AMDAR and AMV data quality and their impacts on the weather analysis and forecasting over Eastern Mediterranean region

This research investigates data quality and impact of the non-conventional datasets including aircraft report (AMDAR) and satellite atmospheric moving vactors (AMV) using the NCAR WRF RTFDDA (Real-time four-dimensional data assimilation and forecasting) system over the data-sparse Eastern Mediterranean region. The datasets from radiosondes and NOAA/MADIS data stream are also used for comparisons. The RTFDDA system was run continuously for a 3 days period, with 4 data assimilation 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. The AMV data quality is investigated according to different satellite channels (e.g., water vapor channel, visible channel, and infrared channel) based on which the wind is derived. 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 quality control (QC) constraints are required in order to properly use the AMV dataset. Impacts of AMDAR and AMV data on analyses forecast are analyzed and will be presented at the meeting.