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Quality indicators in an operational precipitation product

Quality indicators in an operational precipitation product. IPWG meeting 4 Beijing, 13-17 October 2008. Presented by: Thomas Heinemann Meteorological Operations Division EUMETSAT thomas.heinemann@eumetsat.int. Overview. News from METOP/HRPT

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Quality indicators in an operational precipitation product

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  1. Quality indicators in an operational precipitation product IPWG meeting 4 Beijing, 13-17 October 2008 Presented by: Thomas Heinemann Meteorological Operations Division EUMETSAT thomas.heinemann@eumetsat.int

  2. Overview • News from METOP/HRPT • The Multi Sensor precipitation Estimate (MPE), a real-time precipitation algorithm • Why shall we provide quality information • The MPE quality indicators (QI) • How useful are the MPE QIs • Outlook

  3. News from METOP-A HRPT • METOP-A was launched on 19 October 2006 • LRPT direct data transmission was not activated • HRPT direct data transmission service failed soon after activation • Root cause was heavy ion radiation causing the failure of a component of the AHRPT Solid State Power Amplifier (SSPA) • To minimise the risk of failure to the HRPT-B unit a "partial" HRPT service in those areas where the risk of damage from heavy ions is reduced, has been implemented.  • For southbound passes over Europe and the North Atlantic, HRPT side B will be activated starting around 60°N. • First activation was on 29 September 2008  (2 month trial)

  4. MPE: a real-time precipitation algorithm • Combines passive microwave from polar orbiting satellites with IR data from geo-stationary satellites. • Algorithm is based on the classical blending approach. • Instantaneous rain rate data are produced every 15/30min in original Geo-satellite pixel resolution (MET-7 INDOEX, MET-8 RSS, MET-9 0°) in the operational environment of the MSG groundsegment. • Processing is done in near-real time mode with a time delay of < 10 minutes between image acquisition and data dissemination. • Data are provided on the internet and via EUMETCAST in GRIB-2 data format and in addition visualised on the EUMETSAT web-page.

  5. MPE: a real-time precipitation algorithm

  6. Who are the (designated) users of real-time precipitation algorithms ? • NRT or RT precipitation data are • essential for: • Short term weather forecasts and nowcasting • Operational short term hydrological and acricultural applications Photos: WFP In large areas of the world methods based on ground measurements or polar orbiting satellite products cannot fulfil the NRT requirements and a dense radar network is not available ( Africa, Asia !!!)

  7. Why (still) a blending algorithm ? • EUMETSAT ‘s and its users requirements for the rain-rate algorithm are: • To provide a real-time product in high temporal and spatial resolution. • To use a scientifically mature algorithm which has been proven to work operationally. • Most other algorithm types cannot be used in real-time. • Other real-time algorithm’s are either very similar to the used one or still in development phase. • But tests with other algorithms were done: • Hydro-estimator implemented for South Africa, CMORPH version tested, co-operation with H-SAF and NOAA …

  8. MPE and Hydro-Estimator in South Africa MPE results (left) and Hydroestimator results (right) of the instantaneous rain rate (mm/hour) based on the 10:00 UTC MSG image of 6 November 2007.

  9. MPE validation by the European PEHRPP site

  10. MPE validation by the European PEHRPP site Courtesy: Chris Kidd

  11. Why (quantitative) quality indicators? • Users trust data only if they have a clear vision how accurate they are. • Most algorithms perform in some conditions better than in others (especially combined algorithms). • Algorithm developers have more a-priori information available and know their algorithm better than the users. • Many algorithms depend on the results of previous data analysis (eg. cloud mask). The quality of the previous steps affects the quality of the final product. • All this information should be provided to the users. • Different applications need different QI’s!

  12. Continuous re-adjustment of LUTs as source for MPE quality indicators • Blending principle: • Co–located microwave rain-rates and IR brightness temperature for a specific region and time-span are used to derive a monotonic relation between IR BT and rain rate.

  13. Definition of MPE QIs • QI1 := Correlation coefficient between MPE rain-rates for the • co-located IR data and the microwave data rain-rates • QI2 := Standard deviation between MPE rain-rates for the • co-located IR data and the microwave data rain-rates

  14. MPE Correlation QI

  15. MPE standard deviation QI

  16. Test strategy for QIs • Purpose : Test if MPE rain-rates in areas with high QI are really better. • Method: Compare MPE rain rates ffrom the real-time algorithm with microwave rain-rates. • Precondition: None of the microwave rain rates used for the comparison are included in the co-locations. • Limitation: Not a real validation of rain-rates but of the matching-algorithm.

  17. Correlation QI for 0.25° cell size

  18. Correlation QI for 5° cell size

  19. Histogram of QI1, January

  20. Histogram of QI1, July

  21. Summary • EUMETSAT committed to continue the operational service for a disk-wide real-time rain-rate product • The current algorithm should be updated to a mature, state-of-the-art algorithm which fulfils the requirements. • The EUMETSAT Hydrology SAF is developing additional algorithms for various applications • Effective and adapted Quality Indicators are essential for the optimal application of precipitation products, especially in models. • The MPE QIs based on the co-location statistics are useful indicators to identify the areas where the MPE algorithm should not be used.

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