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Abstract
Reliable estimates of future changes in extreme weather phenomena, such as tropical cyclone maximum wind speeds, are critical for climate change impact assessments and the development of appropriate adaptation strategies. However, global and regional climate model outputs are often too coarse for direct use in these applications, with variables such as wind speed having truncated probability distributions compared to those of observations. This poses two problems: How can model-simulated variables best be adjusted to make them more realistic? And how can such adjustments be used to make more reliable predictions of future changes in their distribution?
This study investigates North Atlantic tropical cyclone maximum wind speeds from observations (1950–2010) and regional climate model simulations (1995–2005 and 2045–55 at 12- and 36-km spatial resolutions). The wind speed distributions in these datasets are well represented by the Weibull distribution, albeit with different scale and shape parameters.
A power-law transfer function is used to recalibrate the Weibull variables and obtain future projections of wind speeds. Two different strategies, bias correction and change factor, are tested by using 36-km model data to predict future 12-km model data (pseudo-observations). The strategies are also applied to the observations to obtain likely predictions of the future distributions of wind speeds. The strategies yield similar predictions of likely changes in the fraction of events within Saffir–Simpson categories—for example, an increase from 21% (1995–2005) to 27%–37% (2045–55) for category 3 or above events and an increase from 1.6% (1995–2005) to 2.8%–9.8% (2045–55) for category 5 events.
Abstract
Reliable estimates of future changes in extreme weather phenomena, such as tropical cyclone maximum wind speeds, are critical for climate change impact assessments and the development of appropriate adaptation strategies. However, global and regional climate model outputs are often too coarse for direct use in these applications, with variables such as wind speed having truncated probability distributions compared to those of observations. This poses two problems: How can model-simulated variables best be adjusted to make them more realistic? And how can such adjustments be used to make more reliable predictions of future changes in their distribution?
This study investigates North Atlantic tropical cyclone maximum wind speeds from observations (1950–2010) and regional climate model simulations (1995–2005 and 2045–55 at 12- and 36-km spatial resolutions). The wind speed distributions in these datasets are well represented by the Weibull distribution, albeit with different scale and shape parameters.
A power-law transfer function is used to recalibrate the Weibull variables and obtain future projections of wind speeds. Two different strategies, bias correction and change factor, are tested by using 36-km model data to predict future 12-km model data (pseudo-observations). The strategies are also applied to the observations to obtain likely predictions of the future distributions of wind speeds. The strategies yield similar predictions of likely changes in the fraction of events within Saffir–Simpson categories—for example, an increase from 21% (1995–2005) to 27%–37% (2045–55) for category 3 or above events and an increase from 1.6% (1995–2005) to 2.8%–9.8% (2045–55) for category 5 events.
The outlook for tropical cyclone intensity forecasts from operational and from research perspectives was discussed during a panel discussion at the 19th Conference on Hurricanes and Tropical Meteorology. Whereas the operational requirement at the National Hurricane Center is to predict maximum 1-min sustained wind speeds at specific locations, the research community is addressing the prediction of the maximum wind or minimum sea level pressure in the storm. Commonality was found in the forecast strategies for subjectively predicting storm intensity. The panelists suggested improvements may be gained from additional observations, better conceptual and theoretical models of storm structure and behavior, and enhancements in statistical and numerical models.
The discussion period brought out opposing viewpoints on a number of topics. Both new observations and better use of the existing observations were believed to be necessary. The limitations and advantages of remotely sensed data for this problem were raised. The most vigorous debates were on the physical processes, such as existence or nonexistence of coupling between outer and inner core structure, and whether convection is simply a response to forcing or is an essential contributor to uncertainty in intensity forecasting. Several participants suggested that uncertainties related to the sea surface temperature and its evolution also contribute to the intensity forecast problem. Some specific suggestions for improving intensity forecasts are given in terms of new observations, new basic understandings, and new applied developments.
The outlook for tropical cyclone intensity forecasts from operational and from research perspectives was discussed during a panel discussion at the 19th Conference on Hurricanes and Tropical Meteorology. Whereas the operational requirement at the National Hurricane Center is to predict maximum 1-min sustained wind speeds at specific locations, the research community is addressing the prediction of the maximum wind or minimum sea level pressure in the storm. Commonality was found in the forecast strategies for subjectively predicting storm intensity. The panelists suggested improvements may be gained from additional observations, better conceptual and theoretical models of storm structure and behavior, and enhancements in statistical and numerical models.
The discussion period brought out opposing viewpoints on a number of topics. Both new observations and better use of the existing observations were believed to be necessary. The limitations and advantages of remotely sensed data for this problem were raised. The most vigorous debates were on the physical processes, such as existence or nonexistence of coupling between outer and inner core structure, and whether convection is simply a response to forcing or is an essential contributor to uncertainty in intensity forecasting. Several participants suggested that uncertainties related to the sea surface temperature and its evolution also contribute to the intensity forecast problem. Some specific suggestions for improving intensity forecasts are given in terms of new observations, new basic understandings, and new applied developments.
Abstract
Initialization of the hurricane vortex in weather prediction models is vital to intensity forecasts out to at least 48 h. Airborne Doppler radar (ADR) data have sufficiently high horizontal and vertical resolution to resolve the hurricane vortex and its imbedded structures but have not been extensively used in hurricane initialization. Using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation (3DVAR) system, the ADR data are assimilated to recover the hurricane vortex dynamic and thermodynamic structures at the WRF model initial time. The impact of the ADR data on three hurricanes, Jeanne (2004), Katrina (2005) and Rita (2005), are examined during their rapid intensification and subsequent weakening periods before landfall.
With the ADR wind data assimilated, the three-dimensional winds in the hurricane vortex become stronger and the maximum 10-m winds agree better with independent estimates from best-track data than without ADR data assimilation. Through the multivariate incremental structure in WRF 3DVAR analysis, the central sea level pressures (CSLPs) for the three hurricanes are lower in response to the stronger vortex at initialization. The size and inner-core structure of each vortex are adjusted closer to observations of these attributes. Addition of reflectivity data in assimilation produces cloud water and rainwater analyses in the initial vortex. The temperature and moisture are also better represented in the hurricane initialization.
Forty-eight-hour forecasts are conducted to evaluate the impact of ADR data using the Advanced Research Hurricane WRF (AHW), a derivative of the Advanced Research WRF (ARW) model. Assimilation of ADR data improves the hurricane-intensity forecasts. Vortex asymmetries, size, and rainbands are also simulated better. Hurricane initialization with ADR data is quite promising toward reducing intensity forecast errors at modest computational expense.
Abstract
Initialization of the hurricane vortex in weather prediction models is vital to intensity forecasts out to at least 48 h. Airborne Doppler radar (ADR) data have sufficiently high horizontal and vertical resolution to resolve the hurricane vortex and its imbedded structures but have not been extensively used in hurricane initialization. Using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation (3DVAR) system, the ADR data are assimilated to recover the hurricane vortex dynamic and thermodynamic structures at the WRF model initial time. The impact of the ADR data on three hurricanes, Jeanne (2004), Katrina (2005) and Rita (2005), are examined during their rapid intensification and subsequent weakening periods before landfall.
With the ADR wind data assimilated, the three-dimensional winds in the hurricane vortex become stronger and the maximum 10-m winds agree better with independent estimates from best-track data than without ADR data assimilation. Through the multivariate incremental structure in WRF 3DVAR analysis, the central sea level pressures (CSLPs) for the three hurricanes are lower in response to the stronger vortex at initialization. The size and inner-core structure of each vortex are adjusted closer to observations of these attributes. Addition of reflectivity data in assimilation produces cloud water and rainwater analyses in the initial vortex. The temperature and moisture are also better represented in the hurricane initialization.
Forty-eight-hour forecasts are conducted to evaluate the impact of ADR data using the Advanced Research Hurricane WRF (AHW), a derivative of the Advanced Research WRF (ARW) model. Assimilation of ADR data improves the hurricane-intensity forecasts. Vortex asymmetries, size, and rainbands are also simulated better. Hurricane initialization with ADR data is quite promising toward reducing intensity forecast errors at modest computational expense.
Abstract
The major field phase of the Australian Monsoon Experiment (AMEX Phase II) was conducted over northern Australia from 1 0 January to 1 5 February 1987. It was based on the collection of high-density tropical upper air soundings and radar data at 12 special observation sites. These were complemented by satellite and surface data, the existing upper air network, and two simultaneous aircraft based tropical experiments.
This paper describes the data collected in AMEX and the mean and transient structure of the Australian monsoon circulation during the experiment. Mean soundings across the network am compared with each other and with soundings from other commonly used research datasets.
It is shown that an active monsoon trough lay through the AMEX network, and that the associated convection is located within one of the three global tropical heat sources. Active and inactive periods of monsoon behavior are defined. Monsoon onset occurred within the period of the experiment and four tropical cyclones existed within the enhanced network. Two of these developed inside an array of radiosondes surrounding the Gulf of Carpentaria.
Abstract
The major field phase of the Australian Monsoon Experiment (AMEX Phase II) was conducted over northern Australia from 1 0 January to 1 5 February 1987. It was based on the collection of high-density tropical upper air soundings and radar data at 12 special observation sites. These were complemented by satellite and surface data, the existing upper air network, and two simultaneous aircraft based tropical experiments.
This paper describes the data collected in AMEX and the mean and transient structure of the Australian monsoon circulation during the experiment. Mean soundings across the network am compared with each other and with soundings from other commonly used research datasets.
It is shown that an active monsoon trough lay through the AMEX network, and that the associated convection is located within one of the three global tropical heat sources. Active and inactive periods of monsoon behavior are defined. Monsoon onset occurred within the period of the experiment and four tropical cyclones existed within the enhanced network. Two of these developed inside an array of radiosondes surrounding the Gulf of Carpentaria.
Abstract
The design concept and operational trial of a fully interactive analysis and numerical forecast system for tropical-cyclone motion are described. The design concept emphasizes an interactive system in which forecasters can test various scenarios objectively, rather than having to subjectively decide between conflicting forecasts from standardized techniques. The system is designed for use on a personal computer, or workstation, located on the forecast bench. A choice of a Barnes or statistical interpolation scheme is provided to analyze raw or bogus observations at any atmospheric level or layer mean selected by the forecaster. The track forecast is then made by integration of a nondivergent barotropic model.
An operational trial during the 1990 tropical-cyclone field experiments in the western north Pacific Ocean indicated that the system can be used very effectively in real time. A series of case-study examples is presented.
Abstract
The design concept and operational trial of a fully interactive analysis and numerical forecast system for tropical-cyclone motion are described. The design concept emphasizes an interactive system in which forecasters can test various scenarios objectively, rather than having to subjectively decide between conflicting forecasts from standardized techniques. The system is designed for use on a personal computer, or workstation, located on the forecast bench. A choice of a Barnes or statistical interpolation scheme is provided to analyze raw or bogus observations at any atmospheric level or layer mean selected by the forecaster. The track forecast is then made by integration of a nondivergent barotropic model.
An operational trial during the 1990 tropical-cyclone field experiments in the western north Pacific Ocean indicated that the system can be used very effectively in real time. A series of case-study examples is presented.
The BMRC Australian Monsoon Experiment is part of a concerted tropical research program aimed at improving our understanding of the physics and dynamics of tropical weather systems. It is based on the collection of high-density tropical upper-air soundings and radar data during two observational phases in October 1986 and January/February 1987. The objectives, background, and rationale for this program are described together with an overview of the design and timetable of the observing component.
The BMRC Australian Monsoon Experiment is part of a concerted tropical research program aimed at improving our understanding of the physics and dynamics of tropical weather systems. It is based on the collection of high-density tropical upper-air soundings and radar data during two observational phases in October 1986 and January/February 1987. The objectives, background, and rationale for this program are described together with an overview of the design and timetable of the observing component.