Low stratus (and fog) forecast for Central Europe introducing an empirical enhancement scheme for...

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

Harald Seidl and Alexander Kann

EMS Ljubljana 07.09.2006

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



Problem of inversion initialization and forecast with Aladin



Inversion forecast verificationInversion strength Inversion base

heightInversion top height

+hh MAE BIAS MAE BIAS MAE BIAS

00 1.9 -0.8 346 -253 239 -151

12 2.8 -2.8 892 -644 754 -651

24 2.3 -0.5 328 -245 207 -142

36 3.0 -2.9 1009 -737 864 -730

48 2.4 -0.6 375 -285 242 -173

Modelled inversions systematically too low and too weak

ALADIN model, Jan-Dec 1997



Introduction of sub-inversion (SK) cloudiness schemeSK-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.



Evidence for significant improvements with SK

Focus on case studies Evaluation episodes (statistical scores)



Diagnostic relationship in order to derive visibility categories (no cloud liquid water in the model)

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

COST722 – Model Intercomparison:

How to diagnose ground fog without (prognostic) cloud liquid water ?



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.



3 months evaluation for Lindenberg/Germany (autumn 2005)

→ kind of reference for later model

versions



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



Progn. Liqu. Water& LOPEZ

Traditional SK-scheme

Extended SK-Scheme added

Austrian LAEF methods(test suite)

ETKF ET multi physicsbreeding



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



Some similarities, but still: A lot to improve !


Thank you for your attention !

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