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1 results

  • 5 - Automatic Differentiation

  • from Part II - Practical Tools
  • Seon Ki Park, Milija Zupanski, Colorado State University
  • Book:
    Principles of Data Assimilation
    Published online:
    22 September 2022
    Print publication:
    29 September 2022, pp 111-127

  • Summary

    Generating the adjoint model (ADJM) by hand is tedious, time-consuming, and error prone. In most practical applications of data assimilation these days, the derivative codes, including the ADJM, are generated by the automatic differentiation (AD) tools, which evaluate the exact derivative information of a function in terms of a program. Terminologies and methods in AD are introduced, including the practical exclusion of the forward and reverse modes of differentiation. Various AD tools based on two major AD approaches, source transformation and operator overloading, are compiled with their webpages.