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- Author or Editor: M. A. ALAKA x
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Abstract
Observations made by the specially instrumented aircraft, operated by the National Hurricane Research Project, establish the occurrence of dynamic instability, notably in the form of anomalous winds in the upper troposphere above hurricane Daisy, shortly after its inception. It is inferred that the dynamic instability released by these anomalous winds, which represent anticyclonic rotation in space, triggered Daisy's development.
Since the observed dynamic instability occurred on a mesoscale, the above inference is not amenable to direct verification from synoptic maps. However, synoptic conditions favorable for the development of anomalous winds are discussed and it is found that these conditions prevailed in the upper troposphere directly above Daisy and Gracie a short time before they reached hurricane intensity.
The role of negative absolute vorticity is shown to vary. In the presence of anomalous winds it is a stabilizing factor which is nonetheless important in channeling outflow at the top of the hurricane. With normal winds, negative absolute vorticity is a destabilizing agent and some evidence is presented that it may also be responsible for initiating the development of certain hurricanes.
Abstract
Observations made by the specially instrumented aircraft, operated by the National Hurricane Research Project, establish the occurrence of dynamic instability, notably in the form of anomalous winds in the upper troposphere above hurricane Daisy, shortly after its inception. It is inferred that the dynamic instability released by these anomalous winds, which represent anticyclonic rotation in space, triggered Daisy's development.
Since the observed dynamic instability occurred on a mesoscale, the above inference is not amenable to direct verification from synoptic maps. However, synoptic conditions favorable for the development of anomalous winds are discussed and it is found that these conditions prevailed in the upper troposphere directly above Daisy and Gracie a short time before they reached hurricane intensity.
The role of negative absolute vorticity is shown to vary. In the presence of anomalous winds it is a stabilizing factor which is nonetheless important in channeling outflow at the top of the hurricane. With normal winds, negative absolute vorticity is a destabilizing agent and some evidence is presented that it may also be responsible for initiating the development of certain hurricanes.
Abstract
Observational evidence is provided for the occurrence of anomalous winds which represent an anticyclonic rotation in space, and a mechanism for their development is suggested. The unstable nature of these winds and the role they play in the development of certain types of atmospheric disturbances is then discussed, and it is suggested that anomalous winds provide the dynamic mechanism for triggering hurricane formation and for the observed deepening of troughs downstream from intense pressure ridges. Finally it is noted that although the observational evidence presented is for the occurrence of anomalous winds over small regions of the atmosphere, their development is dependent on large-scale processes and their effect extends beyond the area where they occur.
Abstract
Observational evidence is provided for the occurrence of anomalous winds which represent an anticyclonic rotation in space, and a mechanism for their development is suggested. The unstable nature of these winds and the role they play in the development of certain types of atmospheric disturbances is then discussed, and it is suggested that anomalous winds provide the dynamic mechanism for triggering hurricane formation and for the observed deepening of troughs downstream from intense pressure ridges. Finally it is noted that although the observational evidence presented is for the occurrence of anomalous winds over small regions of the atmosphere, their development is dependent on large-scale processes and their effect extends beyond the area where they occur.
Abstract
On the basis of a 10-year record of rawin observations in the Caribbean, experiments were carried out to determine the appropriate matching between the accuracy and density of meteorological observations.
The results indicate that at 850 mb, if the distance between neighboring stations is of the order of 800 km or more, it makes little difference whether the random errors of observations are 2 kt or twice this amount. This is especially true if the observations are used to construct a regular grid of interpolated values. At 200 mb, an even larger range of observational errors is permissible if the distance between stations is large. The experiments further demonstrate that the distance between the raw observations must be smaller than that between the reconstructed grid points if the field gradients are to be computed with reasonable accuracy.
As the scale of interest becomes smaller, accuracy requirements become more stringent. For instance, if we can measure the zonal wind components at 850 mb in January with an accuracy of 3 kt and if we have two observations 100 km apart, there is only a 0.2 probability that the error in the measured difference between the two observations is equal to or less than one-fifth of the true difference. To increase this probability to 0.4, the accuracy of the measurement must be within 1 kt. Similarly, if the rms error of temperature observations, 100 km apart, is 1C, the probability is 0.15 that the error in the measured difference is equal to or less than one-fifth of the true. On the other hand, if the rms observation error is only 0.1C, the probability is 0.6 that the error is equal to or less than one-fifth of the true difference.
The study is intended to provide planners of meteorological data acquisition experiments with some insight into the options at their disposal. Thus, for field experiments designed to delineate broad-scale atmospheric features, it should help identify the point of diminishing returns for instrumental accuracy. Conversely, if only a given instrumental accuracy is obtainable, it should provide an estimate of the maximum useful sampling resolution.
Abstract
On the basis of a 10-year record of rawin observations in the Caribbean, experiments were carried out to determine the appropriate matching between the accuracy and density of meteorological observations.
The results indicate that at 850 mb, if the distance between neighboring stations is of the order of 800 km or more, it makes little difference whether the random errors of observations are 2 kt or twice this amount. This is especially true if the observations are used to construct a regular grid of interpolated values. At 200 mb, an even larger range of observational errors is permissible if the distance between stations is large. The experiments further demonstrate that the distance between the raw observations must be smaller than that between the reconstructed grid points if the field gradients are to be computed with reasonable accuracy.
As the scale of interest becomes smaller, accuracy requirements become more stringent. For instance, if we can measure the zonal wind components at 850 mb in January with an accuracy of 3 kt and if we have two observations 100 km apart, there is only a 0.2 probability that the error in the measured difference between the two observations is equal to or less than one-fifth of the true difference. To increase this probability to 0.4, the accuracy of the measurement must be within 1 kt. Similarly, if the rms error of temperature observations, 100 km apart, is 1C, the probability is 0.15 that the error in the measured difference is equal to or less than one-fifth of the true. On the other hand, if the rms observation error is only 0.1C, the probability is 0.6 that the error is equal to or less than one-fifth of the true difference.
The study is intended to provide planners of meteorological data acquisition experiments with some insight into the options at their disposal. Thus, for field experiments designed to delineate broad-scale atmospheric features, it should help identify the point of diminishing returns for instrumental accuracy. Conversely, if only a given instrumental accuracy is obtainable, it should provide an estimate of the maximum useful sampling resolution.
Abstract
Observations made at different levels by aircraft of the Research Flight Facility (RFF) of the U.S. Weather Bureau, in conjunction with regular synoptic observations from the coastal United States and Bahamas, are utilized in detailed analysis of conditions prevailing during the crucial period immediately before, during, and after Ella (1962) attained hurricane intensity.
It is shown that, in contrast with other hurricanes described in the literature, Ella did not develop under an upper tropospheric anticyclone. Rather, anticyclonic circulation first appeared in the middle troposphere and gradually extended upward while the storm was intensifying into a hurricane. Correspondingly, the warm-core structure first appeared in the low levels and then spread to the upper troposphere.
Abstract
Observations made at different levels by aircraft of the Research Flight Facility (RFF) of the U.S. Weather Bureau, in conjunction with regular synoptic observations from the coastal United States and Bahamas, are utilized in detailed analysis of conditions prevailing during the crucial period immediately before, during, and after Ella (1962) attained hurricane intensity.
It is shown that, in contrast with other hurricanes described in the literature, Ella did not develop under an upper tropospheric anticyclone. Rather, anticyclonic circulation first appeared in the middle troposphere and gradually extended upward while the storm was intensifying into a hurricane. Correspondingly, the warm-core structure first appeared in the low levels and then spread to the upper troposphere.
Abstract
Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic and Meteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and Gulfstream IV-SP (G-IV) Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions toward improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the next generation of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.
Abstract
Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic and Meteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and Gulfstream IV-SP (G-IV) Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions toward improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the next generation of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.
Abstract
The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.
Abstract
The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.
