Improving Radar Refractivity Retrieval by Considering the Change in the Refractivity Profile and the Varying Altitudes of Ground Targets

Feng, Ya-Chien; Fabry, Frédéric; Weckwerth, Tammy M.

doi:10.1175/jtech-d-15-0224.1

Cited by 10 publications

(17 citation statements)

References 43 publications

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“…These characteristics have significant impacts on radar target detection and target tracking because failure to consider a ducting environment may yield false radar returns. Therefore, the study of atmospheric ducts can not only improve the performance of radar or communications systems but can also contribute to research into the atmospheric boundary layer [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Surface Duct Using Ground-Based GPS Phase Delay and Propagation Loss

et al. 2018

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Abstract:The propagation of Global Positioning System (GPS) signals at low-elevation angles is significantly affected by a surface duct. In this paper, we present an improved algorithm known as NSSAGA, in which simulated annealing (SA) is combined with the non-dominated sorting genetic algorithm II (NSGA-II). Matched-field processing was used to remotely sense the refractivity structure by using the data of ground-based GPS phase delay and propagation loss from multiple antenna heights. The performance was checked by simulation data with and without noise. In comparison with NSGA-II, the new hybrid algorithm retrieved the refractivity structure more efficiently under various noise conditions. We then modified the objective function and found that matched-field processing is more effective than the conventional least-squares method for inferring the refractivity parameters. Comparing the inversion results and in situ sounding data suggests that the improved method presented herein can capture refractivity characteristics in realistic environments.

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Section: Introductionmentioning

confidence: 99%

Estimation of Surface Duct Using Ground-Based GPS Phase Delay and Propagation Loss

et al. 2018

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“…data are obtained from consecutive PPIs (Plan Position Indicators), that is, with a temporal resolution of about 3-4 min, variations between consecutive PPIs of ±8 N-units and ±15 N-units km −1 for N and ∂N/∂h, respectively, are considered. This analysis is additional to the one performed in [40], which considered larger temporal resolutions and smaller differences in height between consecutive targets.…”

Section: Discussionmentioning

confidence: 99%

“…Unfortunately, the limited accuracy of radar coverage estimates is transferred to refractivity vertical gradient estimates. In [40], it was proposed to previously estimate the refractivity vertical gradient from power measurements at two elevation angles. The variation of the refractivity vertical gradient between the measurements at different elevation angles affects the accuracy of this method.…”

Section: Introductionmentioning

confidence: 99%

High Temporal Resolution Refractivity Retrieval from Radar Phase Measurements

López¹,

Rio²

2018

Remote Sensing

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Knowledge of the spatial and temporal variability of near-surface water vapor is of great importance to successfully model reliable radio communications systems and forecast atmospheric phenomena such as convective initiation and boundary layer processes. However, most current methods to measure atmospheric moisture variations hardly provide the temporal and spatial resolutions required for detection of such atmospheric processes. Recently, considering the high correlation between refractivity variations and water vapor pressure variations at warm temperatures, and the good temporal and spatial resolution that weather radars provide, the measurement of the refractivity with radar became of interest. Firstly, it was proposed to estimate refractivity variations from radar phase measurements of ground-based stationary targets returns. For that, it was considered that the backscattering from ground targets is stationary and the vertical gradient of the refractivity could be neglected. Initial experiments showed good results over flat terrain when the radar and target heights are similar. However, the need to consider the non-zero vertical gradient of the refractivity over hilly terrain is clear. Up to date, the methods proposed consider previous estimation of the refractivity gradient in order to correct the measured phases before the refractivity estimation. In this paper, joint estimation of the refractivity variations at the radar height and the refractivity vertical gradient variations using scan-to-scan phase measurement variations is proposed. To reduce the noisiness of the estimates, a least squares method is used. Importantly, to apply this algorithm, it is not necessary to modify the radar scanning mode. For the purpose of this study, radar data obtained during the Refractivity Experiment for H 2 O Research and Collaborative Operational Technology Transfer (REFRACTT_2006), held in northeastern Colorado (USA), are used. The refractivity estimates obtained show a good performance of the algorithm proposed compared to the refractivity derived from two automatic weather stations located close to the radar, demonstrating the possibility of radar based refractivity estimation in hilly terrain and non-homogeneous atmosphere with high spatial resolution.

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“…The phase change caused by the change in refractivity at a given height above the terrain is the signal of interest for radar refractivity estimation (Fabry 2004;Feng et al 2016). However, different reasons other than this atmospheric-driven signal also lead to uncertainties in f or introduce errors in the refractivity estimations.…”

Section: B Uncertainties Of the Phase Measurements Of Ground Targetsmentioning

confidence: 99%

Quantifying the Error of Radar-Estimated Refractivity by Multiple Elevation and Dual-Polarimetric Data

Feng

Fabry

2018

Journal of Atmospheric and Oceanic Technology

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To properly use radar refractivity data quantitatively, good knowledge of its errors is required. The data quality of refractivity critically depends on the phase measurements of ground targets that are used for the refractivity estimation. In this study, the observational error structure of refractivity is first estimated based on quantifying the uncertainties of phase measurements, data processing, and the refractivity estimation method. New correlations between the time series of phase measurements at different elevation angles and between polarizations are developed to assess the bulk phase variability of individual targets. Then, the observational error of refractivity is obtained by simulating the uncertainties of phase measurements through the original refractivity estimation method. Resulting errors in refractivity are found to be smaller than 1 N-unit in areas densely populated with reliable point-like stationary ground targets but grow as the target density becomes sparse.

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Improving Radar Refractivity Retrieval by Considering the Change in the Refractivity Profile and the Varying Altitudes of Ground Targets

Cited by 10 publications

References 43 publications

Estimation of Surface Duct Using Ground-Based GPS Phase Delay and Propagation Loss

Estimation of Surface Duct Using Ground-Based GPS Phase Delay and Propagation Loss

High Temporal Resolution Refractivity Retrieval from Radar Phase Measurements

Quantifying the Error of Radar-Estimated Refractivity by Multiple Elevation and Dual-Polarimetric Data

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