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- Author or Editor: Robert A. Case x
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Abstract
A summary of the 1985 hurricane season is presented, including detailed accounts of individual hurricanes. There were eleven named tropical cyclones, seven of which reached hurricane force. A record-typing six hurricanes crossed the U.S. coastline causing a record damage of $4 billion.
Abstract
A summary of the 1985 hurricane season is presented, including detailed accounts of individual hurricanes. There were eleven named tropical cyclones, seven of which reached hurricane force. A record-typing six hurricanes crossed the U.S. coastline causing a record damage of $4 billion.
Abstract
The general overview of the 1987 hurricane season in the North Atlantic is presented together with detailed accounts of all named storms. In addition, an unnamed tropical storm and a tropical depression that required watches and/or warnings on the U.S. coastline are discussed.
Abstract
The general overview of the 1987 hurricane season in the North Atlantic is presented together with detailed accounts of all named storms. In addition, an unnamed tropical storm and a tropical depression that required watches and/or warnings on the U.S. coastline are discussed.
Abstract
A general summary of the 1983 hurricane season is presented. Four named tropical cyclones were tracked during the season. Three landfalls occurred. Alicia, the first cyclone of the season, ended a three-year period during which no hurricanes reached the United States coastline.
Abstract
A general summary of the 1983 hurricane season is presented. Four named tropical cyclones were tracked during the season. Three landfalls occurred. Alicia, the first cyclone of the season, ended a three-year period during which no hurricanes reached the United States coastline.
Abstract
In oceanography, there has been a growing emphasis on coastal regions, partially because of their inherent complexity, as well as the increasing acknowledgment of anthropogenic impacts. To improve understanding and characterization of coastal dynamics, there has been significant effort devoted to the development of autonomous systems that sample the ocean on relevant scales. Autonomous underwater vehicles (AUVs) are especially well suited for studies of the coastal ocean because they are able to provide near-synoptic spatial observations. These sampling platforms are beginning to transition from the engineering groups that developed and continue to improve them to the science user. With this transition comes novel applications of these vehicles to address new questions in coastal oceanography. Here, the relatively mature Remote Environmental Monitoring Units (REMUS) AUV system is described and assessed. Analysis of data, based on 37 missions and nearly 800 km of in-water operation, shows that the vehicle’s navigational error estimates were consistently less than 10 m, and error estimates of mission duration, distance, velocity, and power usage, once the vehicle was properly ballasted, were below 10%. An example of the transition to science is demonstrated in an experiment conducted in 2002 in Monterey Bay, California, where the vehicle was used to quantify critical horizontal length scales of variability. Length scales on the order of tens to hundreds of meters were found for the region within 25 km of the coastline, which has significant implications for designing proper sampling approaches and parameterizing model domains. Results also demonstrate the overall utility of the REMUS vehicle for use by coastal oceanographers.
Abstract
In oceanography, there has been a growing emphasis on coastal regions, partially because of their inherent complexity, as well as the increasing acknowledgment of anthropogenic impacts. To improve understanding and characterization of coastal dynamics, there has been significant effort devoted to the development of autonomous systems that sample the ocean on relevant scales. Autonomous underwater vehicles (AUVs) are especially well suited for studies of the coastal ocean because they are able to provide near-synoptic spatial observations. These sampling platforms are beginning to transition from the engineering groups that developed and continue to improve them to the science user. With this transition comes novel applications of these vehicles to address new questions in coastal oceanography. Here, the relatively mature Remote Environmental Monitoring Units (REMUS) AUV system is described and assessed. Analysis of data, based on 37 missions and nearly 800 km of in-water operation, shows that the vehicle’s navigational error estimates were consistently less than 10 m, and error estimates of mission duration, distance, velocity, and power usage, once the vehicle was properly ballasted, were below 10%. An example of the transition to science is demonstrated in an experiment conducted in 2002 in Monterey Bay, California, where the vehicle was used to quantify critical horizontal length scales of variability. Length scales on the order of tens to hundreds of meters were found for the region within 25 km of the coastline, which has significant implications for designing proper sampling approaches and parameterizing model domains. Results also demonstrate the overall utility of the REMUS vehicle for use by coastal oceanographers.
Abstract
This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June–August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.
Abstract
This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June–August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.
