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- Author or Editor: E. Paul Mcclain x
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Abstract
Errors in operational forecasts produced by high-speed electronic computers can be classed broadly into two categories: (1) those resulting from inadequacies of the dynamic model, and (2) those resulting from poor specification of the initial fields. Many regions of the Northern Hemisphere, particularly oceanic areas, are poorly observed in terms of conventional meteorological data, especially upper-air data. The SINAP (Satellite Input to Numerical Analysis and Prediction) Project at the Weather Bureau's Meteorological Satellite Laboratory has been working to develop techniques for incorporating information derived from satellite cloud pictures into the operational numerical analysis in data-sparse areas.
Trial reanalyses of the National Meteorological Center (NMC) 500-mb. stream function analysis, or its Laplacian, were performed for data-sparse areas of the central and eastern Pacific Ocean using an analysis modification technique consisting of two steps: (1) inferring features of the flow pattern or of the field of large-scale vertical motion from an interpretation of the TIROS-viewed cloud patterns, and (2) modifying the 500-mb. analyses to produce an appropriate vorticity advection field. Underlying this method are certain simplifying assumptions about the relation of the cloud field to the vertical motion field on the one hand, and of the vertical motion to the vorticity advection on the other.
Application of the method and the results obtained are illustrated for one case. Thirty-six-hr. barotropic forecasts were run from both the original NMC analysis and the SINAP modified analysis and then compared with the verifying chart. Verification statistics, such as the root mean square (RMS) error of the stream values and of the vector geostrophic wind, are presented for the case illustrated and for five additional cases. Significant reductions in forecast error were achieved in most cases, the overall average reduction in the RMS error of the wind being 5.4 percent.
Abstract
Errors in operational forecasts produced by high-speed electronic computers can be classed broadly into two categories: (1) those resulting from inadequacies of the dynamic model, and (2) those resulting from poor specification of the initial fields. Many regions of the Northern Hemisphere, particularly oceanic areas, are poorly observed in terms of conventional meteorological data, especially upper-air data. The SINAP (Satellite Input to Numerical Analysis and Prediction) Project at the Weather Bureau's Meteorological Satellite Laboratory has been working to develop techniques for incorporating information derived from satellite cloud pictures into the operational numerical analysis in data-sparse areas.
Trial reanalyses of the National Meteorological Center (NMC) 500-mb. stream function analysis, or its Laplacian, were performed for data-sparse areas of the central and eastern Pacific Ocean using an analysis modification technique consisting of two steps: (1) inferring features of the flow pattern or of the field of large-scale vertical motion from an interpretation of the TIROS-viewed cloud patterns, and (2) modifying the 500-mb. analyses to produce an appropriate vorticity advection field. Underlying this method are certain simplifying assumptions about the relation of the cloud field to the vertical motion field on the one hand, and of the vertical motion to the vorticity advection on the other.
Application of the method and the results obtained are illustrated for one case. Thirty-six-hr. barotropic forecasts were run from both the original NMC analysis and the SINAP modified analysis and then compared with the verifying chart. Verification statistics, such as the root mean square (RMS) error of the stream values and of the vector geostrophic wind, are presented for the case illustrated and for five additional cases. Significant reductions in forecast error were achieved in most cases, the overall average reduction in the RMS error of the wind being 5.4 percent.
Abstract
An automated pixel-scale algorithm has been developed to retrieve cloud type, related cloud layer(s), and the fractional coverages for all cloud layers in each AVHRR (Advanced Very High Resolution Radiometer) pixel at night. In the algorithm, cloud-contaminated pixels are separated from cloud-free pixels and grouped into three generic cloud types. Cloud layers in each cloud type are obtained through a cloud-type uniformity check, a thermal uniformity check, and a channel 4 ( 11 μm) brightness temperature histogram analysis, within a grid area. The algorithm allows for pixels to be mixed among different cloud layers of different cloud types, as well as between cloud layers and the ocean or land surface. A “neighbor-cheek” method is developed to identify the cloud layers associated with each mixed pixel and to calculate the coverages of each of the cloud layers in the pixel. Digital color images are generated based on information on the location, cloud type, cloud layer, and cloud amount of each individual pixel. Visualization comparisons show good agreement between color-coded images and the standard black and white satellite images. The results of the pixel-scale algorithm also show good agreements with the spatial coherence analysis and with National Weather Service surface and radiosonde observations. The pixel-scale algorithm has been developed for use in validation of output from CLAYR (clouds from AVHRR) project algorithms.
Abstract
An automated pixel-scale algorithm has been developed to retrieve cloud type, related cloud layer(s), and the fractional coverages for all cloud layers in each AVHRR (Advanced Very High Resolution Radiometer) pixel at night. In the algorithm, cloud-contaminated pixels are separated from cloud-free pixels and grouped into three generic cloud types. Cloud layers in each cloud type are obtained through a cloud-type uniformity check, a thermal uniformity check, and a channel 4 ( 11 μm) brightness temperature histogram analysis, within a grid area. The algorithm allows for pixels to be mixed among different cloud layers of different cloud types, as well as between cloud layers and the ocean or land surface. A “neighbor-cheek” method is developed to identify the cloud layers associated with each mixed pixel and to calculate the coverages of each of the cloud layers in the pixel. Digital color images are generated based on information on the location, cloud type, cloud layer, and cloud amount of each individual pixel. Visualization comparisons show good agreement between color-coded images and the standard black and white satellite images. The results of the pixel-scale algorithm also show good agreements with the spatial coherence analysis and with National Weather Service surface and radiosonde observations. The pixel-scale algorithm has been developed for use in validation of output from CLAYR (clouds from AVHRR) project algorithms.
Abstract
This paper deals with the problem of aerosol optical thickness (τ A ) retrieval using sun-photometer measurements. The results of the theoretical analysis and computer processing of the dataset collected during the 40th cruise of the R/V Akademik Vernadsky are presented. Accuracy of retrieved τ A is investigated in detail. It is concluded that 1) the τ A measurements from the three shortest wavelength channels are sufficiently accurate (0.02–0.03) for evaluation of the NOAA Advanced Very High Resolution Radiometer aerosol optical thickness operational product; 2) serious discrepancies exist between observation and theory for the two longest wavelength channels, which preclude their use in aerosol optical property studies. Further investigations are required, with emphasis on the computation of atmospheric gaseous absorption, before these channels can be used. Shipboard τ A will be compared with satellite data from the NOAA/National Environment Satellite Data and Information Service in a subsequent paper.
Abstract
This paper deals with the problem of aerosol optical thickness (τ A ) retrieval using sun-photometer measurements. The results of the theoretical analysis and computer processing of the dataset collected during the 40th cruise of the R/V Akademik Vernadsky are presented. Accuracy of retrieved τ A is investigated in detail. It is concluded that 1) the τ A measurements from the three shortest wavelength channels are sufficiently accurate (0.02–0.03) for evaluation of the NOAA Advanced Very High Resolution Radiometer aerosol optical thickness operational product; 2) serious discrepancies exist between observation and theory for the two longest wavelength channels, which preclude their use in aerosol optical property studies. Further investigations are required, with emphasis on the computation of atmospheric gaseous absorption, before these channels can be used. Shipboard τ A will be compared with satellite data from the NOAA/National Environment Satellite Data and Information Service in a subsequent paper.
Abstract
On 28 July 1977 an unusually cloud-ftee nighttime thermal infrared image of the midwestern and northeastern United States from the NOAA 5 satellite enabled detection of more than 50 urban beat islands. Analysis of digital data from the satellite for selected cities yielded maximum urban-rural temperature differences ranging from 2.6 to 6.5°C. Through computer enhancement and enlargement of the satellite imagery, the urban beat islands of St. Louis, Washington, DC and Baltimore can be depicted at a usable scale as large as 1:500 000. A comparison of the enhanced thermal infrared imagery with the 1970 U.S. Census maps of urbanized areas for the three cities indicates the extent of possible urbanization changes in the last seven years.
Abstract
On 28 July 1977 an unusually cloud-ftee nighttime thermal infrared image of the midwestern and northeastern United States from the NOAA 5 satellite enabled detection of more than 50 urban beat islands. Analysis of digital data from the satellite for selected cities yielded maximum urban-rural temperature differences ranging from 2.6 to 6.5°C. Through computer enhancement and enlargement of the satellite imagery, the urban beat islands of St. Louis, Washington, DC and Baltimore can be depicted at a usable scale as large as 1:500 000. A comparison of the enhanced thermal infrared imagery with the 1970 U.S. Census maps of urbanized areas for the three cities indicates the extent of possible urbanization changes in the last seven years.
