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 today''s earth science and modeling communities.

Pt. 1. Observation. ch. 1. Remote sensing data products for land surface data assimilation system application / Yunjun Yao, Shunlin Liang and Tongren Xu -- ch. 2. Second-generation polar-orbiting meteorological satellites of China: the Fengyun 3 series and its applications in global monitoring / Peng Zhang -- ch. 3. NASA satellite and model land data services: data access tutorial / Suhung Shen, Gregory Leptoukh and Hongliang Fang -- pt. 2. Modeling. ch. 4. Land surface process study and modeling in drylands and high-elevation regions / Yingying Chen and Kun Yang -- ch. 5. Review of parameterization and parameter estimation for hydrologic models / Soroosh Sorooshian and Wei Chu -- pt. 3. Data assimilation. ch. 6. Assimilating remote sensing data into land surface models: theory and methods / Xin Li and Yulong Bai -- ch. 7. Estimating model and observation error covariance information for land data assimilation systems / Wade T. Crow -- ch. 8. Inflation adjustment on error covariance matrices for ensemble Kalman filter assimilation / Xiaogu Zheng ... [et al.[ -- ch. 9. A review of error estimation in land data assimilation systems / Yulong Bai, Xin Li and Qianlong Chai -- ch. 10. An introduction to multi-scale Kalman smoother-based framework and its application to data assimilation / Daniel E. Salas and Xu Liang -- pt. 4. Application. ch. 11. Overview of the North American Land data assimilation system (NLDAS) / Youlong Xia ... [et al.] -- ch. 12. Soil moisture data assimilation for state initialization of seasonal climate prediction / Wenge Ni-Meister -- ch. 13. Assimilation of remote sensing data and crop simulation models for agricultural study: recent advances and future directions / Hongliang Fang, Shunlin Liang and Gerrit Hoogenboom -- ch. 14. Simultaneous state-parameter estimation for hydrologic modeling using ensemble Kalman filter / Xianhong Xie

This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.

The continental hydrological cycle is one of the least understood components of the climate system. The understanding of the different processes involved is important in the fields of hydrology and meteorology.In this volume the main applications for continental hydrology are presented, including the characterization of the states of continental surfaces (water state, snow cover, etc.) using active and passive remote sensing, monitoring the Antarctic ice sheet and land water surface heights using radar altimetry, the characterization of redistributions of water masses using the GRACE mission, the potential of GNSS-R technology in hydrology, and remote sensing data assimilation in hydrological models.This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD) , engineers and scientists, specialists in remote sensing applied to hydrology. Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of Earth observation data. - Provides clear and concise descriptions of modern remote sensing methods - Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications - Provides chapters on physical principles, measurement, and data processing for each technique described - Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made

This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.

This volume presents peer-reviewed papers from the NATO Advanced Research Workshop on Atmospheric Boundary Layers held in April 2006. The papers are divided into thematic sessions: nature and theory of turbulent boundary layers; boundary-layer flows: modeling and applications to environmental security; nature, theory and modeling of boundary-layer flows; air flows within and above urban and other complex canopies: air-sea-ice interaction.

Data assimilation methods were largely developed for operational weather forecasting, but in recent years have been applied to an increasing range of earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observations and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation).

Water is essential to life for humans and their food crops, and for ecosystems. Effective water management requires tracking the inflow, outflow, quantity and quality of ground-water and surface water, much like balancing a bank account. Currently, networks of ground-based instruments measure these in individual locations, while airborne and satellite sensors measure them over larger areas. Recent technological innovations offer unprecedented possibilities to integrate space, air, and land observations to advance water science and guide management decisions. This book concludes that in order to realize the potential of integrated data, agencies, universities, and the private sector must work together to develop new kinds of sensors, test them in field studies, and help users to apply this information to real problems.

Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences

Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data assimilation systems in one place. It includes practical exercises for understanding theoretical formulation and presents some aspects of coding the theory with a toy problem. The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to the atmosphere, oceans, as well as the land surface and other geophysical situations. It offers a comprehensive presentation of the subject, from basic principles to advanced methods, such as Particle Filters and Markov-Chain Monte-Carlo methods. Additionally, Data Assimilation for the Geosciences: From Theory to Application covers the applications of data assimilation techniques in various disciplines of the geosciences, making the book useful to students, teachers, and research scientists. Includes practical exercises, enabling readers to apply concepts in a theoretical formulation Offers explanations for how to code certain parts of the theory Presents a step-by-step guide on how, and why, data assimilation works and can be used