Evaluating Land Surface Models in WRF Simulations over DMIC Region

Jain, Sarika; Panda, Jagabandhu; Rath, Sudhansu S.; Devara, P. C. S.

doi:10.17485/ijst/2017/v10i18/103522

Cited by 5 publications

(6 citation statements)

References 42 publications

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“…In all the WRF experiments, the wet season RMSE values were considerably larger than the respective dry season values, which caused by the higher rainfall magnitude in the wet season. This result agreed with Jain et al. (2017) study in the Delhi-Mumbai Industrial Corridor.…”

Section: Resultssupporting

confidence: 92%

“…Although WRF is a widely used RCM, the choice of parameterization schemes is site-specific (Mooney et al., 2016; Jain et al., 2017; Mugume et al., 2017). The LSMs and land use data have been a substantial influence on local climate simulations, especially in areas where land surface characteristics dynamically changed (Deng et al., 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Recently, Weather Research and Forecasting (WRF) model has been applied as an RCM for research and operational purposes in many parts of the world, for example in Africa (Diaz et al., 2015), Europe (Banks and Baldasano, 2016), North America (Burakowski et al., 2016), and Asia (Cannon et al., 2017). Previous studies showed that the performance of WRF model is influenced by the selection of physical parameter schemes including, microphysics (Gao et al., 2017), radiation (Mooney et al., 2016), planetary boundary layer (Kim et al., 2015), cumulus (Mugume et al., 2017), and land surface model (Jain et al., 2017). Other model input such as initial boundary condition (Yang and Duan, 2016), land use data (Cheng et al., 2013), and domain size and resolution (Zeyaeyan et al., 2017) also affect the performance of WRF model.…”

Section: Introductionmentioning

confidence: 99%

“…(2016) reported that Noah LSM resulted in better simulations of observed climate variables compared to Thermal Diffusion (TD), Rapid Update Cycle (RUC) and Pleim-Xiu LSMs in a case study in South Korea. On the other hand, the Pleim-Xiu LSM simulated better temperature and wind speed over Delhi-Mumbai Industrial Corridor region in India (Jain et al., 2017), while RUC LSM was better for rainfall simulation in the Western Disturbances of India (Thomas et al., 2014). This discrepancy of LSM recommendation in the above studies indicates that the performance of LSM is highly dependent on the simulation region, studied climate variable, seasonality and considerations of other physical parameters.…”

Section: Introductionmentioning

confidence: 99%

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Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

Teklay

Dile

Asfaw

et al. 2019

Heliyon

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The Weather Research and Forecasting (WRF) model is one of the regional climate models for dynamically downscaling climate variables at finer spatial and temporal scales. The objective of this study was to evaluate the performance of WRF model for simulating temperature and rainfall over Lake Tana basin in Ethiopia. The WRF model was configured for six experimental setups using three land surface models (LSMs): Noah, RUC and TD; and two land use datasets: USGS and updated New Land Use (NLU). The performances of WRF configurations were assessed by comparing simulated and observed data from March to August 2015. The result showed that temperature and rainfall simulations were sensitive to LSM and land use data choice. The combination of NLU with RUC and TD produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for 2m maximum temperature (Tmax) and 2m minimum temperature (Tmin), respectively. WRF model with RUC and NLU captured well the observed spatial and temporal variability of Tmax, while TD and NLU for Tmin. Moreover, rainfall simulation was better with NLU; especially NLU and Noah configuration produced the smallest mean bias (2.39 mm/day) and root mean square error (6.6 mm/day). All the WRF experiments overestimated light and heavy rainfall events. Overall, findings showed that the application of updated land use data substantially improved the WRF model performance in simulating temperature and rainfall. The study would provide valuable support for identifying suitable LSM and land use data that can accurately predict the climate variables in the Blue Nile basin.

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Section: Resultssupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

Teklay

Dile

Asfaw

et al. 2019

Heliyon

View full text Add to dashboard Cite

show abstract

“…Multiple important processes of the earth's surface are addressed by this parameterization, such as evapotranspiration from canopy water, evapotranspiration from snow, runoffs and melting of snow, depending on the complexity of the scheme used. Several comparative studies have demonstrated that meteorological models are sensitive to the choice of LSM (Pei et al, 2014;Wharton et al, 2015;Lee et al, 2016;Jain et al, 2017;Salamanca et al, 2018;Liu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of the WRF model in a tropical region: wind speed analysis at different sites

Souza

Nascimento²,

Moreira³

2021

ATM

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In this study, the performance of the mesoscale Weather Research and Forecasting (WRF) model is evaluated using combinations of three Planetary Boundary Layer (PBL) and three Land Surface Model (LSM) schemes, in order to identify the optimal parameters for the determination of wind speed in a tropical region. The state of Bahia in Brazil is selected as the location for the case study and simulations are performed over a period of eight months between 2015 and 2016. This is done to ensure that the dry and rainy seasons at the three different experimental sites—Esplanada, Mucuri, and Mucugê—are well separated from each other. The results of the simulations are compared with the observational data obtained from three towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically placed at each site. Overestimation of wind speed is observed in the simulations, despite similarities between the simulated and observed wind directions. In addition, the accuracies of simulations corresponding to sites that are closer to the ocean are observed to be lower—the most accurate wind speed estimates are obtained corresponding to Mucugê, which is located farthest from the ocean. Finally, analysis of the results obtained from each tower accounting for periods with higher and lower precipitation reveals that the combination of the PBL-YSU scheme with the LSM-RUC scheme yields the best results.

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An assessment of WRF-urban schemes in simulating local meteorology for heat stress analysis in a tropical sub-Saharan African city, Lagos, Nigeria

Obe,

Morakinyo,

Mills

2024

Int J Biometeorol

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Megacities, such as Lagos, Nigeria, face significant challenges due to rapid urbanization and climate change, resulting in a higher intensity of the urban heat island effect, coupled with high population density, making the city fall under the category of moderate to high heat stress/risk. Despite this, very few studies have analyzed the urban impact on heat stress over the coastal city, albeit with poor resolution data. In this study, we assessed the performance of an integrated high-resolution WRF-urban scheme driven by the readily available urban canopy information of the local climate zone (LCZ) to simulate local meteorological data for analyzing the spatiotemporal pattern of heat stress over the megacity. Our results show that the WRF-BEP scheme outperformed the other evaluated urban schemes, reducing the normalized root mean squared error by 25%. Furthermore, using humidex, we found a generally high incidence of intense discomfort in highly urbanized areas and noted the significant influence of urban morphology on the pattern of heat stress, particularly at night due to the combined effect of urban warming and higher relative humidity. The most socioeconomically disadvantaged urban areas, LCZ7, were most affected, with “hot” heat stress conditions observed over 90% of the time. However, during the afternoon, we found reduced heat stress in the core urban areas which might be due to the shading effect and/or cold air advection. Our findings would be relevant in the development of the urgently needed climate/heat adaptation plans for the city and other sub-Saharan African cities.

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Evaluating Land Surface Models in WRF Simulations over DMIC Region

Cited by 5 publications

References 42 publications

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

Performance evaluation of the WRF model in a tropical region: wind speed analysis at different sites

An assessment of WRF-urban schemes in simulating local meteorology for heat stress analysis in a tropical sub-Saharan African city, Lagos, Nigeria

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