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Geometrical description of the hydrometeor images sampled with the AIRBUS imager during the Cayenne flight 1423 Minimal model for the small ice particles.

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Presentation on theme: "Geometrical description of the hydrometeor images sampled with the AIRBUS imager during the Cayenne flight 1423 Minimal model for the small ice particles."— Presentation transcript:

1 Geometrical description of the hydrometeor images sampled with the AIRBUS imager during the Cayenne flight 1423 Minimal model for the small ice particles shapes (D<100 µm) ? C. Duroure, A. Delplanque (LaMP), M. Weber (AIRBUS) 1- We verify some (quite trivial) correlation between some geometrical variables. 1bis- we verify (for this simple case) the coherence of the automatic shape recognition 2- We observe some (not trivial) correlation between these geometrical variables and the bias of TWC measurements using hot wire probe and imaging probe. 3- We propose a statistical model of small ice crystals (D<100 µm) using the observed distribution of geometrical variables (aspect ratio and/or rugosity) 4- Work in progress, not presented: Link with the temperature and vertical velocity field, possible estimation of the “microphysical age” of the studied regions (few seconds after nucleation, few minutes ?) Technical trouble: 1-Why the correlation between TWC of hot wire probe and total concentration of images is better than the correlation using PSD and mass to diameter functions ? 2-Sensibility of the results to the threshold rules ! HAIC working document 22/10/2013 meeting

2 L4 L2 L3 L1 Case study of four legs (20 Km scale) into the one hour leg at 10.6 Km level (T=-42 °C) (Try this fligth strategy in the 2014 Darwin experiment ? Fixed level and multiple circle leg around active region) AIRBUS Cayenne FL1423: « random circle fligth » in a active MCS region

3 Three different geometrical variables: In this case study it exist quite good correlations Perimeter of a equal surface disk / Perimeter of the image « Roughness » coefficient Aspect ratio ( Width / Lmax)

4 How explain the correlation between the geometrical aspect ratio and TWC estimation with two different probes ? Ratio between TWC from the imager and TWC from hot wire probe (Robust) Aspect ratio ( Width / Lmax) ( 1hz, 200 meters average) L1 L2 L3 L4100 Km

5 Correlation between the geometrical aspect ratio and TWC the automatic shape recognition (for this fligth) Ratio between the probability of SPHEROID and SMALL IRREG. shapes Aspect ratio ( Width / Lmax) ( 1hz, 200 meters average) L1 L2 L3 L4100 Km

6 Modelisation of small ice cristal (D<100 µ m) using observed mean aspect ratio distribution (or other geometrical variables) => random distribution of oblate spheroid with fixed distribution of aspect ratio Assuming: Density close to pure ice (0.89 Gr/Cm-3, B=3) Include not isometric aspect ratio evolution with size ? ( B<3) Leg 1,3Leg 2,4

7 Correlation with the mean diameter ??? Ratio between TWC from the imager and TWC from hot wire probe (Robust) Mean diameter ( µ m)

8 Correlation with the total concentration (and/or TWC) ??? Total concentration Ratio between TWC from the imager and TWC from hot wire probe (Robust)

9 Vertical velocity (W) Temperature (Tp) Total concentration (Ct) Local anti-correlation W-Tp and Local correlation Ct-Tp

10 7 Km Hight concentration + hight aspect-ratio ( + temperature jump) => new nucleation region ?

11 Automatic shape recognition procedure definition Ref: Thèse Rémy Lefevre, LaMP, Mars 2007 n°:527

12 Technical troubles : What is the better treshold ? Use of VAL ? All images Valid images New GEO file Old GEO file GEO file low tresh.

13 Technical trouble: the result for the new version of the V1423_GEO file are very sensible to the VAL (validity) variable.


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