Land surface model (LSM) simulations forced by observed meteorological data provide
spatially continuous and temporally complete soil moisture estimates, but the influences of …

The Community Land Model version 4.0 (CLM4. 0) driven by the forcing data of Princeton
University was used to simulate soil moisture (SM) from 1961 to 2010 over China. The …

The spatial distribution of soil moisture, especially the temporal variation at seasonal and
interannual scales, is difficult for many land surface models (LSMs) to capture partly due to …

Evaluation of Reanalysis Soil Moisture Simulations Using Updated Chinese Soil Moisture
Observations in: Journal of Hydrometeorology Volume 6 Issue 2 (2005) Jump to Content …

Reliable soil moisture (SM) estimates are not only crucial for the climate variability but are
also significant for agricultural, ecological, climatic, and hydrometeorological predictions …

Soil moisture is a key variable in hydrological modelling, which could be estimated by land
surface modelling. However the previous studies have focused on evaluating these soil …

Soil moisture is an essential climate variable (ECV) of major importance for land–
atmosphere interactions and global hydrology. An appropriate representation of soil …

Land surface processes considerably influence the global weather and climate patterns
which makes its quantification significant to scientists, hydrologists as well as policymakers …

The quality of simulated soil hydrological variables (ie, soil moisture, evapotranspiration,
and runoff) is largely dependent on the accuracy of meteorological forcing data, especially …

High-quality gridded soil moisture products are essential for many Earth system science
applications, while the recent reanalysis and remote sensing soil moisture data are often …