RPAS based observation on the Arctic Boundary Layer during the … · 2018-09-28 · uib.no U N I V E R S I T Y O F B E R G E N RPAS based observation on the Arctic Boundary Layer

uib.no

U N I V E R S I T Y O F B E R G E N

RPAS based observation on the Arctic Boundary

Layer during the ISOBAR campaigns on Andøya

and Hailuoto

S Kral1, J Reuder1, L Båserud1, G Urbancic1,M Jonassen2;1, A

Bhandari1, A Rautenberg3, J Bange3, M Hundhausen3, P

Hilsheimer3, A Platis3, B Wrenger4, C Langohr4, H Voss4, M Müller5,

C Lindenberg5, T Vihma6;2, I Suomi6, E O’Connor6, R Kouznetsov6 1Geophysical Institute, University of Bergen;

2The University Centre in Svalbard, Longyearbyen; 3University of Tübingen; 4University of Applied Sciences

Ostwestfalen-Lippe, Höxter; 5Lindenberg und Müller GmbH & Co. KG, Hohenhameln; 6Finnish Meteorological

Institute, Helsinki;

Geophysical Institute

uib.no

Overview

• The ISOBAR Project

• Methods

• Andøya campaign

• Hailuoto campaign

• Results

• Summary


uib.no

ISOBAR (Innovative Strategies for Observations in the

arctic atmospheric Boundary lAyeR)

Funded by the Norwegian Research Council + In Kind

Project Partners:

Geophysical Institute, University of Bergen

Uni Research AS, Bergen

The University Centre in Svalbard, Longyearbyen

Finnish Meteorological Institute, Helsinki

University of Tübingen

University of Applied Sciences Ostwestfalen-Lippe

Leibniz University Hannover


uib.no

Purpose

• Understanding of ABL processes in the Arctic

• Characterization of turbulence within the stable ABL


Approach

• Observations targeting all relevant processes

– AWS

– Profiling systems (RPAS, balloon, remote sensing)

– Turbulence systems (RPAS, ground based)

• Numerical Modelling

Goal

• Improvement of ABL parameterization schemes

uib.no

Methods

• Measurement strategy

– ground based flux and met stations

– ABL remote sensing and profiling systems

– RPAS


• Numerical modeling experiments

– Single Column Model (SCM)

– Large-Eddy Simulation (LES)

– Weather Research and Forecasting Model (WRF)

uib.no

Andøya Campaign (Dec. 2016)

• Test and validation campaign

– Rough conditions (cold,

dark, windy)

• Andøya Space Centre

– Flight permission

• UiB, UT, UOWL

– SUMO

– MASC

– AMOR Quadcopters

– Bebop Quadcopters

– 100 m Mast


uib.no

Andøya Campaign


• Lessons learned

– Conditions on Andøya can be very challenging

– Bebop poses considerable quality issues under cold

conditions

– Own flight permissions are desirable for an efficient

test campaign

• To do

– Validation of SUMO wind algorithm against mast data

uib.no

Hailuoto Campaign

• Feb 2017 (3.5 weeks)

• UiB, UT, UOWL, FMI

• Observations over sea-ice

– RPAS (3 different fixed-wing,

5 different rotary-wing)

– Ground stations (EC, AWS)

– Wind scanning Lidar

(Windcube 100s)

– Sodar (FMI)


uib.no

Hailuoto Campaign

• Flight permission

– D-Area

• ca. 20 km2

• Below FL 65 (ca. 1800 m)

– Very positive attitude by

Finnish authorities

– Easy communication with

tower in Oulu

– Cell phone contact for

activation


uib.no

Hailuoto Campaign

• RPAS operations

• SUMO profiles up to 1800 m

• Quadcopter profiles up to 400 m

• MASC/miniTalon turbulence legs between 30 m and

300 m


RPAS SUMO Bebop MASC miniTalon AMOR

Scientific

flights

42 60 31 3 33

uib.no

Hailuoto Campaign


SUMO profile

Bebop profile

MASC race track

uib.no

Temperature, wind and net radiation

• Temperature, wind, net-radiation


uib.no

Results: T-profiles Bebop


uib.no



uib.no



uib.no



uib.no



uib.no



uib.no



uib.no



uib.no



uib.no

Results: T-profiles SUMO


uib.no



uib.no



uib.no



uib.no



uib.no

Results: Combined T-profiles (AWS, Bebop, SUMO)


uib.no



Bebop profile

mast profile

time SUMO

time Bebop

SUMO profile

different z

scaling

uib.no



uib.no



uib.no



uib.no



uib.no



uib.no



uib.no



uib.no



uib.no

Wind speed profiles Bebop (very rough estimate)

• Simple but crude assumptions

– Based on tilt angles

– Symmetric behavior for pitch and roll

– Neglecting horizontal movements

– Neutral for 𝜑 = 𝜃 = 0

𝑢 = 𝐶 ∗ sin 𝜑

𝑣 = 𝐶 ∗ sin 𝜃

𝑈 = 𝑢2 + 𝑣2

– Proper calibration required

– "face−wind" control algorithm (𝜃 ≈ 0)


uib.no



uib.no



uib.no

Summary

• High resolution data covering the entire ABL and a good part of the

free atmosphere

– Estimate ABL fluxes from profiles

– RPAS based fluxes

– Link profiles to surface fluxes

• Remote sensing data as reference and for monitoring temporal

evolution

• Strong gradients require even slower climb rate or faster sensors

• GPS altitude might be misleading when combining profiles from

different systems

• Robustness of quadcopter needs to be improved for Arctic

conditions

• Quadcopter wind estimation needs to be improved



Documents

RPAS based observation on the Arctic Boundary Layer during the … · 2018-09-28 · uib.no U N I V E R S I T Y O F B E R G E N RPAS based observation on the Arctic Boundary Layer