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Two-Dimensional Variational Analysis of Near-Surface Moisture from Simulated Radar Refractivity-Related Phase Change Observations 被引量:1

Two-Dimensional Variational Analysis of Near-Surface Moisture from Simulated Radar Refractivity-Related Phase Change Observations
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摘要 Because they are most sensitive to atmospheric moisture content, radar refractivity observations can provide high-resolution information about the highly variable low-level moisture field. In this study, simulated radar refractivity-related phase-change data were created using a radar simulator from realistic highresolution model simulation data for a dryline case. These data were analyzed using the 2DVAR system developed specifically for the phase-change data. Two sets of experiments with the simulated observations were performed, one assuming a uniform target spacing of 250 m and one assuming nonuniform spacing between 250 m to 4 km. Several sources of observation error were considered, and their impacts were examined. They included errors due to ground target position uncertainty, typical random errors associated with radar measurements, and gross error due to phase wrapping. Without any additional information, the 2DVAR system was incapable of dealing with phase-wrapped data directly. When there was no phase wrapping in the data, the 2DVAR produced ex- cellent analyses, even in the presence of both position uncertainty and random radar measurement errors. When a separate pre-processing step was applied to unwrap the phase-wrapped data, quality moisture anal- yses were again obtained, although the analyses were smoother due to the reduced effective resolution of the observations by interpolation and smoothing involved in the unwrapping procedure. The unwrapping procedure was effective even when significant differences existed between the analyzed state and the state at a reference time. The results affirm the promise of using radar refractivity phase-change measurements for near-surface moisture analysis. Because they are most sensitive to atmospheric moisture content, radar refractivity observations can provide high-resolution information about the highly variable low-level moisture field. In this study, simulated radar refractivity-related phase-change data were created using a radar simulator from realistic highresolution model simulation data for a dryline case. These data were analyzed using the 2DVAR system developed specifically for the phase-change data. Two sets of experiments with the simulated observations were performed, one assuming a uniform target spacing of 250 m and one assuming nonuniform spacing between 250 m to 4 km. Several sources of observation error were considered, and their impacts were examined. They included errors due to ground target position uncertainty, typical random errors associated with radar measurements, and gross error due to phase wrapping. Without any additional information, the 2DVAR system was incapable of dealing with phase-wrapped data directly. When there was no phase wrapping in the data, the 2DVAR produced ex- cellent analyses, even in the presence of both position uncertainty and random radar measurement errors. When a separate pre-processing step was applied to unwrap the phase-wrapped data, quality moisture anal- yses were again obtained, although the analyses were smoother due to the reduced effective resolution of the observations by interpolation and smoothing involved in the unwrapping procedure. The unwrapping procedure was effective even when significant differences existed between the analyzed state and the state at a reference time. The results affirm the promise of using radar refractivity phase-change measurements for near-surface moisture analysis.
出处 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2013年第2期291-305,共15页 大气科学进展(英文版)
基金 supported by the National Science Foundation (Grant No. AGS-0750790) supported by the NSF grants (Grant Nos. AGS-0802888,OCI-0905040,AGS-0941491,AGS-1046171,and AGS-1046081)
关键词 radar refractivity variational analysis low-level moisture radar refractivity, variational analysis, low-level moisture
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