Land Surface Observation, Modeling and Data Assimilation [Book Review

Abstract

This book is devoted to data assimilation methodologies. It covers a wide range of topics in 464 pages and 14 chapters including detailed descriptions of both methodologies and applications and is based on lecture notes from the Summer School and Workshop on Land Data Assimilation held in July 2010 at the Beijing Normal University, China. A variety of both applications and methods are treated. The book provides an overview of the methodologies used in data assimilation such as Ensemble Kalman filter and multi-scale Kalman Smoother-Based framework. Moreover, attention is devoted to open issues in particular the estimation of model and observation errors providing some approaches to solve the problem. The book is divided in four main parts. The first three parts focus on the main components in a data assimilation experiment that is remote sensed observations and data products, land surface modeling, and data assimilation techniques. The fourth part is dedicated to application in the domain of climate prediction, hydrology and agricultural monitoring.