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Abstract
A number of large tropical cumulus clouds which developed and decayed over a one-day period were monitored by both ship-based radar and the reflected solar radiance experiment on the geosynchronous satellite ATS-3. A comparison of the radar height of these clouds to their reflected solar radiance has shown a strong correlation (0.88) such that cumulus cloud height and growth may apparently be inferred from a geostationary satellite platform without the use of ground-based radar.
Abstract
A number of large tropical cumulus clouds which developed and decayed over a one-day period were monitored by both ship-based radar and the reflected solar radiance experiment on the geosynchronous satellite ATS-3. A comparison of the radar height of these clouds to their reflected solar radiance has shown a strong correlation (0.88) such that cumulus cloud height and growth may apparently be inferred from a geostationary satellite platform without the use of ground-based radar.
Abstract
Recent measurements of the earth's radiation budget from satellites, together with extensive atmospheric energy transport summaries based on rawinsonde data, allow a new estimate of the required poleward energy transport by Northern Hemisphere oceans for the mean annual case. In the region of maximum net northward energy transport (30–35N), the oceans transport 47% of the required energy (1.7×1022 cal year−1). At 20N, the peak ocean transport accounts for 74% at that latitude; for the region 0–70N the ocean contribution averages 40%.
Abstract
Recent measurements of the earth's radiation budget from satellites, together with extensive atmospheric energy transport summaries based on rawinsonde data, allow a new estimate of the required poleward energy transport by Northern Hemisphere oceans for the mean annual case. In the region of maximum net northward energy transport (30–35N), the oceans transport 47% of the required energy (1.7×1022 cal year−1). At 20N, the peak ocean transport accounts for 74% at that latitude; for the region 0–70N the ocean contribution averages 40%.
Abstract
The development and evaluation of a system for time-continuous mesoscale analysis is presented, with a focus on retrieving water vapor concentrations and ground surface temperatures from VISSR Atmospheric Sounder (VAS) data. The analysis system is distinguished by an intimate coupling of retrieval and numerical modeling processes that avoids some of the problem researchers have encountered when satellite-retrieved parameters have been input to models. The system incorporates virtually all of the temporal, vertical and horizontal structure that can be resolved in VAS soundings while maintaining model-generated gradients. The two primary components of the system are a version of the CSU Regional Atmospheric Modeling System (RAMS) and an algorithm for retrieving meteorological parameters from VAS data.
The analysis system was evaluated by means of simulations, with a domain that consisted of a vertical cross section through a broad mountain slope. The purposes were to determine the accuracy of coupled analysis results under controlled conditions and to compare results of the coupled scheme with those of other analysis schemes. For water vapor analysis, vertical gradients were more accurately resolved with the coupled method than with conventional retrieval from satellite data. The coupled method's incorporation of VAS data from multiple observation times was valuable for making mesoscale horizontal gradients stand out more clearly amid the noise in the water vapor analysis. In addition, the method was relatively robust when confronted with a common problem in analysis of the preconvective atmosphere—contamination of the satellite data by increasing amounts of small convective clouds. Analyses in which surface temperatures were derived from satellite-based retrievals were compared with the alternative of relying on energy balance computations without mesoscale data about soil characteristics. The surface temperatures from the two methods differed by as much as 5 K, giving rise to prominent differences in the induced mesoscale circulations. The energy balance computations were so sensitive to soil characteristics that the satellite retrieval method gave more accurate results even with cloud contamination.
Abstract
The development and evaluation of a system for time-continuous mesoscale analysis is presented, with a focus on retrieving water vapor concentrations and ground surface temperatures from VISSR Atmospheric Sounder (VAS) data. The analysis system is distinguished by an intimate coupling of retrieval and numerical modeling processes that avoids some of the problem researchers have encountered when satellite-retrieved parameters have been input to models. The system incorporates virtually all of the temporal, vertical and horizontal structure that can be resolved in VAS soundings while maintaining model-generated gradients. The two primary components of the system are a version of the CSU Regional Atmospheric Modeling System (RAMS) and an algorithm for retrieving meteorological parameters from VAS data.
The analysis system was evaluated by means of simulations, with a domain that consisted of a vertical cross section through a broad mountain slope. The purposes were to determine the accuracy of coupled analysis results under controlled conditions and to compare results of the coupled scheme with those of other analysis schemes. For water vapor analysis, vertical gradients were more accurately resolved with the coupled method than with conventional retrieval from satellite data. The coupled method's incorporation of VAS data from multiple observation times was valuable for making mesoscale horizontal gradients stand out more clearly amid the noise in the water vapor analysis. In addition, the method was relatively robust when confronted with a common problem in analysis of the preconvective atmosphere—contamination of the satellite data by increasing amounts of small convective clouds. Analyses in which surface temperatures were derived from satellite-based retrievals were compared with the alternative of relying on energy balance computations without mesoscale data about soil characteristics. The surface temperatures from the two methods differed by as much as 5 K, giving rise to prominent differences in the induced mesoscale circulations. The energy balance computations were so sensitive to soil characteristics that the satellite retrieval method gave more accurate results even with cloud contamination.
Abstract
Influences on the mesoscale distribution of summertime convective cloud development in the northeastern Colorado region are described using a new system for time-continuous mesoscale analysis. The analysis system is distinctive in that there is an intimate coupling between integration of a numerical model and retrieval of temperature and water vapor concentrations from VISSR Atmospheric Sounder (VAS) data. We present a case study to compare results of the coupled analysis method with those of related methods, focusing on the roles of variations in ground surface temperatures and water vapor concentrations.
The horizontal and time variations represented in satellite-based (coupled) surface temperature analyses closely corresponded to information from conventional shelter temperature observations, but had much greater detail. In contrast, temperature based on energy balance computations tended to increase too quickly during the morning and were lacking in mesoscale feature. In the water vapor analyses, when the first set of satellite data is less reliable than the later sets, some of the contamination lingers throughout the time-continuous coupled analysis results. However, the coupled method generally appears to be the most valuable method considered in this study because it exploits the major strengths of the numerical model and the satellite data while making it relatively easy to recognize and compensate for any impacts of their weaknesses. In addition, the coupled analysis results illustrated that there can be very large mesoscale gradients in temperatures at the ground surface even on relatively flat terrain. These gradients, in combination with terrain height variations, can play an important role in preconvective water vapor kinematics through their influences on vertical and horizontal winds. The analysis system proved to be valuable for forecasting through the close correspondence between derived stability indices and later convective development in the case we studied.
Abstract
Influences on the mesoscale distribution of summertime convective cloud development in the northeastern Colorado region are described using a new system for time-continuous mesoscale analysis. The analysis system is distinctive in that there is an intimate coupling between integration of a numerical model and retrieval of temperature and water vapor concentrations from VISSR Atmospheric Sounder (VAS) data. We present a case study to compare results of the coupled analysis method with those of related methods, focusing on the roles of variations in ground surface temperatures and water vapor concentrations.
The horizontal and time variations represented in satellite-based (coupled) surface temperature analyses closely corresponded to information from conventional shelter temperature observations, but had much greater detail. In contrast, temperature based on energy balance computations tended to increase too quickly during the morning and were lacking in mesoscale feature. In the water vapor analyses, when the first set of satellite data is less reliable than the later sets, some of the contamination lingers throughout the time-continuous coupled analysis results. However, the coupled method generally appears to be the most valuable method considered in this study because it exploits the major strengths of the numerical model and the satellite data while making it relatively easy to recognize and compensate for any impacts of their weaknesses. In addition, the coupled analysis results illustrated that there can be very large mesoscale gradients in temperatures at the ground surface even on relatively flat terrain. These gradients, in combination with terrain height variations, can play an important role in preconvective water vapor kinematics through their influences on vertical and horizontal winds. The analysis system proved to be valuable for forecasting through the close correspondence between derived stability indices and later convective development in the case we studied.
Abstract
Reflected radiance measurements from the multicolor spin-scan cloud camera on Applications Technology Satellite III are used to determine the percentages of selected areas of the earth that are cloud-free. The areas chosen are meteorologically active and represent common cloud patterns. Use of several data unit sizes shows how the observed percent clear area decreases with decreasing spatial resolution of a simulated sensor. Methods of determining a cloud-no cloud threshold are discussed. The change of cloud cover over a period of a few hours is examined. It is found that clouds smaller than the instantaneous field of view are often not recognized as clouds and therefore tend to affect the interpretation of spacecraft camera measurements. The results of this investigation are used to suggest the optimum spatial resolution for radiometrically sounding the atmosphere from a geosynchronous satellite using an instrument described in the report.
Abstract
Reflected radiance measurements from the multicolor spin-scan cloud camera on Applications Technology Satellite III are used to determine the percentages of selected areas of the earth that are cloud-free. The areas chosen are meteorologically active and represent common cloud patterns. Use of several data unit sizes shows how the observed percent clear area decreases with decreasing spatial resolution of a simulated sensor. Methods of determining a cloud-no cloud threshold are discussed. The change of cloud cover over a period of a few hours is examined. It is found that clouds smaller than the instantaneous field of view are often not recognized as clouds and therefore tend to affect the interpretation of spacecraft camera measurements. The results of this investigation are used to suggest the optimum spatial resolution for radiometrically sounding the atmosphere from a geosynchronous satellite using an instrument described in the report.
Abstract
A statistical analysis of satellite infrared sounding data from the Vertical Temperature Profile Radiometer (VTPR) on NOAA 4 was performed in conjunction with the National Severe Storms Laboratory (NSSL) mesoscale sounding period (10 May-12 June 1976). Satellite radiances, retrieved temperatures and moisture information in the form of radiance residuals at a resolution of ∼70 km were examined for a 14-day composite period using structure and correlation functions. A structure analysis as a function of data separation distance for a field of measured values can detect the mean nondirectional gradient in the field. Estimates of the relative noise level in the measurements were also obtained by extrapolating the obtained structure to zero separation distance. The rms radiance noise levels for the VTPR channels were found to be close to the design specifications for the VTPR instrument. For retrieved temperatures, the noise level was determined to be ∼0.5°C at the three pressure levels examined.
The structure functions for all available satellite-derived temperatures in the composite period compared favorably to similar results computed using high-resolution NSSL rawinsonde data. However, moisture correlation results demonstrated that the satellite-derived moisture in the integrated sense is not an equivalent substitute for mesoscale rawinsonde soundings. The structure-function analysis was also applied to each of the 14 individual days of available satellite data. The structure as a function of distance for VTPR channels 6 and 7 reflect mainly lower tropospheric temperature and moisture gradients, respectively. On days with both large temperature and moisture gradients as detected by the satellite these gradients appeared to be associated with severe storms later in the day. A structure-function analysis of satellite-derived 500 mb temperature fields was also found to detect existing upper air patterns on individual days.
The information content of individual temperature and moisture fields derived from the satellite soundings was interpreted by comparison with similar fields from conventional rawinsonde soundings. Fields of both temperature and moisture from the two instruments were compared by direct correlation of the two sets of measurements. Discrepancies existed between the compared fields, but they were to a large extent explained by differences between the two measuring systems and time and space scale differences between the measurements. According to the analysis, temperatures were retrieved from the satellite data with reasonable success on most of the days at both 300 and 500 mb, but with much less success at 700 mb. Again, the moisture information extracted from the satellite data was not as promising due to its integrated effect and due to the small observed moisture gradients on some days.
Structure-function analysis of satellite temperature soundings was shown to provide a means of interpreting these satellite data. It demonstrated that high-resolution satellite soundings provide information about spatial variations of temperature structure equivalent to that provided by high-density rawinsondes.
Abstract
A statistical analysis of satellite infrared sounding data from the Vertical Temperature Profile Radiometer (VTPR) on NOAA 4 was performed in conjunction with the National Severe Storms Laboratory (NSSL) mesoscale sounding period (10 May-12 June 1976). Satellite radiances, retrieved temperatures and moisture information in the form of radiance residuals at a resolution of ∼70 km were examined for a 14-day composite period using structure and correlation functions. A structure analysis as a function of data separation distance for a field of measured values can detect the mean nondirectional gradient in the field. Estimates of the relative noise level in the measurements were also obtained by extrapolating the obtained structure to zero separation distance. The rms radiance noise levels for the VTPR channels were found to be close to the design specifications for the VTPR instrument. For retrieved temperatures, the noise level was determined to be ∼0.5°C at the three pressure levels examined.
The structure functions for all available satellite-derived temperatures in the composite period compared favorably to similar results computed using high-resolution NSSL rawinsonde data. However, moisture correlation results demonstrated that the satellite-derived moisture in the integrated sense is not an equivalent substitute for mesoscale rawinsonde soundings. The structure-function analysis was also applied to each of the 14 individual days of available satellite data. The structure as a function of distance for VTPR channels 6 and 7 reflect mainly lower tropospheric temperature and moisture gradients, respectively. On days with both large temperature and moisture gradients as detected by the satellite these gradients appeared to be associated with severe storms later in the day. A structure-function analysis of satellite-derived 500 mb temperature fields was also found to detect existing upper air patterns on individual days.
The information content of individual temperature and moisture fields derived from the satellite soundings was interpreted by comparison with similar fields from conventional rawinsonde soundings. Fields of both temperature and moisture from the two instruments were compared by direct correlation of the two sets of measurements. Discrepancies existed between the compared fields, but they were to a large extent explained by differences between the two measuring systems and time and space scale differences between the measurements. According to the analysis, temperatures were retrieved from the satellite data with reasonable success on most of the days at both 300 and 500 mb, but with much less success at 700 mb. Again, the moisture information extracted from the satellite data was not as promising due to its integrated effect and due to the small observed moisture gradients on some days.
Structure-function analysis of satellite temperature soundings was shown to provide a means of interpreting these satellite data. It demonstrated that high-resolution satellite soundings provide information about spatial variations of temperature structure equivalent to that provided by high-density rawinsondes.
Abstract
Five-minute interval 1 km resolution SMS visible channel data were used to derive low-level wind fields by tracking small cumulus clouds on NASA's Atmospheric and Oceanographic Information Processing System (AOIPS). The satellite-derived wind fields were combined with surface mixing ratios to derive horizontal moisture convergence in the pre-storm environment of 24 April 1975. Storms began developing in an area extending from southwest Oklahoma to eastern Tennessee 2 h subsequent to the time of the derived fields. The maximum moisture convergence was computed to be 2.2 × 10−3 g kg−1 s−1 and areas of low-level convergence of moisture were in general indicative of regions of severe storm genesis. The resultant moisture convergence fields derived from two wind acts 20 min apart were spatially consistent and reflected the mesoscale forcing of ensuing storm development. Results are discussed with regard to possible limitations in quantifying the relationship between low-level flow and satellite-derived cumulus motion in an antecedent storm environment.
Abstract
Five-minute interval 1 km resolution SMS visible channel data were used to derive low-level wind fields by tracking small cumulus clouds on NASA's Atmospheric and Oceanographic Information Processing System (AOIPS). The satellite-derived wind fields were combined with surface mixing ratios to derive horizontal moisture convergence in the pre-storm environment of 24 April 1975. Storms began developing in an area extending from southwest Oklahoma to eastern Tennessee 2 h subsequent to the time of the derived fields. The maximum moisture convergence was computed to be 2.2 × 10−3 g kg−1 s−1 and areas of low-level convergence of moisture were in general indicative of regions of severe storm genesis. The resultant moisture convergence fields derived from two wind acts 20 min apart were spatially consistent and reflected the mesoscale forcing of ensuing storm development. Results are discussed with regard to possible limitations in quantifying the relationship between low-level flow and satellite-derived cumulus motion in an antecedent storm environment.
Abstract
Principal components have been widely used in regression retrieval of atmospheric parameters, but when applied to water vapor concentrations their use entails special problems. We discuss two of these problem and present results of retrieval experiments designed to alleviate them. The experiments employed High-resolution Infrared Radiation Sounder satellite data in conjunction with radiosonde observations. We found that mixing ratio is a less appropriate parameter for principal component-based retrieval than is a mean-saturation adjusted mixing ratio. Also, retrieval accuracy was vapor by identifying the optimum numbers of eigenvectors to use when transforming the water vapor profiles and the satellite brightness temperature, respectively, into their principal components. In our studies three eigenvectors were optimal for representation of water vapor, implying that HIRS-2 data are capable of retrieving at least third-order vertical resolution in water vapor profiles. In addition, we compared principal component-based retrieval with standard multiple regression and found that a hybrid of the two methods gave the greatest retrieval accuracy.
Abstract
Principal components have been widely used in regression retrieval of atmospheric parameters, but when applied to water vapor concentrations their use entails special problems. We discuss two of these problem and present results of retrieval experiments designed to alleviate them. The experiments employed High-resolution Infrared Radiation Sounder satellite data in conjunction with radiosonde observations. We found that mixing ratio is a less appropriate parameter for principal component-based retrieval than is a mean-saturation adjusted mixing ratio. Also, retrieval accuracy was vapor by identifying the optimum numbers of eigenvectors to use when transforming the water vapor profiles and the satellite brightness temperature, respectively, into their principal components. In our studies three eigenvectors were optimal for representation of water vapor, implying that HIRS-2 data are capable of retrieving at least third-order vertical resolution in water vapor profiles. In addition, we compared principal component-based retrieval with standard multiple regression and found that a hybrid of the two methods gave the greatest retrieval accuracy.
