Search Results
You are looking at 1 - 7 of 7 items for :
- Author or Editor: S. C. Pryor x
- Bulletin of the American Meteorological Society x
- Refine by Access: All Content x
Abstract
Infrared and microwave sounder measurements from polar-orbiting satellites are used to retrieve profiles of temperature, water vapor, and trace gases utilizing a suite of algorithms called the National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS). Meteorologists operationally use the retrievals similar to radiosonde measurements to assess atmospheric stability and aid them in issuing forecasts and severe weather warnings. Measurements of trace gases by NUCAPS enable detection, tracking, and monitoring of greenhouse gases and emissions from fires that impact air quality. During the polar winters, when ultraviolet measurements of ozone are not possible, absorption features in the infrared spectrum of the sounders enable the assessment of ozone concentration in the stratosphere. These retrievals are used as inputs to monitor the ozone hole over Antarctica. This article illustrates the utility of NUCAPS atmospheric profile retrievals in assessing meteorological events using several examples of severe thunderstorms, tropical cyclones, fires, and ozone maps.
Abstract
Infrared and microwave sounder measurements from polar-orbiting satellites are used to retrieve profiles of temperature, water vapor, and trace gases utilizing a suite of algorithms called the National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS). Meteorologists operationally use the retrievals similar to radiosonde measurements to assess atmospheric stability and aid them in issuing forecasts and severe weather warnings. Measurements of trace gases by NUCAPS enable detection, tracking, and monitoring of greenhouse gases and emissions from fires that impact air quality. During the polar winters, when ultraviolet measurements of ozone are not possible, absorption features in the infrared spectrum of the sounders enable the assessment of ozone concentration in the stratosphere. These retrievals are used as inputs to monitor the ozone hole over Antarctica. This article illustrates the utility of NUCAPS atmospheric profile retrievals in assessing meteorological events using several examples of severe thunderstorms, tropical cyclones, fires, and ozone maps.
The 3D wind and turbulence characteristics of the atmospheric boundary layer experiment (3D Wind) was conducted to evaluate innovative remote sensing and in situ platforms for measurements of wind and turbulence regimes. The experiment is part of a planned series that focuses on quantifying wind and turbulence characteristics at the scales of modern wind turbines and wind farms and was conducted in northern Indiana in May 2012. 3D Wind had the following specific objectives: (i) intercomparison experiments evaluating wind speed profiles across the wind turbine rotor plane from traditional cup anemometers and wind vanes on a meteorological mast and from a tethered balloon, sonic anemometers (mast mounted and on an unmanned aerial vehicle), three vertical-pointing (continuous wave) lidars and a pulsed scanning lidar, and (ii) integrate these measurements and output from 3-km-resolution (over the inner domain) simulations with the Weather Research and Forecasting Model to develop a detailed depiction of the atmospheric flow, upwind, within, and downwind of a large, irregularly spaced wind farm. This paper provides an overview of the measurement techniques, their advantages and disadvantages focusing on the integration of wind and turbulence characteristics that are necessary for wind farm development and operation. Analyses of the measurements are summarized to characterize instrument cross comparison, wind profiles, and spatial gradients and wind turbine wakes.
The 3D wind and turbulence characteristics of the atmospheric boundary layer experiment (3D Wind) was conducted to evaluate innovative remote sensing and in situ platforms for measurements of wind and turbulence regimes. The experiment is part of a planned series that focuses on quantifying wind and turbulence characteristics at the scales of modern wind turbines and wind farms and was conducted in northern Indiana in May 2012. 3D Wind had the following specific objectives: (i) intercomparison experiments evaluating wind speed profiles across the wind turbine rotor plane from traditional cup anemometers and wind vanes on a meteorological mast and from a tethered balloon, sonic anemometers (mast mounted and on an unmanned aerial vehicle), three vertical-pointing (continuous wave) lidars and a pulsed scanning lidar, and (ii) integrate these measurements and output from 3-km-resolution (over the inner domain) simulations with the Weather Research and Forecasting Model to develop a detailed depiction of the atmospheric flow, upwind, within, and downwind of a large, irregularly spaced wind farm. This paper provides an overview of the measurement techniques, their advantages and disadvantages focusing on the integration of wind and turbulence characteristics that are necessary for wind farm development and operation. Analyses of the measurements are summarized to characterize instrument cross comparison, wind profiles, and spatial gradients and wind turbine wakes.
ABSTRACT
Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.
ABSTRACT
Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.
Abstract
A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.
Abstract
A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.
This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.
This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.
