Impact of Traditional and Non-traditional Observation Sources using the Grid-point Statistical Interpolation Data Assimilation System for Regional Applications

The Grid-point Statistical Interpolation (GSI) Data Assimilation (DA) System is a three-dimensional (3D-Var) and hybrid DA system currently used by various United States agencies as part of operational forecast systems for both regional and global applications. In 2013, the Air Force Weather Agency (AFWA) updated their operational DA system to GSI. The Developmental Testbed Center (DTC) performed extensive testing and evaluation of GSI coupled with Advanced Research Weather Research and Forecasting (WRF-ARW) in a “functionally-similar” operational environment with the goal of assessing the impact of multiple proposed observation sources for AFWA DA operations.

Tests were run over a 15-km limited-area northern hemisphere (NH) domain covering large areas of both land and water over a 1-month period. The baseline configuration was based on the AFWA operational configuration for NH regional theaters with the inclusion of a raised model top (10– to 2-mb) to increase assimilated radiances, while the experimental configurations assimilated the additional observation source of interest. To further investigate the observation impacts of the proposed new data types on the GSI analysis and resulting forecasts, the forecast sensitivity to observations (FSO) tool for GSI was employed. This presentation will investigate the impact of the current suite of observations assimilated (conventional, GPS radio occultation, and multiple microwave and infrared (IR) satellite radiances) as well as the potential impacts of including additional microwave (e.g. AMSR2), IR (e.g. CrIS), and/or ozone (e.g. SBUV, GOME-2) sources. In addition to the FSO investigation, advanced verification methods will be presented to better understand the impact of the new observation types on the current operational system.