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 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 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 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.

scholarly journals Estimating Daytime Planetary Boundary Layer Heights over a Valley from Rawinsonde Observations at a Nearby Airport: An Application to the Page Valley in Virginia, United States

2016 ◽  
Vol 55 (3) ◽  
pp. 791-809 ◽  
Author(s):  
Temple R. Lee ◽  
Stephan F. J. De Wekker
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Forecasting ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Dispersion Modeling ◽  
Blue Ridge Mountains ◽  
Terrain Following ◽  
Regional Reanalysis

AbstractThe planetary boundary layer (PBL) height is an essential parameter required for many applications, including weather forecasting and dispersion modeling for air quality. Estimates of PBL height are not easily available and often come from twice-daily rawinsonde observations at airports, typically at 0000 and 1200 UTC. Questions often arise regarding the applicability of PBL heights retrieved from these twice-daily observations to surrounding locations. Obtaining this information requires knowledge of the spatial variability of PBL heights. This knowledge is particularly limited in regions with mountainous terrain. The goal of this study is to develop a method for estimating daytime PBL heights in the Page Valley, located in the Blue Ridge Mountains of Virginia. The approach includes using 1) rawinsonde observations from the nearest sounding station [Dulles Airport (IAD)], which is located 90 km northeast of the Page Valley, 2) North American Regional Reanalysis (NARR) output, and 3) simulations with the Weather Research and Forecasting (WRF) Model. When selecting days on which PBL heights from NARR compare well to PBL heights determined from the IAD soundings, it is found that PBL heights are higher (on the order of 200–400 m) over the Page Valley than at IAD and that these differences are typically larger in summer than in winter. WRF simulations indicate that larger sensible heat fluxes and terrain-following characteristics of PBL height both contribute to PBL heights being higher over the Page Valley than at IAD.

scholarly journals Impacts of the Lowest Model Level Height on the Performance of Planetary Boundary Layer Parameterizations

2012 ◽  
Vol 140 (2) ◽  
pp. 664-682 ◽  
Author(s):  
Hyeyum Hailey Shin ◽  
Song-You Hong ◽  
Jimy Dudhia
Keyword(s):  
Boundary Layer ◽  
Surface Layer ◽  
Planetary Boundary Layer ◽  
Numerical Models ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Implicit Assumption ◽  
Convective Model ◽  
Local Scheme ◽  
Level Height

The lowest model level height z1 is important in atmospheric numerical models, since surface layer similarity is applied to the height in most of the models. This indicates an implicit assumption that z1 is within the surface layer. In this study, impacts of z1 on the performance of planetary boundary layer (PBL) parameterizations are investigated. Three conceptually different schemes in the Weather Research and Forecasting (WRF) model are tested for one complete diurnal cycle: the nonlocal, first-order Yonsei University (YSU) and Asymmetric Convective Model version 2 (ACM2) schemes and the local, 1.5-order Mellor–Yamada–Janjić (MYJ) scheme. Surface variables are sensitive to z1 in daytime when z1 is below 12 m, even though the height is within the surface layer. Meanwhile during nighttime, the variables are systematically altered as z1 becomes shallower from 40 m. PBL structures show the sensitivity in the similar manner, but weaker. The order of sensitivity among the three schemes is YSU, ACM2, and MYJ. The significant sensitivity of the YSU parameterization comes from the PBL height calculation. This is considerably alleviated by excluding the thermal excess term in determining the PBL height when z1 is within the surface layer. The factor that specifies the ratio of nonlocal transport to total mixing is critical to the sensitivity of the ACM2 scheme. The MYJ scheme has no systematic sensitivity, since it is a local scheme. It is also noted that a numerical instability appears accompanying the unrealistic PBL structures when the grid spacing in the surface layer suddenly jumps.

scholarly journals Planetary boundary layer height by means of lidar and numerical simulations over New Delhi, India

2019 ◽  
Vol 12 (5) ◽  
pp. 2595-2610 ◽  
Author(s):  
Konstantina Nakoudi ◽  
Elina Giannakaki ◽  
Aggeliki Dandou ◽  
Maria Tombrou ◽  
Mika Komppula
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
High Efficiency ◽  
Monsoon Season ◽  
Wrf Model ◽  
Satellite Observation ◽  
Weather Research And Forecasting ◽  
New Delhi ◽  
Boundary Layer Height ◽  
The Stability

Abstract. In this work, the height of the planetary boundary layer (PBLH) is investigated over Gwal Pahari (Gual Pahari), New Delhi, for almost a year. To this end, ground-based measurements from a multiwavelength Raman lidar were used. The modified wavelet covariance transform (WCT) method was utilized for PBLH retrievals. Results were compared to data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and the Weather Research and Forecasting (WRF) model. In order to examine the difficulties of PBLH detection from lidar, we analyzed three cases of PBLH diurnal evolution under different meteorological and aerosol load conditions. In the presence of multiple aerosol layers, the employed algorithm exhibited high efficiency (r=0.9) in the attribution of PBLH, whereas weak aerosol gradients induced high variability in the PBLH. A sensitivity analysis corroborated the stability of the utilized methodology. The comparison with CALIPSO observations yielded satisfying results (r=0.8), with CALIPSO slightly overestimating the PBLH. Due to the relatively warmer and drier winter and, correspondingly, colder and rainier pre-monsoon season, the seasonal PBLH cycle during the measurement period was slightly weaker than the cycle expected from long-term climate records.

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