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 GNSS RO OSSE

 NOAA's Office of Oceanic and Atmospheric Research 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 in current operational numerical weather prediction systems.  To confirm and extend these results, additional experiments were conducted with two additional rigorous OSSE systems: an advanced “next-generation” global OSSE system and a regional hurricane OSSE system.  These experiments considered different future RO systems consisting of 6 to 30 receiver satellites. The most recent NOAA RO OSSE used the advanced OSSE system and quantified the impact of RO observations on global weather analyses and forecasts, and the effects of these global analyses and forecasts on regional hurricane forecasts and on the specification of weather indices useful in the prediction of severe storms and tornados. The RO observations were simulated with the geographic sampling expected from the Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) system, with six equatorial (total of ~6,000 soundings/day) and six polar (total of ~6,000 soundings/day) receiver satellites.


The findings of the combined set of experiments are the following:

  1. Removing existing RO observations from the operational data assimilation system degrades global weather forecasts in the Southern Hemisphere extratropics and tropics. This is found in OSSEs and confirmed in Observing System Experiments (OSEs).


  2. 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 latest NOAA RO OSSE, the impact of RO observations was to increase the length of the useful 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 data assimilation systems can lead to meaningful improvement in some hurricane track forecasts.


  5. Improvement of hurricane intensity and precipitation forecasts through global assimilation of RO data was not demonstrated for the cases studied. The impact on severe local storm indices was mixed. Further experiments will examine other cases and the impact of regional assimilation of RO data on hurricane intensity and severe local storm forecasts.

 A report of these experiments will be posted on NOAA’s Quantitative Observing Systems Assessment Program (QOSAP) web site (http://www.aoml.noaa.gov/qosap/) in the next 30 days. Results are also made public in conference presentations and peer-reviewed journal articles. Links to these documents will also be found on the this web site.



1For reference, the comparable ECMWF forecast metric has increased from about 5 days to about 6.8 days since 1998. That is, a one-day increase in forecast time per decade of very intense improvements in computing, observing systems, data assimilation systems, and forecast models (Visit: http://www.ecmwf.int/en/forecasts/charts/catalogue/plwww_m_hr_ccafreach_ts_hs?time=2017051100&area=NHem%20Extratropics).


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