Optimal multiscale Kalman filter for assimilation of near-surface soil moisture into land surface models

By L. M. Parada, Xu Liang. 2004

50 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/6e5d1ccd2d67cec15cb32568ac15696495464ab6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Xu Liang
2. B. Medlyn
3. I. C. Prentice
4. Ying Ping Wang

In Water Science and Technology

1. Xu Liang
2. B. Medlyn
3. I. C. Prentice
4. Ying Ping Wang

Citations in the corpus

• Reliable, robust and realistic: the three R's of next-generation land-surface modelling (2014, background): “Parada and Liang (2004) developed a new spatial data assimilation framework, an extension of the multiscale Kalman Smoother-based (MKS-based) framework (Chou et al., 1994; Fieguth et al., 1995; Luettgen and Willsky, 1995; Kumar, 1999).”