Unlike some other forecast model components, a data assimilation (DA) system is usually built to be flexible in order to be run by different forecast systems at varying scales.
Its testing and evaluation must therefore be performed in the context of a specific application; in other words, it must be adaptable to different operational requirements as well as to research advances. Established in 2009, the DTC DA team started providing data assimilation support and testing and evaluation for Air Force Weather Agency (AFWA) mesoscale applications throughout its global theaters. This task has become one important component of the DTC’s effort to accelerate transitions from research to operations (R2O). Between 2009 and 2011, the focus of extensive DA testing for AFWA at the DTC was to provide a rational basis for the choice of the next generation DA system. Various analysis techniques and systems were selected by AFWA for testing, including WRF Data Assimilation (WRFDA), Gridpoint Statistical Interpolation (GSI), and the NCAR Ensemble Adjustment Kalman Filter. During this testing, the impacts of different data types, background error generation, and observation formats were also investigated.
Testing activity by the DTC DA team took a sharp turn in August 2012. To assist AFWA in setting up an appropriate configuration for their 2013 implementation of GSI, the DTC adapted their DA testbed to complement AFWA’s pre-implementation parallel tests in real-time. In support of providing new code and configurations, the team now performs two types of tests for AFWA:
The baseline experiment is usually generated by running the current operational or parallel system at AFWA. Whenever an AFWA baseline is updated, the DTC checks its reproducibility (or similarity) using the DTC functionally-similar testing environment to ensure that any following tests are comparable, and that there is no code divergence between research and operations. One such test conducted during the summer of 2013 (see figure next page) revealed that wind analysis fits to observations in AFWA forecasts were not reproduced by the DTC due to an inadvertent AFWA code change reading their own conventional data files. Other data assimilation components and applications (new configurations, techniques, observations, etc.) can also be tested in the DTC end-to-end DA testbed, see figure to the left.
During DTC real-time tests of the AFWA 2013 implementation, the AFWA GO index (a multivariate combined statistical score) dropped when the (then) AFWA parallel run configuration was used. When the GO index exceeded 1 (i.e., before November), the developmental experiment (which used the DTC-suggested configuration) outperformed the baseline (here, GFS-initialized). For wind variables in particular, the DTC configuration significantly improved the wind analyses. Further retrospective tests narrowed down the contributing factors, and the DTC suggested that the North American Mesoscale (NAM) static background errors generated by NCEP be used. AFWA adopted this configuration for its first GSI implementation in its global coverage domains in July 2013.