Data Assimilation And Its Applications

Data Assimilation and its Applications

Data assimilation is a novel, versatile methodology for estimating atmospheric and oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation. This volume contains many original findings in data assimilation and its applications related to atmospheric, oceanic and environmental systems. This covers various data assimilation techniques with in Bayesian and non-Bayesian framework ranging from Least-Square, nudging, three dimensional variational (3DVAR), four-dimensional variational (4DVAR), Local Ensemble Kalman filter, Genetic algorithm etc. This also covers the applications to extreme weather event, hurricane, Asian summer monsoon, structure of the barrier layer in the equatorial Pacific ocean and identification of emission sources. This volume will be useful as a reading material in graduate level courses dealing with data assimilation and its application to meteorology, ocean and air quality. The scientific community at large especially younger scientists will find this book a useful addition to their personal and institutional libraries.

Applications of Data Assimilation and Inverse Problems in the Earth Sciences

Many contemporary problems within the Earth sciences are complex, and require an interdisciplinary approach. This book provides a comprehensive reference on data assimilation and inverse problems, as well as their applications across a broad range of geophysical disciplines. With contributions from world leading researchers, it covers basic knowledge about geophysical inversions and data assimilation and discusses a range of important research issues and applications in atmospheric and cryospheric sciences, hydrology, geochronology, geodesy, geodynamics, geomagnetism, gravity, near-Earth electron radiation, seismology, and volcanology. Highlighting the importance of research in data assimilation for understanding dynamical processes of the Earth and its space environment and for predictability, it summarizes relevant new advances in data assimilation and inverse problems related to different geophysical fields. Covering both theory and practical applications, it is an ideal reference for researchers and graduate students within the geosciences who are interested in inverse problems, data assimilation, predictability, and numerical methods.

Special Issue: Data Assimilation and Its Applications