Monday, 23 January 2017: 1:30 PM
607 (Washington State Convention Center )
Observing System Simulation Experiments (OSSEs) are an important tool for evaluating the potential impact of proposed new observing systems, as well as for evaluating trade-offs in observing system design, and in developing and assessing improved methodology for assimilating new observations. It is important for OSSE systems to be validated and for all of the components of an OSSE system to be as realistic as possible. Early OSSEs, that were conducted in the 1960's and early 1970's, provided an analysis of data requirements for the Global Atmospheric Research Program (GARP), the useful range of predictability, the need for reference level data, and the relative importance of asynoptic vs. synoptic data assimilation. Susequent evaluations of these early OSSEs revealed a number of significant limitations. These limitations were largely corrected in the early 1980's, and since that time an extensive series of OSSEs has been performed. These OSSEs determined correctly the quantitative potential for several proposed satellite observing systems to improve weather analysis and prediction prior to their launch, evaluated trade-offs in orbits, coverage and accuracy for space-based wind lidars, and were used in the development of the methodology that led to the first beneficial impacts of satellite surface winds on numerical weather prediction. This keynote lecture will summarize development and evolution of OSSE methodology, illustrate the performance of a global numerical weather prediction OSSE, and discuss the expansion of rigorous OSSE methodology to other applications, and how OSSEs will evolve in the near future.
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