15:00 〜 15:15
[ACG45-06] Quantifying Regional Climate Change within the South Asian Summer Monsoon domain
キーワード：South Asian Summer Monsoon、Northeast India 、Indian Summer Monsoon Rainfall、Humidex
The South Asian Summer Monsoon (SASM) system is undergoing significant changes due to anthropogenic climate change, impacting regional hydroclimate variability and extreme events. Northeast India (NEI; 89°E-98°E, 21°N-30°N) is a key sub-domain of the SASM, known for its intense rainfall and ecological significance. Despite covering only 8% of India’s landmass, NEI accounts for nearly one-fourth of the country’s total forested area (~17 million hectares) and contributes ~63% to the Indian Summer Monsoon Rainfall (ISMR). With an average seasonal rainfall of ~1200 mm during June–September (JJAS), this region plays a crucial role in the regional hydrological cycle. However, ongoing climate change is altering monsoonal characteristics, impacting rainfall variability and associated atmospheric processes.
This study quantifies historical and projected shifts in monsoon dynamics over NEI and the broader South Asian domain using ERA5 reanalysis, ground observations, NCEPv3 datasets, and CMIP6 projections. An analysis of the 2m temperature anomaly probability distribution (ERA5) relative to the 1951–1980 baseline reveals a strong warming trend. The frequency of cool anomalies (<−1°C) declined from 30.8% (1940–1949) to 4.8% (2010–2019), while extreme warm anomalies (>+2°C) increased from ~0% to 13.3% over the same period.
To examine rainfall variability, we apply the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (iCEEMDAN) method to isolate different modes of variability. The nonlinear trend extracted from this analysis indicates a 6.2% decline in total rainfall, accompanied by an 83.7% increase in extreme rainfall frequency and a 9.8% rise in intensity. Declines in vertically integrated moisture flux convergence (−14.5%), low-level wind convergence (−46.5%), and low-level moisture convergence (−19.6%) highlight a weakening of large-scale monsoonal convergence processes.
Future projections from CMIP6 under the SSP5-8.5 scenario indicate a fundamental shift in the dominant mechanisms driving precipitation variability over NEI. The currently dominant dynamic processes (2021–2040) are projected to transition toward thermodynamic dominance by 2081–2100. A regionally averaged analysis confirms that both thermodynamic (TH) and dynamic (DY) components contribute positively to future precipitation trends, but with a notable shift from DY to TH dominance in the far future. A key factor driving this transition is the warming of the tropical Indian Ocean, which weakens the north-south temperature gradient and disrupts the orographic rain-bearing system. Projected rainfall sensitivity to warming suggests an increase of ~4.3%/°C under SSP2-4.5 and ~5%/°C under SSP5-8.5, though historical simulations indicate weaker correlations. Additionally, extreme events such as humid heat stress and intensified weather systems, including Mesoscale Convective Systems (MCS), are expected to become more frequent under future warming scenarios.
These findings highlight the urgent need for interdisciplinary studies that integrate climate projections into a hydro economic optimization framework. Such an approach can help simulate the impacts of climate variability on water availability, agricultural productivity, eco-tourism, and other water-dependent sectors, enabling more effective adaptation strategies.
Figure 1. Kernel density estimates of normalized 2-meter temperature anomalies (±σ = 1.1°C) over Northeast India, comparing the periods 1940–1949 (blue) and 2010–2019 (red) based on 1951–1980 reference period for May-September (MJJAS) season.
This study quantifies historical and projected shifts in monsoon dynamics over NEI and the broader South Asian domain using ERA5 reanalysis, ground observations, NCEPv3 datasets, and CMIP6 projections. An analysis of the 2m temperature anomaly probability distribution (ERA5) relative to the 1951–1980 baseline reveals a strong warming trend. The frequency of cool anomalies (<−1°C) declined from 30.8% (1940–1949) to 4.8% (2010–2019), while extreme warm anomalies (>+2°C) increased from ~0% to 13.3% over the same period.
To examine rainfall variability, we apply the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (iCEEMDAN) method to isolate different modes of variability. The nonlinear trend extracted from this analysis indicates a 6.2% decline in total rainfall, accompanied by an 83.7% increase in extreme rainfall frequency and a 9.8% rise in intensity. Declines in vertically integrated moisture flux convergence (−14.5%), low-level wind convergence (−46.5%), and low-level moisture convergence (−19.6%) highlight a weakening of large-scale monsoonal convergence processes.
Future projections from CMIP6 under the SSP5-8.5 scenario indicate a fundamental shift in the dominant mechanisms driving precipitation variability over NEI. The currently dominant dynamic processes (2021–2040) are projected to transition toward thermodynamic dominance by 2081–2100. A regionally averaged analysis confirms that both thermodynamic (TH) and dynamic (DY) components contribute positively to future precipitation trends, but with a notable shift from DY to TH dominance in the far future. A key factor driving this transition is the warming of the tropical Indian Ocean, which weakens the north-south temperature gradient and disrupts the orographic rain-bearing system. Projected rainfall sensitivity to warming suggests an increase of ~4.3%/°C under SSP2-4.5 and ~5%/°C under SSP5-8.5, though historical simulations indicate weaker correlations. Additionally, extreme events such as humid heat stress and intensified weather systems, including Mesoscale Convective Systems (MCS), are expected to become more frequent under future warming scenarios.
These findings highlight the urgent need for interdisciplinary studies that integrate climate projections into a hydro economic optimization framework. Such an approach can help simulate the impacts of climate variability on water availability, agricultural productivity, eco-tourism, and other water-dependent sectors, enabling more effective adaptation strategies.
Figure 1. Kernel density estimates of normalized 2-meter temperature anomalies (±σ = 1.1°C) over Northeast India, comparing the periods 1940–1949 (blue) and 2010–2019 (red) based on 1951–1980 reference period for May-September (MJJAS) season.