TITLE:
A Diagnostic Approach towards the Causes of Energy Balance Closure Problem
AUTHORS:
Ali Varmaghani, William E. Eichinger, John H. Prueger
KEYWORDS:
Energy Balance Closure, Corn, Soybeans, Prairie, A-Posteriori Analysis
JOURNAL NAME:
Open Journal of Modern Hydrology,
Vol.6 No.2,
April
29,
2016
ABSTRACT: Hydrometeorological models are often evaluated and optimized on the basis of micrometeorological measurements. However, it has been known for more than three decades that surface measurements of sensible and latent heat energy (LE) are systematically underestimated. We studied this problem using six years of eddy-correlation measurements for four fields (corn, soybean, and prairie) in central Iowa, USA. We recorded major components of the energy equation (i.e. net radiation, sensible heat flux, LE, and soil heat flux, photosynthesis), and indirectly estimated most of the minor components of energy balance (namely storage in the soil, canopy and air). Storage in the canopy was related to leaf area index (LAI) acquired from Moderate Resolution Imaging Spectrometer (MODIS). In this paper, a diagnostic approach is investigated where systematic error is identified first. Three dimensional (3D) plots of the residual of energy equation vs. potential variables indicated the imbalance was largest mainly during the cold non-growing season when the soil was dry. Correlations between energy balance residual (EBR) and energy components showed that soil storage was not precisely estimated. Finally, an a-posteriori analysis (constrained linear multiple regression (CMLR)) was conducted to quantify the contribution of major/minor components of the energy equation towards EBR. The result highlights that the contribution of pertinent components of energy to EBR is mainly controlled by prevailing monthly hydrometeorological conditions; however, precise quantification of causes of imbalance is site-specific. A comparison between the a-posteriori analysis technique and the Bowen-ratio method demonstrates that the Bowen-ratio basically presumes a higher level of underestimation in LE. The results obtained in this study suggest that a-posteriori analysis may offer a superior methodology to correct measured eddy-correlation measurements. Furthermore, the overall trends in the correction of LE measurements suggest that there is a potential for rough monthly corrections of LE, irrespective of the type of crop.