[ncl-talk] Using bootstrap resampling

[Andrew Kren - NOAA Affiliate]

Dear ncl-talk,

I'm trying to determine whether hurricane forecasts (track, wind, and
intensity errors) are statistically different from each other given two
model experiments in which one is a control and second contains added
observations. The idea is to examine what impact the observations have on
hurricane track.

A number of forecasts are included in the analysis to where the arrays are
a function of (storm name, forecast cycle, and forecast hour). I used the
test to determine if the means were significantly different but I'm
wondering if using bootstrap reampling is a more robust measure (
https://www.ncl.ucar.edu/Document/Functions/Bootstrap/bootstrap_diff.shtml)?

I have not used this function before however I've looked over the examples,
specifically this one (
https://www.ncl.ucar.edu/Applications/Scripts/bootstrap_diff_1.ncl) but it
only includes 1-dimensional data. If I want to use bootstrap on my data,
would nDim be (/0,1/) in order to get results as function of forecast hour?

Thanks much!

-- 
Andrew Kren
Research Scientist I, Global Observing Systems Analysis (GOSA) Group
NOAA ESRL Global Systems Division (Rm 3C515)
325 Broadway, Boulder, CO 80305
(303) 497-5418
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