Quantitative Observing System Assessment Program (QOSAP)




AOML houses NOAA's Quantitative Observing System Assessment Program (QOSAP), which provides quantitative and objective assessment capabilities to analyze and evaluate current and future earth observation systems. These capabilities include observing system experiments (OSEs), which focus on identifying the impact of a current observing system on data assimilation and numerical weather prediction while testing ways to improve the quality and usefulness of data products.


The program also includes observing system simulation experiments (OSSEs) which focus on assessing the potential impact of proposed and future observing systems on numerical weather, ocean, and climate prediction.


By leveraging both OSEs and OSSEs, QOSAP aims to inform major decisions on the design and implementation of optimal observing systems, as well as increase NOAA’s capacity to conduct quantitative observing system assessments.


AOML scientists created a step-by-step process to encourage consideration of aspects of good OSSE design principles. The resulting OSSE checklist, based on a recent AMS publication titled "Future Observing System Simulation Experiments", is available online here.


Summary of Results

H.R. 353, the “Weather Research and Forecasting Innovation Act of 2017” (Public Law 115-25) Section 107(d)(1), states “Not later than 30 days after the date of the enactment of this Act, the Assistant Administrator for Oceanic and Atmospheric Research shall complete an Observing System Simulation Experiment [OSSE] to assess the value of data from Global Navigation Satellite System Radio Occultation.” In response to this requirement, NOAA completed the Global Navigation Satellite System (GNSS) radio occultation (RO) OSSE experiments by May 18, 2017.


NOAA conducted comprehensive experiments with a previously existing global Observing System Simulation Experiment (OSSE) system to determine the potential value of proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellations for current operational numerical weather prediction systems. To confirm and extend these results, additional experiments were conducted with two newly developed, rigorous OSSE systems: an advanced “next-generation” global OSSE system and a regional hurricane OSSE system.  These experiments considered a range of possible future RO systems. The RO observations used in these experiments were simulated with the geographic sampling expected from the Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) system, with 6 equatorial (total of ~6,000 soundings/day) and 6 polar (total of ~6,000 soundings/day) receiver satellites.


In brief, the combined findings from all GNSS-RO OSSE experiments include:

  1. In general, removing all existing RO observations being used at NOAA from the operational numerical weather prediction system degrades global weather forecasts in the Southern Hemisphere extratropics and tropics.
  2. In general, increasing the number of assimilated RO receiving satellites improves global weather forecasts. The improvement is greatest in the Southern Hemisphere extratropics and tropics.
  3. In the RO experiments using the newly developed, advanced OSSE system, RO observations increased the length of the reliable forecast by 0.6 hours in the Northern Hemisphere extratropics1 (a negligible 0.4% improvement), 5.9 hours in the Southern Hemisphere extratropics (a significant 4.0% improvement) and 12.1 hours in the tropics (a substantial 28.4% improvement).
  4. Assimilation of RO data into global and regional hurricane numerical weather prediction systems can lead to meaningful improvement in some hurricane track forecasts.
  5. No improvement of hurricane intensity and precipitation forecasts through global assimilation of RO data was demonstrated for the cases studied. The impact on severe local storm indices was mixed. Future planned experiments will examine other cases and the impact of regional assimilation of RO data on hurricane intensity and severe local storm forecasts.

Results will be made public in conference presentations and peer-reviewed journal articles. Links to these documents will also be found at the QOSAP web site.



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