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How Global Warming Affects Forecasting?

Context: The record warming observed during 2023-2024 has provided clearer insights into the impacts of global warming, characterised by a range of extreme weather events. These include heatwaves, cyclones, floods, droughts, wildfires.

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  • Estimates suggest that the world has surpassed the 1.5°C warming threshold compared to pre-industrial averages.
  • However, this figure is based on a combination of data and climate models, and it remains unclear how long temperatures must stay above this threshold for significant environmental impacts to occur.

IPCC Assessment Report 6 (AR6)

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Climate Predictions and Observations

  • Meteorologists had predicted the occurrence of El Niño in spring 2023, but the level of warming experienced was unexpectedly high.
  • Contributing factors include:
    • Water vapour released from the Hunga Tonga–Hunga Ha‘apai underwater volcano eruption in 2022.
    • Increased CO2 emissions from wildfires.
  • The 2023 monsoon was below average but not an El Niño drought.
    • Predictions for a strong La Niña in late 2024 now seem unlikely, demonstrating the unpredictability of weather patterns.
  • Cyclone activity in the North Indian Ocean was weaker than expected, and the anticipated Indian Ocean Dipole (IOD) did not materialise as predicted.
Quote
“Prediction is difficult, especially if it’s about the future.” – Neil Bohr

Predictive Limitations

  • Complex Predictive Models: Current models can reproduce climate patterns based on solar energy but often disagree on specific outcomes.
    • Existing models struggle to accurately reproduce historical monsoon trends and are often unreliable for future forecasts.
  • Natural Variability vs. Climate Trends: There is uncertainty regarding whether current patterns are genuine trends or merely decade-to-decade variability.
    • Warming may alter the timescales of these variabilities, complicating predictive accuracy.

Lessons from Recent Extremes

  • Projections and Uncertainties: Climate projections hinge on emissions scenarios, population growth, and mitigation policies.
    • Uncertainties in these models, combined with natural variabilities, limit long-term predictability.
  • Decadal Focus: Projections beyond a few decades are speculative due to the complex interplay of geopolitical, economic, and societal changes.
    • Thus, focusing on near-term projections (10-20 years) might yield more reliable results.

Strategy for Future Predictions

  • Technological Improvements: Advancements in AI, machine learning, and enhanced data networks offer potential to improve model reliability and develop better early warning systems at localised scales.
  • Balancing Resources: Policymakers must weigh the costs and benefits of investing in long-term climate projections, considering the vast resources required to model scenarios extending to 2100.

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