Open AccessThe “Shukla–Gutzler” Method for Estimating Potential Seasonal Predictability
Author(s) -
Timothy DelSole,
Xinlong Feng
Publication year - 2013
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/mwr-d-12-00007.1
Subject(s) - predictability , reliability (semiconductor) , autocorrelation , scale (ratio) , econometrics , computer science , monte carlo method , compromise , statistics , environmental science , mathematics , social science , power (physics) , physics , quantum mechanics , sociology
This paper reexamines a procedure proposed by Shukla and Gutzler for estimating potential seasonal predictability. Certain subtle and unverified assumptions required for the method to work are clarified, and Monte Carlo experiments are used to demonstrate that these assumptions are adequate even for autocorrelated processes in typical applications, provided the effective time scale T0 of the stochastic process is known. This paper highlights the fact that the time scale T0 is difficult to estimate reliably (as noted in other papers) and can be biased by an order of magnitude. This bias can seriously compromise the reliability of the Shukla–Gutzler method.