Observing Systems Simulation Experiments of Hypothetical Hourly Global Coverage of Microwave Satellite Radiances: Imbalance and Adaptive Observation Error Inflation

Abstract This study investigates the potential impacts of frequent global coverage of satellite microwave radiances using a global atmospheric data assimilation (DA) system. Observing Systems Simulation Experiments (OSSEs) were performed using the Local Ensemble Transform Kalman Filter with the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). Three different observation time intervals are examined: hourly (1H), bi‐hourly (2H), and six‐hourly (6H). 6H mimics the current coverage of Advanced Microwave Sounding Unit‐A in orbits. 1 and 2H show higher Root Mean Square Errors (RMSEs) for temperature compared to 6H due to dynamical imbalances indicated by the second time derivatives of sea level pressure. To mitigate the imbalances in 1H, we first inflate the observation error standard deviation in DA by 60% (1H‐Rinfl) and successfully reduce imbalances by 5%–10% with the temperature RMSE decreased by 10%–15%. Next, we apply the Adaptive Observation Error Inflation (AOEI) method, which adjusts the observation error standard deviations online based on the innovation statistics. 1H with AOEI (1H‐AOEI) reduces the dynamical imbalance and shows lower RMSE than that of 6H. 1H‐AOEI also shows more skill in forecasting precipitation events with intensity >2 mm/hr on small scales than 6H.