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Abstract
During the months of May, June, July and August, 1978, a record number of damaging hailstorms, causing losses upward of $100 million, struck along the High Plains and Front Range regions of New Mexico, Colorado, Wyoming and Montana. Nine of these storms were observed from the GOES-E geostationary satellite with the digital visible and infrared data recorded at the CSU Direct Readout Satellite Groundstation. The digital, navigated imagery were processed on an interactive image processing system for detection of hail signatures.
In all but one case of reported hail, the coldest cloud-top temperature of the storm system located nearest the hailfall was from 1 to 8°C colder than the environmental tropopause temperature during at least a portion of its lifetime. In most cases this occurred coincident with the best estimate of the onset of hail. Also, the imagery showed each of these storm complexes having long lifetimes (2–5 h), with some exhibiting temperatures colder than the tropopause temperature for this length of time. Through analysis of the 22 June 1976 NHRE storm complex, it was determined that hailfall occurred at close to the maximum growth rate of the storm. This paper thus begins to identify a potential technique for identifying damaging hailstorms through proper enhancement of digital GOES infrared imagery.
Abstract
During the months of May, June, July and August, 1978, a record number of damaging hailstorms, causing losses upward of $100 million, struck along the High Plains and Front Range regions of New Mexico, Colorado, Wyoming and Montana. Nine of these storms were observed from the GOES-E geostationary satellite with the digital visible and infrared data recorded at the CSU Direct Readout Satellite Groundstation. The digital, navigated imagery were processed on an interactive image processing system for detection of hail signatures.
In all but one case of reported hail, the coldest cloud-top temperature of the storm system located nearest the hailfall was from 1 to 8°C colder than the environmental tropopause temperature during at least a portion of its lifetime. In most cases this occurred coincident with the best estimate of the onset of hail. Also, the imagery showed each of these storm complexes having long lifetimes (2–5 h), with some exhibiting temperatures colder than the tropopause temperature for this length of time. Through analysis of the 22 June 1976 NHRE storm complex, it was determined that hailfall occurred at close to the maximum growth rate of the storm. This paper thus begins to identify a potential technique for identifying damaging hailstorms through proper enhancement of digital GOES infrared imagery.
Abstract
Geostationary Operational Environmental Satellite (GOES) enhanced infrared (IR) imagery depicted very cold temperatures over Colorado on the morning of 8 December 1978. The situation was unusual because skies were clear and the cold temperatures were not associated with high cloud tops. Instead, satellite data mapped large areas that were experiencing extremely cold surface temperatures. The GOES data were also examined using the Colorado State University interactive data processing system and it was found that the cold IR readings corresponded well with early morning low temperatures over the state. GOES data can be of use in monitoring surface temperatures and can, in certain situations, provide detailed spatial and temporal information over regions experiencing extreme temperatures.
Abstract
Geostationary Operational Environmental Satellite (GOES) enhanced infrared (IR) imagery depicted very cold temperatures over Colorado on the morning of 8 December 1978. The situation was unusual because skies were clear and the cold temperatures were not associated with high cloud tops. Instead, satellite data mapped large areas that were experiencing extremely cold surface temperatures. The GOES data were also examined using the Colorado State University interactive data processing system and it was found that the cold IR readings corresponded well with early morning low temperatures over the state. GOES data can be of use in monitoring surface temperatures and can, in certain situations, provide detailed spatial and temporal information over regions experiencing extreme temperatures.
Abstract
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Abstract
Radiometric data from the SMS-2 and GOES-1 geostationary satellites together with ground-based lidar scans have been combined to determine the visible albedo, infrared emittance and visible optical depth of cirrus clouds. The combined observations were made on an area of cirrus of about 10 km by 10 km square at Boulder, Colorado during two days.
A method of analysis was developed to separate out the cloud albedo from surface albedo effects, to allow for possible anisotropy in the bi-directional reflectance of solar radiation from the clouds, and to compare the data with results of theoretical calculations.
Relations between the visible albedo and the infrared emittance, which were derived from satellite data, and the visible optical depth, which was derived from lidar measurements, were compared with theoretical relations derived from two models of cloud particle scattering. The first model assumes that the cloud is composed of water (or ice) spheres and the second that it is composed of long ice cylinders. It was found that the observational data agree best with the latter model, although there are still some discrepancies.
The infrared emittances varied between 0.2 and 0.95, the corresponding albedos between 0.10 and 0.32 and the visible optical depths between 0.5 and 3.5.
Abstract
Radiometric data from the SMS-2 and GOES-1 geostationary satellites together with ground-based lidar scans have been combined to determine the visible albedo, infrared emittance and visible optical depth of cirrus clouds. The combined observations were made on an area of cirrus of about 10 km by 10 km square at Boulder, Colorado during two days.
A method of analysis was developed to separate out the cloud albedo from surface albedo effects, to allow for possible anisotropy in the bi-directional reflectance of solar radiation from the clouds, and to compare the data with results of theoretical calculations.
Relations between the visible albedo and the infrared emittance, which were derived from satellite data, and the visible optical depth, which was derived from lidar measurements, were compared with theoretical relations derived from two models of cloud particle scattering. The first model assumes that the cloud is composed of water (or ice) spheres and the second that it is composed of long ice cylinders. It was found that the observational data agree best with the latter model, although there are still some discrepancies.
The infrared emittances varied between 0.2 and 0.95, the corresponding albedos between 0.10 and 0.32 and the visible optical depths between 0.5 and 3.5.
Abstract
A case study is presented of an atmospheric river (AR) that produced heavy precipitation in the U.S. Pacific Northwest during March 2005. The study documents several key ingredients from the planetary scale to the mesoscale that contributed to the extreme nature of this event. The multiscale analysis uses unique experimental data collected by the National Oceanic and Atmospheric Administration (NOAA) P-3 aircraft operated from Hawaii, coastal wind profiler and global positioning system (GPS) meteorological stations in Oregon, and satellite and global reanalysis data. Moving from larger scales to smaller scales, the primary findings of this study are as follow: 1) phasing of several major planetary-scale phenomena influenced by tropical––extratropical interactions led to the direct entrainment of tropical water vapor into the AR near Hawaii, 2) dropsonde observations documented the northward advection of tropical water vapor into the subtropical extension of the midlatitude AR, and 3) a mesoscale frontal wave increased the duration of AR conditions at landfall in the Pacific Northwest.
Abstract
A case study is presented of an atmospheric river (AR) that produced heavy precipitation in the U.S. Pacific Northwest during March 2005. The study documents several key ingredients from the planetary scale to the mesoscale that contributed to the extreme nature of this event. The multiscale analysis uses unique experimental data collected by the National Oceanic and Atmospheric Administration (NOAA) P-3 aircraft operated from Hawaii, coastal wind profiler and global positioning system (GPS) meteorological stations in Oregon, and satellite and global reanalysis data. Moving from larger scales to smaller scales, the primary findings of this study are as follow: 1) phasing of several major planetary-scale phenomena influenced by tropical––extratropical interactions led to the direct entrainment of tropical water vapor into the AR near Hawaii, 2) dropsonde observations documented the northward advection of tropical water vapor into the subtropical extension of the midlatitude AR, and 3) a mesoscale frontal wave increased the duration of AR conditions at landfall in the Pacific Northwest.
Abstract
A technique is presented for discriminating different cloud types through an image subtraction of visible and infrared SMS/GOES picture pairs. The technique emphasizes how one could separate snow from clouds and identify cirrus by the subtraction method. Quantitative threshold values are shown which can be used in an objective manner to make this separation.
Use is made of an all-digital image display device allowing such mathematical operations to be performed on satellite data. Techniques such as this can be made operational through the interfacing of the image analysis system with a direct-readout SMS/GOES ground station and distribution network.
Abstract
A technique is presented for discriminating different cloud types through an image subtraction of visible and infrared SMS/GOES picture pairs. The technique emphasizes how one could separate snow from clouds and identify cirrus by the subtraction method. Quantitative threshold values are shown which can be used in an objective manner to make this separation.
Use is made of an all-digital image display device allowing such mathematical operations to be performed on satellite data. Techniques such as this can be made operational through the interfacing of the image analysis system with a direct-readout SMS/GOES ground station and distribution network.
Abstract
A data assimilation system (DAS) is described for global atmospheric reanalysis from 0- to 100-km altitude. We apply it to the 2014 austral winter of the Deep Propagating Gravity Wave Experiment (DEEPWAVE), an international field campaign focused on gravity wave dynamics from 0 to 100 km, where an absence of reanalysis above 60 km inhibits research. Four experiments were performed from April to September 2014 and assessed for reanalysis skill above 50 km. A four-dimensional variational (4DVAR) run specified initial background error covariances statically. A hybrid-4DVAR (HYBRID) run formed background error covariances from an 80-member forecast ensemble blended with a static estimate. Each configuration was run at low and high horizontal resolution. In addition to operational observations below 50 km, each experiment assimilated 
Abstract
A data assimilation system (DAS) is described for global atmospheric reanalysis from 0- to 100-km altitude. We apply it to the 2014 austral winter of the Deep Propagating Gravity Wave Experiment (DEEPWAVE), an international field campaign focused on gravity wave dynamics from 0 to 100 km, where an absence of reanalysis above 60 km inhibits research. Four experiments were performed from April to September 2014 and assessed for reanalysis skill above 50 km. A four-dimensional variational (4DVAR) run specified initial background error covariances statically. A hybrid-4DVAR (HYBRID) run formed background error covariances from an 80-member forecast ensemble blended with a static estimate. Each configuration was run at low and high horizontal resolution. In addition to operational observations below 50 km, each experiment assimilated
