologists, forecasters, and outreach experts within the region. Anomalous wet and dry maps for each ENSO phase are used by the regional constituents to better understand precipitation patterns across their regions and to produce more accurate forecasts to inform adaptation, conservation, and mitigation options for drought and f looding events.
The International Best Track Archive for Climate Stewardship (IBTrACS)
Unifying Tropical Cyclone Data
The goal of the International Best Track Archive for Climate Stewardship (IBTrACS) project is to collect the historical tropical cyclone best-track data from all available Regional Specialized Meteorological Centers (RSMCs) and other agencies, combine the disparate datasets into one product, and disseminate in formats used by the tropical cyclone community. Each RSMC forecasts and monitors storms for a specific region and annually archives best-track data, which consist of information on a storm's position, intensity, and other related parameters. IBTrACS is a new dataset based on the best-track data from numerous sources. Moreover, rather than preferentially selecting one track and intensity for each storm, the mean position, the original intensities from the agencies, and summary statistics are provided. This article discusses the dataset construction, explores the tropical cyclone climatology from IBTrACS, and concludes with an analysis of uncertainty in the tropical cyclone intensity record.
The goal of the International Best Track Archive for Climate Stewardship (IBTrACS) project is to collect the historical tropical cyclone best-track data from all available Regional Specialized Meteorological Centers (RSMCs) and other agencies, combine the disparate datasets into one product, and disseminate in formats used by the tropical cyclone community. Each RSMC forecasts and monitors storms for a specific region and annually archives best-track data, which consist of information on a storm's position, intensity, and other related parameters. IBTrACS is a new dataset based on the best-track data from numerous sources. Moreover, rather than preferentially selecting one track and intensity for each storm, the mean position, the original intensities from the agencies, and summary statistics are provided. This article discusses the dataset construction, explores the tropical cyclone climatology from IBTrACS, and concludes with an analysis of uncertainty in the tropical cyclone intensity record.
Abstract
A recent comprehensive effort to digitize U.S. daily temperature and precipitation data observed prior to 1948 has resulted in a major enhancement in the computer database of the records of the National Weather Service’s cooperative observer network. Previous digitization efforts had been selective, concentrating on state or regional areas. Special quality control procedures were applied to these data to enhance their value for climatological analysis. The procedures involved a two-step process. In the first step, each individual temperature and precipitation data value was evaluated against a set of objective screening criteria to flag outliers. These criteria included extreme limits and spatial comparisons with nearby stations. The following data were automatically flagged: 1) all precipitation values exceeding 254 mm (10 in.) and 2) all temperature values whose anomaly from the monthly mean for that station exceeded five standard deviations. Additional values were flagged based on differences with nearby stations; in this case, metrics were used to rank outliers so that the limited resources were concentrated on those values most likely to be invalid. In the second step, each outlier was manually assessed by climatologists and assigned one of the four following flags: valid, plausible, questionable, or invalid. In excess of 22 400 values were manually assessed, of which about 48% were judged to be invalid. Although additional manual assessment of outliers might further improve the quality of the database, the procedures applied in this study appear to have been successful in identifying the most flagrant errors.
Abstract
A recent comprehensive effort to digitize U.S. daily temperature and precipitation data observed prior to 1948 has resulted in a major enhancement in the computer database of the records of the National Weather Service’s cooperative observer network. Previous digitization efforts had been selective, concentrating on state or regional areas. Special quality control procedures were applied to these data to enhance their value for climatological analysis. The procedures involved a two-step process. In the first step, each individual temperature and precipitation data value was evaluated against a set of objective screening criteria to flag outliers. These criteria included extreme limits and spatial comparisons with nearby stations. The following data were automatically flagged: 1) all precipitation values exceeding 254 mm (10 in.) and 2) all temperature values whose anomaly from the monthly mean for that station exceeded five standard deviations. Additional values were flagged based on differences with nearby stations; in this case, metrics were used to rank outliers so that the limited resources were concentrated on those values most likely to be invalid. In the second step, each outlier was manually assessed by climatologists and assigned one of the four following flags: valid, plausible, questionable, or invalid. In excess of 22 400 values were manually assessed, of which about 48% were judged to be invalid. Although additional manual assessment of outliers might further improve the quality of the database, the procedures applied in this study appear to have been successful in identifying the most flagrant errors.
