The added value of forcing, surface parameter and land model to the high resolution soil moisture modeling in China

Soil moisture is a vital land surface variable that influences the terrestrial hydrothermal cycles, modulates the land-atmosphere interactions and provides important predictability for weather and climate forecasting. Numerous efforts have been made to investigate the contribution of meteorological forcings, land surface parameters and land models to the uncertainties or precision of soil moisture modeling through both complex statistical approaches and simple comparative land surface modeling experiments. However, previous research mainly focus on one or two factors and the influence of a specific factor is usually quantified by comparing two different datasets. It still unclear that how much added value the current high resolution forcings, surface parameters and land models have to the soil moisture modeling and whether the results depend on the choice of model, datasets and even study regions.

To address the above issue, we first performed a high resolution (6km) soil moisture modeling over China during 2012~2017 by using the newly developed Conjunctive Surface-Subsurface Process version 2 (CSSPv2) land model forced by high-resolution meteorological forcing and high-resolution soil hydraulic property data. The high-resolution simulation has good performance in representing the observed magnitudes and variations of the rootzone (0~1 m) soil moisture based on >1,500 soil moisture stations, and improves the Kling-Gupta efficiency by 33~118% from the current high-resolution global land reanalysis (e.g., ERA5-Land and GLDASv2.1) and remote sensing based products (e.g., ESA CCI and GLEAMv3.1). In order to quantify the contributions from forcings, parameters and CSSPv2 model, we repeated the simulation by using coarse resolution datasets and different models including three meteorological forcing datasets, two soil hydraulic property datasets and three land models. By comparing 48 sets of experiments, the model and soil parameter are found to contribute more than 50% of the improvements at national scale which indicates necessity of developing high resolution land models and model parameters. On the regional scale, however, the meteorological forcing is shown to has the largest added value over the northwestern and southwestern China while land model is most important for the improvement over southern and eastern China. Further works will analyze the specific physical process in CSSPv2 model that improve the soil moisture simulation which will shed light on the future land model development.