Estimating Model Parameters with Ensemble-Based Data Assimilation: A Review

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Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations (2017, methodology): “…over timescales of hours or days [e.g., Emanuel and Živković Rothman, 1999; Grell and Dévényi, 2002; Aksoy et al., 2006; Schirber et al., 2013; Ruiz et al., 2013; Ruiz and Pulido, 2015], or by minimizing deviations between simulated and observed longer-term aggregates of climate statistics,…”
Neural general circulation models for weather and climate (2023, result): “Our results provide strong evidence for the disputed hypothesis 37–39 that learning to predict short-term weather is an effective way to tune parameterizations for climate.”