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- Author or Editor: Anthony Mostek x
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Abstract
Monthly meteorological data for the years 1900–77 are used in an eigenvector analysis of the anomaly patterns of surface temperature, precipitation and sea level pressure over the United States. Approximately 70% of the variance is contained in the first three of 61 temperature eigenvectors and in the first three of 25 pressure eigenvectors. Large-scale patterns of precipitation are also identified, although the compression of the data is somewhat less effective. The first eigenvector of each variable contains anomalies of the same sign over most of the United States; the second and third modes describe gradients in approximately perpendicular directions.
Cross correlations between the amplitudes of eigenvectors of different variables are statistically significant, consistent with physical expectations, and, in some cases, are seasonally dependent. The first modes of both temperature and pressure are most persistent in the summer. Persistence on the seasonal time scale is generally largest for temperature and largest when summer is the antecedent season. The seasonal persistences of the amplitudes of the temperature eigenvectors are generally consistent with the persistences of station temperatures obtained recently by Namias (1978).
The most prominent feature of the frequency spectra is a strong peak at 2.1 years in the amplitude of the third temperature eigenvector.
Abstract
Monthly meteorological data for the years 1900–77 are used in an eigenvector analysis of the anomaly patterns of surface temperature, precipitation and sea level pressure over the United States. Approximately 70% of the variance is contained in the first three of 61 temperature eigenvectors and in the first three of 25 pressure eigenvectors. Large-scale patterns of precipitation are also identified, although the compression of the data is somewhat less effective. The first eigenvector of each variable contains anomalies of the same sign over most of the United States; the second and third modes describe gradients in approximately perpendicular directions.
Cross correlations between the amplitudes of eigenvectors of different variables are statistically significant, consistent with physical expectations, and, in some cases, are seasonally dependent. The first modes of both temperature and pressure are most persistent in the summer. Persistence on the seasonal time scale is generally largest for temperature and largest when summer is the antecedent season. The seasonal persistences of the amplitudes of the temperature eigenvectors are generally consistent with the persistences of station temperatures obtained recently by Namias (1978).
The most prominent feature of the frequency spectra is a strong peak at 2.1 years in the amplitude of the third temperature eigenvector.
Abstract
Local forecasts often rely upon the extrapolation of trends seen in images of clouds from the GOES satellite. This work presents correspondingly high resolution images of atmospheric soundings calculated from the VAS radiometer on GOES. These VAS sounding images vividly depict moisture and stability conditions in preconvective regions, as though GOES were observing the United States with “stability detectors” instead of infrared detectors at 1–3 h intervals and 60 km horizontal resolution. False color images are presented for VAS-derived precipitable water and lifted index fields during two midsummer days that contain a wide variety of preconvective and convective conditions. Since each sounding image requires only 5 min to calculate with an automated regression algorithm on a minicomputer, it should be possible to process VAS data operationally for real-time objective analysis of potential convective instabilities.
Abstract
Local forecasts often rely upon the extrapolation of trends seen in images of clouds from the GOES satellite. This work presents correspondingly high resolution images of atmospheric soundings calculated from the VAS radiometer on GOES. These VAS sounding images vividly depict moisture and stability conditions in preconvective regions, as though GOES were observing the United States with “stability detectors” instead of infrared detectors at 1–3 h intervals and 60 km horizontal resolution. False color images are presented for VAS-derived precipitable water and lifted index fields during two midsummer days that contain a wide variety of preconvective and convective conditions. Since each sounding image requires only 5 min to calculate with an automated regression algorithm on a minicomputer, it should be possible to process VAS data operationally for real-time objective analysis of potential convective instabilities.
Abstract
Surface temperature and dewpoint reports are added to the infrared radiances from the VISSR Atmospheric Sounder (VAS) in order to improve the retrieval of temperature and moisture profiles in the lower troposphere. The conventional (airways) surface data are combined with the 12 VAS channels as additional predictors in a ridge regression retrieval scheme, with the aim of using all available data to make high resolution space-time interpolations of the radiosonde network. For one day of VAS observations, retrievals using only VAS radiances are compared with retrievals using VAS radiances plus surface data. Temperature retrieval accuracy evaluated at coincident radiosonde sites shows a significant impact within the boundary layer. Dewpoint retrieval accuracy shows a broader improvement within the lowest tropospheric layers. The most dramatic impact of surface data is observer in the spatial and temporal continuity of low-level fields retrieved over the Midwestern United States.
Abstract
Surface temperature and dewpoint reports are added to the infrared radiances from the VISSR Atmospheric Sounder (VAS) in order to improve the retrieval of temperature and moisture profiles in the lower troposphere. The conventional (airways) surface data are combined with the 12 VAS channels as additional predictors in a ridge regression retrieval scheme, with the aim of using all available data to make high resolution space-time interpolations of the radiosonde network. For one day of VAS observations, retrievals using only VAS radiances are compared with retrievals using VAS radiances plus surface data. Temperature retrieval accuracy evaluated at coincident radiosonde sites shows a significant impact within the boundary layer. Dewpoint retrieval accuracy shows a broader improvement within the lowest tropospheric layers. The most dramatic impact of surface data is observer in the spatial and temporal continuity of low-level fields retrieved over the Midwestern United States.
Abstract
The GOES satellites launched in the 1980's are carrying an instrument called the VISSR Atmospheric Sounder (VAS), which is designed to provide temperature and moisture profile-sounding capability for mesoscale weather systems. As a controlled study of this capability, VAS radiance fields are simulated for pre-thunderstorm environments in Oklahoma to demonstrate three points: 1) significant moisture gradients can be seen directly in images of the VAS channels, 2) temperature and moisture profiles can be retrieved from VAS radiances with sufficient accuracy to delineate the major features of a severe storm environment, and 3) the quality of VAS mesoscale soundings improve with conditioning by local weather statistics.
Even though the simulated VAS soundings have the usual limitations in absolute accuracy, gradient strength and vertical resolution (especially in the lower tropospheric moisture retrievals), it is still possible to retrieve mesoscale regions of potential instability from the synthetic VAS radiances for a mostly clear pre-thunderstorm environment. The rms tropospheric profile errors are ±1°C and ±25% in temperature and mixing ratio, respectively. The results represent the optimum retrievability of mesoscale information from VAS radiances without the use of ancillary data. The simulations suggest that VAS data will yield the best soundings when a human being classifies the scene, picks relatively clear areas for retrieval, and applies a “local” statistical database to resolve the ambiguities of satellite observations in favor of the most probable atmospheric structure.
Abstract
The GOES satellites launched in the 1980's are carrying an instrument called the VISSR Atmospheric Sounder (VAS), which is designed to provide temperature and moisture profile-sounding capability for mesoscale weather systems. As a controlled study of this capability, VAS radiance fields are simulated for pre-thunderstorm environments in Oklahoma to demonstrate three points: 1) significant moisture gradients can be seen directly in images of the VAS channels, 2) temperature and moisture profiles can be retrieved from VAS radiances with sufficient accuracy to delineate the major features of a severe storm environment, and 3) the quality of VAS mesoscale soundings improve with conditioning by local weather statistics.
Even though the simulated VAS soundings have the usual limitations in absolute accuracy, gradient strength and vertical resolution (especially in the lower tropospheric moisture retrievals), it is still possible to retrieve mesoscale regions of potential instability from the synthetic VAS radiances for a mostly clear pre-thunderstorm environment. The rms tropospheric profile errors are ±1°C and ±25% in temperature and mixing ratio, respectively. The results represent the optimum retrievability of mesoscale information from VAS radiances without the use of ancillary data. The simulations suggest that VAS data will yield the best soundings when a human being classifies the scene, picks relatively clear areas for retrieval, and applies a “local” statistical database to resolve the ambiguities of satellite observations in favor of the most probable atmospheric structure.
Abstract
Retrievals from the VISSR Atmospheric Sounder (VAS) an combined with conventional data to assess the impact of geosynchronous satellite soundings upon the analysis of a pre-convective environment over the central United States on 13 July 1981. VAS retrievals of temperature, dewpoint, equivalent potential temperature, precipitable water, and lifted index are derived with 30 km resolution at 3 hour intervals. When VAS fields are combined with analyses from conventional data sources regions with convective instability are more clearly delineated prior to the rapid development of the thunderstorms. The retrievals differentiate isolated areas in which most air extends throughout the lower troposphere (and are therefore more conducive for the development of deep convective storms) from those regions where moisture is confined to a thin layer near the earth's surface (where convection is less likely to occur). The analyses of the VAS retrievals identify significant spatial gradients and temporal changes in the thermal and moisture fields, especially in the regions between radiosonde observations. The detailed analyses also point to limitations in using VAS data. Even with nearly optimal conditions for passive remote sounding (generally clew skies, minimal orographic effects, and a rapidly changing moisture field), the VAS retrievals were still degraded in some regions by small clouds which are unresolved in the infrared imagery. These analyses, however, demonstrate that the geosynchronous VAS can be used in a case study mode to produce high-resolution spatial and temporal measurements that are useful for the quantitative analysis of a cloud-free pre-convective environment.
Abstract
Retrievals from the VISSR Atmospheric Sounder (VAS) an combined with conventional data to assess the impact of geosynchronous satellite soundings upon the analysis of a pre-convective environment over the central United States on 13 July 1981. VAS retrievals of temperature, dewpoint, equivalent potential temperature, precipitable water, and lifted index are derived with 30 km resolution at 3 hour intervals. When VAS fields are combined with analyses from conventional data sources regions with convective instability are more clearly delineated prior to the rapid development of the thunderstorms. The retrievals differentiate isolated areas in which most air extends throughout the lower troposphere (and are therefore more conducive for the development of deep convective storms) from those regions where moisture is confined to a thin layer near the earth's surface (where convection is less likely to occur). The analyses of the VAS retrievals identify significant spatial gradients and temporal changes in the thermal and moisture fields, especially in the regions between radiosonde observations. The detailed analyses also point to limitations in using VAS data. Even with nearly optimal conditions for passive remote sounding (generally clew skies, minimal orographic effects, and a rapidly changing moisture field), the VAS retrievals were still degraded in some regions by small clouds which are unresolved in the infrared imagery. These analyses, however, demonstrate that the geosynchronous VAS can be used in a case study mode to produce high-resolution spatial and temporal measurements that are useful for the quantitative analysis of a cloud-free pre-convective environment.
Abstract
Infrared and visible imagery from VAS are used to delineate mid- and lower-tropospheric moisture fields for a variety of severe storm cases in the southern and central United States. The ability of sequences of images to isolate areas of large negative vertical moisture gradients and apparent convective instability prior to the onset of convective storms is assessed. Midlevel dryness is diagnosed directly from the VAS 6.7 channel observations, while low-level water vapor is either inferred from the presence of clouds in visible and infrared imagery or, in cloud-free areas, calculated from VAS "split window" channels. A variety ofimage combination procedures are used to deduce the stability fields which are then compared with the available radiosonde data. The results for several severe storm cases indicate that VAS can detect mid- and low-level mesoscale water vapor fields as distinct radiometric signals. The VAS imagery shows a strong tendency for thunderstorms to develop along the edges of bands of midlevel dryness as they overtake either pre-existing or developing low-level moisture maxima. Image sequences depict the speed with which deep moist and dry layers can develop and move, often at scales not resolvable using conventional radiosonde data. The images thus demonstrate the ability of VAS radiance data to detect differential moisture advectionsin rapidly changing pre-convective environments.
Abstract
Infrared and visible imagery from VAS are used to delineate mid- and lower-tropospheric moisture fields for a variety of severe storm cases in the southern and central United States. The ability of sequences of images to isolate areas of large negative vertical moisture gradients and apparent convective instability prior to the onset of convective storms is assessed. Midlevel dryness is diagnosed directly from the VAS 6.7 channel observations, while low-level water vapor is either inferred from the presence of clouds in visible and infrared imagery or, in cloud-free areas, calculated from VAS "split window" channels. A variety ofimage combination procedures are used to deduce the stability fields which are then compared with the available radiosonde data. The results for several severe storm cases indicate that VAS can detect mid- and low-level mesoscale water vapor fields as distinct radiometric signals. The VAS imagery shows a strong tendency for thunderstorms to develop along the edges of bands of midlevel dryness as they overtake either pre-existing or developing low-level moisture maxima. Image sequences depict the speed with which deep moist and dry layers can develop and move, often at scales not resolvable using conventional radiosonde data. The images thus demonstrate the ability of VAS radiance data to detect differential moisture advectionsin rapidly changing pre-convective environments.
The Geostationary Operational Environmental Satellite R series (GOES-R) Proving Ground engages the National Weather Service (NWS) forecast, watch, and warning community and other agency users in preoperational demonstrations of the new and advanced capabilities to be available from GOES-R compared to the current GOES constellation. GOES-R will provide significant advances in observing capabilities but will also offer a significant challenge to ensure that users are ready to exploit the new 16-channel imager that will provide 3 times more spectral information, 4 times the spatial coverage, and 5 times the temporal resolution compared to the current imager. In addition, a geostationary lightning mapper will provide continuous and near-uniform real-time surveillance of total lightning activity throughout the Americas and adjacent oceans encompassing much of the Western Hemisphere. To ensure user readiness, forecasters and other users must have access to prototype advanced products within their operational environment well before launch. Examples of the advanced products include improved volcanic ash detection, lightning detection, 1-min-interval rapid-scan imagery, dust and aerosol detection, and synthetic cloud and moisture imagery. A key component of the GOES-R Proving Ground is the two-way interaction between the researchers who introduce new products and techniques and the forecasters who then provide feedback and ideas for improvements that can best be incorporated into NOAA's integrated observing and analysis operations. In 2012 and beyond, the GOES-R Proving Ground will test and validate display and visualization techniques, decision aids, future capabilities, training materials, and the data processing and product distribution systems to enable greater use of these products in operational settings.
The Geostationary Operational Environmental Satellite R series (GOES-R) Proving Ground engages the National Weather Service (NWS) forecast, watch, and warning community and other agency users in preoperational demonstrations of the new and advanced capabilities to be available from GOES-R compared to the current GOES constellation. GOES-R will provide significant advances in observing capabilities but will also offer a significant challenge to ensure that users are ready to exploit the new 16-channel imager that will provide 3 times more spectral information, 4 times the spatial coverage, and 5 times the temporal resolution compared to the current imager. In addition, a geostationary lightning mapper will provide continuous and near-uniform real-time surveillance of total lightning activity throughout the Americas and adjacent oceans encompassing much of the Western Hemisphere. To ensure user readiness, forecasters and other users must have access to prototype advanced products within their operational environment well before launch. Examples of the advanced products include improved volcanic ash detection, lightning detection, 1-min-interval rapid-scan imagery, dust and aerosol detection, and synthetic cloud and moisture imagery. A key component of the GOES-R Proving Ground is the two-way interaction between the researchers who introduce new products and techniques and the forecasters who then provide feedback and ideas for improvements that can best be incorporated into NOAA's integrated observing and analysis operations. In 2012 and beyond, the GOES-R Proving Ground will test and validate display and visualization techniques, decision aids, future capabilities, training materials, and the data processing and product distribution systems to enable greater use of these products in operational settings.
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