Use of Wind Profiler Estimates of Significant Moisture Gradients to Improve Humidity Profile Retrieval

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  • 1 Environmental Technology Laboratory, NOAA, Boulder, Colorado
  • | 2 CIRES, University of Colorado, Boulder, Colorado
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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.

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