The Projections of Climate Change using Conformal Cubic Atmospheric Model (CCAM) in Bali - Indonesia

Abstract

Research on climate change was conducted in Bali, Indonesia, using the Conformal Cubic Atmospheric Model (CCAM), which works with the Representative Concentration Pathway (RCP) 4.5. The history data means average data from 1971 to 2000, climate projections with RCP4.5 scenario means average data from 2040 to 2069, and anomaly (climate change) is RCP4.5 minus history. The results represent the history of temperature between 22.5-27.5 0C and the projection between 25.5-29.5 0C. Temperature anomalies can be observed in much of northern Bali, which has increased from about 1.6 to 2.9 0C. There is a trend towards reduced (drier) humidity in most parts of Bali, particularly in the northern part of Bali. In contrast, a small amount in the south increases the (wetter) humidity. The comfort index of the Bali region in history is still relatively comfortable (20-26 0C). The projection condition RCP 4.5, there is no comfortable area with an index of more than 26 0C (hot and dry).

Seasonal Urban Heat Island Observation from Remote Sensing by Using Google Earth Engine Over New Capital (IKN) East Kalimantan, Indonesia

“…For future research, several factors related to UHI will be examined, namely Land Use and Land Cover Change (LULCC) [2,29,30], Normalized Difference Built-Up Index (NDBI) [35], Albedo, Normalized Difference Vegetation Index (NDVI) [36,37], anthropogenic heat and Comfortable Index [38][39][40], Normalized Difference Water Index (NDWI) [31,36], and Air Pollution [41][42][43].…”

Sensitivity of Australian rainfall to driving SST datasets in a variable-resolution global atmospheric model

“…CCAM has recently been used for climate projections in different Australian regions, including extreme weather projections developed by the National Environmental Science Programme's (NESP) Earth Systems and Climate Change Hub (ESCC Hub) and climate projections for the end of the 21 st century in Victoria, Tasmania, and Queensland for the government. CCAM has also been used in studies on the teleconnections between ENSO and regional weather (e.g., Chapman et al 2020;Dechpichai et al 2022) and long-term climate modelling (e.g., Katzfey et al 2016;Nurlatifah et al 2019;Toersilowati et al 2022) in Southeast Asia. CCAM performs similarly to other RCMs in intercomparison assessments in Australia (Evans et al 2016;Di Virgilio et al 2019).…”