Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil
On 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extre...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/16/5/548 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849327531168104448 |
|---|---|
| author | Denis William Garcia Michelle Simões Reboita Vanessa Silveira Barreto Carvalho |
| author_facet | Denis William Garcia Michelle Simões Reboita Vanessa Silveira Barreto Carvalho |
| author_sort | Denis William Garcia |
| collection | DOAJ |
| description | On 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extreme event through a set of sensitivity numerical experiments. The control simulation followed the operational configuration used daily by the Center for Weather and Climate Forecasting Studies of Minas Gerais (CEPreMG). Additional experiments tested the use of different microphysics schemes (WSM3, WSM6, WDM6), initial and boundary conditions (GFS, GDAS, ERA5), and surface datasets (sea surface temperature and soil moisture from ERA5 and GDAS). The model’s performance was evaluated by comparing the simulated variables with those from various datasets. We primarily focused on the representation of the spatial precipitation pattern, statistical metrics (bias, Pearson correlation, and Kling–Gupta Efficiency), and atmospheric instability indices (CAPE, K, and TT). The results showed that none of the simulations accurately captured the amount and spatial distribution of precipitation over the region, likely due to the complex topography and convective nature of the studied event. However, the WSM3 microphysics scheme and the use of ERA5 SST data provided slightly better representation of instability indices, although these configurations still underperformed in simulating the rainfall intensity. All simulations overestimated the instability indices compared to ERA5, although ERA5 itself may underestimate the convective environments. Despite some performance limitations, the sensitivity experiments provided valuable insights into the model’s behavior under different configurations for southeastern Brazil—particularly in a convective environment within mountainous terrain. However, further evaluation across multiple events is recommended. |
| format | Article |
| id | doaj-art-30aee792d0a4413597e1f62fd3552d75 |
| institution | Kabale University |
| issn | 2073-4433 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-30aee792d0a4413597e1f62fd3552d752025-08-20T03:47:50ZengMDPI AGAtmosphere2073-44332025-05-0116554810.3390/atmos16050548Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast BrazilDenis William Garcia0Michelle Simões Reboita1Vanessa Silveira Barreto Carvalho2Instituto de Recursos Naturais, Universidade Federal de Itajubá, UNIFEI, Av. BPS, 1303, Itajubá 37500-903, MG, BrazilInstituto de Recursos Naturais, Universidade Federal de Itajubá, UNIFEI, Av. BPS, 1303, Itajubá 37500-903, MG, BrazilInstituto de Recursos Naturais, Universidade Federal de Itajubá, UNIFEI, Av. BPS, 1303, Itajubá 37500-903, MG, BrazilOn 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extreme event through a set of sensitivity numerical experiments. The control simulation followed the operational configuration used daily by the Center for Weather and Climate Forecasting Studies of Minas Gerais (CEPreMG). Additional experiments tested the use of different microphysics schemes (WSM3, WSM6, WDM6), initial and boundary conditions (GFS, GDAS, ERA5), and surface datasets (sea surface temperature and soil moisture from ERA5 and GDAS). The model’s performance was evaluated by comparing the simulated variables with those from various datasets. We primarily focused on the representation of the spatial precipitation pattern, statistical metrics (bias, Pearson correlation, and Kling–Gupta Efficiency), and atmospheric instability indices (CAPE, K, and TT). The results showed that none of the simulations accurately captured the amount and spatial distribution of precipitation over the region, likely due to the complex topography and convective nature of the studied event. However, the WSM3 microphysics scheme and the use of ERA5 SST data provided slightly better representation of instability indices, although these configurations still underperformed in simulating the rainfall intensity. All simulations overestimated the instability indices compared to ERA5, although ERA5 itself may underestimate the convective environments. Despite some performance limitations, the sensitivity experiments provided valuable insights into the model’s behavior under different configurations for southeastern Brazil—particularly in a convective environment within mountainous terrain. However, further evaluation across multiple events is recommended.https://www.mdpi.com/2073-4433/16/5/548extreme eventprecipitationsensitivity numerical experimentsWRFsoutheast Brazil |
| spellingShingle | Denis William Garcia Michelle Simões Reboita Vanessa Silveira Barreto Carvalho Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil Atmosphere extreme event precipitation sensitivity numerical experiments WRF southeast Brazil |
| title | Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil |
| title_full | Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil |
| title_fullStr | Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil |
| title_full_unstemmed | Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil |
| title_short | Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil |
| title_sort | sensitivity analysis and performance evaluation of the wrf model in forecasting an extreme rainfall event in itajuba southeast brazil |
| topic | extreme event precipitation sensitivity numerical experiments WRF southeast Brazil |
| url | https://www.mdpi.com/2073-4433/16/5/548 |
| work_keys_str_mv | AT deniswilliamgarcia sensitivityanalysisandperformanceevaluationofthewrfmodelinforecastinganextremerainfalleventinitajubasoutheastbrazil AT michellesimoesreboita sensitivityanalysisandperformanceevaluationofthewrfmodelinforecastinganextremerainfalleventinitajubasoutheastbrazil AT vanessasilveirabarretocarvalho sensitivityanalysisandperformanceevaluationofthewrfmodelinforecastinganextremerainfalleventinitajubasoutheastbrazil |