A Study on Reducing Uncertainties in Climate Change Projections and Decadal Forecasts

Project Details

Description

Climate change is a pressing issue that the global society is facing. Accurate decadal predictions and projection are the corner stone for mitigation planning of climate change problems. Recently, the Coupled Model Intercomparison Project, Phase 5(CMIP5) provides a huge collection of decadal forecasts and climate change scenario runs from many different climate models to help improving our skills in decadal predictions and climate change projections. Furthermore, I developed a scale dependent empirical orthogonal function analysis in recent years. Because the scale dependent empirical orthogonal function analysis allow one to effectively extract the most stable spatial patterns from original data, therefore the purpose of this study is to apply this method to both observed and CMIP5 decadal forecasts and climate change scenario runs to find a better way to use MME to reduce uncertainties in decadal forecasts and climate change projection than just use the mean and spread of MME. Through this study, we hope to improve decadal forecasts and climate change projections to allow for more accurate mitigation planning of climate change problem.
StatusFinished
Effective start/end date1/08/1631/12/17

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 8 - Decent Work and Economic Growth
  • SDG 13 - Climate Action
  • SDG 17 - Partnerships for the Goals

Keywords

  • Scale dependent empirical orthogonal functions
  • Multi-Model Ensembles
  • Decadal forecasts
  • Climate change projections

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