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.

Most actual polarimetric weather radars consider either alternate transmission of horizontal and vertical polarizations or simultaneous transmission of both polarizations. Simultaneous reception of vertical and horizontal components is always performed. The way these operating modes have to be modified, to cope with the loss of polarization purity and the increase of polarization channels coupling at some pointing directions when planar phased-array radars (PARs) are used, has already been discussed. Complete correction of these effects showed to be difficult, requiring precise control of the relative amplitudes and phases of the dipoles feeding signals on transmission in a pulse-to-pulse basis. If simultaneous transmission of vertical and horizontal polarizations is considered, complete correction has not been achieved. In this paper, the implementation of a third polarimetric measurement mode based on alternate transmission of three different polarizations with PARs is discussed. It is found that implementation of this method, which provides minimum-variance unbiased linear polarimetric covariance matrix estimates, with phased-array systems only requires simple adjustments at reception.

Tropospheric refractivity, which is closely related to temperature, pressure, and relative humidity, is a valuable parameter for weather forecasting and climate analysis. It has already been demonstrated that refractivity estimates can be derived using the phase measurements corresponding to radar signals backscattered from stationary targets over any terrain orography, with high temporal resolution. However, the random distribution of stationary targets affects the spatial resolution provided by the computed refractivity estimates. It is of interest to obtain reliable radar-based refractivity maps to assist final users with data interpretation and analysis, so the use of the a suitable geostatistical interpolation technique to obtain refractivity maps is studied in this paper. Refractivity estimates obtained from C-band radar data gathered during 2019 by the United Kingdom’s national weather service (Met Office) are used to evaluate the accuracy of the method by comparing the results to ground-based weather stations and the ECMWF’s ERA5 reanalysis dataset.

Tropospheric refractivity, related to temperature, pressure and humidity is an interesting parameter for weather analysis, prediction and study of climate trends. It has been shown to be useful for the detection and forecast of convective events. It has already been demonstrated that tropospheric refractivity can be estimated from radar phase measurements. In this paper a non-linear least squares based approach for the estimation of the tropospheric refractivity that simultaneously provides estimates of the refractivity vertical gradient is presented. A significant improvement of the presented technique is that it allows estimation of the refractivity over any terrain orography, flat or hilly. Furthermore, the method developed can be implemented on klystron as well as on magnetron based radars. Results for both radar types, at S- and C-band, located over flat and hilly terrain show the potential of the method.

The analysis and correction of the bias occurring in weather radar polarimetric measurements is a challenging problem. Polarization coupling due to the cross-polar radiation pattern of the radar's antenna is known to be responsible for errors in the estimation of the polarimetric covariance matrix, and consequently in the hydrometeor classification and quantification, either when using the ATSR or the SHV method. An alternative method for Doppler and polarimetric measurements based on transmitting three different polarizations (3-PolD) has been proven to provide accurate polarimetric covariance matrix estimates without making any hypothesis about the target polarimetric response or its Doppler spectrum. This method does not reduce the Doppler capabilities or the unambiguous range of the radar despite alternately transmitting 3-PolD. These characteristics have encouraged evaluating the polarimetric parameter biases due to cross-polar radiation when this method is used. Biases are calculated considering reflector antenna systems as well as phased-array antenna systems. The results show that this method may guarantee a tolerable bias level even with a poor co- to cross-polar antenna pattern ratio.

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International $H_{2}O$ Project ($IHOP\_2002$) is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations.