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Harald Seidl and Alexander Kann

Low stratus (and fog) forecast for Central Europe introducing an empirical enhancement scheme for sub-inversion cloudiness. Harald Seidl and Alexander Kann. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness. Content

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Harald Seidl and Alexander Kann

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  1. Low stratus (and fog) forecast for Central Europe introducing an empirical enhancement scheme for sub-inversion cloudiness Harald Seidl and Alexander Kann

  2. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Content • Problem of inversion initialization and forecast with Aladin • Introduction of sub-inversion (SK) cloudiness scheme • Evidence for significant improvements with SK • How to diagnose ground fog without (prognostic) cloud liquid water ? • Introduction of cloud liquid water, recent developments • Outlook

  3. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness • Problem of inversion initialization and forecast with Aladin

  4. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Inversion forecast verification ALADIN model, Jan-Dec 1997 Modelled inversions systematically too low and too weak

  5. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness • Introduction of sub-inversion (SK) cloudiness scheme SK-1) Coherent levels of quasi-saturation must define a layer of thickness Ф exceeding a critical thickness value Фc. SK-2) Coherent inversion of critical strength in terms of temperature difference  > c must also exist in order to trigger Stratus diagnosis. SK-3) “Shift criterion”: quasi-saturation zone may not arbitrarily penetrate into inversion layer: Penetration depth δ may not exceed critical value: δ < δc. Current settings are: c=0.1, Фc=2000 (m2/s2), c=1.5K, and δc=2000 (m2/s2). (Фc and δc are in terms of geopotential) • Now if all three criteria are fulfilled at any gridpoint SK-scheme runs also its enhancement section (fig. 1b) at this certain grid point, in the following way: • Cloudiness for each level within low cloud etage is re-initialised to zero, and each quasi-saturated level as well as total low cloudiness is set to 1.0 (100 per cent). • This will trigger a strong response from radiation routine “ACRANEB” tending to intensify or at least keep the pre-existing inversion(s) through infrared flux divergence inducing cloud-top cooling and heating at lower levels.

  6. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness

  7. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness

  8. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Evidence for significant improvements with SK • Focus on case studies • Evaluation episodes (statistical scores)

  9. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness

  10. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness

  11. Visibility Skrhcrit[%] Inrhcrit[%] Norhcrit[%] SFCinvCrit 350m 95 98 99.8 0.5K 600m 94 97 99.3 0.5K 1000m 93 96 99.0 0.5K 1500m 92 95 98.5 0.5K 3000m 91 94 97.0 0.5K Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness COST722 – Model Intercomparison: How to diagnose ground fog without (prognostic) cloud liquid water ? • Diagnostic relationship in order to derive visibility categories (no cloud liquid water in the model)

  12. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness • IF SK-scheme has diagnosed lifted fog conditions, criterion rh(1) ≥ Skrhcrit is used. • OTHERWISE test for surface inversion strength ≥ SFCinvCrit. • IF the latter is TRUE, rh(1) ≥ Inrhcrit in order for visibility below threshold • IF NOT THEN rh(1) ≥ Norhcrit in order to remain under visibility threshold.

  13. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness 3 months evaluation for Lindenberg/Germany (autumn 2005) →kind of reference for later model versions

  14. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Recent developments & Outlook • Tests with INCA analysis (&nowcasting) system to gain more accurate initial vertical state of the model atmosphere (esp. Lifted inversions !!) => not yet very successful (influence radius of observed soundings not large enough for the analysis) • Experiments with soil moisture initialization (preliminary results indicate improvements of cloudiness but rather of the Sc Cugen. type than the lifted stratus type; ground fog forecast however should improve !) • Aladin/AUT cycle29-30 with prognostic cloud water (Lopez scheme): precondition for fog simulation and forecast closer to natural physical processes

  15. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Austrian LAEF methods (test suite) breeding ETKF ET multiphysics TraditionalSK-scheme Progn. Liqu. Water &LOPEZ ExtendedSK- Schemeadded

  16. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Tests with Aladin/AUT cy29 (+cloud water +SK) • Direct use of cloud liquid water at lowest model level → ground fog indicator • SK scheme still working • Benefits in comparison with reference run (no SK) seem to reduce → Calibration of SK, incorporation of cloud water into this sub-inversion scheme

  17. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness

  18. Low stratus (and fog) forecast for Central Europe introducing an empirical scheme for sub-inversion cloudiness Some similarities, but still: A lot to improve !

  19. Thank you for your attention !

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