[1] Keynote 1

[1-1] February 27, 10:00-10:45


Results of New Applications of Data Assimilation

E Kalnay (UMD), T Miyoshi (RIKEN), G-Y Lien (RIKEN), S Kotsuki (RIKEN), D Hotta (JMA), T-C Chen (UMD), K Bhargava (UMD), J Carton (UMD), J-S Kang (KIST), N Zeng (UMD), Y Liu (UMD), G Asrar (PNNL), S Motesharrei (UMD).


Data assimilation has been traditionally used to obtain accurate initial conditions for forecasting by combining observations with short-range forecasts. We will show that it can also be used to improve the models and the observations. Examples and new results of such applications of advanced data assimilation are: 1) Use of Ensemble Forecast Sensitivity to Observations (EFSO) to detect flawed observations that make the 6hr forecast worse (Proactive QC), its application to estimate the observations error covariance R, and efficient operational implementation of new observing systems; 2) Estimation and correction of model bias through the use of analysis increments; 3) Estimation of surface fluxes of carbon, momentum, heat, and moisture; 4) Modeling Sustainability

  Presentation file: 01_1_E.Kalnay.pdf