Christian Lemmerz, Stephan Rahm DLR German Aerospace Center , - - PowerPoint PPT Presentation

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Christian Lemmerz, Stephan Rahm DLR German Aerospace Center , - - PowerPoint PPT Presentation

Apr 29, 2023 322 likes •496 views

Lessons learnt for Aeolus from the pre-launch validation campaigns with the A2D Uwe Marksteiner, Oliver Reitebuch, Benjamin Witschas, Christian Lemmerz, Stephan Rahm DLR German Aerospace Center , Institute of Atmospheric Physics ,

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SLIDE 1

Lessons learnt for Aeolus from the pre-launch validation campaigns with the A2D Uwe Marksteiner, Oliver Reitebuch, Benjamin Witschas, Christian Lemmerz, Stephan Rahm

DLR German Aerospace Center , Institute of Atmospheric Physics , Oberpfaffenhofen , Germany

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SLIDE 2

2 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

Objectives of A2D (ALADIN Airborne Demonstrator)

HuricaneHiRes_credits-ESA_ATG-Medialab

Acknowledgement: Funding for the development of the ALADIN Airborne Demonstrator A2D and performance

  • f campaigns was provided by ESA and DLR.
  • Validation of ALADIN instrument with atmospheric signals

before launch

  • Derivation of conclusions for:

 retrieval algorithms 

  • n-ground and in-orbit tests

 verification and calibration of satellite instrument

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SLIDE 3

3 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

A2D (ALADIN Airborne Demonstrator):

  • „twin instrument“ (receiver, detector, …)
  • space industry performs test and characterisation in laboratory
  • DLR performs also atmospheric measurements
  • viewing geometry comparable to Aeolus
  • possibility of ground detection

Comparison of Aeolus and A2D

 A2D is particularly suited to verify the wind measurement & calibration strategy of Aeolus

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SLIDE 4

4 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

2-µm Doppler wind lidar A2D receiver thermal hood A2D telescope 2-µm DWL electronic rack

The ALADIN airborne demonstrator

Payload in DLR Falcon aircraft during campaigns in 2007, 2008 & 2009

  • Development of the A2D with the
  • ptical receiver and laser breadboard

from ESA´s Pre-Development Programme

  • Delivery of A2D and first flights of a

direct-detection Doppler lidar worldwide in 2005

  • Ground campaigns in 2006 and 2007
  • First flights of coherent and direct-

detection wind lidar on-board the same aircraft in 2007  10 years of experience with A2D

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SLIDE 5

5 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

Fizeau Interferometer The optical receivers of the airborne demonstrator from DLR (A2D) and the satellite instrument (ALADIN) are based on almost identical design Fabry-Perot Interferometer

Reitebuch et al. 2009

A2D hardware

1. combined arrangement

  • f two different

spectrometers 2. Fizeau spectrometer for Mie channel 3. sequential implementation of Fabry Perot interferometers 4. custom-built ADM specific ACCD chip

Novel technology

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SLIDE 6

6 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

  • low aerosol load

 pure Ray. scatter

  • jet-stream

 high wind speeds

  • ice albedo

 calibration as Aeolus

  • ocean

 change of reflexion Reasons for choice of Iceland/Greenland 10 flights with a duration

  • f 33 hours including

transfer and test flight

3rd Aeolus campaign in Sept. 2009

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SLIDE 7

7 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

3rd Aeolus campaign in Sept. 2009

2 calibrations wind observations

26 km  6 min

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SLIDE 8

8 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

Instrument Response Calibrations of A2D

⇒ Apparently very consistent calibrations. However, resulting in differences in wind speeds of up to ≈4 m/s.

2 calibration curves almost on top of each other wind speeds

Cal.1 Cal.2 Internal Reference ≈ 3 m/s

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SLIDE 9

9 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

  • in this case calibration curves of single

„range-gates“ are partly deviating by ≈120 m/s ⇒ preceding summation of signal yields a useful calibration curve

  • Ground echo signal distributed
  • ver 2 „range-gates“
  • deviations depending on non-

perfect location of Rayleigh spots and Mie fringe on ACCD and range-gate overlap

Ground calibration ⇒ summation of signal

intensity relative frequency / MHz

≈ 120 m/s

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SLIDE 10

10 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

ground 18 s (ca. 3.5 km) 300 - 2400 m terrain 1 µs ≈ 150 m ratio in % 100 (integration) time detector Comparison of detected ground height: A2D  Digital Elevation Model

Distributed ground echo & range-gate overlap

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SLIDE 11

11 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

ground does not move  signal must yield 0 m/s  Zero-Wind Correction Additionally induced „virtual“ wind speed, e.g. due to:

  • 1. component of aircraft velocity in direction of LOS

(know)

  • 2. Instrumental error or error in flight attitude

(unknown)

  • vA/C

vA/C vZWC vLOS,A/C

, , /

( ) 2

I LOS wind A LOS A C ZWC

v f f v v       

Line-Of-Sight wind and corrections

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SLIDE 12

12 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

A2D (Rayleigh) 2-µm lidar A2D (Mie) cloud jet-stream 368 km

1st airborne measurements of 2 different lidars in 2009

30 min wind measurement

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SLIDE 13

13 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

2-µm Mie Rayleigh ECMWF MODIS, Oct. 1st , 2009

Airborne lidar observations and ECMWF model

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SLIDE 14

14 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

Mie Rayleigh

slope: 1.14

  • std. dev.:

1.5 m/s # of points: 932 slope: 1.04

  • std. dev.:

2.5 m/s # of points: 596

Statistical comparison for ALADIN airborne demonstrator against 2-µm lidar

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SLIDE 15

15 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

200 400 600 800 1000 4000 4100 4200 4300 4400 4500 4600 4700

Background/(LSB) - trend corrected time/(s)

4300 4350 4400 4450 4500 4550 4600 100 200 300 400 500 600 700 800 900

counts Background signal/(LSB)

BKGmean = 4464 LSB BKG = 42.3 LSB Poisson = 38.4 LSB

  • An ideal (photon) counting process obeys Poisson statistics
  • For Aeolus it is expected, that all instrumental noise sources are so small that Poisson Noise

is the largest contributor („shot noise limited detection“)

Ongoing study on A2D instrumental noise sources

1000 2000 3000 4000 5000 6000 28000 29000 30000 31000 32000 33000 34000 35000 36000

SignalInt.A Poisson NoiseInt.A SignalInt.B Poisson NoiseInt.B meanInt_A = 33471 ± 689 (Poisson = 106) meanInt_B = 30087 ± 624 (Poisson = 100)

intensity/(LSB) (internal) time/(s)

  • A2D is Poisson noise

limited in regarding the background signal intensity ⇒ no increased electronic noise

  • signal intensity of the

Internal Reference Poisson noise limited up to 40 s Noise study for A2D to investigate instrumental errors:

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SLIDE 16

16 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner

Summary and Conclusion

  • Experience of more than 10 years with operation of the unique

A2D instrument

  • New methods & new wind retrieval algorithms were developed

using A2D data from airborne and ground measurements

  • High quality wind measurements
  • Principle of calibration and wind retrieval for Aeolus was

validated with airborne demonstrator A2D at DLR during several ground and airborne campaigns

  • The A2D will be used after launch for validation of Aeolus wind

measurement and calibration strategy

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SLIDE 17

17 Aeolus Cal/Val – ESA ESRIN – February 10th, 2015 – Uwe Marksteiner