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... study was carried over Tanzania with Dar es Salaam as the case study ( Figure 1). Dar es Salaam is located in the Eastern part of Tanzania mainland between latitude 6.36ånd 7˚South7˚South and longitudes 36˚to36˚to 39˚East39˚East and to her East is the Indian Ocean. ...
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... 21st December 2011 extreme rainfall event occurred in Dar es Salaam ( Figure 2), Tanzania and caused flooding of coastal areas. The flooding event caused December 2011 was 156:4 mm which was well above 117:8 mm December monthly mean (TMA, 2011) as shown in Figure 1. According to the Tanzania Meteorolog- ical Agency (TMA) this amount of rainfall was record breaking in the 58 years since the establishment of the station in 1953. ...
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... daily observed rainfall data for the period 14 -28th December 2011 for Dar es Salaam was obtained from Tanzania Meteorological Agency (TMA) along with rainfall data for other 14 stations ( Figure 1) for spatial analysis. The initial and lateral boundary conditions to run the model were obtained from the Na- tional Centers for Environmental Prediction at a horizontal resolution of 1˚×1˚× 1˚ degree [22] and it is updated every six hours. ...
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... performance of the selected parameterization schemes is presented using Figure 7 and Figure 8 and additional analysis illustrated using Figure 10. In Figure 7, results for KLA experiment show that by 0000UTC, the precipitation tendency of more than 50 mm covered the coast including Dar es Salaam which spread off coast to Indian Ocean by 0600UTC. ...
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... also contributes to avoiding artificial dynamical feedbacks between grids that can cause instability in the model simu- lations [21]. The analysis of synoptic conditions for surface temperature, sea lev- el pressure and wind field is presented using Figure 10. heavy rainfall that led to flooding. ...
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... The negative effects of increasing temperature have further reduced investment, depressed labor productivity, causing poorer human health [7,8], and lowering agricultural and industrial output among others [9]. These extreme weather events further negatively affect livelihoods, contributing to forced migration from landslide-and flood-prone areas in a bid to limit the impacts of these events [10][11][12]. ...
The changing environment, climate, and the increasing manifestation of disasters, has generated an increased demand for accurate and timely weather information. This information is provided by the National meteorological authorities (NMAs) through different dissemination channels e.g., using radios, Televisions, emails among others. The use of ICTs to provide weather information is recently gaining popularity. A study was conducted in three countries, namely Nigeria, Uganda, and South Sudan to assess the efficiency of an ICT tool, known as “Weather Information Dissemination System”. The study involved 254 participants (Uganda: 71; South Sudan: 133; and Nigeria: 50). The collected primary data were first quality controlled and organized thematically for detailed analysis. Descriptive statistics was used to provide quantitative analysis as well as content scrutinized for qualitative analysis. The results showed that there is a need for timely weather information to plan farming activities such as planting and application of fertilizers and pesticides as well as to manage flood and drought by the water sector and disaster management. Results further showed that the majority of the respondents have access to the technology needed to access weather and climate information. The respondents who received weather information from NMAs noted that the forecast was good. However, they further noted that there is more room for improvement especially with making the forecasts location-specific, ensuring mobile access is adequate in all regions, provision of weather information by SMS (in countries where this service is currently unavailable) and improved timing of the weather information. Finally, uncertainty about the accuracy of weather information and the weather information not meeting specific needs are key barriers to people’s willingness to pay for it (Uganda: 33.3%; South Sudan: 46.1%; and Nigeria: 33.3%). Improved collaborations between the NMAs, ICT service providers, policymakers and farmers will facilitate an effective approach to weather information access and dissemination. Innovative sensitization approaches through the media houses will enable better understanding of weather products and utilization, and access to enabling ICTs would increase access to weather forecasts
... The negative effects of increasing temperature have further reduced investment, depressed labor productivity, causing poorer human health [7,8], and lowering agricultural and industrial output among others [9]. These extreme weather events further negatively affect livelihoods, contributing to forced migration from landslide-and flood-prone areas in a bid to limit the impacts of these events [10][11][12]. ...
... WRF is a non-hydrostatic, next-generation mesoscale NWP model that can simulate the complete set of atmospheric processes with optional adjustments to physics schemes, initialized boundary conditions and data assimilation [44]. This study adopted a similar WRF domain as used in the previous studies [39,[44][45][46][47]. ...
... WRF is a non-hydrostatic, next-generation mesoscale NWP model that can simulate the complete set of atmospheric processes with optional adjustments to physics schemes, initialized boundary conditions and data assimilation [44]. This study adopted a similar WRF domain as used in the previous studies [39,[44][45][46][47]. The physical options used in this study were the same as those used by Tanzania Meteorological Authority (TMA) for operation and research purposes ( Table 1). ...
Future changes of land use and land cover (LULC) due to urbanization can cause variations in the frequency and severity of extreme weather events, affecting local climate and potentially worsening impact of such events. This work examines the local climatic impacts associated with projected urban expansion through simulations of rainfall and temperature over the rapidly growing city of the middle-eastern region in Tanzania. Simulations were conducted using a mesoscale Weather Research and Forecasting (WRF) model for a period of 10 days during the rainfall season in April 2018. The Global Forecasting System data of 0.25° resolution was used to simulate the WRF model in two-way nested domains at resolutions of 12 km and 4 km correspondingly. Urban and built-up areas under the current state, low urbanization (30%), and high urbanization (99%) scenarios were taken into account as LULC categories. As the urbanized area increased, daily mean, maximum and minimum air temperatures, as well as precipitation increased. Local circulation affected the spatial irregularities of air temperature and precipitation. Results imply that urbanization can amplify the impacts of future climate changes dramatically. These results can be applicable to the city planning to minimize the adverse effect of urbanization on temperature and precipitation.
... 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). ...
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 collected and analyzed during the rainy and dry seasons in April and July 2019, respectively, to capture seasonal variability. FS from pit latrines (PT) took longer to dewater followed by mixer containments, while soak-away sludge (SO) took a relatively short time to dewater. Also, FS from PT was found to have a 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. HIGHLIGHTS
Variability of FS characteristics from different containments.;
Seasonal variability of FS within the containment.;
Dewaterability potential of FS.;
Variation of dewaterability potential of FS among and within containments.;
The containment type and seasonal variation influenced the treatment of FS.;
... 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. ...
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-hour 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.
... Not every parameterization scheme will work well under all circumstances and for all regions, and for this reason it is important for sensitivity experiments to be conducted in order for preferred schemes to be identified. Internationally, a vast amount of research has gone into sensitivity testing of different WRF-ARW model options (such as Planetary Boundary Layer (PBL), radiation, convection, and microphysics schemes, and land-surface models) and their influence on the prediction of meteorological variables Borge et al., 2008;Giannaros et al., 2019;Hu et al., 2010;Jin et al., 2010;López-Bravo et al., 2018;Ngailo et al., 2018;Politi et al., 2018;Ratna et al., 2014;Zeyaeyan et al., 2017). In South Africa (SA), the simulation of rainfall using the WRF-ARW model with different parameterizations for atmospheric convection has been studied Pohl et al., 2014;Ratna et al., 2014). ...
The accuracy of meteorological fields produced by Numerical Weather Prediction (NWP) models are highly dependent on the physical parameterization schemes used. Any errors in simulations of meteorological fields will be passed on to subsequent processes (i.e. air quality models), and will have an effect on their outputs. Therefore, the realistic simulation of meteorological parameters is of utmost importance. The aim of the present research is to evaluate the performance of Planetary Boundary Layer (PBL) schemes contained in the non-hydrostatic Advanced Research Weather Research and Forecasting (WRF-ARW) model when simulating meteorological variables. Four frequently used PBL schemes were investigated by conducting sensitivity experiments during a month in spring and winter in the South African Highveld region for 2016. The simulations resulting from the different schemes were compared against one another, and statistically evaluated by making use of observational meteorological data at five sites. From these results, it is recommended that a local scheme be used for the Highveld region during winter. During spring, the clearly preferred scheme for the Highveld is Mellor–Yamada– Janjić (MYJ) scheme. Results from this study contributes to the establishment of a preferred PBL scheme in the WRF-ARW model, for use in South African Highveld region. Future planned research will considered the effect of the above-mentioned PBL schemes in the simulation of air quality over the same region.
... It has annual minimum, maximum and average temperatures of 16 o C, 33 o C and 26 o C respectively. The average annual rainfall within the region is 1050 mm experienced in two rainy seasons; a short rainy season occurs from October to December at a monthly average of 75 -100 mm and the more extended season is experienced from March to May, at a monthly average of 150-300 mm (Ndetto and Matzarakis, 2013;Ngailo et al., 2018). The annual total and maximum rainfall characteristic from 1985 to 2015 is indicated in Fig. 2. The watershed is within sedimentary bedrock with coarse-grained sandy soil spreading on a broader area (Mtoni et al., 2012). ...
The lack of hydrological data for urbanizing watersheds in developing countries is one of the challenges facing decision making. Msimbazi River is located in the city center of Dar es Salaam and is highly influenced by human activities; this includes dense populations that are characterized by informal settlements. The catchment is currently undergoing flooding, which triggers a dilemma in its surface runoff trending. This study aimed to simulate rainfall-runoff of an urbanizing Msimbazi watershed that will provide an understanding of hydrological data including peak flows and discharge volumes of Msimbazi River. The data used in the study include soil, rainfall, DEM and land use. HEC-GeoHMS and ArchHydro tools in ArcGIS were used to generate hydrological inputs to be used in the HEC-HMS interface. The resulted sub-watersheds have high CN values ranging from 70 to 90 implying the possibility of high runoff potential. Sub-watershed W620 indicates the highest runoff, among others with the highest runoff of 290mm for the year 2015. The peak flow on the river indicates the value ranging from 7.2 m 3 /s to 30m 3 /s with the highest values being on the downstream. The overall trend indicates an increasing surface runoff and peak flow in sub-watersheds from 1985 to 2015. Simulated results in this study were validated with the observational data of the catchment recorded in 2017. Given that most of the rivers in Tanzania are ungauged, the approach applied in this study can be used to enhance decision making on settlement planning, water resource, and disaster management in the currently observed urbanizing areas.
... Many of the previous studies e.g. Bouagila and Sushama [27] focused on the inter-annual rainfall variability at monthly, seasonal and annual timescales; Ngailo et al. [29] modeled extreme rainfall over Dar es Salaam. With the demand for improved quantitative rainfall prediction [3], it is crucial that numerical experiments are designed that target intra-seasonal rainfall characteristics. ...
Rainfall is a major climate parameter whose variation in space and time influences activities in different weather sensitive sectors such as agriculture, transport, and energy among others. Therefore, accurately forecasting rainfall is of paramount importance to the development of these sectors. In this regard, this study sought to contribute to quantitative forecasting of rainfall over Eastern Uganda through assessing the Weather Research and Forecasting model’s ability to simulate the intra–seasonal characteristics of the September to December rain season. These were: onset and cessation dates; wet days and lengths of the wet spells. The data used in the study included daily ground rainfall observations and lateral and boundary conditions data from the National Centers for Environmental Prediction (NCEP) final analysis at 1 0 horizontal resolution and at a temporal resolution of 6 hours for the entire study period were used to initialize the Weather Research and Forecasting (WRF) model. The study considered four weather synoptic weather stations namely; Jinja, Serere, Soroti and Tororo. The results show that the WRF model generally simulated fewer wet days at each station except for Tororo. Also, the WRF model simulated earlier onset and cessation dates of the rainfall season and overestimated the length of the wet spells.
... 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. ...
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.
... Atmospheric Research 218 (2019) 195-206 better simulations of the high precipitation rates. Ngailo et al. (2018) reported that the combination of KF cumulus scheme, Lin microphysics scheme and Asymmetric Convection Model 2 (ACM2) planetary boundary layer scheme shows encouraging and better results statistically for the simulation of extreme rainfall event reported over Dar es Salaam, Tanzania using WRF model. Minamiguchi et al. (2018) conducted a series of experiments to investigate the impact of uncertainity of sea surface temperature over the simulated rainfall during high precipitation period over Japan in the month of August 2014 using WRF model. ...
In this study, an attempt has been made to investigate one of the recently occurred extreme rainfall events (EREs) viz.; cloudburst over Pithoragarh district (July 1, 2016) of Uttrakhand in the North-West Himalayan (NWH) region using Weather Research and Forecast model (WRF 3.8.1) based on optimal ensemble approach. Four ensemble members, initialized with perturbed initial conditions corresponding to various cumulus parameterization (CP) schemes, have been generated. Accumulated rainfall for 24 h based on 4 ensemble members have been validated against the remotely sensed HE-rain derived from INSAT-3D measurements. For the simulation purpose, WRF model is tuned with variations in various scale not-aware and scale aware CP schemes viz.; Kain-Fritsch (KF), Bettes’ Miller Janjic (BMJ), Arakawa Schubert (AS), Tiedtke, Grell-Freitas (GF), Multi-Scale Kain-Fritsch (MSKF) and new Tiedtke. It is noted from the present analysis that two out of four ensemble members corresponding to KF scheme simulate rainfall close to the observation. In addition, it is also noted that the spread amongst the ensemble members is very large in case of BMJ, AS, MSKF, Tiedtke, GF and new Tiedtke schemes. Considering large bias amongst various ensemble members for each of the CP schemes, it is suggested that the results based on one ensemble member may be regarded spurious. Further, based on the closest match of ensemble mean with the observation and comparison amongst the simulated grid scale and sub grid scale rainfall corresponding to various CP schemes, it is suggested that scale aware MSKF scheme may be utilized for the simulations of EREs over the NWH region.
