Initialised Earth System Predictionms

HBS Guy

Head Honcho
Staff member
Abstract
Initialized Earth System predictions are made by starting a numerical prediction model in a state as consistent as possible to observations and running it forward in time for up to 10 years. Skilful predictions at time slices from subseasonal to seasonal (S2S), seasonal to interannual (S2I) and seasonal to decadal (S2D) offer information useful for various stakeholders, ranging from agriculture to water resource management to human and infrastructure safety. In this Review, we examine the processes influencing predictability, and discuss estimates of skill across S2S, S2I and S2D timescales. There are encouraging signs that skilful predictions can be made: on S2S timescales, there has been some skill in predicting the Madden–Julian Oscillation and North Atlantic Oscillation; on S2I, in predicting the El Niño–Southern Oscillation; and on S2D, in predicting ocean and atmosphere variability in the North Atlantic region. However, challenges remain, and future work must prioritize reducing model error, more effectively communicating forecasts to users, and increasing process and mechanistic understanding that could enhance predictive skill and, in turn, confidence. As numerical models progress towards Earth System models, initialized predictions are expanding to include prediction of sea ice, air pollution, and terrestrial and ocean biochemistry that can bring clear benefit to society and various stakeholders.
Key points
  • Initialization methods vary greatly across different prediction timescales, creating difficulties for seamless prediction.
  • Model error and drift limit predictability across all timescales. Although higher resolution models show promise in reducing these errors, improvements in physical parameterizations are needed to improve predictability.
  • The effects of land processes, interactions across various ocean basins and the role of stratospheric processes in predictability are not well understood.
  • Predictability on seasonal to decadal timescales is largely associated with predictability of the major modes of variability in the atmosphere and the ocean.
  • Evolution of Earth System models will lead to predictability of more societal-relevant variables spanning multiple parts of the Earth System.
https://www.nature.com/articles/s43017-021-00155-x
 

HBS Guy

Head Honcho
Staff member
Means if you set a proven model to current conditions you can predict seasonal weather.
 

HBS Guy

Head Honcho
Staff member
3 months before the season you are interested in? Like whether and what to plant next season?
 
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