To quantitatively evaluate the benefits of new observations in numerical weather prediction, both Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs) are necessary. OSEs are data denial studies that allow the evaluation of existing data but cannot be used to analyze the impact of future observing systems. Atmospheric OSSEs are modeling experiments used to perform an objective evaluation of the potential benefits of proposed observing systems in weather forecasting. These experiments explore the value of enhancing the current global observing system with additional observations that do not yet exist. For OSSEs to produce accurate quantitative results, all of the components of the OSSE system must be realistic. This includes the following: (1) A long atmospheric model integration using a “state of the art” numerical model to provide a complete record of the assumed true state of the atmosphere, usually referred to as the nature run
. The nature run should represent the main characteristics of the real atmosphere, e.g. its climatology, general patterns of storm tracks, etc. (2) Observations simulated from the nature run for existing conventional and satellite platforms. These synthetic observations need to be simulated with the same spatial and temporal coverage, resolution, and accuracy as the real-world observations have. (3) Simulation of new, proposed observations from the nature run with realistic coverage and accuracy. (4) An assimilation system including a numerical model for the generation of first guess forecasts, where the synthetic observations from both the current and proposed instruments are assimilated and evaluated. (5) Validation of the entire OSSE system to ensure that the accuracy of analyses and forecasts, and the impact of existing observing systems in the OSSE environment, are comparable to the accuracies and impacts of the same observing systems in the real world.
A variety of OSSEs were conducted under SHOUT to quantify the impact of assimilating dropsondes from the Global Hawk in global and hurricane prediction systems. Experiments covered a wide range of configuration scenarios, from idealized sampling domains over large geographical areas to specific flight paths designed with the use of targeting observation techniques. Furthermore, automated and subjective simulated flight patterns were investigated. In the hurricane model, the impact of sampling the inner core versus the outer core of the storm with additional Global Hawk dropsondes was analyzed.
In this talk, the different OSSE configurations used in our experiments will be presented and results for a few selected storms will be discussed in the context of global and hurricane prediction models.