Forecast Error Correction using Dynamic Data Assimilation
This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)—an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known
- PDF / 7,613,065 Bytes
- 278 Pages / 439.43 x 683.15 pts Page_size
- 55 Downloads / 245 Views
Sivaramakrishnan Lakshmivarahan John M. Lewis Rafal Jabrzemski
Forecast Error Correction using Dynamic Data Assimilation
Springer Atmospheric Sciences
More information about this series at http://www.springer.com/series/10176
Sivaramakrishnan Lakshmivarahan John M. Lewis • Rafal Jabrzemski
Forecast Error Correction using Dynamic Data Assimilation
123
Sivaramakrishnan Lakshmivarahan School of Computer Science University of Oklahoma Norman, OK, USA Rafal Jabrzemski Oklahoma Climatological Survey University of Oklahoma Norman, OK, USA
John M. Lewis National Severe Storms Laboratory Norman, OK, USA Desert Research Institute Reno, NV, USA
ISSN 2194-5217 ISSN 2194-5225 (electronic) Springer Atmospheric Sciences ISBN 978-3-319-39995-9 ISBN 978-3-319-39997-3 (eBook) DOI 10.1007/978-3-319-39997-3 Library of Congress Control Number: 2016940961 © Springer International Publishing Switzerland 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Yoshikazu Sasaki (1927–2015), Father of Variational Data Assimilation in Meteorology
Preface
In this book, we focus on deterministic forecasting based on governing dynamical equations (typically in the form of differential equations). These equations require specification of a control vector for their solution (initial conditions, boundary conditions, physical and/or empirical parameters). Defining forecast error is central to our study as the book title implies. An all-inclusive definition of forecast error is difficult to formulate. Therefore, we find it best to define this error categorically: (1) error due to incorrectly specified terms in the governing equations (or the absence of important terms in these equations), (2) inexact numerical approximations to the analytic form of the dynamical equations including artificial amplification/damping of solutions in the numerical
Data Loading...