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- Author or Editor: B. Stankov x
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Abstract
A new method for deriving profiles of tropospheric water vapor and liquid water from a combination of ground-based remote sensors was applied and tested under winter conditions in Colorado. The method is an extension of physical retrieval techniques used to derive coarse profiles from passive microwave radiometer measurements. Unlike an earlier method, it does not depend on climatological data for first-guess profile inputs. Instead, information about current cloud conditions aloft, obtained with active remote sensors, is used to determine physically realistic, first-guess vertical distributions of the radiometer's integrated vapor and liquid measurements. In preliminary tests, the retrieved profiles were compared with in situ measurements by aircraft and radiosondes during the Winter Icing and Storms Project. The shape of the retrieved liquid profiles agreed well with the aircraft measurements, but heights, thicknesses, and amplitudes differed considerably in some cases. The derived vapor profiles agreed better with radiosonde measurements than the traditional climatological retrievals, but standard deviations of the dewpoint differences wore still quite large (5°C). In an integrated, unattended instrument design, the new method has the potential to provide continuous real-lime profiles of temperature, wind, humidity, liquid water, and pressure.
Abstract
A new method for deriving profiles of tropospheric water vapor and liquid water from a combination of ground-based remote sensors was applied and tested under winter conditions in Colorado. The method is an extension of physical retrieval techniques used to derive coarse profiles from passive microwave radiometer measurements. Unlike an earlier method, it does not depend on climatological data for first-guess profile inputs. Instead, information about current cloud conditions aloft, obtained with active remote sensors, is used to determine physically realistic, first-guess vertical distributions of the radiometer's integrated vapor and liquid measurements. In preliminary tests, the retrieved profiles were compared with in situ measurements by aircraft and radiosondes during the Winter Icing and Storms Project. The shape of the retrieved liquid profiles agreed well with the aircraft measurements, but heights, thicknesses, and amplitudes differed considerably in some cases. The derived vapor profiles agreed better with radiosonde measurements than the traditional climatological retrievals, but standard deviations of the dewpoint differences wore still quite large (5°C). In an integrated, unattended instrument design, the new method has the potential to provide continuous real-lime profiles of temperature, wind, humidity, liquid water, and pressure.
Abstract
A method is presented to obtain a high-vertical-resolution humidity profile if the location and strength of only a few significant segments of the humidity gradient profile are known. The method is based on a previously developed statistical inversion technique coupled with moisture gradient information derived from wind profiler and the radiosonde temperature measurements. An existing retrieval algorithm uses an independent historical radiosonde-derived dataset and data from a two-channel microwave radiometer, standard surface meteorological instruments, and a lidar ceilometer. In this study, the possibility of constraining the statistical retrieval using measurements of significant moisture gradients derived from wind profiler signals and radiosonde temperature observations is investigated. An example is given to illustrate the method: on 26 May 1994 the 449-MHz wind profiler/RASS at Erie, Colorado, detected a strong humidity gradient at 4.9 km MSL. A statistical inversion algorithm constrained to the radar-measured gradient at 4.9 km was used to estimate the moisture profile. Results from this example show that an improvement in retrieved humidity profiles in particular, in the strength and location of a shallow layer, can be obtained if only significant radar-sensed humidity gradient information is added to other ground-based remote sensing measurements.
Abstract
A method is presented to obtain a high-vertical-resolution humidity profile if the location and strength of only a few significant segments of the humidity gradient profile are known. The method is based on a previously developed statistical inversion technique coupled with moisture gradient information derived from wind profiler and the radiosonde temperature measurements. An existing retrieval algorithm uses an independent historical radiosonde-derived dataset and data from a two-channel microwave radiometer, standard surface meteorological instruments, and a lidar ceilometer. In this study, the possibility of constraining the statistical retrieval using measurements of significant moisture gradients derived from wind profiler signals and radiosonde temperature observations is investigated. An example is given to illustrate the method: on 26 May 1994 the 449-MHz wind profiler/RASS at Erie, Colorado, detected a strong humidity gradient at 4.9 km MSL. A statistical inversion algorithm constrained to the radar-measured gradient at 4.9 km was used to estimate the moisture profile. Results from this example show that an improvement in retrieved humidity profiles in particular, in the strength and location of a shallow layer, can be obtained if only significant radar-sensed humidity gradient information is added to other ground-based remote sensing measurements.
Abstract
Bragg backscatter of radar waves from elevated turbulent layers is very highly correlated with the height profile of the gradient of radio refractive index through elevated turbulent layers, as has often been documented in past research. However, many users need profiles of radio refractive index or the associated humidity rather than profiles of their gradients. Simple integration of the gradients is usually not feasible because clutter and various noise sources often severely contaminate the lower-range gates. The authors show that if the total integrated humidity is independently available [for example, from the Global Positioning System (GPS)] and if the surface value of humidity is known, the profiles of humidity are retrievable with good accuracy. This method is demonstrated with data collected in Southern California, where 7 h of 449-MHz data were recorded along with GPS data. Three radiosonde balloons were launched during that period, and the profiles of humidity from the two sources are compared. Simulations are used to assess errors that result from factors such as lack of the sign of the humidity gradients. In conclusion, a humidity profile found by statistical retrieval is compared with one found by the technique proposed in this paper.
Abstract
Bragg backscatter of radar waves from elevated turbulent layers is very highly correlated with the height profile of the gradient of radio refractive index through elevated turbulent layers, as has often been documented in past research. However, many users need profiles of radio refractive index or the associated humidity rather than profiles of their gradients. Simple integration of the gradients is usually not feasible because clutter and various noise sources often severely contaminate the lower-range gates. The authors show that if the total integrated humidity is independently available [for example, from the Global Positioning System (GPS)] and if the surface value of humidity is known, the profiles of humidity are retrievable with good accuracy. This method is demonstrated with data collected in Southern California, where 7 h of 449-MHz data were recorded along with GPS data. Three radiosonde balloons were launched during that period, and the profiles of humidity from the two sources are compared. Simulations are used to assess errors that result from factors such as lack of the sign of the humidity gradients. In conclusion, a humidity profile found by statistical retrieval is compared with one found by the technique proposed in this paper.
Abstract
An algorithm to compute the magnitude of humidity gradient profiles from the measurements of the zeroth, first, and second moments of wind profiling radar (WPR) Doppler spectra was developed and tested. The algorithm extends the National Oceanic and Atmospheric Administration (NOAA)/Environmental Technology Laboratory (ETL) Advanced Signal Processing System (SPS), which provides quality control of radar data in the spectral domain for wind profile retrievals, to include the retrieval of humidity gradient profiles. The algorithm uses a recently developed approximate formula for correcting Doppler spectral widths for the spatial and temporal filtering effects. Data collected by a 3-beam 915-MHz WPR onboard the NOAA research vessel Ronald H. Brown (RHB) and a 5-beam 449-MHz WPR developed at the ETL were used in this study. The two datasets cover vastly different atmospheric conditions, with the 915-MHz shipborne system probing the tropical ocean atmosphere and the 449-MHz WPR probing continental winter upslope icing storm in the Colorado Front Range. Vaisala radiosonde measurements of humidity and temperature profiles on board the RHB and the standard National Weather Service (NWS) radiosonde measurements at Stapleton, Colorado, were used for comparisons. The cases chosen represent typical atmospheric conditions and not special atmospheric situations. Results show that using SPS-obtained measurements of the zeroth, first, and second spectral moments provide radar-obtained humidity gradient profiles up to 3 km AGL.
Abstract
An algorithm to compute the magnitude of humidity gradient profiles from the measurements of the zeroth, first, and second moments of wind profiling radar (WPR) Doppler spectra was developed and tested. The algorithm extends the National Oceanic and Atmospheric Administration (NOAA)/Environmental Technology Laboratory (ETL) Advanced Signal Processing System (SPS), which provides quality control of radar data in the spectral domain for wind profile retrievals, to include the retrieval of humidity gradient profiles. The algorithm uses a recently developed approximate formula for correcting Doppler spectral widths for the spatial and temporal filtering effects. Data collected by a 3-beam 915-MHz WPR onboard the NOAA research vessel Ronald H. Brown (RHB) and a 5-beam 449-MHz WPR developed at the ETL were used in this study. The two datasets cover vastly different atmospheric conditions, with the 915-MHz shipborne system probing the tropical ocean atmosphere and the 449-MHz WPR probing continental winter upslope icing storm in the Colorado Front Range. Vaisala radiosonde measurements of humidity and temperature profiles on board the RHB and the standard National Weather Service (NWS) radiosonde measurements at Stapleton, Colorado, were used for comparisons. The cases chosen represent typical atmospheric conditions and not special atmospheric situations. Results show that using SPS-obtained measurements of the zeroth, first, and second spectral moments provide radar-obtained humidity gradient profiles up to 3 km AGL.
Abstract
During June–July 1999, the NOAA R/V Ron H. Brown (RHB) sailed from Australia to the Republic of Nauru where the Department of Energy's Atmospheric Radiation Measurement (ARM) Program operates a long-term climate observing station. During July, when the RHB was in close proximity to the island of Nauru, detailed comparisons of ship- and island-based instruments were possible. Essentially identical instruments were operated from the ship and the island's Atmospheric Radiation and Cloud Station (ARCS)-2. These instruments included simultaneously launched Vaisala RS80-H radiosondes, the Environmental Technology Laboratory's (ETL) Fourier transform infrared radiometer (FTIR), and ARM's atmospheric emitted radiance interferometer (AERI), as well as cloud radars/ceilometers to identify clear conditions.
The ARM microwave radiometer (MWR) operating on Nauru provided another excellent dataset for the entire Nauru99 experiment. The calibration accuracy was verified by a liquid nitrogen blackbody target experiment and by consistent high quality tipping calibrations throughout the experiment. Comparisons were made for calculated clear-sky brightness temperature (T b ) and for precipitable water vapor (PWV). These results indicate that substantial errors, sometimes of the order of 20% in PWV, occurred with the original radiosondes. When a Vaisala correction algorithm was applied, calculated T b s were in better agreement with the MWR than were the calculations based on the original data. However, the improvement in T b comparisons was noticeably different for different radiosonde lots and was not a monotonic function of radiosonde age. Three different absorption algorithms were compared: Liebe and Layton, Liebe et al., and Rosenkranz. Using AERI spectral radiance observations as a comparison standard, scaling of radiosondes by MWR data was compared with both original and corrected soundings.
Abstract
During June–July 1999, the NOAA R/V Ron H. Brown (RHB) sailed from Australia to the Republic of Nauru where the Department of Energy's Atmospheric Radiation Measurement (ARM) Program operates a long-term climate observing station. During July, when the RHB was in close proximity to the island of Nauru, detailed comparisons of ship- and island-based instruments were possible. Essentially identical instruments were operated from the ship and the island's Atmospheric Radiation and Cloud Station (ARCS)-2. These instruments included simultaneously launched Vaisala RS80-H radiosondes, the Environmental Technology Laboratory's (ETL) Fourier transform infrared radiometer (FTIR), and ARM's atmospheric emitted radiance interferometer (AERI), as well as cloud radars/ceilometers to identify clear conditions.
The ARM microwave radiometer (MWR) operating on Nauru provided another excellent dataset for the entire Nauru99 experiment. The calibration accuracy was verified by a liquid nitrogen blackbody target experiment and by consistent high quality tipping calibrations throughout the experiment. Comparisons were made for calculated clear-sky brightness temperature (T b ) and for precipitable water vapor (PWV). These results indicate that substantial errors, sometimes of the order of 20% in PWV, occurred with the original radiosondes. When a Vaisala correction algorithm was applied, calculated T b s were in better agreement with the MWR than were the calculations based on the original data. However, the improvement in T b comparisons was noticeably different for different radiosonde lots and was not a monotonic function of radiosonde age. Three different absorption algorithms were compared: Liebe and Layton, Liebe et al., and Rosenkranz. Using AERI spectral radiance observations as a comparison standard, scaling of radiosondes by MWR data was compared with both original and corrected soundings.
