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Tetsuya (Ted) Fujita was a pioneer in remote sensing of atmospheric motion. When meteorological satellites were introduced, he developed techniques for precise analysis of satellite measurements (sequences of images from polar orbiting platforms first and then from geostationary platforms). Soon after his initial work, the ability to track clouds and relate them to flow patterns in the atmosphere was transferred into routine operations at the national forecast centers. Cloud motion vectors derived from geostationary satellite imagery have evolved into an important data source of meteorological information, especially over the oceans. The current National Environmental Satellite, Data, and Information Service operational production of Geostationary Operational Environmental Satellite cloud and water vapor motion winds continues to perform well; rms differences with respect to raob's are found to be 6.5–7.5 m s−1
Tetsuya (Ted) Fujita was a pioneer in remote sensing of atmospheric motion. When meteorological satellites were introduced, he developed techniques for precise analysis of satellite measurements (sequences of images from polar orbiting platforms first and then from geostationary platforms). Soon after his initial work, the ability to track clouds and relate them to flow patterns in the atmosphere was transferred into routine operations at the national forecast centers. Cloud motion vectors derived from geostationary satellite imagery have evolved into an important data source of meteorological information, especially over the oceans. The current National Environmental Satellite, Data, and Information Service operational production of Geostationary Operational Environmental Satellite cloud and water vapor motion winds continues to perform well; rms differences with respect to raob's are found to be 6.5–7.5 m s−1
Satellite Meteorology
How it all Started, 50 Years Ago
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No Abstract available.
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Abstract
Estimates of cloud-top pressure and effective fractional cloud cover may be retrieved from satellite infrared sounder data. This paper presents the results of a simulation study which provides some insights into the relative performance of different retrieval methods and of different combinations of spectral channels. The “minimum residual method,” a variant of a technique described previously by other authors, is presented. It is applied here to groups of HIRS-2 channels and some aspects of its performance for different combinations of channels are examined using simulated data. It is also compared with the “radiance rationing method.” Calculations suggest that the minimum residual method is comparable in performance to the radiance rationing method for high cloud but better for midlevel cloud. The relationship (and relative performance) of these methods to that used operationally to assign pressures to cloud tracers in Meteosat data is also discussed. The methods presented are for retrieving cloud parameters alone and have practical applications as such. However, they may also be used as a means of obtaining first-guess cloud parameters within satellite sounding inversion schemes which retrieve simultaneously atmospheric temperature and humidity profiles along with cloud and surface parameters.
Abstract
Estimates of cloud-top pressure and effective fractional cloud cover may be retrieved from satellite infrared sounder data. This paper presents the results of a simulation study which provides some insights into the relative performance of different retrieval methods and of different combinations of spectral channels. The “minimum residual method,” a variant of a technique described previously by other authors, is presented. It is applied here to groups of HIRS-2 channels and some aspects of its performance for different combinations of channels are examined using simulated data. It is also compared with the “radiance rationing method.” Calculations suggest that the minimum residual method is comparable in performance to the radiance rationing method for high cloud but better for midlevel cloud. The relationship (and relative performance) of these methods to that used operationally to assign pressures to cloud tracers in Meteosat data is also discussed. The methods presented are for retrieving cloud parameters alone and have practical applications as such. However, they may also be used as a means of obtaining first-guess cloud parameters within satellite sounding inversion schemes which retrieve simultaneously atmospheric temperature and humidity profiles along with cloud and surface parameters.
Abstract
The accuracy of temperature and moisture vertical profiles retrieved from infrared spectral measurements is dependent on accurate definition of all contributions from the observed “surface–atmosphere” system to the outgoing radiances. The associated inverse problem is ill posed. Instrument noise is a major contributor to errors in modeling spectral measurements. This paper considers an approach for noise reduction in the Geostationary Operational Environmental Satellite (GOES) spectral channels using spatial averaging that is based upon spectral characteristics of the measurements, spatial properties of atmospheric fields of temperature and moisture, and properties of the inverse problem. Spatial averaging over different fields of regard is studied for the GOES-8 sounder spectral bands. Results of the statistical analysis are presented.
Abstract
The accuracy of temperature and moisture vertical profiles retrieved from infrared spectral measurements is dependent on accurate definition of all contributions from the observed “surface–atmosphere” system to the outgoing radiances. The associated inverse problem is ill posed. Instrument noise is a major contributor to errors in modeling spectral measurements. This paper considers an approach for noise reduction in the Geostationary Operational Environmental Satellite (GOES) spectral channels using spatial averaging that is based upon spectral characteristics of the measurements, spatial properties of atmospheric fields of temperature and moisture, and properties of the inverse problem. Spatial averaging over different fields of regard is studied for the GOES-8 sounder spectral bands. Results of the statistical analysis are presented.
Abstract
To improve the accuracy of vertical profiles of temperature and moisture retrieved from infrared spectral measurements, the surface emissivity must be accounted for in the solution of the inverse problem (based upon the radiative transfer equation). A model that accounts for the emission and reflection on the lower atmospheric boundary and an algorithm of solution are presented. Results using spectral measurements from an airborne radiometer over land surfaces are discussed. The solution of the inverse problem includes the surface emissivity, the surface temperature, and the vertical temperature–humidity profile. It is shown that accounting for the surface emissivity in the solution of the inverse problem substantially and positively changes the meteorological profiles.
Abstract
To improve the accuracy of vertical profiles of temperature and moisture retrieved from infrared spectral measurements, the surface emissivity must be accounted for in the solution of the inverse problem (based upon the radiative transfer equation). A model that accounts for the emission and reflection on the lower atmospheric boundary and an algorithm of solution are presented. Results using spectral measurements from an airborne radiometer over land surfaces are discussed. The solution of the inverse problem includes the surface emissivity, the surface temperature, and the vertical temperature–humidity profile. It is shown that accounting for the surface emissivity in the solution of the inverse problem substantially and positively changes the meteorological profiles.
Abstract
This paper compares the cloud parameter data records derived from High Resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from the years 2003 through 2013. Cloud-top pressure (CTP) and effective emissivity (ε f; cloud emissivity multiplied by cloud fraction) are derived using the 15-μm spectral bands in the CO2 absorption band and implementing the CO2-slicing technique; the approach is robust for high semitransparent clouds but weak for low clouds with little thermal contrast from clear-sky radiances. The high-cloud (HiCld; with CTP less than 440 hPa) seasonal cycles of HIRS and MODIS observations are found to be in sync, but the HIRS frequency of detection is about 10% higher than that of MODIS (which is attributed to a lower threshold for cloud detection in the HIRS CO2 bands). Differences are largest during nighttime and at the beginning of the time series (2003–06). Both show Northern Hemisphere (NH) and Southern Hemisphere (SH) seasonal HiClds are out of phase and both agree within 2% on NH–SH HiCld differences. During the summer, maximum HiCld frequency averages 5% more in the NH.
Abstract
This paper compares the cloud parameter data records derived from High Resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from the years 2003 through 2013. Cloud-top pressure (CTP) and effective emissivity (ε f; cloud emissivity multiplied by cloud fraction) are derived using the 15-μm spectral bands in the CO2 absorption band and implementing the CO2-slicing technique; the approach is robust for high semitransparent clouds but weak for low clouds with little thermal contrast from clear-sky radiances. The high-cloud (HiCld; with CTP less than 440 hPa) seasonal cycles of HIRS and MODIS observations are found to be in sync, but the HIRS frequency of detection is about 10% higher than that of MODIS (which is attributed to a lower threshold for cloud detection in the HIRS CO2 bands). Differences are largest during nighttime and at the beginning of the time series (2003–06). Both show Northern Hemisphere (NH) and Southern Hemisphere (SH) seasonal HiClds are out of phase and both agree within 2% on NH–SH HiCld differences. During the summer, maximum HiCld frequency averages 5% more in the NH.
Abstract
Over the last 8 yr frequency and location of cloud observations have been compiled using multispectral High Resolution Infrared Radiation Sounder (HIRS) data from the National Oceanic and Atmospheric Administration polar-orbiting satellites; this work is an extension of the 4-yr dataset reported by D. Wylie et al. The CO2 slicing algorithm applied to the HIRS data exhibits a higher sensitivity to semitransparent cirrus clouds than the cloud algorithm used by the International Satellite Cloud Climatology Project; the threshold for cloud detection appears to require visible optical depths (τ vis) greater than 0.1.
The geographical distributions of clouds in the 8-yr dataset are nearly the same as those reported from 4 yr of data. The detection of upper-tropospheric clouds occurs most often in the intertropical convergence zone and midlatitude storm belts with lower concentrations in subtropical deserts and oceanic subtropical highs. The areas of concentrated cloud cover exhibit latitudinal movement with the seasons as in other cloud datasets. HIRS finds clear sky in 25%, opaque cloud in 32%, and semitransparent cloud in 43% of all its observations. The effective emissivity of the all semitransparent clouds (τ vis < 6) ranges from 0.2 to 0.6 with an average value of about 0.5.
Time trends are reexamined in detail. A possible cirrus increase in 1991 reported by Wylie and coauthors in 1994 is found to be diminished upon reinspection. The revised 8-yr record has indications of an increase in high clouds in the northern midlatitudes (0.5% yr−1) but little change elsewhere. The seasonal cycle of cloud cover in the Southern Hemisphere becomes very noticeable in 1993.
Abstract
Over the last 8 yr frequency and location of cloud observations have been compiled using multispectral High Resolution Infrared Radiation Sounder (HIRS) data from the National Oceanic and Atmospheric Administration polar-orbiting satellites; this work is an extension of the 4-yr dataset reported by D. Wylie et al. The CO2 slicing algorithm applied to the HIRS data exhibits a higher sensitivity to semitransparent cirrus clouds than the cloud algorithm used by the International Satellite Cloud Climatology Project; the threshold for cloud detection appears to require visible optical depths (τ vis) greater than 0.1.
The geographical distributions of clouds in the 8-yr dataset are nearly the same as those reported from 4 yr of data. The detection of upper-tropospheric clouds occurs most often in the intertropical convergence zone and midlatitude storm belts with lower concentrations in subtropical deserts and oceanic subtropical highs. The areas of concentrated cloud cover exhibit latitudinal movement with the seasons as in other cloud datasets. HIRS finds clear sky in 25%, opaque cloud in 32%, and semitransparent cloud in 43% of all its observations. The effective emissivity of the all semitransparent clouds (τ vis < 6) ranges from 0.2 to 0.6 with an average value of about 0.5.
Time trends are reexamined in detail. A possible cirrus increase in 1991 reported by Wylie and coauthors in 1994 is found to be diminished upon reinspection. The revised 8-yr record has indications of an increase in high clouds in the northern midlatitudes (0.5% yr−1) but little change elsewhere. The seasonal cycle of cloud cover in the Southern Hemisphere becomes very noticeable in 1993.
Abstract
In this paper, the authors offer their observations from more than 30 years of involvement in the evolution of the space-based meteorological remote sensing systems. Successes and issues from the past are recalled that established meteorological satellites into their current pivotal role. Evolution of imaging and sounding satellite systems from user requirements to affordable realizations is noted; some examples from recent U.S. and European experiences in the area of operational meteorological satellites are presented. The authors discuss the importance of the balanced roles of the three partners in satellite development (government, research, and industry), the need to develop full utilization of new satellite programs quickly during their early life, and a vision for global cooperation early in the planning stages of meteorological satellite missions. The authors offer suggestions that could foster expanded international collaboration on science and applications as well as expedite more satellite observations being pursued in a sustained manner.
Abstract
In this paper, the authors offer their observations from more than 30 years of involvement in the evolution of the space-based meteorological remote sensing systems. Successes and issues from the past are recalled that established meteorological satellites into their current pivotal role. Evolution of imaging and sounding satellite systems from user requirements to affordable realizations is noted; some examples from recent U.S. and European experiences in the area of operational meteorological satellites are presented. The authors discuss the importance of the balanced roles of the three partners in satellite development (government, research, and industry), the need to develop full utilization of new satellite programs quickly during their early life, and a vision for global cooperation early in the planning stages of meteorological satellite missions. The authors offer suggestions that could foster expanded international collaboration on science and applications as well as expedite more satellite observations being pursued in a sustained manner.
In the spring of 1994, the first of the National Oceanic and Atmospheric Administration's (NOAA's) next generation of geostationary satellites, GOES-I, is scheduled for launch. The introduction of this major component of NOAA's modernization represents a significant advance in geostationary remote sensing. All major components of the GOES-I system are new or greatly improved: 1) the satellite is earth oriented to improve instrument performance; 2) sounding and imaging operations are now performed by different and separate instruments; 3) a five-band multispectral radiometer with higher spatial resolution improves imaging capabilities; 4) a sounder with higher radiometric sensitivity enables operational temperature and moisture profile retrieval from geostationary altitude for the first time; 5) a different data format is used to retransmit raw data to directreceive users; and 6) a new ground data processing system handles the high data volume and distributes advanced products to a variety of users.
This article describes the features of the GOES-I spacecraft and instruments, imaging and sounding schedules, data handling systems, and remote sensing products. Simulations of GOES-I imager and sounder products are presented and compared with GOES-7 products. The simulations show that GOES-I imagery, derived product images, and sounder products should be significant improvements in both frequency of coverage and accuracy.
In the spring of 1994, the first of the National Oceanic and Atmospheric Administration's (NOAA's) next generation of geostationary satellites, GOES-I, is scheduled for launch. The introduction of this major component of NOAA's modernization represents a significant advance in geostationary remote sensing. All major components of the GOES-I system are new or greatly improved: 1) the satellite is earth oriented to improve instrument performance; 2) sounding and imaging operations are now performed by different and separate instruments; 3) a five-band multispectral radiometer with higher spatial resolution improves imaging capabilities; 4) a sounder with higher radiometric sensitivity enables operational temperature and moisture profile retrieval from geostationary altitude for the first time; 5) a different data format is used to retransmit raw data to directreceive users; and 6) a new ground data processing system handles the high data volume and distributes advanced products to a variety of users.
This article describes the features of the GOES-I spacecraft and instruments, imaging and sounding schedules, data handling systems, and remote sensing products. Simulations of GOES-I imager and sounder products are presented and compared with GOES-7 products. The simulations show that GOES-I imagery, derived product images, and sounder products should be significant improvements in both frequency of coverage and accuracy.
Abstract
To retrieve vertical profiles of temperature and moisture from infrared spectral measurements, surface emissivity must be accounted for in the physical solution of the inverse problem. A radiative model that includes the emission and reflection on the lower atmospheric boundary is introduced. An algorithm is developed for the solution of the vertical temperature–humidity profile and the estimation of an effective surface emissivity and temperature within the sounding area. Results using spectral measurements from the Geostationary Operational Environmental Satellite (GOES)-8 sounder are presented. It is found that accounting for the surface emissivity in the solution of the inverse problem has a positive impact on the meteorological profiles.
Abstract
To retrieve vertical profiles of temperature and moisture from infrared spectral measurements, surface emissivity must be accounted for in the physical solution of the inverse problem. A radiative model that includes the emission and reflection on the lower atmospheric boundary is introduced. An algorithm is developed for the solution of the vertical temperature–humidity profile and the estimation of an effective surface emissivity and temperature within the sounding area. Results using spectral measurements from the Geostationary Operational Environmental Satellite (GOES)-8 sounder are presented. It is found that accounting for the surface emissivity in the solution of the inverse problem has a positive impact on the meteorological profiles.
