Correcting airborne flux measurements for aircraft speed variation

1993 ◽  
Vol 66 (3) ◽  
pp. 237-245 ◽  
Author(s):  
Timothy L. Crawford ◽  
Robert T. McMillen ◽  
Ronald J. Dobosy ◽  
Ian MacPherson
Keyword(s):  
Speed Variation ◽  
Flux Measurements ◽  
Airborne Flux Measurements

scholarly journals Spatial resolution and regionalization of airborne flux measurements using environmental response functions

2012 ◽  
Vol 9 (11) ◽  
pp. 15937-16003 ◽  
Author(s):  
S. Metzger ◽  
W. Junkermann ◽  
M. Mauder ◽  
K. Butterbach-Bahl ◽  
B. Trancón y Widemann ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Boosted Regression Trees ◽  
Environmental Response ◽  
Catchment Scale ◽  
River Catchment ◽  
Flux Measurements ◽  
Xilin River Catchment ◽  
Airborne Flux Measurements

Abstract. The goal of this study is to characterize the sensible (H) and latent (LE) heat exchange for different land covers in the heterogeneous steppe landscape of the Xilin River Catchment, Inner Mongolia, China. Eddy-covariance flux measurements at 50–100 m above ground were conducted in July 2009 using a weight-shift microlight aircraft. Wavelet decomposition of the turbulence data enables a spatial discretization of 90 m of the flux measurements. For a total of 8446 flux observations during 12 flights, MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in each flux footprint are determined. Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical- (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River Catchment (&amp;approx; 3670 km2) are accurate to ≤ 18%. The predictions are then summarized for each land cover type, providing individual estimates of source strength (36 W m−2 < H < 364 W m−2, 46 W m−2 < LE < 425 W m−2) and spatial variability (11 W m−2 < σH < 169 W m−2, 14 W m−2 < σLE < 152 W m−2) to a precision of ≤ 5%. Lastly, ERF predictions of land cover specific Bowen ratios are compared between subsequent flights at different locations in the Xilin River Catchment. Agreement of the land cover specific Bowen ratios to within 12 ± 9% emphasizes the robustness of the presented approach. This study indicates the potential of ERFs for (i) extending airborne flux measurements to the catchment scale, (ii) assessing the spatial representativeness of long-term tower flux measurements, and (iii) designing, constraining and evaluating flux algorithms for remote sensing and numerical modelling applications.

Dis-aggregation of airborne flux measurements using footprint analysis

2010 ◽  
Vol 150 (7-8) ◽  
pp. 966-983 ◽  
Author(s):  
R.W.A. Hutjes ◽  
O.S. Vellinga ◽  
B. Gioli ◽  
F. Miglietta
Keyword(s):  
Flux Measurements ◽  
Footprint Analysis ◽  
Airborne Flux Measurements

scholarly journals Spatially explicit regionalization of airborne flux measurements using environmental response functions

2013 ◽  
Vol 10 (4) ◽  
pp. 2193-2217 ◽  
Author(s):  
S. Metzger ◽  
W. Junkermann ◽  
M. Mauder ◽  
K. Butterbach-Bahl ◽  
B. Trancón y Widemann ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Boosted Regression Trees ◽  
Environmental Response ◽  
Catchment Scale ◽  
River Catchment ◽  
Flux Measurements ◽  
Xilin River Catchment ◽  
Airborne Flux Measurements

Abstract. The goal of this study is to characterize the sensible (H) and latent (LE) heat exchange for different land covers in the heterogeneous steppe landscape of the Xilin River catchment, Inner Mongolia, China. Eddy-covariance flux measurements at 50–100 m above ground were conducted in July 2009 using a weight-shift microlight aircraft. Wavelet decomposition of the turbulence data enables a spatial discretization of 90 m of the flux measurements. For a total of 8446 flux observations during 12 flights, MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in each flux footprint are determined. Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River catchment (&amp;approx;3670 km2) are accurate to ≤18% (1 σ). The predictions are then summarized for each land cover type, providing individual estimates of source strength (36 W m−2 < H < 364 W m−2, 46 W m−2 < LE < 425 W m−2) and spatial variability (11 W m−2 < σH < 169 W m−2, 14 W m−2 < σLE < 152 W m−2) to a precision of ≤5%. Lastly, ERF predictions of land cover specific Bowen ratios are compared between subsequent flights at different locations in the Xilin River catchment. Agreement of the land cover specific Bowen ratios to within 12 &amp;pm; 9% emphasizes the robustness of the presented approach. This study indicates the potential of ERFs for (i) extending airborne flux measurements to the catchment scale, (ii) assessing the spatial representativeness of long-term tower flux measurements, and (iii) designing, constraining and evaluating flux algorithms for remote sensing and numerical modelling applications.

Airborne flux measurements of CO2, sensible, and latent heat over the Hudson Bay lowland

1994 ◽  
Vol 99 (D1) ◽  
pp. 1551 ◽  
Author(s):  
R. L. Desjardins ◽  
J. I. MacPherson ◽  
P. H. Schuepp ◽  
H. N. Hayhoe
Keyword(s):  
Latent Heat ◽  
Hudson Bay ◽  
Flux Measurements ◽  
Hudson Bay Lowland ◽  
Airborne Flux Measurements

Airborne flux measurements of trace species in an Arctic boundary layer

1992 ◽  
Vol 97 (D15) ◽  
pp. 16601 ◽  
Author(s):  
John A. Ritter ◽  
John D. W. Barrick ◽  
Glen W. Sachse ◽  
Gerald L. Gregory ◽  
Mary A. Woerner ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Arctic Boundary Layer ◽  
Trace Species ◽  
Flux Measurements ◽  
Airborne Flux Measurements

Errors in airborne flux measurements

1994 ◽  
Vol 99 (D7) ◽  
pp. 14519 ◽  
Author(s):  
Jakob Mann ◽  
Donald H. Lenschow
Keyword(s):  
Flux Measurements ◽  
Airborne Flux Measurements
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