Search Results
You are looking at 1 - 6 of 6 items for :
- Author or Editor: T. Potter x
- Bulletin of the American Meteorological Society x
- Refine by Access: Content accessible to me x
A simple method of finding the percentage frequency that areas near a target will be affected by radioactive fallout of a critical dose is presented. The target location, the climatological period, the fission yield, and a critical dose or dose rate must be specified. If the distribution of the actual effective winds is not available, the assumption of a circular normal distribution of the effective wind is made. This distribution can be obtained by C. E. P. Brooks' method or, if the points are numerous as in describing an areal frequency pattern, by a mechanical method described herein.
A simple method of finding the percentage frequency that areas near a target will be affected by radioactive fallout of a critical dose is presented. The target location, the climatological period, the fission yield, and a critical dose or dose rate must be specified. If the distribution of the actual effective winds is not available, the assumption of a circular normal distribution of the effective wind is made. This distribution can be obtained by C. E. P. Brooks' method or, if the points are numerous as in describing an areal frequency pattern, by a mechanical method described herein.
The 2002 Winter Olympic and Paralympic Games will be hosted by Salt Lake City, Utah, during February–March 2002. Adverse weather during this period may delay sporting events, while snow and ice-covered streets and highways may impede access by the athletes and spectators to the venues. While winter snowstorms and other large-scale weather systems typically have widespread impacts throughout northern Utah, hazardous winter weather is often related to local terrain features (the Wasatch Mountains and Great Salt Lake are the most prominent ones). Examples of such hazardous weather include lake-effect snowstorms, ice fog, gap winds, down-slope windstorms, and low visibility over mountain passes.
A weather support system has been developed to provide weather information to the athletes, games officials, spectators, and the interested public around the world. This system is managed by the Salt Lake Olympic Committee and relies upon meteorologists from the public, private, and academic sectors of the atmospheric science community. Weather forecasting duties will be led by National Weather Service forecasters and a team of private weather forecasters organized by KSL, the Salt Lake City NBC television affiliate. Other government agencies, commercial firms, and the University of Utah are providing specialized forecasts and support services for the Olympics. The weather support system developed for the 2002 Winter Olympics is expected to provide long-term benefits to the public through improved understanding, monitoring, and prediction of winter weather in the Intermountain West.
The 2002 Winter Olympic and Paralympic Games will be hosted by Salt Lake City, Utah, during February–March 2002. Adverse weather during this period may delay sporting events, while snow and ice-covered streets and highways may impede access by the athletes and spectators to the venues. While winter snowstorms and other large-scale weather systems typically have widespread impacts throughout northern Utah, hazardous winter weather is often related to local terrain features (the Wasatch Mountains and Great Salt Lake are the most prominent ones). Examples of such hazardous weather include lake-effect snowstorms, ice fog, gap winds, down-slope windstorms, and low visibility over mountain passes.
A weather support system has been developed to provide weather information to the athletes, games officials, spectators, and the interested public around the world. This system is managed by the Salt Lake Olympic Committee and relies upon meteorologists from the public, private, and academic sectors of the atmospheric science community. Weather forecasting duties will be led by National Weather Service forecasters and a team of private weather forecasters organized by KSL, the Salt Lake City NBC television affiliate. Other government agencies, commercial firms, and the University of Utah are providing specialized forecasts and support services for the Olympics. The weather support system developed for the 2002 Winter Olympics is expected to provide long-term benefits to the public through improved understanding, monitoring, and prediction of winter weather in the Intermountain West.
ABSTRACT
We introduce a simple method for detecting changes, both transient and persistent, in reanalysis and merged satellite products due to both natural climate variability and changes to the data sources/analyses used as input. This note demonstrates this Histogram Anomaly Time Series (HATS) method using tropical ocean daily precipitation from MERRA-2 and from GPCP One-Degree Daily (1DD) precipitation estimates. Rather than averaging over space or time, we create a time series display of histograms for each increment of data (such as a day or month). Regional masks such as land–ocean can be used to isolate particular domains. While the histograms reveal subtle structures in the time series, we can amplify the signal by computing the histogram’s anomalies from its climatological seasonal cycle. The qualitative analysis provided by this scheme can then form the basis for more quantitative analyses of specific features, both real and analysis induced. As an example, in the tropical oceans the analysis clearly identifies changes in the time series of both reanalysis and observations that may be related to changing inputs.
ABSTRACT
We introduce a simple method for detecting changes, both transient and persistent, in reanalysis and merged satellite products due to both natural climate variability and changes to the data sources/analyses used as input. This note demonstrates this Histogram Anomaly Time Series (HATS) method using tropical ocean daily precipitation from MERRA-2 and from GPCP One-Degree Daily (1DD) precipitation estimates. Rather than averaging over space or time, we create a time series display of histograms for each increment of data (such as a day or month). Regional masks such as land–ocean can be used to isolate particular domains. While the histograms reveal subtle structures in the time series, we can amplify the signal by computing the histogram’s anomalies from its climatological seasonal cycle. The qualitative analysis provided by this scheme can then form the basis for more quantitative analyses of specific features, both real and analysis induced. As an example, in the tropical oceans the analysis clearly identifies changes in the time series of both reanalysis and observations that may be related to changing inputs.
To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework.
To further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.
To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework.
To further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.
Abstract
The Global Wind Atlas (GWA) provides high-resolution databases and maps of the wind resource for all land points and for water points within 200 km of the coastline, excluding Antarctica. The GWA is used to identify and understand the global, national, regional, and local potential for wind energy and to guide energy specialists, policymakers, and planners in the transition to a sustainable energy system. This information is vital to ensuring the growth of wind energy, helping to transition to a sustainable energy system, which will mitigate climate change and meet the world’s need for reliable, affordable, and clean energy. The GWA uses the established numerical wind atlas methodology to downscale coarse-resolution wind data to microscale, using linearized flow modeling and high-resolution topographic data. There have been three versions of the GWA, each using mesoscale model data at successively higher spatial resolution. A website and geographic information system (GIS) files support quick and in-depth analysis. Validation data and analysis, using measurements from tall masts located worldwide, are also provided through the web application. The development process of the GWA involves a dialogue between meteorological modelers, wind energy development experts, web designers, and representatives of the end users to provide accurate data in a dynamic and relevant way. This article outlines the general method, specific development, and application of the Global Wind Atlas.
Abstract
The Global Wind Atlas (GWA) provides high-resolution databases and maps of the wind resource for all land points and for water points within 200 km of the coastline, excluding Antarctica. The GWA is used to identify and understand the global, national, regional, and local potential for wind energy and to guide energy specialists, policymakers, and planners in the transition to a sustainable energy system. This information is vital to ensuring the growth of wind energy, helping to transition to a sustainable energy system, which will mitigate climate change and meet the world’s need for reliable, affordable, and clean energy. The GWA uses the established numerical wind atlas methodology to downscale coarse-resolution wind data to microscale, using linearized flow modeling and high-resolution topographic data. There have been three versions of the GWA, each using mesoscale model data at successively higher spatial resolution. A website and geographic information system (GIS) files support quick and in-depth analysis. Validation data and analysis, using measurements from tall masts located worldwide, are also provided through the web application. The development process of the GWA involves a dialogue between meteorological modelers, wind energy development experts, web designers, and representatives of the end users to provide accurate data in a dynamic and relevant way. This article outlines the general method, specific development, and application of the Global Wind Atlas.
