Browsing by Author "Ward, Helen C."

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On the exchange of sensible and latent heat between the atmosphere and melting snow
(2018-04) Stoy, Paul C.; Peitzsch, Erich H.; Wood, David J. A.; Rottinghaus, Daniel; Wohlfahrt, Georg; Goulden, Michael; Ward, Helen C.
The snow energy balance is difficult to measure during the snowmelt period, yet critical for predictions of water yield in regions characterized by snow cover. Robust simplifications of the snowmelt energy balance can aid our understanding of water resources in a changing climate. Research to date has demonstrated that the net turbulent flux (FT) between a melting snowpack and the atmosphere is negligible if the sum of atmospheric vapor pressure (ea) and temperature (Ta) equals a constant, but it is unclear how frequently this situation holds across different sites. Here, we quantified the contribution of FT to the snowpack energy balance during 59 snowmelt periods across 11 sites in the FLUXNET2015 database with a detailed analysis of snowmelt in subarctic tundra near Abisko, Sweden. At the Abisko site we investigated the frequency of occurrences during which sensible heat flux (H) and latent heat flux (λE) are of (approximately) equal but opposite sign, and if the sum of these terms, FT, is therefore negligible during the snowmelt period. H approximately equaled -λE for less than 50% of the melt period and FT was infrequently a trivial term in the snowmelt energy balance at Abisko. The reason is that the relationship between observed ea and Ta is roughly orthogonal to the “line of equality” at which H equals -λE as warmer Ta during the melt period usually resulted in greater ea. This relationship holds both within melt periods at individual sites and across different sites in the FLUXNET2015 database, where FT comprised less than 20% of the energy available to melt snow, Qm, in 44% of the snowmelt periods studied here. FT/Qm was significantly related to the mean ea during the melt period, but not mean Ta, and FT tended to be near 0 W m−2 when ea averaged ca. 0.5 kPa. FT may become an increasingly important term in the snowmelt energy balance across many global regions as warmer temperatures are projected to cause snow to melt more slowly and earlier in the year under conditions of lower net radiation (Rn). Eddy covariance research networks such as Ameriflux must improve their ability to observe cold-season processes to enhance our understanding of water resources and surface-atmosphere exchange in a changing climate.
Upscaling tundra CO2 exchange from chamber to eddy covariance tower
(2013-05) Stoy, Paul C.; Williams, Mathew; Evans, Jonathan G.; Prieto-Blanco, Ana; Disney, Mathias; Hill, Timothy C.; Ward, Helen C.; Wade, Thomas J.; Street, Lorna E.
Extrapolating biosphere-atmosphere CO2 flux observations to larger scales in space, part of the so-called “upscaling” problem, is a central challenge for surface-atmosphere exchange research. Upscaling CO2 flux in tundra is complicated by the pronounced spatial variability of vegetation cover. We demonstrate that a simple model based on chamber observations with a pan-Arctic parameterization accurately describes up to 75% of the observed temporal variability of eddy covariance—measured net ecosystem exchange (NEE) during the growing season in an Abisko, Sweden, subarctic tundra ecosystem, and differed from NEE observations by less than 4% for the month of June. These results contrast with previous studies that found a 60% discrepancy between upscaled chamber and eddy covariance NEE sums. Sampling an aircraft-measured normalized difference vegetation index (NDVI) map for leaf area index (L) estimates using a dynamic flux footprint model explained less of the variability of NEE across the late June to mid-September period, but resulted in a lower root mean squared error and better replicated large flux events. Findings suggest that ecosystem structure via L is a critical input for modeling CO2 flux in tundra during the growing season. Future research should focus on quantifying microclimate, namely photosynthetically active radiation and air temperature, as well as ecosystem structure via L, to accurately model growing season tundra CO2 flux at chamber and plot scales.