Recent micrometeorological studies of sensible heat flux in the plant-atmosphere system

For many years scientists working in fields related to micrometeorology have used the “Eddy Covariance (EC)” technique to study the transfer of water vapour, carbon dioxide and other greenhouse gases between plants, soils, bodies of water and the atmosphere at the boundary layer. This complex statistical technique uses high frequency measurements of the movement of air in the three dimensions along with the analysis of an air sample taken from the same position at the same time to determine the net exchange, or flux, of carbon dioxide, water vapour and sensible heat. Monitoring stations are typically installed above a canopy, field of crop or grassland, where some of the prerequisites of meaningful readings such as homogeneity of terrain can be attained. Acquisition and maintenance of the instrumentation required are expensive. Therefore, alternative methods are of interest and, if proven reliable, they may also be implemented to overcome routinely problems in direct measurements obtained by EC, such as gap filling. On the basis of recent literature, this paper reports the results of experiments carried out to evaluate the reliability of two alternative methods based on surface renewal analysis to estimate sensible heat flux.The study was carried out under the auspices of the projects: “Innovations and tools for adapting agriculture to climatic change (ISAACC)” grant no. 594/2011 of the Sicilian Region and “Assessment of mass and energy fluxes for the irrigation management of Mediterranean tree crops (PRIN 2008)” grant no. 2008CR84NF by Italian Ministry of Research and University (M.I.U.R.)

Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land‐surface temperature observations

Equations based on surface renewal (SR) analysis to estimate the sensible heat flux (H) require as input the mean ramp amplitude and period observed in the ramp‐like pattern of the air temperature measured at high frequency. A SR‐based method to estimate sensible heat flux (HSR‐LST) requiring only low‐frequency measurements of the air temperature, horizontal mean wind speed, and land‐surface temperature as input was derived and tested under unstable conditions over a heterogeneous canopy (olive grove). HSR‐LST assumes that the mean ramp amplitude can be inferred from the difference between land‐surface temperature and mean air temperature through a linear relationship and that the ramp frequency is related to a wind shear scale characteristic of the canopy flow. The land‐surface temperature was retrieved by integrating in situ sensing measures of thermal infrared energy emitted by the surface. The performance of HSR‐LST was analyzed against flux tower measurements collected at two heights (close to and well above the canopy top). Crucial parameters involved in HSR‐LST, which define the above mentioned linear relationship, were explained using the canopy height and the land surface temperature observed at sunrise and sunset. Although the olive grove can behave as either an isothermal or anisothermal surface, HSR‐LST performed close to H measured using the eddy covariance and the Bowen ratio energy balance methods. Root mean square differences between HSR‐LST and measured H were of about 55 W m−2. Thus, by using multitemporal thermal acquisitions, HSR‐LST appears to bypass inconsistency between land surface temperature and the mean aerodynamic temperature. The one‐source bulk transfer formulation for estimating H performed reliable after calibration against the eddy covariance method. After calibration, the latter performed similar to the proposed SR‐LST method.This research was funded by project CGL2012‐37416‐C04‐01 and CGL2015‐65627‐C3‐1‐R (Ministerio de Ciencia y Innovación of Spain), CEI Iberus, 2014 (Proyecto financiado por el Ministerio de Educación en el marco del Programa Campus de Excelencia Internacional of Spain), and Ayuda para estancias en centros extranjeros (Ministerio de Educación, Cultura y Deporte of Spain)

Sensible heat and latent heat flux estimates in a tall and dense forest canopy under unstable conditions

A method to estimate the sensible heat flux (H) for unstable atmospheric condition requiring measurements taken in half-hourly basis as input and involving the land surface temperature (LST), HLST, was tested over a tall and dense aspen stand. The method avoids the need to estimate the zero-plane displacement and the roughness length for momentum. The net radiation (Rn) and the latent heat flux (λE) dominated the surface energy balance (SEB). Therefore, λE was estimated applying the residual method using HLST as input, λER-LST. The sum of H and λE determined with the eddy covariance (EC) method led to a surface energy imbalance of 20% Rn. Thus, the reference taken for the comparisons were determined forcing the SEB using the EC Bowen ratio (BREB method). For clear sky days, HLST performed close to HBREB. Therefore, it showed potential in the framework of remote sensing because the input requirements are similar to current methods widely used. For cloudy days, HLST scattered HBREB and nearly matched the accumulated sensible hear flux. Regardless of the time basis and cloudiness, λER-LST was close to λEBREB. For all the data, both HLST and λER-LST were not biased and showed, respectively, a mean absolute relative error of 24.5% and 12.5% and an index of agreement of 68.5% and 80%.This work was supported under project RTI2018-098693-B-C31 (Ministerio de Ciencia, Economia y Universidades of Spain). The data was freely downloadable at http://daac.ornl.gov/BOREAS/boreas.shtml (accessed on 28 December 2021). Key R & D Program of Jiangsu Province (BE2021340) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD-2018-87)