Investigating Impacts of the Wind Field and

Unknown Flying Objects on High-Res

Ceilometer Profiles during ScaleX 2016Christoph Münkel1, Klaus Schäfer2, Matthias Zeeman2

1Vaisala GmbH, Hamburg, Germany 2IMK-IFU at KIT, Garmisch-Partenkirchen, Germany

ScaleX

„Observations Lead the Way“

• Is a collaborative measurement campaign, co-located with a long-term environmental

observatory of the German TERENO (TERrestrial ENvironmental Observatories) network in

mountainous terrain of the Bavarian Prealps, Germany.

• Combines the benefits of a long-term environmental monitoring approach (TERENO) with a

series of intensive campaigns, to bridge across a wide span of spatial and temporal scales.

• Explores the question how well measured and modeled components of biogeochemical and

biophysical cycles match at the interfaces of soils, vegetation and the atmosphere, and across

various spatial and temporal scales.

• Hosted a variety of ground-based and airborne instruments for in-situ and remote sensing in

June and July 2016.

For more details, see

http://journals.ametsoc.org/doi/

10.1175/BAMS-D-15-00277.1,

http://scalex.imk-ifu.kit.edu

UFO experiment

• Vaisala Ceilometer CL51

• Tilted from the vertical by 25°

• Operated in Hi-Res mode

• Range 550 m

• Range resolution 10 m

• Laser pulse length 70 ns

• Profile report interval 0.2 s

Hi-Res CL51

Standard CL51

1. First-priority needs for mesoscale measuring includeI. Height (and structure) of the PBLII. Hi-res vertical profiles of atmospheric humidityIII. Air quality concentrations above the atmospheric surface layerUncertainty requirements for these depend on the application and should be defined by the user community.

2. Instruments required for thisI. Ceilometers or lidars with dedicated PBL algorithms (for example BL-VIEW)II. Profiler for atmospheric humidity like Water Vapor DIAL, dronesIII. In-situ air quality sensors, ceilometers and lidars, drones

3. Examples

Measure NO2, SO2, CO, O3,

PM2.5 and PM10

Presentations: Thursday, 11:30, Yakima 1 Thursday, 11:00, Skagit 4 Booth Number 313

Motivation

• Ceilometers use averaging periods of 2 s to

2 min to probe the atmosphere for

• Cloud base and vertical visibility

• Aerosol layers

• Insects, birds, bats, leafs, etc. reflect laser pulses

back to the ceilometer and cause sudden signal

increase, possibly resulting in

• False cloud base reports (very unlikely)

• False aerosol layer reports (more likely)

• This study concentrates on all 2 min intervals

without precipitation or low clouds recorded by

the Hi-Res ceilometer described below between

2016-06-01 and 2016-11-18 to examine the impact

of UFO reflections on aerosol layer analysis .

• Excluding all profiles with UFO reflections from

averaging improves layer detection performance.

Finding UFOs, UFO statistics

1. Examine all Hi-Res 2 min data intervals with

a) No cloud base below 500 m

b) No fog or precipitation

2. For these 2 min intervals, calculate signal

mean M(i) and standard deviation σ(i) for

all range gates i

3. All signals S(i,j) from profile j with

S(i,j) > M(i) + 8*σ(i)

indicate an UFO

4. An UFO is called significant if it increases

the 2 min average signal by at least 5 %

• Measurements during 3956 hours

• Periods qualifying for UFO examination

Summer: 62.6 % Autumn: 53.4 %

• 2 min intervals with UFOs

Summer: 43.7 % Autumn: 33.9 %

• 2 min intervals with significant UFOs

Summer: 2.2 % Autumn: 1.4 %Instrument21:54:00 21:54:30 21:55:00 21:55:30

UTC on 21. 06. 2016

0

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UFOs in 4 of 562 profiles (0.71 %)

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All data

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Max. deviation: 30.1 %

Mean all

Mean no UFOs

4 UFOs in 2 min, none of them significant

Significant UFO causing false 80 m layerUFO hits per hour, 2016-06-01 - 2016-08-31

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Wind field investigation

• ScaleX hosted three Halo Photonics Streamline wind lidars

• Two of these systems operated close to the Hi-Res ceilometer

• Wind lidar 26: 160 m East of ceilometer

• Wind lidar 74: 640 m South-East of ceilometer

• One of the wind lidar data products was vertical wind speed

Fendt Wind Lidar 26 vertical wind speed in m s -1

1.9

m s

-1

52 54 56 58 60 62 64 66 68 70 72

10:52 - 11:12 UTC on 20160628

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07:17:10 07:17:15 07:17:20 07:17:25 07:17:30 07:17:35

UTC on 28. 06. 2016

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Fendt HiRes Ceilometer attenuated backscatter

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w =−180m

17 s= −10.6m s

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Fendt Wind Lidar 26 vertical wind speed in m s -1

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07:10 - 07:20 UTC on 20160628

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Fendt Wind Lidar 74 vertical wind speed in m s -1

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07:10 - 07:20 UTC on 20160628

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Increased Hi-Res ceilometer

backscatter suggests downward

moving aerosol bubbles at 07:17.

At that minute, both wind lidars

report low mean vertical wind speed .

An aerosol bubble starts its rise at 11:02:00

and the Hi-Res ceilometer sees it during 90 s.

Both wind lidars report similar mean vertical

wind speeds.

Fendt Wind Lidar 74 vertical wind speed in m s -1

1.6

m s

-1

52 54 56 58 60 62 64 66 68 70 72

10:52 - 11:12 UTC on 20160628

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Conclusions, Outlook, Acknowledgements

Ceilometer

Wind lidar 26

Halo Photonics Streamline

Doppler wind lidar at IMK-IFU

Halo Photonics Streamline

Doppler wind lidar at ScaleX

Vaisala CL51 and BL-VIEW for PBL analysis Vaisala DIAL water vapor profile Vaisala AQT transmitters

• Hi-Res ceilometer profiling

• has been performed at one location for more than 5 months

• is capable of reducing false aerosol layer hits

• confirms that insects and birds are most busy around sunset

• enables monitoring of moving aerosol bubbles

• Future ScaleX evaluation of ceilometer and wind lidar data will

• investigate the applicability of Hi-Res ceilometer profiles for estimating turbulence parameters

• result in detailed information about 3D wind fields based on measurements from 3 wind lidars

• lead to more conference presentations and publications

The TERENO pre-Alpine infrastructure is funded by the Helmholtz Association and the Federal Ministry

of Education and Research. Aerial view of the ScaleX site was provided by the Institute for Software &

Systems Engineering (ISSE) of the University of Augsburg; ScaleX ground based pictures are from

Martin Kunz, Max Planck Institute for Biogeochemistry, and from Matthias Zeeman, IMK-IFU at KIT.

06:49:00 06:49:30 06:50:00 06:50:30

UTC on 07. 06. 2016

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UFOs in 4 of 561 profiles (0.71 %)

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Max. deviation: 2.1 %

Mean all

Mean no UFOs

11:01:50 11:02:00 11:02:10 11:02:20 11:02:30 11:02:40 11:02:50 11:03:00 11:03:10 11:03:20 11:03:30 11:03:40 11:03:50

UTC on 28. 06. 2016

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Fendt HiRes Ceilometer attenuated backscatter

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w =171m

90 s= 1.9m s

−1