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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Abstract. The rainfall outputs from the latest convection-scaleWeather Research and Forecasting (WRF) model are shown to provide aneffective means of extending prediction lead times in flood forecasting. Inthis study, the performance of the WRF model in simulating a regionalsub-daily extreme rainfall event centred over Beijing, China is evaluated athigh temporal (sub-daily) and spatial (convective-resolving) scales usingdifferent domain configurations and spin-up times. Seven objectiveverification metrics that are calculated against the gridded groundobservations and the ERA-Interim reanalysis are analysed jointly usingsubjective verification methods to identify the likely best WRFconfigurations. The rainfall simulations are found to be highly sensitive tothe choice of domain size and spin-up time at the convective scale. A modelrun covering northern China with a 1 : 5 : 5 horizontal downscaling ratio(1.62 km), 57 vertical layers (less than 0.5 km), and a 60 h spin-up timeexhibits the best performance in terms of the accuracy of rainfall intensityand the spatial correlation coefficient ( R′ ). A comparison of the optimal runand the initial run performed using the most common settings reveals clearimprovements in the verification metrics. Specifically, R′  increasesfrom 0.226 to 0.67, the relative error of the maximum precipitation at a pointrises from − 56 to − 11.7 %, and the root mean squared error decreasesby 33.65 %. In summary, re-evaluation of the domain configuration optionsand spin-up times used in WRF is crucial for improving the accuracy andreliability of rainfall outputs used in applications related to regional sub-daily heavy rainfall (SDHR).

hydrology and earth system sciences

Evaluation of the ability of the Weather Research and Forecasting model to reproduce a sub-daily extreme rainfall event in Beijing, China using different domain configurations and spin-up times