• DocumentCode
    69408
  • Title

    Land Surface Observation, Modeling and Data Assimilation [Book Review]

  • Author

    Notarnicola, Claudia

  • Author_Institution
    EURAC-Institute for Applied Remote Sensing, Bolzano, 39100, Italy
  • Volume
    2
  • Issue
    1
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    34
  • Lastpage
    37
  • 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.
  • Keywords
    Atmospheric modeling; Book reviews; Data assimilation; Data models; Kalman filters; Land surface; Modeling; Remote sensing; Soil moisture;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    2168-6831
  • Type

    jour

  • DOI
    10.1109/MGRS.2014.2304631
  • Filename
    6784454