Sensitivity of Land Surface Processes and Its Variation during Contrasting Seasons over India

Abstract

The study investigates the influence of near-surface atmospheric parameters on land surface processes at the land–atmosphere interface through the offline simulation of the 2D Noah Land Surface Model-based High-Resolution Land Data Assimilation System (HRLDAS). The HRLDAS is used to conduct sensitive experiments by introducing perturbation in the atmospheric parameters, and the experiments were conducted for the period 2011–2013 in India. In each sensitive experiment, a single parameter is perturbed at a time, keeping the rest of the forcing parameters unchanged, and the procedure is followed for all the forcing parameters. The results revealed that the downward longwave radiation and T2 are highly sensitive to land surface processes, while wind speed is the least sensitive. The land surface process sensitivity varies with soil moisture content. The annual mean soil moisture at the surface layer is increased (decreased) by 8% when long wave radiation is decreased (increased) by 20%. Similarly, the annual mean soil temperature increased (decreased) by 2.2 °C when T2 increased (decreased) by 1%. The latent heat flux is highly sensitive to longwave radiation over the wetter soil, while its sensitivity to rainfall is higher over the drier soil. This is attributed to evapotranspiration’s sensitivity to the preferred soil moisture state. Further, the land surface sensitivity varies with contrasting seasons. The sensitivity of soil moisture and latent heat flux is high in OND and JJA seasons, respectively, and are least sensitive in the MAM season. In contrast, the sensible heat flux is highly sensitive to solar radiation in the MAM season and comparatively less sensitive in the JJA season. The study suggests that the antecedent soil moisture state plays a critical role in modulating land surface process sensitivity, and, therefore, a realistic soil moisture state is important for land surface feedback processes.