scholarly journals Evaluation of the WRF model with different domain configurations and spin-up time in reproducing a sub-daily extreme rainfall event in Beijing, China

2017 ◽  
Author(s):  
Qi Chu ◽  
Zongxue Xu ◽  
Yiheng Chen ◽  
Dawei Han
Keyword(s):  
Wrf Model ◽  
Evaluation Process ◽  
Domain Size ◽  
Extreme Rainfall ◽  
Northern China ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Extreme Rainfall Event ◽  
Convective Scale ◽  
Beijing China

Abstract. The use of rainfall outputs from the latest convection-scale Weather Research and Forecasting (WRF) model is proven to be an effective way to extend the prediction lead time for flood forecasting. In this study, the effects of WRF domain configurations and spin-up time on rainfall simulations were evaluated at high temporal (sub-daily) and spatial (convective-permitting) scales for simulating a regional sub-daily extreme rainfall event occurred in Beijing, China. Seven objective verification metrics calculated against the ground precipitation observations and the ERA-Interim reanalysis, were analyzed jointly by the subjective verification to explore the likely best set of domain configurations and spin-up time. It was found that the rainfall simulations were quite sensitive to the change of the WRF domain size and spin-up time when evaluated at the convective scale. A model run with 1 : 5 : 5 horizontal downscaling ratio (1.6 km), 57 vertical layers (0.5 km), and 60-hour spin-up time covering Northern China exhibited the best skill in terms of the accuracy of rainfall intensity and the spatial correlation coefficient (R). Comparison made between the optimal run with the above set of the configurations and the initial run of the comparative test setup based on the most common settings revealed an evidential increase in each verification metric after the evaluation process, with R increased from 0.49 to 0.678, the relative error of point maximum precipitation rose from 0.41 to 0.881, and the spatial accumulated error fell by 43.22 %. In summary, the reevaluation of the domain configurations and spin-up time is of great importance and worthwhile in improving the accuracy and reliability of the rainfall simulations in the regional sub-daily heavy rainfall (SDHR) applications.

scholarly journals 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

2018 ◽  
Vol 22 (6) ◽  
pp. 3391-3407 ◽  
Author(s):  
Qi Chu ◽  
Zongxue Xu ◽  
Yiheng Chen ◽  
Dawei Han
Keyword(s):  
Mean Squared Error ◽  
Effective Means ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Extreme Rainfall Event ◽  
Verification Methods ◽  
Beijing China ◽  
Weather Research

Abstract. The rainfall outputs from the latest convection-scale Weather Research and Forecasting (WRF) model are shown to provide an effective means of extending prediction lead times in flood forecasting. In this study, the performance of the WRF model in simulating a regional sub-daily extreme rainfall event centred over Beijing, China is evaluated at high temporal (sub-daily) and spatial (convective-resolving) scales using different domain configurations and spin-up times. Seven objective verification metrics that are calculated against the gridded ground observations and the ERA-Interim reanalysis are analysed jointly using subjective verification methods to identify the likely best WRF configurations. The rainfall simulations are found to be highly sensitive to the choice of domain size and spin-up time at the convective scale. A model run 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 time exhibits the best performance in terms of the accuracy of rainfall intensity and the spatial correlation coefficient (R′). A comparison of the optimal run and the initial run performed using the most common settings reveals clear improvements in the verification metrics. Specifically, R′ increases from 0.226 to 0.67, the relative error of the maximum precipitation at a point rises from −56 to −11.7 %, and the root mean squared error decreases by 33.65 %. In summary, re-evaluation of the domain configuration options and spin-up times used in WRF is crucial for improving the accuracy and reliability of rainfall outputs used in applications related to regional sub-daily heavy rainfall (SDHR).

scholarly journals Evaluation of the WRF-ARW model during an extreme rainfall event: subtropical storm Guará

2021 ◽  
Author(s):  
Yasmin Kaore Lago Kitagawa ◽  
Erick Giovani Sperandio Nascimento ◽  
Noéle Bissoli Perini Souza ◽  
Pedro Junior Zucatelli ◽  
Prashant Kumar ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Temporal Evolution ◽  
Extreme Event ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Extreme Rainfall Event ◽  
Arw Model

This study simulates an unusual extreme rainfall event that occurred in Salvador City, Bahia, Brazil, on December 9, 2017, which was the subtropical storm Guará and had precipitation of approximately 24 mm within less than 1 h. Numerical simulations were conducted using the weather research and forecasting (WRF) model over three domains with horizontal resolutions of 9, 3, and 1 km. Different combinations of seven microphysics, three cumulus, and three planetary boundary layer schemes were evaluated based on their ability to simulate the hourly precipitation during this rainfall event. The results were compared with the data measured at the Brazilian National Institute of Meteorology (INMET) meteorological stations. The best configuration for the planetary boundary layer, cumulus, and microphysics schemes were Mellor-Yamada-Janjić, Grell-Devenyi, and Lin, respectively. The WRF model could depict the daily variations on the hourly parameters well, along with the spatial and temporal evolution of the extreme event.

scholarly journals Extreme rainfall impacts on soil CO2 efflux in an urban forest ecosystem in Beijing, China

2016 ◽  
Vol 96 (4) ◽  
pp. 504-514 ◽  
Author(s):  
Wenjing Chen ◽  
Xin Jia ◽  
Chunyi Li ◽  
Haiqun Yu ◽  
Jing Xie ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Forest Ecosystem ◽  
Urban Forest ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event ◽  
Co2 Efflux ◽  
Abrupt Decrease ◽  
Environmental Controls ◽  
Beijing China

Extreme rainfall events are infrequent disturbances that affect urban environments and soil respiration (Rs). Using data measured in an urban forest ecosystem in Beijing, China, we examined the link between gross primary production (GPP) and soil respiration on a diurnal scale during an extreme rainfall event (i.e., the “21 July 2012 event”), and we examined diel and seasonal environmental controls on Rs. Over the seasonal cycle, Rs increased exponentially with soil temperature (Ts). In addition, Rs was hyperbolically related to soil volumetric water content (VWC), increasing with VWC below a threshold of 0.17 m3 m−3, and then decreasing with further increases in VWC. Following the extreme rainfall event (177 mm), Rs showed an abrupt decrease and then maintained a low value of ∼0.3 μmol m−2 s−1 for about 8 h as soil VWC reached the field capacity (0.34 m3 m−3). Rs became decoupled from Ts and increased very slowly, while GPP showed a greater increase. A bivariate Q10-hyperbolical model, which incorporates both Ts and VWC effects, better fits Rs than the Q10 model in summer but not for whole year.

Observational analyses of topographic effects on convective systems in an extreme rainfall event in Northern China

2019 ◽  
Vol 229 ◽  
pp. 127-144 ◽  
Author(s):  
Yanzhen Kang ◽  
Xindong Peng ◽  
Shigong Wang ◽  
Yuling Hu ◽  
Kezheng Shang ◽  
...  
Keyword(s):  
Extreme Rainfall ◽  
Northern China ◽  
Rainfall Event ◽  
Topographic Effects ◽  
Extreme Rainfall Event ◽  
Convective Systems

scholarly journals Assessment of the Weather Research and Forecasting (WRF) Model for Extreme Rainfall Event Simulations in the Upper Ganga Basin

2017 ◽  
Author(s):  
Ila Chawla ◽  
Krishna K. Osuri ◽  
Pradeep P. Mujumdar ◽  
Dev Niyogi
Keyword(s):  
Land Surface ◽  
Heavy Rainfall ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Simulated Rainfall ◽  
Grid Spacing ◽  
Rainfall Events ◽  
Arw Model

Abstract. Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model, are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multiscale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF-ARW model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15–18 June 2013 over the Ganges basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layer (PBL), and two land surface physics options; and different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it is noted that the selection of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influence the magnitude of rainfall in the model simulations. Further, WRF run with Goddard MP, Mellor–Yamada–Janjic PBL and Betts–Miller–Janjic' CU scheme is found to perform best in simulating this heavy rain event. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme as compared to the simple Slab model. To analyze the effect of model grid spacing, two sets of downscaling ratios – (i) 1 : 3, Global to Regional (G2R) scale; and (ii) 1 : 9, Global to Convection-permitting scale (G2C) are employed. Results indicate that higher downscaling ratio (G2C) causes higher variability and consequently, large errors in the simulations. Therefore, G2R is opted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF simulated rainfall is found to exhibit least bias when compared with that of the Coordinated Regional Climate Downscaling Experiment (CORDEX) data and the NCEP FiNaL (FNL) reanalysis data.

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