<em>T</em><sub>air</sub> (green) and 10 cm <em>T</em><sub>soil</sub> (yellow) over time at Daring Lake MT (2005) K A Luus R E J Kelly J C Lin E R Humphreys P M Lafleur W C Oechel 10.6084/m9.figshare.1011906.v1 https://iop.figshare.com/articles/figure/_em_T_em_sub_air_sub_green_and_10_cm_em_T_em_sub_soil_sub_yellow_over_time_at_Daring_Lake_MT_2005_/1011906 <p><strong>Figure 4.</strong> <em>T</em><sub>air</sub> (green) and 10 cm <em>T</em><sub>soil</sub> (yellow) over time at Daring Lake MT (2005).</p> <p><strong>Abstract</strong></p> <p>The Arctic net ecosystem exchange (NEE) of CO<sub>2</sub> between the land surface and the atmosphere is influenced by the timing of snow onset and melt. The objective of this study was to examine whether uncertainty in model estimates of NEE could be reduced by representing the influence of snow on NEE using remote sensing observations of snow cover area (SCA). Observations of NEE and time-lapse images of SCA were collected over four locations at a low Arctic site (Daring Lake, NWT) in May–June 2010. Analysis of these observations indicated that SCA influences NEE, and that good agreement exists between SCA derived from time-lapse images, Landsat and MODIS. MODIS SCA was therefore incorporated into the vegetation photosynthesis respiration model (VPRM). VPRM was calibrated using observations collected in 2005 at Daring Lake. Estimates of NEE were then generated over Daring Lake and Ivotuk, Alaska (2004–2007) using VPRM formulations with and without explicit representations of the influence of SCA on respiration and/or photosynthesis. Model performance was assessed by comparing VPRM output against unfilled eddy covariance observations from Daring Lake and Ivotuk (2004–2007). The uncertainty in VPRM estimates of NEE was reduced when respiration was estimated as a function of air temperature when SCA ≤ 50% and as a function of soil temperature when SCA > 50%.</p> 2013-09-11 00:00:00 Daring Lake SCA influences NEE nwt modis vegetation photosynthesis respiration model mt co vprm eddy covariance observations Environmental Science