Evaluation of IMERG V6 and V7 satellite precipitation and their application on lifetime prediction of wind turbine blades

Accurate precipitation estimation is crucial for various meteorological and climatological applications, including renewable energy generation. The NASA Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product provides precipitation data derived from microwave and infrared satellite sensors. In this study, we evaluate the performance of two successive versions, V6 and V7, of the IMERG Final Precipitation Satellite Product. 

The evaluation of IMERG V6 and V7 products involves comparing rainfall time series of 6 years (2015-2020) against rain gauge measurements from 28 weather stations in complex terrain in Navarra, Spain. We assess various statistical metrics such as correlation coefficient, bias, root mean square error, and probability of detection. 

We hypothesize that the V7 product displays improvements from the V6, particularly in terms of accuracy. The objective is to assess if the V7 product demonstrates enhanced performance in capturing precipitation events in a region with complex terrain, such as Navarra. We aim to provide evaluation results and valuable insights for users relying on IMERG precipitation data for hydrological, meteorological, and climate studies.  

We also investigate the utility of IMERG precipitation products in the context of wind energy applications. Precipitation, including rain and hail, can impact the structural integrity and performance of wind turbines over time. Surface erosion of wind turbine blades is caused by heavy precipitation and strong winds and represents a major challenge in the wind energy industry. Therefore, we focus on predicting the lifetime of wind turbine blades in the 28 stations by integrating IMERG precipitation in an erosion onset prediction model along with New European Wind Atlas (NEWA) wind speeds. Previous studies that have used IMERG V6 in a blade lifetime prediction model have shown that IMERG V6 is sufficient to predict erosion onset time in blades in selected European sites, but it requires further calibration and adjustments since it tends to overestimate orographic rainfall. We hereby explore any improvements in the prediction of erosion onset time by incorporating the newly published IMERG V7 product. Finally, we aim to highlight the usefulness of satellite data in monitoring leading-edge erosion in wind turbine blades.

The proposed approach holds promise for improving the reliability and efficiency of wind turbines. The knowledge of erosion onset time in blades can optimize maintenance schedules, reduce downtime, and enhance the overall operational performance of wind farms. Our findings may offer valuable implications for the renewable energy sector and precipitation monitoring.

This work is supported by the AIRE project, which has received funding from the European Union under the grant agreement 101083716.