Bringing physical reasoning into statistical practice in forecast verification on S2S timescales

Add to your list(s) Download to your calendar using vCal

• Ted Shepherd (University of Reading)
• Friday 23 September 2022, 12:00-12:20
• No Room Required.

If you have a question about this talk, please contact nobody.

GFDW02 - Forecast Verification and Data Assimilation in intermediate and large scale models of geophysical fluid dynamics, with applications to medium range and seasonal forecasting

There is a longstanding disconnect between physical reasoning and statistical practice in mainstream climate science. This disconnect extends to forecasting on subseasonal to seasonal timescales, which generally employs a frequentist definition of probability, counting members of a forecast ensemble. Such an approach struggles in the face of systematic model error, the inevitably sparse sampling in a finite ensemble, and limited verification data. In this talk I reflect on this historical disconnect and illustrate a few ways in which physical reasoning can be brought into the statistical framing of the forecast verification problem, through Bayesian reasoning and causal networks.

This talk is part of the Isaac Newton Institute Seminar Series series.

This talk is included in these lists:

• All CMS events
• Featured lists
• INI info aggregator
• Isaac Newton Institute Seminar Series
• No Room Required
• School of Physical Sciences
• bld31

Note that ex-directory lists are not shown.