Improving heavy precipitation forecasts through phase‐aware nonlinear bias correction of all‐sky infrared radiances using cloud top temperature differences
Infrared (IR) radiances are highly sensitive to cloud top properties, making all‐sky data assimilation (DA) challenging due to scene‐dependent biases arising from uncertainties in cloud representation and radiative transfer modeling. This study introduces a phase‐aware nonlinear bias correction (BC) framework for all...