15.1A An Assessment of the Installation and Performance of the eIAWS™ Aviation Weather Forecast System in East China

Thursday, 10 January 2019: 1:30 PM
North 224B (Phoenix Convention Center - West and North Buildings)
Jose M. Garcia-Rivera, IMSG, Rockville, MD; and J. Cheng, R. Chen, W. Guo, Y. Weng, Q. Xing, Q. Shi, and L. Jiang

Developing and installing a state-of-the-art aviation weather system in China has brought a number of challenges and lessons learned. For over 18 months (system delivered in May 2017,) the Enterprise Integrated Aviation Weather System (eIAWS™) has been providing operational, high spatiotemporal resolution weather forecasts for the East China Air Traffic Management Bureau (EC ATMB) in Shanghai. eIAWSTM is made of modules, which can be tailorable, and mainly consist of: 1) Radar/satellite nowcasting system, 2) Regional Rapid-Refresh (3R) high-resolution numerical weather prediction model, and 3) Air Traffic Management (ATM) decision support tools (DSTs). The successful operational deployment of this system has been the result of an unprecedented collaborative effort between US-based I.M. Systems Group (IMSG) and EC ATMB. More importantly, case results and feedbacks from forecasters at the EC ATMB Meteorological Center and ATM decision makers in the control center point to an improvement in their forecasting, awareness and communicational capabilities. However, a number of technical challenges where identified during the development and delivery phases of this project. For example, key issues on data availability, format and transfer, and unknown numerical model performance on that region presented an added level of uncertainty for operational implementation. While most of these where overcome, verification and user feedback have revealed a dry bias on forecasts inland within the model domain. This was confirmed by IMSG’s own verification of weather impact days during the spring and summer convective seasons of 2017 and 2018. Given these findings, ideas for future eIAWSTM updates aimed at improving operational forecast reliability, and DST development in the context of weather translation to ATM impacts will also be presented.
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