Current models for seasonal climate prediction are limited due to poor initialization of the land surface soil moisture states. Passive microwave remote sensing provides quantitative information on soil moisture in a thin near-surface soil layer at large scale. This information can be integrated with a land surface process model through data assimilation to give better prediction of the near su...

Satellite remote sensing observations have the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from microwave remote sensing techniques are typically complex due to inherent difficulty in characterizing the interactions among land surface parameters that contribute to the retrieval process. Therefore, adequate physical mathe...

Three independent surface soil moisture datasets for the period 1979–87 are compared: 1) global retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), 2) global soil moisture derived from observed meteorological forcing using the NASA Catchment Land Surface Model, and 3) ground-based measurements in Eurasia and North America from the Global Soil Moisture Data Bank. Time-average ...

[1] Climate model prediction skill is currently limited in response to poor land surface soil moisture state initialization. However, initial soil moisture state prediction skill can potentially be enhanced by the assimilation of remotely sensed near-surface soil moisture data in off-line simulation. This study is one of the first to evaluate such potential using actual remote sensing data toge...

Ground penetrating radar (GPR) is an efficient method for soil moisture mapping at the field scale, bridging the scale gap between small-scale invasive sensors and large-scale remote sensing instruments. Nevertheless, commonly-used GPR approaches for soil moisture characterization suffer from several limitations and the determination of the uncertainties in GPR soil moisture sensing has been po...

[1] The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the ground resolution (typically >10 km) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from current and upcoming soil moisture satellite missions. Given typical levels of observed spatial variability in soil moisture fields, t...

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m(2)), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal controls on soil CO2 efflu...

Surface soil moisture is an important environment variable that is dominant in a variety of research and application areas. Acquiring spatiotemporal continuous soil moisture observations is therefore of great importance. Weather conditions can contaminate optical remote sensing observations on soil moisture, and the absence of remote sensors causes gaps in regional soil moisture observation tim...

Knowledge about the spatio-temporal variability of soil moisture is essential to understand and predict processes in climate science and hydrology. A significant body of literature exists on the characterization of the spatial variability and the rank stability (also called temporal stability) of absolute soil moisture. Yet previous studies were generally based on short-term measurement campaig...