final_program_abstracts[1]

11 IMSC Session Program
New techniques and software package for detection and
adjustment of shifts in daily precipitation data series
Tuesday - Parallel Session 8
Xiaolan L. Wang 1,2 , Hanfeng Chen 3 , Yuehua Wu 2 , Yang Feng 1 and Qiang Pu 2
1
Climate Research Division, Science and Technology Branch, Environment Canada,
Toronto, Canada
2
Department of Mathematics and Statistics, York University, Toronto, Canada
3
Department of Mathematics and Statistics, Bowling Green State University, Bowling
Green, USA
This study integrates a Box-Cox power transformation procedure into a common
trend two-phase regression model based test (the PMFred algorithm) for detecting
changepoints, to make the test applicable to non-Gaussian data series, such as nonzero
daily precipitation amounts. The detection power aspects of the transformed
method (transPMFred) were assessed using Monte Carlo simulations, which show
that this new algorithm is much better than the corresponding untransformed method
for non-Gaussian data series. The transPMFred algorithm was also shown to be able
to detect three changepoints in a non-zero precipitation series recorded at a Canadian
station, with the detected changepoints being in good agreement with documented
times of changes.
A set of functions for implementing the transPMFred algorithm to detect
changepoints in non-zero daily precipitation amounts were developed and made
available online free of charge, along with a quantile matching (QM) algorithm for
adjusting shifts in non-zero daily precipitation series, which should work well in
absence of any discontinuity in the frequency of precipitation measured (i.e.,
frequency discontinuity) and should work well for continuous variables such as daily
temperature series.
However, frequency discontinuities are often inevitable, especially in the
measurement of small precipitation due to changes in the measuring precision etc.
Thus, it was recommended to use the transPMFred to test the series of daily
precipitation amounts that are larger than a threshold, using a set of different small
thresholds, and to use the PMFred algorithm to check the homogeneity of the series of
monthly or annual frequency of precipitation occurrence (or non-occurrence, i.e., zero
precipitation days) and of various small precipitations measured. These would help
gain some insight into the characteristics of discontinuity and attain better
adjustments. It was also noted that, when a frequency discontinuity is present,
adjustments derived from the measured daily precipitation amounts, regardless of how
they were derived, could make the data deviate more from the truth. In this case, one
must adjust for the frequency discontinuities before conducting any adjustment to the
measured precipitation amounts.
Abstracts 150