TITLE:
Detecting Climate Change Trend, Size, and Change Point Date on Annual Maximum Time Series Rainfall Data for Warri, Nigeria
AUTHORS:
Masi G. Sam, Ify L. Nwaogazie, Chiedozie Ikebude, Chigozie Dimgba, Diaa W. El-Hourani
KEYWORDS:
Climate Change, Annual Maximum Series, Statistical Test, Rainfall Trend and Size, Change Point Date
JOURNAL NAME:
Open Journal of Modern Hydrology,
Vol.13 No.3,
July
31,
2023
ABSTRACT: The study focused on the
detection of indicators of climate change in 24-hourly annual maximum
series (AMS) rainfall data collected for 36 years (1982-2017) for Warri
Township, using different statistical methods yielded a statistically
insignificant positive mild trend. The IMD and MCIMD downscaled model’s time series data respectively produced MK
statistics varying from 1.403 to 1.4729, and 1.403 to 1.463 which were less
than the critical Z-value of 1.96. Also, the slope magnitude obtained showed a
mild increasing trend in variation from 0.0189 to 0.3713, and 0.0175 to 0.5426,
with the rate of change in rainfall intensity at 24 hours duration as 0.4536 and
0.42 mm/hr.year (4.536 and 4.2 mm/decade) for the IMD and the MCIMD time series
data, respectively. The trend change point date occurred in the year 2000 from
the distribution-free CUSUM test with the trend maintaining a significant and
steady increase from 2010 to 2015. Thus, this study established the existence
of a trend, which is an indication of a changing climate, and satisfied the
condition for rainfall Non-stationary intensity-duration-frequency (NS-IDF)
modeling required for infrastructural design for combating flooding events.