Observed Atmospheric and Surface Variability on Heterogeneous Terrain at the Hectometer Scale and Related Advective Transports

Abstract

The values of the atmospheric variables follow from mass, momentum, and energy conservation equations. These equations involve gradients which, in heterogeneous terrain, lead to a connection of the values at one point to the values in their nearby surroundings, due to turbulence mixing or advective local transports. In this work the observed variability of the air and soil variables is analyzed for a 1‐km2 surface in a semirural area for a number of weather stations separated typically 150 m. Data show a large variability at the hectometer scale, with several degrees of difference in temperature sustained in time between neighboring points. While in the daytime turbulence contributes to keep the differences moderate, in weak wind nights the spatial variability increases significantly. The variability of soil variables can be large depending on the soil moisture and the vegetation cover and is less sensitive to the diurnal cycle. The inspection of the vertical gradients of temperature and humidity reveals that their sign and intensity, and consequently the corresponding sensible and latent heat fluxes, differ depending on the measuring point. The thermal advection is obtained from the hectometer‐scale network, which is comparable in magnitude to the turbulent fluxes and to the imbalance of the surface energy budget for clear and calm nights. During the day, the advection term may explain part of the energy budget imbalance, particularly when it is computed on a 30‐min time scale. A similar method is applied to the water vapor, finding that in the very dry conditions of the experiment, moisture advection is significant and with values comparable to the evapotranspiration.

Seasonal and Diurnal Cycles of Surface Boundary Layer and Energy Balance in the Central Andes of Perú, Mantaro Valley

“…According to the results presented in Section 3.4, the LST estimated using the LW irradiance components was found to be associated to uncertainties in the range of 2-3 • C [16] mainly because of the sensitivity of the long-wave radiation sensor and the uncertainty of the emissivity. In winter months, at night hours, the T2-LST had positive values between 0 and 1 • C, which are small compared to the uncertainty of LST, indicating the presence of slightly stable stratification of the surface boundary layer as average condition for the Mantaro Valley.…”

“…According to the results presented in Section 4.8, the most important difference between the aerodynamic method and the Bowen-ratio energy-balance method to estimate the turbulent energy fluxes is that the latter presumes a perfect balance between the traditional energy-balance elements while the former allows the existence of imbalance terms because it does not assume a perfect balance. However, it should be noted that both are approximate methods, and a better estimation of turbulent energy fluxes (Q H and Q E ) is by using an eddy covariance equipment, as verified by several studies [10,15,16,18,57]. Despite this, as the first approximation, the imbalance term in Equation (14) was estimated by using the turbulent energy-balance fluxes using the aerodynamic method.…”

“…This assumption could generate important uncertainties [18,44]. The Imb term is an unavoidable part of the experimentally determined surface energy budget, and it is usually between 10-15% in wide homogeneous conditions (as during the EBEX campaign, [45]) increasing as the terrain becomes more heterogeneous (as for LITFASS-2003 [46]) or topographically complex to 20-35% [15,16]. For both methods (aerodynamic and Bowen ratio), we used differences of wind, temperature and moisture at six levels of height, taking differences between measurements of the sensors located at highest levels (6 m, 12 m, 18 m, 24 m and 29 m) and the lowest level (2 m) of the gradient tower ( Figure 2).…”

“…Next, the imbalance increased up to reach positive values with the minimum close to zero (July) and the maximum close to +50 W m −2 (October). Apart from the instrumental errors and the errors associated with the methods to estimate turbulent energy fluxes, these values for the imbalance can be seen due to the long-lasting terrain heterogeneities on the hectometer (100 m) scale [15,16]. The surface on which the sensors measured the meteorological variables is a natural vegetation canopy that it is not irrigated at any time of the year.…”

“…Several recent studies have shown the heterogeneity of the surface terrain at the hectometer scale can facilitate transport of energy, mass, and momentum due to turbulent mixing or advective local transports [15,16]. The lack of energy-balance closure typically found to be in the range of 10% to 35% [17] and mostly related to instrumental uncertainties, lateral contributions induced by heterogeneities of surface terrain, and some missing sources or sinks [18].…”