Estimation of Turbulent Heat Fluxes via Assimilation of Air Temperature and Specific Humidity into an Atmospheric Boundary Layer Model

Abstract

A number of studies have used time series of air temperature and specific humidity observations to estimate turbulent heat fluxes. These studies require the specification of surface roughness lengths for heat and momentum (that are directly related to the neutral bulk heat transfer coefficient CHN) and/or ground heat flux, which are often unavailable. In this study, sequences of air temperature and specific humidity are assimilated into an atmospheric boundary layer model within a variational data assimilation (VDA) framework to estimate CHN, evaporative fraction (EF), turbulent heat fluxes, and atmospheric boundary layer (ABL) height, potential temperature, and humidity. The developed VDA approach needs neither the surface roughness parameterization (as it is optimized by the VDA approach) nor ground heat flux measurements. The VDA approach is tested over the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) site in the summers of 1987 and 1988. The results indicate that the estimated sensible and latent heat fluxes agree fairly well with the corresponding measurements. For FIFE 1987 (1988), the daily sensible and latent heat fluxes estimates have a root-mean-square error of 25.72 W m−2 (27.77 W m−2) and 53.63 W m−2 (48.22 W m−2), respectively. In addition, the ABL height, specific humidity, and potential temperature estimates from the VDA system are in good agreement with those inferred from the radiosondes both in terms of magnitude and diurnal trend.

LIDA: A Land Integrated Data Assimilation Framework for Mapping Land Surface Heat and Evaporative Fluxes by Assimilating Space‐Borne Soil Moisture and Land Surface Temperature

“…The key unknown parameters of this model are the dimensionless neutral bulk heat transfer coefficient, C HN (‐), and the soil and canopy evaporative fraction, EF s (‐) and EF c (‐), respectively. C HN accounts for the effect of the roughness length for momentum and sensible heat fluxes (Caparrini et al, 2003; Tajfar et al, 2020). EF s and EF c scale the partitioning of available energy between sensible and latent heat fluxes and are affected by soil moisture conditions and vegetation cover (Caparrini et al, 2004b; Lu et al, 2019).…”

Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations

“…Given the abovementioned shortcomings of the existing VDA approaches, Tajfar et al [81] developed a VDA approach that estimates H and LE by assimilating sequences of reference-level air temperature and specific humidity (i.e., state variables of the atmosphere) into an atmospheric boundary layer (ABL) model. The main unknowns of the Tajfar et al [81] VDA approach are the neutral bulk heat transfer coefficient (C HN ) (that scales the sum of H and LE) and evaporative fraction (EF) (that scales the partitioning of available energy between H and LE).…”

“…Given the abovementioned shortcomings of the existing VDA approaches, Tajfar et al [81] developed a VDA approach that estimates H and LE by assimilating sequences of reference-level air temperature and specific humidity (i.e., state variables of the atmosphere) into an atmospheric boundary layer (ABL) model. The main unknowns of the Tajfar et al [81] VDA approach are the neutral bulk heat transfer coefficient (C HN ) (that scales the sum of H and LE) and evaporative fraction (EF) (that scales the partitioning of available energy between H and LE). Tajfar et al [81] tested their VDA approach only at a grass-dominated sub-humid site in Kansas, and showed that sequences of the reference-level air temperature and specific humidity have implicit information for constraining C HN and EF, and retrieving turbulent heat fluxes.…”

“…The main unknowns of the Tajfar et al [81] VDA approach are the neutral bulk heat transfer coefficient (C HN ) (that scales the sum of H and LE) and evaporative fraction (EF) (that scales the partitioning of available energy between H and LE). Tajfar et al [81] tested their VDA approach only at a grass-dominated sub-humid site in Kansas, and showed that sequences of the reference-level air temperature and specific humidity have implicit information for constraining C HN and EF, and retrieving turbulent heat fluxes.…”

Estimating Turbulent Fluxes in the Tropical Andes

“…However, the eddy covariance method has some restrictions that limit its applicability: (i) it requires constant supervision and maintenance, (ii) measurements in complex terrain are challenging because of the theoretical assumptions to transform the high-frequency measurements to turbulent fluxes [5], and (iii) because of extensive data quality requisites, gaps are inevitable, particularly under low turbulence mixing conditions [6,7]. Because of these difficulties, efforts have been made to parameterise them based on more commonly measured variables [8][9][10][11][12][13] and to compare among different methods to estimate and measure these fluxes [14][15][16][17][18]. One of the most frequently used approaches is to follow the work of [19] and [20], which relates the average temperature, humidity, and wind speed profiles in the boundary layer to the turbulent fluxes.…”