Bias correction of monthly air temperature from the NASA POWER gridded meteorological dataset over Bangalore Urban, India: a comparative evaluation of statistical and machine-learning methods

Evaluation of the performance of the Weather Research and Forecasting model in simulating surface solar radiation over Penang Island, Malaysia, through comparing with reanalysis and in situ data

Bias correction of ERA5-Land air temperature in remote tropical regions using participatory monitoring data

Many remote tropical mountainous regions lack precise, spatially distributed air temperature data. This limits both scientific research and applied solutions in fields such as hydrology, meteorology, health and agriculture. As regular monitoring networks do not provide sufficient spatial coverage in these regions, al...

Evaluating Rainfall Forecast Skill in Numerical Weather Prediction Models and the Effects of Bias Correction on the PCJ (Piracicaba-Capivari-Jundiaí) River Basins in Brazil

Precipitation forecasts from numerical weather prediction systems can contain systematic errors in both occurrence and magnitude, limiting their usefulness for hydrological applications. This study evaluated two operational precipitation forecasting systems against two observational reference datasets across three basi...

Evaluation and bias correction of high-resolution satellite and reanalysis rainfall products across Egypt’s hydrological zones

Machine Learning-Based Reconstruction of Missing Meteorological Observations Using Reanalysis and Satellite Data in West Africa

A machine learning-based framework for reconstructing missing hourly observations from automatic weather stations by integrating in situ AWS measurements with ERA5-Land reanalysis fields and Global Precipitation Measurement (GPM) satellite-derived products is presented.

Assessment of bias correction techniques for satellite soil moisture data assimilation in the dry season of Southeastern South America

Estimation of surface soil moisture (SSM) is fundamental for hydrological monitoring and agricultural management, particularly in drought-prone regions such as central–northeastern Argentina. Data assimilation provides a robust approach for estimating SSM by integrating land surface models with remote sensing data. S...