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Hongyan Wang, Gaili Wang, and Liping Liu


The vertical refractivity gradient (VRG) is critical to weather radar beam propagation. The most common method of calculating beam paths uses the 4/3 Earth radius model, which corresponds to standard refraction conditions. In the present work, to better document propagation conditions for radar electromagnetic waves, which is essential for hydrology and numerical weather forecast models to more fully benefit from observations taken from the new-generation weather radar network in China, VRG spatial and temporal variations in the first kilometers above the surface are explored using 6-yr sounding observations. Under the effects of both regional climatic and topographic conditions, VRG values for most of the radars are generally smaller than those of the standard conditions for much of the year. There are similar or slightly larger values at only a few radar sites. Smaller VRG values are more frequent and widespread, especially during rainy seasons when weather radar observations are important. In such conditions, beam heights estimated using standard atmospheric refraction are overestimated relative to actual heights for most of the radars. Underestimates are much less common and of much shorter duration. However, height deviations are acceptable for being well within the uncertainty of radar echo height owing to the ~1° beamwidth. In coastal areas and the middle and lower reaches of the Yangtze River, radar observations should be applied with much more caution because of the greater risk of beam blockage and clutter contamination.

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Gaili Wang, Da-Lin Zhang, and Jisong Sun


A multiscale observational analysis of a nocturnal extreme rainfall event that occurred at Changtu in Northeast China on 14 July 2017 is performed using global analysis, automated surface observations, Doppler radar, rawinsonde, and disdrometer data. Results show that the large-scale environment was characterized by high convective available potential energy and precipitable water, moderate convective inhibition, and a southwesterly low-level jet (LLJ) capped by an inversion layer. The first and subsequent convective cells developed along a quasi-stationary surface convergence zone in a convection-void region of a previously dissipated meso-α-scale convective line. Continuous convective initiation through backbuilding at the western end and the subsequent merging of eastward-moving convective cells led to the formation of a near-zonally oriented meso-β-scale rainband, with reflectivity exceeding 45 dBZ (i.e., convective core intensity). This quasi-stationary rainband was maintained along the convergence zone by the LLJ of warm moist air, aided by local topographical lifting and convectively generated outflows. A maximum hourly rainfall amount of 96 mm occurred during 0200–0300 Beijing standard time as individual convective cores with a melting layer of >55 dBZ reflectivity moved across Changtu with little intermittency. The extreme-rain-producing stage was characterized with near-saturated vertical columns, and rapid number concentration increases of all raindrop sizes. It is concluded that the formation of the meso-β-scale rainband with continuous convective backbuilding, and the subsequent echo-training of convective cores with growing intensity and width as well as significant fallouts of frozen particles accounted for the generation of this extreme rainfall event. This extreme event was enhanced by local topography and the formation of a mesovortex of 20–30 km in diameter.

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Yu Zhang, Yang Hong, Xuguang Wang, Jonathan J. Gourley, Xianwu Xue, Manabendra Saharia, Guangheng Ni, Gaili Wang, Yong Huang, Sheng Chen, and Guoqiang Tang


Prediction, and thus preparedness, in advance of flood events is crucial for proactively reducing their impacts. In the summer of 2012, Beijing, China, experienced extreme rainfall and flooding that caused 79 fatalities and economic losses of $1.6 billion. Using rain gauge networks as a benchmark, this study investigated the detectability and predictability of the 2012 Beijing event via the Global Hydrological Prediction System (GHPS), forced by the NASA Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis at near–real time and by the deterministic and ensemble precipitation forecast products from the NOAA Global Forecast System (GFS) at several lead times. The results indicate that the disastrous flooding event was detectable by the satellite-based global precipitation observing system and predictable by the GHPS forced by the GFS 4 days in advance. However, the GFS demonstrated inconsistencies from run to run, limiting the confidence in predicting the extreme event. The GFS ensemble precipitation forecast products from NOAA for streamflow forecasts provided additional information useful for estimating the probability of the extreme event. Given the global availability of satellite-based precipitation in near–real time and GFS precipitation forecast products at varying lead times, this study demonstrates the opportunities and challenges that exist for an integrated application of GHPS. This system is particularly useful for the vast ungauged regions of the globe.

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