English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

An analysis to evaluate the impact of multiple radar reflectivity\uddata with a three-dimensional variational (3-D-Var) assimilation\udsystem on a heavy precipitation event is presented. The main goal is\udto build a regionally tuned numerical prediction model and\uda decision-support system for environmental civil protection\udservices and demonstrate it in the central Italian regions,\uddistinguishing which type of observations, conventional and not (or\uda combination of them), is more effective in improving the accuracy\udof the forecasted rainfall. In that respect, during the first\udspecial observation period (SOP1) of HyMeX (Hydrological cycle in\udthe Mediterranean Experiment) campaign several intensive observing\udperiods (IOPs) were launched and nine of which occurred in\udItaly. Among them, IOP4 is chosen for this study because of its low\udpredictability regarding the exact location and amount of\udprecipitation. This event hit central Italy on 14 September 2012\udproducing heavy precipitation and causing several cases of damage to\udbuildings, infrastructure, and roads. Reflectivity data taken from\udthree C-band Doppler radars running operationally during the event\udare assimilated using the 3-D-Var technique to improve high-resolution\udinitial conditions. In order to evaluate the impact of the\udassimilation procedure at different horizontal resolutions and to\udassess the impact of assimilating reflectivity data from multiple\udradars, several experiments using the Weather Research and Forecasting\ud(WRF) model are performed. Finally, traditional verification scores such\udas accuracy, equitable threat score, false alarm ratio, and frequency\udbias – interpreted by analysing their uncertainty through bootstrap\udconfidence intervals (CIs) – are used to objectively compare the\udexperiments, using rain gauge data as a benchmark

Impact of multiple radar reflectivity data assimilation on the numerical simulation of a flash flood event during the HyMeX campaign