This study will validate the S-band dual-polarization Doppler radar (S-Pol) radar refractivity retrieval using measurements from the International H2O Project conducted in the southern Great Plains in May–June 2002. The range of refractivity measurements during this project extended out to 40–60 km from the radar. Comparisons between the radar refractivity field and fixed and mobile mesonet refractivity values within the S-Pol refractivity domain show a strong correlation. Comparisons between the radar refractivity field and low-flying aircraft also show high correlations. Thus, the radar refractivity retrieval provides a good representation of low-level atmospheric refractivity. Numerous instruments that profile the temperature and moisture are also compared with the refractivity field. Radiosonde measurements, Atmospheric Emitted Radiance Interferometers, and a vertical-pointing Raman lidar show good agreement, especially at low levels. Under most daytime summertime conditions, radar refractivity measurements are representative of an ∼250-m-deep layer. Analyses are also performed on the utility of refractivity for short-term forecasting applications. It is found that the refractivity field may detect low-level boundaries prior to the more traditional radar reflectivity and Doppler velocity fields showing their existence. Data from two days on which convection initiated within S-Pol refractivity range suggest that the refractivity field may exhibit some potential utility in forecasting convection initiation. This study suggests that unprecedented advances in mapping near-surface water vapor and subsequent improvements in predicting convective storms could result from implementing the radar refractivity retrieval on the national network of operational radars.

No abstract

No abstract

Monitoring continental precipitation over Europe with high resolution (2 km, 15 minutes) has been possible since the operational production of the OPERA composites from the European weather radar networks. The OPERA data are the essential input to a hazard assessment tool for identifying localized rainfall-induced flash floods at European scale, and their quality determines the performance of the tool. This paper analyses the OPERA data quality during the warm seasons of 2015-2017 by comparing the estimated rainfall accumulations with the SYNOP rain gauge records over Europe. To compensate the OPERA underestimation, a simple spatiallyvariable bias adjustment method has been applied. The long-term comparison between the OPERA and gauge point daily rainfall accumulations at the gauge locations shows the benefit of the bias adjustment. Additionally, the daily monitoring shows gradual improvement of the OPERA data year by year. The impact of the quality of the OPERA data for effective flash flood identification is demonstrated for the case of the flash floods that occurred from

The radar refractivity retrieval algorithm applied to radar phase measurements from ground targets can provide high-resolution, near-surface moisture estimates in time and space. The reliability of the retrieval depends on the quality of the returned phase measurements, which are affected by factors such as 1) the vertical variation of the refractive index along the ray path and 2) the properties of illuminated ground targets (e.g., the height and shape of the targets intercepted by radar rays over complex terrain). These factors introduce ambiguities in the phase measurement that have not yet been considered in the refractivity algorithm and that hamper its performance.A phase measurement simulator was designed to better understand the effect of these factors. The results from the simulation were compared with observed phase measurements for selected atmospheric propagation conditions estimated from low-level radio sounding profiles. Changes in the vertical gradient of refractivity coupled with the varying heights of targets are shown to have some influence on the variability of phase fields. However, they do not fully explain the noisiness of the real phase observations because other factors that are not included in the simulation, such as moving ground targets, affect the noisiness of phase measurements.