Validation of Rainfall Reanalysis Data to Explore Changes in Oldeman Agricultural Climate Patterns Due to Variability of Surface Temperature Anomalies with Time Series Analysis Techniques (Case Study of Dumai City for 30 Years Period)

Abstract

Indonesia is a country with a population that still uses the agricultural sector as the highest livelihood. The Central Statistics Agency said 38.61% were in this sector. However, the issue of climate change caused by an increase in global temperature has begun to impact the agricultural sector in several regions. Therefore, this study aims to understand the effect of increasing surface temperature anomaly on the Oldeman climate pattern in Dumai City. The data used are in-situ observation rainfall data for 1981 -2010, rainfall reanalysis data for 1991 -2020, surface temperature anomaly data for 1991 -2020. The data validation methods used are spearman correlation and Kendall-tau methods. The approach to explore changes in the Oldeman climate pattern uses time series analysis techniques such as ACF, PACF, and moving average of 1 year lag-time with a period of 10 years. The rainfall data validation test result show that the average spatial correlation value is 0.86. It can be used to explore time-series climate data in 3 locations in Dumai. As a result, time series analysis found a positive trend in rainfall data significantly along with the temperature anomaly but the Oldeman's climate pattern analysis in Dumai is monitored as stable in type B1. Overall, it is concluded that the change in the surface temperature anomaly variability and trend as a manifestation of climate change in Dumai has not impacted in the Oldeman agricultural climate patterns.

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