High Temporal Resolution Refractivity Retrieval from Radar Phase Measurements

Abstract

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.

Prediction of Target Detection Probability Based on Air-to-Air Long-Range Scenarios in Anomalous Atmospheric Environments

“…L g = γ g R t (10) where γ g is the specific gas attenuation in dB/km, and f is the frequency in GHz. N Ox and N Wat are the imaginary parts of complex refractivities in terms of oxygen and water vapor.…”

“…Therefore, it is important to model the detailed atmospheric refractive index in order for the precise predictions of the propagation path loss and propagation factor. Many studies have been conducted to model the refractive index under anomalous atmospheric conditions through the radar signal measurement [10][11][12], global positioning system tropospheric delay observation [13], and statistical analysis of the stored meteorological observatory data [14,15]. In addition, various studies have been conducted to analyze the wave propagation characteristics in consideration of low-altitude actual atmospheric data in ground-to-ground and ground-to-air scenarios.…”

Refractivity Observations from Radar Phase Measurements: The 22 May 2002 Dryline Case during IHOP Project

“…Though in the flat area where the IHOP_2002 project took place the bias observed was small; the need to estimate the vertical gradient of the refractivity in order to expand the applicability of radar refractivity estimation to hilly areas where the bias caused by the height difference between the radar and the stationary ground targets could be unacceptably high. Different approaches based on power measurements [33,34] and phase measurements [35,36] were proposed. Using the data collected during the IHOP_2002 project the method proposed in [33] to estimate the vertical gradient of the refractivity was tested.…”

“…For this case, results also showed a moderate performance of the refractivity vertical gradient estimates since significant biases were observed for very small errors of the antenna elevation pointing angle. Later, joint estimation of the refractivity and the refractivity vertical gradient from phase measurements was proposed [35,36]. Considering the model for the backscattered phase from a stationary target discussed in [33,35], it is found that the difference between the phases backscattered from two stationary targets is a linear function of the refractivity and the refractivity vertical gradient.…”

Using Improved XGBoost Algorithm to Obtain Modified Atmospheric Refractive Index

“…e traditional way to obtain the refractive index of the atmosphere is to measure profiles of temperature and humidity by radiosonde and then estimate the atmospheric refractive index [14,15]; later, Mathai and Harrison [16] used the measured volume scattering coefficient and particle size distribution to estimate the refractive index of atmospheric aerosol. Besides, radar phase information can also be used to retrieve atmospheric refractive index [17,18], and some estimation methods of the atmospheric structure constant also provide reference for obtaining atmospheric refractive index [19][20][21]. In recent years, some scholars use new methods to measure the refractive index of the atmosphere.…”