Analysis of the energy balance closure over a FLUXNET boreal forest in Finland

Abstract

Abstract. The imbalance in the surface energy budget, when using eddy-covariance techniques to measure turbulent fluxes, is still an unresolved problem. Important progresses have been reported in recent years identifying potential reasons for this lack of energy balance closure. In this paper we focus on the data collected in a FLUXNET boreal forest site in Sodankylä, Finland. Using one month half-hourly data, an average Energy Balance Ratio (EBR) of 0.72 is obtained. The inclusion of the heat storage terms in the energy budget yields an improvement of about 6% in the total closure. The sensitivity of the energy balance closure to the turbulence intensity is analysed in terms of the friction velocity, and atmospheric stability/instability conditions. Significant better closure is obtained for high values of the friction velocity and unstable conditions. The mismatch in variable footprints for different fluxes is checked by analysing the dependence of the closure on wind direction. The inhomogeneities of the emplacement surrounding the flux tower induce a critical decrease in the EBR of up to 30% for specific wind directions. After filtering all unfavourable conditions, EBR=0.94. This is a reasonable good result for the energy balance closure. However there is still a 6% of the available energy unaccounted. Part of this remaining imbalance could be justified as the impossibility of the 30 min averaging time to capture the low frequency flux contributions, since the closure is improved by a 5% when the averaging time is expanded to 2 h.

Hurricane disturbance and recovery of energy balance, CO2 fluxes and canopy structure in a mangrove forest of the Florida Everglades

“…This degree of closure is within the range of values reported for FluxNet sites across 50-site years (Wilson et al, 2002) and boreal forests (Barr et al, 2006;Sanchez et al, 2010). For the mangrove forest, one potential cause of the surface energy imbalance includes the lateral transport of heat associated with high and low tides.…”

Analysing surface energy balance closure and partitioning over a semi-arid savanna FLUXNET site in Skukuza, Kruger National Park, South Africa

“…Zuo et al (2011) reported an improvement of 6 to 7 % when they included the soil heat storage in their calculation of EBR, at the Semi-Arid Climate and Environment Observatory of Lan-Zhou University (SACOL) site in semi-arid grassland over the Loess Plateau of China. The improvement of the EBR in the study in a FLUXNET boreal site in Finland by Sánchez et al (2010) was shown to be 3 % when the soil heat storage was included, which increased to 6 % when other storage terms (canopy air) were taken into account.…”

“…net radiation minus soil heat flux, is equal to the sum of the turbulent fluxes (Rn − G = LE + H); however, in most instances, the measured available energy is larger than the sum of the measured turbulent fluxes of sensible heat and latent heat. Extensive research on the issue of surface energy imbalance in EC observations has been done (Barr et al, 2012;Chen et al, 2009;Foken et al, 2010;Franssen et al, 2010;Mauder et al, 2007), and closure error (or imbalance) has been documented to be around 10-30 % (Wilson et al, 2002;von Randow et al, 2004;Sánchez et al, 2010).…”

Variations of Energy Fluxes and Ecosystem Evapotranspiration in a Young Secondary Dry Dipterocarp Forest in Western Thailand

“…Further investigations and comparison among other secondary forests are needed, especially on the relationship between site heterogeneity and lack of energy balance. The energy balance closure in this young secondary forest was relatively low (84-85%) when compared to that reported in boreal forests (94%) [22], and in evergreen broadleaf forests and savannas (91-94%) [32]. According to Stoy et al [32], lower closure (70-78%) can be found in short canopy ecosystems such as crop, deciduous forests, mixed forests, and wetland.…”

“…The soil heat flux at the surface (Gs f ) is calculated by Equation (5), and this component is modified by soil storage term (∆G) as shown in Equations (6) and (7) [21,22]. ∆Ts is the soil temperature change over the output time interval (t, in this case ∆Ts = 30 min); Cs is the heat capacity of moist soil and d is the energy stored in the layer above the heat flux plates (8 cm depth); θv is the soil water content on a volume basis (m 3 m −3 ); Cd is the specific heat of dry soil (840 J kg −1 K −1 ); Cw is the specific heat of water (4185.5 J kg −1 K −1 ); ρw is the density of water (1000 kg m −3 ); and ρb is the bulk density of soil as reported in a previous study (1.35 g cm −3 , [17]) for 0-10 cm depths.…”