CLIMATE VARIABILITY STUDY FOR ARID REGIONS

Abstract

Water is the primary source for all living species to thrive, and water scarcity has been a primary concern for biological species and plants in arid regions due to urban planning, population growth, poor water management, and overgrazing. The objective of this research was to study the climate variability in precipitation and temperature for an arid region. This research encompasses two distinct studies. The first study examined the impact of climate variability on precipitation in Phoenix. Precipitation data were acquired from NOAA from 1948 to 2023 and the study was broken down into three time scales: annually, seasonally, and monthly. The accumulated annual precipitation was used to classify specific years as very wet year, wet year, average year, dry year, and very dry year, corresponding to their rainfall depth. Annual precipitation showed stability in the trendline with some fluctuations over the 76-year period of study. In addition, the seasonal analysis showed more precipitation during the summer season more frequently than in other seasons. The monthly analysis showed that months within the non-monsoon season had the driest months as expected. February had the highest precipitation in very dry years and January had the highest precipitation in the very wet years. Also, the prediction of the accumulated yearly precipitation for the years 2030,2040, and 2050 is based on the correlation.

The second study was the impact of climate variability on temperature in an arid region. Temperature was obtained from NOAA for the period of 1948 to 2023. The years were classified based on the average annual temperature dataset as hot years, warm years, moderate years, cool years, and cold years. The average annual temperature showed an increase in the trendline. The results showed minor CV for the average annual temperature over the 76-year period. The seasonal temperature showed more variability during the winter season, with a CV of 5%, compared to other seasons. The monthly analysis showed that months within the winter season had more variability at a CV ranging from 4% to 6% than months in the summer season which were around 2%. In addition, the prediction for the average annual temperature for the years 2030,2040, and 2050. In conclusion, these two studies are comprehensive studies on climate variables applying historical data to gain a cognitive comprehension of climate weather behavior. This case study was conducted on arid regions that have high temperatures during summer and relatively low precipitation. These studies hold future awareness of the climate for more practical purposes in engineering. This will be an effective application for future water scarcity, urban planning, agriculture, and food supply.