Assessing Weather Research and Forecasting (WRF) Model Parameterization Schemes Skill to Simulate Extreme Rainfall Events over Dar es Salaam on 21 December 2011

Ngailo, Triphonia Jacob; Shaban, Nyimvua; Reuder, Joachim; Mesquita, Michel D. S.; Rutalebwa, Edwin; Mugume, Isaac; Sangalungembe, Chiku

doi:10.4236/gep.2018.61003

Cited by 11 publications

(9 citation statements)

References 26 publications

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“…When we consider the outperforming PBL, the scheme that was designed for unstable conditions in the PBL, such as ACM2, outperforms in this study. A similar study in the tropical region by [62] also indicated that the KF cumulus parametrization scheme and ACM2 PBL, in combination with Lin microphysics, perform better in simulating heavy rainfall events in Tanzania. In their study, however, the use of GF and ACM2 in combination with WSM6 shows poor results with high error scores.…”

Section: Discussionmentioning

confidence: 75%

Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Umer

Ettema

Jetten

et al. 2021

Water

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Simulating high-intensity rainfall events that trigger local floods using a Numerical Weather Prediction model is challenging as rain-bearing systems are highly complex and localized. In this study, we analyze the performance of the Weather Research and Forecasting (WRF) model’s capability in simulating a high-intensity rainfall event using a variety of parameterization combinations over the Kampala catchment, Uganda. The study uses the high-intensity rainfall event that caused the local flood hazard on 25 June 2012 as a case study. The model capability to simulate the high-intensity rainfall event is performed for 24 simulations with a different combination of eight microphysics (MP), four cumulus (CP), and three planetary boundary layer (PBL) schemes. The model results are evaluated in terms of the total 24-h rainfall amount and its temporal and spatial distributions over the Kampala catchment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. Rainfall observations from two gauging stations and the CHIRPS satellite product served as benchmark. Based on the TOPSIS analysis, we find that the most successful combination consists of complex microphysics such as the Morrison 2-moment scheme combined with Grell-Freitas (GF) and ACM2 PBL with a good TOPSIS score. However, the WRF performance to simulate a high-intensity rainfall event that has triggered the local flood in parts of the catchment seems weak (i.e., 0.5, where the ideal score is 1). Although there is high spatial variability of the event with the high-intensity rainfall event triggering the localized floods simulated only in a few pockets of the catchment, it is remarkable to see that WRF is capable of producing this kind of event in the neighborhood of Kampala. This study confirms that the capability of the WRF model in producing high-intensity tropical rain events depends on the proper choice of parametrization combinations.

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Section: Discussionmentioning

confidence: 75%

Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Umer

Ettema

Jetten

et al. 2021

Water

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“…Their study, however, investigates a range of grid lengths down to 12 km only. Ngailo et al (2018) also found Kain-Fritsch to be the best performing cumulus scheme for extreme precipitation in Tanzania, where Grell-Freitas produced very high MAEs. Encouraging results with Grell-Freitas were found by (Fowler et al 2016) on a variable-resolution mesh centered over South Africa.…”

Section: Discussionmentioning

confidence: 82%

Evaluation of Cumulus and Microphysics Parameterizations in WRF across the Convective Gray Zone

Jeworrek

West

Stull

2019

Weather and Forecasting

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This study evaluates the grid-length dependency of the Weather Research and Forecasting (WRF) Model precipitation performance for two cases in the Southern Great Plains of the United States. The aim is to investigate the ability of different cumulus and microphysics parameterization schemes to represent precipitation processes throughout the transition between parameterized and resolved convective scales (e.g., the gray zone). The cases include the following: 1) a mesoscale convective system causing intense local precipitation, and 2) a frontal passage with light but continuous rainfall. The choice of cumulus parameterization appears to be a crucial differentiator in convective development and resulting precipitation patterns in the WRF simulations. Different microphysics schemes produce very similar outcomes, yet some of the more sophisticated schemes have substantially longer run times. This suggests that this additional computational expense does not necessarily provide meaningful forecast improvements, and those looking to run such schemes should perform their own evaluation to determine if this expense is warranted for their application. The best performing cumulus scheme overall for the two cases studies here was the scale-aware Grell–Freitas cumulus scheme. It was able to reproduce a smooth transition from subgrid- (cumulus) to resolved-scale (microphysics) precipitation with increasing resolution. It also produced the smallest errors for the convective event, outperforming the other cumulus schemes in predicting the timing and intensity of the precipitation.

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“…The study area is characterized by having two main seasons. The dry season starts from June to August and the rainy season starts from March to May (Ngailo et al 2018). The city comprises an estimated population of 6.4 million with a growth rate of 5.29% (NBS 2017).…”

Section: Methodology Description Of Study Areamentioning

confidence: 99%

Variability of faecal sludge characteristics and its implication for dewaterability across different on-site sanitation containments in unplanned settlements in Dar es Salaam, Tanzania

Doglas

Kimwaga

Mayo

2021

Water Practice and Technology

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This article evaluates the physical-chemical parameters of Faecal Sludge (FS) as possible predictors of dewatering performances. Also, the variability of FS dewatering characteristics was assessed from different containments and in different seasons in relationship with dewatering performance. A total of 120 samples were analyzed were collected and analyzed during the rainy and dry seasons in April and July 2019, respectively to capture season variability. FS from pit latrine (PT) took longer to dewater followed mixer containments, while soak-away sludge (SO) took a relatively short time to dewater. Also, FS from PT was found to have high amount of settled solids hence high % of TS in dry cakes. Slow dewatering and turbid supernatant corresponded to high pH, Electrical conductivity and Total solids, but cake solids after dewatering were correlated with Total solids of FS. The FS dewaterability was higher for SO (DI = 0.9) and least for PT (DI = 0.3). Seasonal variability of FS dewaterability within the containments was higher for PT (DI = 0.74) and least for SO (DI = 0.5). Planning of FS treatment plants including sizing and design for effective dewatering performance, variation of physical-chemical dewatering predictors in sources and season could provide a relatively low-cost way to predict dewatering performance.

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Assessing Weather Research and Forecasting (WRF) Model Parameterization Schemes Skill to Simulate Extreme Rainfall Events over Dar es Salaam on 21 December 2011

Cited by 11 publications

References 26 publications

Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Evaluation of Cumulus and Microphysics Parameterizations in WRF across the Convective Gray Zone

Variability of faecal sludge characteristics and its implication for dewaterability across different on-site sanitation containments in unplanned settlements in Dar es Salaam, Tanzania

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