An Analysis of Climate trends from
1995-2024 in selected cities of the Philippines
Julianni Kaye C. Jayoma, insert name of
members alphabetical,
Xavier University-Ateneo de Cagayan
Corrales Avenue, Cagayan de Oro City, Misamis
Oriental 9000. 20240031045@my.xu.edu.ph,
insert school email of members
Abstract - Climate variability and its
impacts have become an increasing concern
in the Philippines, a country highly
vulnerable to climate change. This study
analyzed meteorological data from three
major cities—Quezon City, Dumaguete City,
and Cagayan de Oro City—to assess climate
patterns and relationships. The objectives
were: (1) to determine climate trends over
time, (2) to compare climate variables
among the cities, and (3) to examine
relationships between temperature, rainfall,
humidity, and pressure. Data included mean
temperature, humidity, rainfall, rain days,
sunshine hours, and pressure. Statistical
tools employed were descriptive statistics,
linear regression, One-Way ANOVA with
Tukey Post-Hoc tests, Kruskal-Wallis tests,
and Pearson correlation. Results indicated
that most climate variables did not exhibit
significant trends over time, except for
pressure which significantly declined (p <
0.001). Significant differences were found
among the three cities for temperature,
humidity, sunshine hours, rainfall, and rain
days (p < 0.001), while pressure differences
were weaker. Correlation analysis revealed
negative relationships between rainfall and
both pressure (r = -0.421, p < 0.001) and
humidity (r = -0.337, p = 0.001), but no
significant correlation between temperature
and rainfall. These findings highlight both
the stability and variability of climate
factors in the Philippines and provide
valuable insights for local climate
monitoring and adaptation strategies.
Introduction
Climate is one of the most influential factors
shaping ecosystems, urban development,
and human well-being. In recent years, the
Philippines has faced growing challenges
linked to climate variability, including
extreme rainfall, flooding, and urban heat
stress (IPCC, 2021). Understanding how
climate behaves across regions is essential
for adaptation planning and environmental
management.
Quezon City, Dumaguete City, and Cagayan
de Oro City represent three distinct
geographical regions of the Philippines—
Luzon, Visayas, and Mindanao. Each
location experiences unique climatic
influences, making them suitable for
comparative analysis.
This study was guided by three objectives:
1. To determine climate trends over
time in Quezon City, Dumaguete
City, and Cagayan de Oro City.

One-Way ANOVA with Tukey
Post-Hoc
tests
to
identify
differences among the three cities.
2. To examine the differences in
climate variables among the three
cities.

Kruskal-Wallis tests as a nonparametric alternative to ANOVA
when variance assumptions were
questionable.

Pearson correlation to analyze the
relationships between selected pairs
of variables.
3. To determine the relationships
between selected climate variables,
specifically mean temperature and
rainfall, rainfall and pressure, and
rainfall and humidity.
The null hypotheses stated that there are no
significant climate trends, no significant
differences among the three cities, and no
significant relationships among the tested
climate variables.
By testing these hypotheses, the study
contributes to a deeper understanding of
climate dynamics in the Philippines.
Assumption Checks:

Normality was assumed but not
always fully met.

Homogeneity of variances was
partially met; thus, non-parametric
tests were used to confirm results.

Linearity and independence were
considered acceptable for regression
and correlation analyses.
Methodology
This study utilized a quantitative research
design based on secondary meteorological
data collected from Quezon City,
Dumaguete City, and Cagayan de Oro City.
The following variables were examined:
mean temperature, humidity, rainfall, rain
days, sunshine hours, and pressure.
Statistical Tools Used:

Descriptive statistics to summarize
data.

Linear regression to test climate
trends over time.
Results and Discussion
Objective 1: Climate Trends
Regression analyses revealed that
most climate variables (temperature,
humidity, rainfall, sunshine hours,
and rain days) showed no significant
trends (p > 0.05). Only atmospheric
pressure exhibited a statistically
significant negative trend (p <
0.001), suggesting a gradual decline
over time. This implies that while
general weather patterns have been
relatively stable in these cities,
atmospheric pressure shifts may
reflect broader regional or global
climate changes.
Objective 2: Differences Among
Cities
ANOVA and Kruskal-Wallis results
consistently indicated significant
differences in temperature, humidity,
rainfall, sunshine hours, and rain
days among the three cities (p <
0.001). Tukey Post-Hoc tests further
revealed which city pairs differed.
For example, Quezon City had
significantly lower humidity but
higher
rainfall
compared
to
Dumaguete and Cagayan de Oro.
Pressure differences were weaker,
with significance found only
between Dumaguete and Quezon (p
= 0.041). These findings confirm
distinct local climate patterns shaped
by geography and regional weather
systems.
Objective 3: Relationships Among
Climate
Variables
Pearson correlation analysis showed
that temperature and rainfall were
not significantly correlated (p =
0.466), indicating their relative
independence. However, rainfall was
negatively correlated with both
pressure (r = -0.421, p < 0.001) and
humidity (r = -0.337, p = 0.001).
This suggests that heavier rainfall
events are associated with lower
atmospheric pressure and reduced
humidity. Such interactions are
consistent with tropical meteorology,
where rainfall is often linked with
pressure drops during storms.
Conclusion
This study concludes that:
1. Climate variables across the three
cities are largely stable over time,
with the exception of a significant
decline in pressure.
2. The three cities differ significantly in
most climate variables, reflecting
distinct regional climate conditions.
3. Rainfall is significantly associated
with both pressure and humidity, but
not with temperature.
Recommendations

Future studies should use longer
datasets and incorporate time-series
models to confirm observed patterns.

Further research could explore socioeconomic impacts of these climate
differences,
particularly
on
agriculture, health, and disaster
preparedness.

Local governments may use these
findings to design targeted climate
adaptation and mitigation strategies.
References
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Contribution of Working Group I to
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K. Leitzell, E. Lonnoy, J. B. R.
Matthews, T. K. Maycock, T.
Waterfield, O. Yelekçi, R. Yu, & B.
Zhou, Eds.). Cambridge University
Press.
https://doi.org/10.1017/97810091578
96
Philippine Atmospheric, Geophysical and
Astronomical
Services
Administration. (2020). Climate data
and projections for the Philippines.
PAGASA.