a weight-shift microlight aircraft study.

EMS Annual Meeting Abstracts Vol. 7, EMS2010-PREVIEW, 2010 10th EMS / 8th ECAC © Author(s) 2010

High resolution climatology - towards climate change services

Regional energy and CO2 exchange over transitional grassland of Inner Mongolia - a weight-shift microlight aircraft study. S. Metzger (1), W. Junkermann (1), L. Wang (2), K. Butterbach-Bahl (1), X.H. Zheng (2), and T. Foken (3) (1) Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany ([email protected]), (2) Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China, (3) Department of Micrometeorology, University of Bayreuth, Bayreuth, Germany

In environmental science spatial representativeness of measurements is a general problem. Often ground-based measurements can be commenced only at the expense of either scale or resolution. Airborne platforms have been shown to overcome this problem. However typical research aircraft are expensive to operate or not even applicable, e.g. in remote areas. Unmanned aerial vehicles do not yet allow a comprehensive sensor package due to payload restrictions. Here the Weight-Shift Microlight Aircraft (WSMA) can provide an alternative. After successfully applying a WSMA to aerial imagery, aerosol and radiation transfer studies, the feasibility of Eddy Covariance (EC) flux measurements in the Atmospheric Boundary Layer (ABL) was explored. Careful calibration and validation was followed by application of the WSMA to comprehensive ABL soundings over the grassland of the Xilin River Catchment (XRC) in Inner Mongolia, China. The XRC is subject to vast human activity, which influence to capture was objective of measurements from June to August 2009. Simultaneously to the WSMA soundings, half-hourly tower EC fluxes were measured at 3 control sites, two of them non-grazed (C4 dominated Leymus, C3 dominated Stipa) and one heavily grazed (3 sheep unit ha−1 y−1 , HG). The idea of this setup was to a) validate the spatial representativity of process-based regional flux simulation and b) allow for scenario study of advancing grassland degradation. WSMA soundings took place around sun apex, and followed multiple repetitions of 2 to 80 km long line transects, organized in vertical stacks. Operational results at lowest flight level (50 m, AC50) averaged to fluxes of sensible heat QH = -177±78 Wm−2 , latent heat QE = -78±40 Wm−2 and carbon dioxide QC = 0.02±0.2 mg CO2 m−2 s−1 throughout the campaign. At a radiation budget QS∗ = -412±86 Wm−2 , which was 16 % lower than the control sites, the energy balance from AC50 measurements was closed to 72±18 % on average. AC50 measured QH was found comparable in magnitude to the HG control site, whereas Leymus and Stipa sites were 30 % higher on average. The magnitude of QE was comparable to the Leymus site, QE from Stipa and HG were ≥35 % higher on average. AC50, Stipa and HG measurements indicate marginal CO2 release / uptake, only Leymus displayed notable CO2 assimilation (-0.07±0.3 mg CO2 m−2 s−1 ). The chronology of AC50 QH , QE , QC measurements throughout the campaign correlated best to Stipa, Stipa / HG and Leymus site, respectively. Ceilometer backscatter and radiosonde data allowed to determine the ABL height (1860±680 m) and to estimate the average QH VFG throughout the ABL (-0.12±0.08 Wm−3 campaign average). Stacked patterns however show that the QH VFG throughout the surface layer was significantly enhanced and more variable with -0.19±0.38 Wm−3 , indicating possible development of internal boundary layers. Consideration of stacked pattern VFGs during post-processing should improve comparability to control sites and the closure of energy balance. This study shows that the WSMA, which can be easily shipped to and operated from remote places, provides a suitable tool to close the gap between local and spatial measurements.

Regional energy and CO2 exchange over transitional grassland of Inner Mongolia – a weight-shift microlight aircraft study. S. Metzger1, 2, 3, W. Junkermann1, L. Wang2, M. Mauder1, K. Butterbach-Bahl1, X.H. Zheng2, H.P. Schmid1, and T. Foken3 (1) Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Garmisch-Partenkirchen, Germany (2) Chinese Academy of Sciences, Institute of Atmospheric Physics, Beijing, China (3) Bayreuth University, Department of Micrometeorology, Bayreuth, Germany

KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association

www.kit.edu

Motivation Bridging scales: regional measurements Fixed wing aircraft: wide range, but expensive Unmanned aircraft: flexible, but limited payload Alternative? Mengelkamp et al. (2006)

© Agriculture and Agri-Food Canada

2

© British Antartic Survey

Turbulent fluxes from weight-shift microlight aircraft over transitional grassland of Inner Mongolia Stefan Metzger

Institute for Meteorology and Climate Research Atmospheric Environmental Research Division

Weight-shift microlight aircraft Easy transport and certification Existing sensor package Surface imagery Aerosols and radiation

Eddy Covariance Fluxes?

Wind measurement sophisticated Trike has rotational freedom

3



Weight-shift microlight operation

4



Setup for Eddy Covariance measurement 5 hole wind probe true airspeed, flow angles

Inertial navigation system groundspeed, attitude angles

50 μm Ni-Cr thermocouple air intrinsic temperature

Infrared gas analyzer H2O, CO2 concentration

Date acquistation at 10 Hz spatial resolution ~ 2.6 m

5



Fast 3d wind: in situ comparison

Ground truth: Sonic Cup and vane SODAR

German Weather Service Lindenberg, meaasurement field ‘Falkenberg‘

6



3d wind: in situ comparison

Ground truth: Sonic Cup and vane SODAR

20 data couples RMSD < 0.4 ms-1 German Weather Service Lindenberg, meaasurement field ‘Falkenberg‘

7



Application: Energy and CO2 fluxes in grassland

Distribution 6% 3% 4%

10% 4%

Aircraft: background fluxes Leymus: ungrazed C4 Stipa: ungrazed C3 Overgrazed: 3 sheep/ha

73% 8



How do blended aircraft fluxes compare to ‘pure’ tower fluxes? Sensible heat flux H [Wm-2]

Net radiation -Qs* [Wm-2] 700 600 500 400 300 200 100 0 -100 -200 -300 -400

700 600 500 400 300 200 100 0 -100 -200 -300 -400

Aircraft 16 % lower

CO2 flux [µg CO2 m-2s-1]

Latent heat flux LE [Wm-2] 700 600 500 400 300 200 100 0 -100 -200 -300 -400

700 600 500 400 300 200 100 0 -100 -200 -300 -400

Aircraft

9

Leymus C4

Stipa C3

Overgrazed


Only Leymus C4 significant uptake

Aircraft

Leymus C4

Stipa C3

Overgrazed


What is the spatial resolution of aircraft measurements? flight altitude 50 m above ground 2 km flight legs downwind of 400 x 400 m Stipa C3

H [Wm-2]

Stipa C3 flux signal resolved during stationary condition

DIR Turbulent fluxes from weight-shift microlight aircraft over transitional grassland of Inner Mongolia 10 Stefan Metzger


Flux disaggregation Measured flux is linear combination of surface feature contributions

solve system of N equations for M regressors (Chen et al., 1999): Mengelkamp et al. (2006)

N: number of flux samples M: number of surface feature classes Fn: measured flux (regressand) Cnm: source weight Fm: surface feature flux (regressor) Turbulent fluxes from weight-shift microlight aircraft over transitional grassland of Inner Mongolia 11 Stefan Metzger


Flux disaggregation Source area of fluxes 2 km segments, N > 20 flux samples per flight Footprint model (Kormann and Meixner 2001)

solve system of N equations for M regressors (Chen et al., 1999): Mengelkamp et al. (2006)

N: number of flux samples M: number of surface feature classes Fn: measured flux (regressand) Cnm: source weight Fm: surface feature flux (regressor) Turbulent fluxes from weight-shift microlight aircraft over transitional grassland of Inner Mongolia 12 Stefan Metzger


‘Tile‘ fluxes for flight on 2009-06-25 Sensible heat flux H [Wm-2] 500 400 300 200 100 0 -100

Latent heat flux LE [Wm-2]

UTM Northing

-200

500

-300

400

-400 dunes

300

marsh

steppe

arable

200 100 0 -100

CO2 flux [µg CO2 m-2s-1]

-200

-300 500 Only for steppe well determined. -400 400

H & LE:

R2

300

> 0.8, p200< 0.001

dunes

marsh

steppe

arable

100 0 -100 -200 UTM Easting -300 -400 dunes

marsh

Turbulent fluxes from weight-shift microlight aircraft over transitional grassland of Inner Mongolia 13 Stefan Metzger

steppe

arable


Weight-shift microlight as comprehensive environmental research aircraft Accurate turbulence measurement 3d wind RMSD < 0.4 ms-1 Sensible and latent heat RMSD < 15 %

Application in remote areas possible Convenient transport, certification and start / landing Comprehensive sensor package

Flux disaggregation must be improved to allow for regionalization Can solely land use explain flux variability? Footprint model sufficiently reliable? Can wavelet covariance aid by increasing sample size?



Regional energy and CO2 exchange over transitional grassland of Inner Mongolia – a weight-shift microlight aircraft study. S. Metzger1, 2, 3, W. Junkermann1, L. Wang2, M. Mauder1, K. Butterbach-Bahl1, X.H. Zheng2, H.P. Schmid1, and T. Foken3 (1) Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Garmisch-Partenkirchen, Germany (2) Chinese Academy of Sciences, Institute of Atmospheric Physics, Beijing, China (3) Bayreuth University, Department of Micrometeorology, Bayreuth, Germany

KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association

www.kit.edu

3d wind: tunnel validation Specially designed 5 hole wind probe Objectives applicability of flow angle computation accuracy in the operational range

Performance in flow angle range ±17.5°: Flow angles: RMSD = 0.4°, R2 = 0.99 Dynamic pressure: RMSD = 0.4 kPa, R2 > 0.99



3d wind: upwash correction upwash scales with lift correlation COR(w,TAS): 0.79 → -0.11 COR(w,pch): -0.78 → 0.17

accuracy sd(w) / sd(uz): 3.8 → 2.7 % RMSD: 0.17 → 0.13 ms-1



Sensible heat flux: ground truth comparison 1.00

9

0.80 WSMA leg LAS WSMA leg EC LAS EC 3 m EC 50 m EC 90 m

z / zi

0.60

0.40

0.20

0.00 0.00

0.20

0.40

0.60

0.80

1.00

QH / QH0

2

propagation of wind measurement uncertainties 4.3% for leg las (4.7 km) 3.9% for leg 2 (20 km)



The MAGIM research group Work topic part of DFG research group “MAtter fluxes of Grassland in Inner Mongolia as influenced by stocking rate“: Observing effects of increased animal based husbandry... …on matter fluxes… gaseous → climate effective trace gases; particles → sand storm; water → erosion, pollution; → research network of 11 German / Chines partner institutions.

...in semiarid grasslands.



Application: energy and CO2 fluxes in grasslands

D

on i t a d a r eg

ss e c o r p

9.0 sheep/ha


1.5 sheep/ha


Internal boundary layers? Ceilometer ABL (1860±680 m) QH flux gradient 0.12 Wm-3 stacked patterns 0.19 Wm-3

