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Abstract
Cook and Nicholls recently argued in this journal that the city of Darwin (Northern Territory), Australia, should be located in wind region D rather than in the current region C in the Australian/New Zealand Standard AS/NZS 1170.2 wind actions standard, in which region D has significantly higher risk. These comments critically examine the methods used by Cook and Nicholls and find serious flaws in them, sufficient to invalidate their conclusions. Specific flaws include 1) invalid assumptions in their analysis method, including that cyclones are assumed to be at the maximum intensity along their entire path across the sampling circle even after they have crossed extensive land areas; 2) a lack of verification that the simulated cyclone tracks are consistent with the known climatological data and in particular that the annual rate of simulated cyclones at each station greatly exceeds the numbers recorded for the entire Australian region; and 3) the apparent omission of key cyclones when comparing the risk at Darwin with two other locations. It is shown here that the number of cyclones that have affected Port Hedland (Western Australia), a site in Australia’s region D, greatly exceeds the number that have influenced Darwin over the same period for any chosen threshold of intensity. Analysis of the recorded gusts from anemometers at Port Hedland and Darwin that is presented here further supports this result. On the basis of this evidence, the authors conclude that Darwin’s tropical cyclone wind risk is adequately described by its current location in region C.
Abstract
Cook and Nicholls recently argued in this journal that the city of Darwin (Northern Territory), Australia, should be located in wind region D rather than in the current region C in the Australian/New Zealand Standard AS/NZS 1170.2 wind actions standard, in which region D has significantly higher risk. These comments critically examine the methods used by Cook and Nicholls and find serious flaws in them, sufficient to invalidate their conclusions. Specific flaws include 1) invalid assumptions in their analysis method, including that cyclones are assumed to be at the maximum intensity along their entire path across the sampling circle even after they have crossed extensive land areas; 2) a lack of verification that the simulated cyclone tracks are consistent with the known climatological data and in particular that the annual rate of simulated cyclones at each station greatly exceeds the numbers recorded for the entire Australian region; and 3) the apparent omission of key cyclones when comparing the risk at Darwin with two other locations. It is shown here that the number of cyclones that have affected Port Hedland (Western Australia), a site in Australia’s region D, greatly exceeds the number that have influenced Darwin over the same period for any chosen threshold of intensity. Analysis of the recorded gusts from anemometers at Port Hedland and Darwin that is presented here further supports this result. On the basis of this evidence, the authors conclude that Darwin’s tropical cyclone wind risk is adequately described by its current location in region C.
The history of meteorology has taught us that weather analysis and prediction usually advances by a series of small, progressive studies. Occasionally, however, a special body of work can accelerate this process. When that work pertains to high-impact weather events that can affect large populations, it is especially notable. In this paper we review the contributions by Vernon F. Dvorak, whose innovations using satellite observations of cloud patterns fundamentally enhanced the ability to monitor tropical cyclones on a global scale. We discuss how his original technique has progressed, and the ways in which new spaceborne instruments are being employed to complement Dvorak's original visions.
The history of meteorology has taught us that weather analysis and prediction usually advances by a series of small, progressive studies. Occasionally, however, a special body of work can accelerate this process. When that work pertains to high-impact weather events that can affect large populations, it is especially notable. In this paper we review the contributions by Vernon F. Dvorak, whose innovations using satellite observations of cloud patterns fundamentally enhanced the ability to monitor tropical cyclones on a global scale. We discuss how his original technique has progressed, and the ways in which new spaceborne instruments are being employed to complement Dvorak's original visions.
Abstract
Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.
Abstract
Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.
