Abstract: Current attempts to measure short-term (<1 month) rainfall accumulations using spaceborne radiometers are characterized by large sampling errors associated with low observation frequencies for any single point on the globe ...

Abstract: A novel methodology is introduced for quantifying the added value of remotely sensed soil moisture products for global land surface modeling applications. The approach is based on the assimilation of soil moisture retrievals ...

Abstract: Using high-resolution (1 km) hydrologic modeling of the 575 000-km2 Red?Arkansas River basin, the impact of spatially aggregating soil moisture imagery up to the footprint scale (32?64 km) of spaceborne microwave radiometers ...

Abstract: riple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually independent methods. Several statistical assumptions ...

Abstract: ncertainties in precipitation forcing and prestorm soil moisture states represent important sources of error in streamflow predictions obtained from a hydrologic model. An earlier synthetic twin experiment has demonstrated ...

Abstract: Data assimilation approaches require some type of state forecast error covariance information in order to optimally merge model predictions with observations. The ensemble Kalman filter (EnKF) dynamically derives such ...

Abstract: t is well known that systematic differences exist between modeled and observed realizations of hydrological variables like soil moisture. Prior to data assimilation, these differences must be removed in order to obtain an ...

Abstract: Data assimilation (DA) techniques have been widely applied to assimilate satellite-based soil moisture (SM) measurements into hydrologic models to improve streamflow simulations. However, past studies have reached mixed ...