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{ "item_title" : "Forecast Error Correction Using Dynamic Data Assimilation", "item_author" : [" Sivaramakrishnan Lakshmivarahan", "John M. Lewis", "Rafal Jabrzemski "], "item_description" : "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 four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/31/982/010/3319820109_b.jpg", "price_data" : { "retail_price" : "119.99", "online_price" : "119.99", "our_price" : "119.99", "club_price" : "119.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Forecast Error Correction Using Dynamic Data Assimilation|Sivaramakrishnan Lakshmivarahan

Forecast Error Correction Using Dynamic Data Assimilation

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Overview

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 four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation.

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Details

  • ISBN-13: 9783319820101
  • ISBN-10: 3319820109
  • Publisher: Springer
  • Publish Date: June 2018
  • Dimensions: 9.21 x 6.14 x 0.6 inches
  • Shipping Weight: 0.9 pounds
  • Page Count: 270

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