Sensitivity of Latent Heat Flux from PILPS Land-Surface Schemes to Perturbations of Surface Air Temperature

Abstract

In the PILPS Phase 2a experiment, 23 land-surface schemes were compared in an off-line control experiment using observed meteorological data from Cabauw, the Netherlands. Two simple sensitivity experiments were also undertaken in which the observed surface air temperature was artificially increased or decreased by 2 K while all other factors remained as observed. On the annual timescale, all schemes show similar responses to these perturbations in latent, sensible heat flux, and other key variables. For the 2-K increase in temperature, surface temperatures and latent heat fluxes all increase while net radiation, sensible heat fluxes, and soil moistures all decrease. The results are reversed for a 2-K temperature decrease. The changes in sensible heat fluxes and, especially, the changes in the latent heat fluxes are not linearly related to the change of temperature. Theoretically, the nonlinear relationship between air temperature and the latent heat flux is evident and due to the convex relationship between air temperature and saturation vapor pressure. A simple test shows that, the effect of the change of air temperature on the atmospheric stratification aside, this nonlinear relationship is shown in the form that the increase of the latent heat flux for a 2-K temperature increase is larger than its decrease for a 2-K temperature decrease. However, the results from the Cabauw sensitivity experiments show that the increase of the latent heat flux in the ϩ2-K experiment is smaller than the decrease of the latent heat flux in the Ϫ2-K experiment (we refer to this as the asymmetry). The analysis in this paper shows that this inconsistency between the theoretical relationship and the Cabauw sensitivity experiments results (or the asymmetry) is due to (i) the involvement of the ␤ g formulation, which is a function of a series stress factors that limited the evaporation and whose values change in the Ϯ2-K experiments, leading to strong modifications of the latent heat flux; (ii) the change of the drag coefficient induced by the changes in stratification due to the imposed air temperature changes (Ϯ2 K) in parameterizations of latent heat flux common in current land-surface schemes. Among all stress factors involved in the ␤ g formulation, the soil moisture stress in the ϩ2-K experiment induced by the increased evaporation is the main factor that contributes to the asymmetry.

Description and Evaluation of the Characteristics of the NCAR High-Resolution Land Data Assimilation System

“…Important is that changes of HRLDAS latent heat and sensible heat flux are not linear with respect to the change of air temperature, consistent with the work of Qu et al (1998). For instance, decreasing air temperature in HRLDAS resulted in greater differences in surface fluxes and soil moisture than increasing air temperature, and similar results apply to other forcing variables.…”

“…Qu et al (1998) studied the sensitivity of latent heat flux to variations of surface air temperature, and Luo et al (2003) used two sets of forcing conditions (NCEP EDAS and station observations) in NLDAS experiments to investigate differences in NLDAS output caused by differences in these two sets of forcing conditions. Nevertheless, the LSM response of surface heat fluxes, soil moisture, and soil temperature to each of the forcing variables has not been systematically explored in the past.…”

Simulations of a Boreal Grassland Hydrology at Valdai, Russia: PILPS Phase 2(d)

“…Phase 2(a) focused on the partitioning between sensible and latent heat fluxes for a grassland site at Cabauw, Netherlands (Chen et al 1997), and the response of simulated heat fluxes to changes in air temperature (Qu et al 1998). The analysis revealed that, for the Cabauw site, consideration of the stomatal control and soil-moisture stress formulations among the LSSs was crucial to the interpretation of the results.…”

Adjoint retrieval of prognostic land surface model variables for an NWP model: Assimilation of ground surface temperature

“…In the case of the API method, much tuning of the weighting parameter is usually needed for each location, while the lack of direct observations may prevent effective tuning at most locations. For the LDAS approach that involves extended model runs, the final analyses depend on the skill/quality of the land model [8,9] and also on model forcing errors.…”