news concerning the cloud microphysical measurements during...

Thermodynamic correction of particle concentrations

measured by underwing probes on fast flying aircraft

Ralf Weigel, Peter Spichtinger, Christoph Mahnke, Marcus Klingebiel,

Armin Afchine, Andreas Petzold, Martina Krämer, Anja Costa, Sergej Molleker,

Max Port, Lucas Grulich, Andreas Minikin, Stephan Borrmann

ACRIDICON-CHUVA Workshop

News concerning the cloud microphysical

measurements during

ACRIDICON-CHUVA 2014:

-Christoph Mahnke-

Ilha Bela (Brazil), 01.03.2016


CCP PIP

DLR HALO, right wing (A.Minikin, 2013) DLR HALO, left wing (A.Minikin, 2013)

CCP and PIP in HALO PMS-Configuration

Measurement principle of

optical array probes (OAP)

e.g. the CCP

CIPgs detector

pitot-tube

CDP detector

Source: Baumgardner and Korolev (1997)


distance covered over Δt

�� = � · 1

�� · �� ·

1

∆�

= �

��

Ingredients � particle number concentrations:

• Number of particles n,…

• …detected per time unit Δt,…

• …over which the sample area As is

penetrated by the air volume Vmeas .

flight direction Measurement principle of

optical array probes (OAP)

e.g. the CCP

Source: Baumgardner and Korolev (1997)

Source: Marcus Klingebiel


Unaware the air speed

(e.g. no pitot tube)

� = �

�� · �� ·

1

∆�� = � ·

1

�� · �� ·

1

∆�

Alternatively: own air speed

measurements available

· ��

��

with the purpose

to correct

Nmeas� Namb

�� · ��

�� =

�

�� · ∆� · �� · ��

��

With own air speed

(with pitot tube)

�� =�

�� · �� ·

1

∆�

� = �

�� · �� ·

1

∆�

believing

PAS represents

particle speed

believing

TAS represents

particle speed

Hypothesis: None of these approaches really gives Namb

� = �

�� · �� ·

1

∆�� =

�

�� · �� ·

1

∆�

Different ways of treating the data


distance covered over Δt

�� = � · 1

�� · �� ·

1

∆�

= �

��






flight direction


�� = � · 1

�� · �� ·

1

∆�

= �

��






remains as suchremains as such

remains as such

Increased by linear

expansion in line with

flight direction.

� · 1

�� · �� ·

1

∆�

= �

��

enlarged distance covered over Δt

≠

flight direction


T1

p1

ρ1

v1=TAS

vp ≈ v1

T2>T1

p2>p1

ρ2>ρ1

v2=PAS

PAS<TAS

vp ≈ PAS

Fundamental

assumption:

otherwise

spheroidal drops

would generally show

distorted images

Ambient conditions

versus

Measurement conditions


vp ≈ PASFundamental assumption:

for calibrations with spinning disk:

PAS is manually set to be equal to

disk’s rotation speed: ~24 m s-1

set PAS

HIGHER than

disk’s rotation speed

� scanning frequency increased

� particle is reconstructed based on more

slides than necessary � elongated images

set PAS

LOWER than

disk’s rotation speed

� scanning frequency decreased

� particle is reconstructed based on lesser

slides than necessary � squeezed images

dir

ect

ion

of

pa

rtic

lefl

ow


�� =�� · ��

�� ·

1 + �� − ��

�

2008!

"# · $

·1

��

�� = �� · %

�� = ��· ��

��= �� ·

��

��

��

Ambient conditions

versus

Measurement conditions

T1

p1

ρ1

v1=TAS

vp ≈ v1

T2>T1

p2>p1

ρ2>ρ1

v2=PAS

PAS<TAS

with Bernoulli‘s law

1

2��

� +&� +ℎ� =1

2��

� +&� +ℎ�

ΔT (or T2) calculated via increasing enthalpy

(Δh) accompanied with Δv.


Three different positions of underwing probes

ML-CIRRUS instrumentation ⟺ ACRIDICON instrumentation

Outboard

position

Inboard

position

Intermediate

position


Probe‘s individual PAS

measurement (ML-CIRRUS)

systematic offset between

CCP and NIXE-CAPS as well as

CCP and PIP of less than 10%.

� within uncertainty

Probe‘s individual static pressure

measurement (ML-CIRRUS)

Strong agreement between

Three independent instruments.

� Measurement seems robust!


Impact of different corrections on PMS-measured number concentrations (ACRIDICON AC13)

uncorrected Nmeas vs PAS/TAS-corrected vs ξ-corrected Nmeas

- straight level flight with 215 m s-1 < TAS < 225 m s-1 (�� = 222 m s-1)

- liquid droplet regime

� spheroids are imaged as such

� eff. correction CCP & NIXE & PIP: 27-30 %

� eff. correction CCP & NIXE & PIP: ~12 %


Icing problem of the pitot-tube airspeed measurement(CCP) at flight AC07

Corrupted CCP-PAS

measurement due

to icing!


Parameterization of 1Hz-resolved CCP-PAS-values for ML-CIRRUS

PASCCP-Para = K0 + K1 * TAS + K2 TAS2

K0 = -12.789 ± 0.0552

K1 = 0.99788 ± 0.000631

K2 = -0.00095938 ± 1.75e-006

Reconstruction of the PAS gives us the possibility to:

• Rescue all Icing-corrupted CDP-Data

• Rescue big parts of the CIPgs-Data

• Depending on degree of false-imaging

• PIP-PAS reconstruction will follow (work in

progress)


Note: data reassessed

concerning outliers!

Parameterization of calculated 1Hz-resolved ξ-values

for ML-CIRRUS

Outboard position Inboard position Intermediate position

� Comparatively compact behaviour as a function of TAS

> 130 000 single data points (> 36 flight hours)

flight dates


ACRIDICON-CHUVA 2014 AC17: Cloud constrast (forested-deforested)

Leg1

Leg2

Leg1: Cloud contrast

• West: Forested area

• East: Deforested area

Leg2: Cloud contrast

• North: Forested area

• South: Deforested area



Leg1

ca. 120 km

1: Forested area 2: Deforested area

2 1 1 2 2 1Sample area:



Forested area Deforested area

843 hPa

812 hPa

753 hPa

Pressure level

Ntotal = 64 cm-3

Ntotal = 90 cm-3

Ntotal = 54 cm-3 Ntotal = 256 cm-3

Ntotal = 381 cm-3

Ntotal = 215 cm-3


Distillate:

1) For a correction from Nmeas to Namb air compression (Δp and ΔT)

has to be considered!

2) the ξ-factor

a) originates from a thermodynamic perspective (accounting for Δp and ΔT)

b) demonstrated consistency over three underwing positions

c) is compact as function of TAS

d) has a plausible effectiveness as a function of TAS

Complete story with more datails is subject of publication at AMTD entitled:

Thermodynamic correction of particle concentrations

measured by underwing probes on fast flying aircraft


Distillate:

4) ACRIDICON-CHUVA 2014 : Cloud contrast between forested and deforested areas.

a) Higher number concentrations over the deforested areas compared to the

forested areas

b) Broadening of the maximum of the size distribution with increasing altitude

c) No significant difference in the shape of the size distributions between the

forested and deforested area

3) Parametrization of the PAS as function of TAS gives us the possibility to:

a) rescue icing corrupted measurements (e.g.: CDP, CIPgs, PIP)

b) calculate the PAS for probes without an own pitot-tube

(more wing positions will follow)


Thanks for

your attention!


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