Land Surface Observation, Modeling And Data Assimilation, 1st Edition

  • Published By: World Scientific Publishing Company
  • ISBN-10: 9814472611
  • ISBN-13: 9789814472616
  • DDC: 550.285
  • Grade Level Range: College Freshman - College Senior
  • 492 Pages | eBook
  • Original Copyright 2013 | Published/Released January 2015
  • This publication's content originally published in print form: 2013

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This book is unique in its ambitious and comprehensive coverage of earth system land surface characterization, from observation and modeling to data assimilation, including recent developments in theory and techniques, and novel application cases. The contributing authors are active research scientists, and many of them are internationally known leading experts in their areas, ensuring that the text is authoritative.This book comprises four parts that are logically connected from data, modeling, data assimilation integrating data and models to applications. Land data assimilation is the key focus of the book, which encompasses both theoretical and applied aspects with various novel methodologies and applications to the water cycle, carbon cycle, crop monitoring, and yield estimation.Readers can benefit from a state-of-the-art presentation of the latest tools and their usage for understanding earth system processes. Discussions in the book present and stimulate new challenges and questions facing todays earth science and modeling communities

Table of Contents

Front Cover.
Halftitle Page.
Title Page.
Copyright Page.
1: Observation.
2: Remote Sensing Data Products for Land Surface Data Assimilation System Application.
3: Second-Generation Polar-Orbiting Meteorological Satellites of China: The Fengyun 3 Series and Its Applications in Global Monitoring.
4: NASA Satellite and Model Land Data Services: Data Access Tutorial*.
5: Modeling.
6: Land Surface Process Study and Modeling in Drylands and High-Elevation Regions.
7: Review of Parameterization and Parameter Estimation for Hydrologic Models.
8: Data Assimilation.
9: Assimilating Remote Sensing Data into Land Surface Models: Theory and Methods.
10: Estimating Model and Observation Error Covariance Information for Land Data Assimilation Systems.
11: Inflation Adjustment on Error Covariance Matrices for Ensemble Kalman Filter Assimilation.
12: A Review of Error Estimation in Land Data Assimilation Systems.
13: An Introduction to Multi-Scale Kalman Smoother-Based Framework and Its Application to Data Assimilation.
14: Application.
15: Overview of the North American Land Data Assimilation System (NLDAS).
16: Soil Moisture Data Assimilation for State Initialization of Seasonal Climate Prediction.
17: Assimilation of Remote Sensing Data and Crop Simulation Models for Agricultural Study: Recent Advances and Future Directions.
18: Simultaneous State-Parameter Estimation for Hydrologic Modeling Using Ensemble Kalman Filter.