Retrieval of Land Surface Model State Variables through Assimilating Screen Level Humidity and Temperature Measurements

Abstract

This study demonstrates successful variational retrieval of land surface states by assimilating screen level atmospheric measurements of specific humidity and air temperature. To this end, the land surface scheme is first validated against the Oklahoma Atmospheric Surface Layer Instrumentation System measurements with necessary refinements to the forward model implemented. The retrieval scheme involves a 1D land surface-atmosphere model, the corresponding adjoint codes, and a cost function that measures residuals between observed and modeled screen level atmospheric temperature and specific humidity. The retrieval scheme is robust when subjected to observational errors with magnitudes comparable to instrument accuracy and for initial guess errors larger than typical model forecast errors. Using varying assimilation window lengths centered on different periods of a day, the sampling strategy is assessed. The daytime observations are more informative compared to nocturnal observations. An assimilation window as narrow as four hours, if centered on local noon, contains comparable information to an expanded window covering the whole day. There exists an optimal assimilation window length resulting from the contest between degrading forecast accuracy and increasing information content. For an assimilation window less than two days, the "optimal" assimilation window length is inversely proportional to the data ingesting frequency.

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

“…In a departure with assimilating LST measurements, a number of studies showed that the screen-level air temperature and humidity measurements in addition to surface parameterization in itself contain useful information about soil moisture (Mahfouf 1991;Bouttier et al 1993a,b;Mahfouf et al 2000Mahfouf et al , 2009Douville et al 2000;Hess 2001;Drusch and Viterbo 2007;de Rosnay et al 2013;Ren and Xue 2016;de Lannoy et al 2016) and turbulent heat fluxes (Holtslag and Van Ulden 1983;Entekhabi 2001, 2003;Alapaty et al 2001;Balsamo et al 2007;Shang et al 2007;Salvucci and Gentine 2013;Rigden and Salvucci 2015;Gentine et al 2016;Lum et al 2017). These studies typically require specification of surface roughness for heat and momentum (that are directly related to the neutral bulk heat transfer coefficient C HN ) as well as ground heat flux to estimate the sensible and latent heat fluxes, which are mostly unavailable.…”

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

“…In a departure from the use of sequences of LST measurements, several studies showed that the reference-level air temperature and humidity measurements contain useful information about soil moisture [61][62][63][64][65][66][67][68][69][70][71] and turbulent heat fluxes [72][73][74][75][76][77][78][79][80]. However, these studies mostly require the specification of surface roughness lengths for heat and momentum as well as ground heat flux, which are often unavailable.…”