A high resolution modelling perspective on food security and streamflow over Southeast Asia

Summary

This thesis evaluates the performance of climate models in representing rainfall patterns in Southeast Asia, focusing on the rainy season and extreme rainfall events, as well as projections of future rainfall patterns and their implications for streamflow and agriculture, particularly rice production. The first two chapters compare datasets from regional climate models (RCMs) based on the Coupled Model Intercomparison Project phase 5 (CMIP5) and High-Resolution Model Intercomparison Project (HighResMIP) outputs under CORDEX. The comparison assesses the models' accuracy in representing monsoon characteristics and extreme rainfall. The HighResMIP models generally offer better accuracy in capturing monsoon onset, total rainy-season precipitation, and extreme rainfall events than the CORDEX models. However, biases in rainfall intensity simulations persist, indicating the need for further bias correction. Accurate monsoon rainfall modeling is crucial for Southeast Asia’s agriculture, where delayed monsoons limit crop cycles. The HighResMIP’s historical coupled and atmosphere-forced runs (Hist-1950 and HighresSST) align more closely with observational data than CMIP5’s models, especially in capturing the onset date and total seasonal rainfall. The HighResSST experiment provides the most accurate representation of monsoon onset anomalies and seasonal precipitation under various El Niño-Southern Oscillation (ENSO) conditions, although it slightly underestimates the magnitude of onset date shifts. For extreme rainfall, regions affected by tropical cyclones and dry spells, such as Indochina and southern Indonesia, exhibit high rainfall intensities. HighResMIP models align more closely with these observed patterns than CORDEX models. However, biases in rainfall intensity, particularly in CORDEX models, remain a challenge, suggesting that increasing resolution alone may not enhance model accuracy for extreme events. The last two chapters of the thesis project future climate scenarios, focusing on extreme rainfall, streamflow, and rice production. Myanmar faces significant challenges compared to other Southeast Asian nations, while regions like Sumatra and Java are projected to see a 40% increase in the length of dry spells. Conversely, extreme high rainfall is expected to intensify in Borneo and Papua’s mountainous regions. Streamflow analysis indicates that climate change impacts are more pronounced in low-flow events than in high-flow events. Rivers in areas such as Sumatra, Borneo, and Java are projected to experience more frequent and severe low-flow events. The probability of low-flow occurrences is expected to rise by an average of 101% over Sumatra and 90% over Java. The thesis also examines the impact of shifting rainfall patterns on rice production. Reduced rainfall is observed in the December-January-February period over mainland Southeast Asia and the Philippines, and rainfall decreases in Indonesia during the June-July-August period. These changes, combined with delayed monsoon onset and shorter rainy seasons, pose challenges for rainfed rice production. The southern Philippines, for example, may experience a 27-day reduction in the rainy season. Although increased rainfall during the second growing season may improve yields, reduced rainfall in the first and third seasons significantly impacts production, particularly in Java. Simulations of rice irrigation indicate that rising temperatures shorten growing seasons, further reducing yields. Enhancing and optimizing agricultural systems appears to be a necessary strategy to mitigate these challenges.