P11  Evaluation of AMDAR and AMV Data Quality and their Impact on RTFDDA Analysis and Forecasting Control at Eastern Mediterranean Region

Pan, Linlin, National Center for Atmospheric Research, Yubao Liu, Yonghui Wu, Dorita Rostkier-Edelstein, Israel Institute for Biological Research, Ness-Ziona, Israel, and Rong-Shyang Sheu, NCAR

This study focuses on data quality control (QC) and impact study of the non-conventional datasets from aircraft and Satellite with the NCAR (National Center for Atmospheric Research) WRF RTFDDA (Real-time four-dimensional data assimilation) system set up over the data-sparse Eastern Mediterranean region.

The data investigated in this research includes AMDAR and AMV datasets. The datasets from radiosondes and MADIS are also used for comparisons. The RTFDDA system was run continuously for a 3 days period, with 4 FDDA and forecast cycles a day, 13 h forecasts in each cycle. The AMDAR data reports pressure-altitudes instead of pressure. Correct conversion from the height to pressure is very important. It is demonstrated that improper conversion formula can increase the data error/bias. The AMV data quality is investigated as a whole as well as in term of different satellite channel channels (e.g., water vapor channel, visible channel, and infrared channel). The study shows that AMV data contain some lower quality data and contains many more outliers. The data from water vapor channel have the largest bias and root mean squared error (RMSE). More rigorous QC constraints are required in order to achieve positive impact using the AMV dataset.