A New Framework for the Assessment and Calibration of Medium Range Ensemble Temperature Forecasts

Abstract

We present a new framework for the assessment and calibration of medium range ensemble temperature forecasts. The method is based on maximising the likelihood of a simple parametric model for the temperature distribution, and leads to some new insights into the predictability of uncertainty.

Submitted to ASL

References in corpus (5)

• Moment based methods for ensemble assessment and calibration
• Comparing the ensemble mean and the ensemble standard deviation as inputs for probabilistic medium-range temperature forecasts
• Use of the likelihood for measuring the skill of probabilistic forecasts
• Do probabilistic medium-range temperature forecasts need to allow for non-normality?
• A note on the use of the word 'likelihood' in statistics and meteorology

Cited by in corpus (5)

• Use of the likelihood for measuring the skill of probabilistic forecasts
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• A note on the use of the word 'likelihood' in statistics and meteorology
• Improving probabilistic forecasts of extreme wind speeds by training statistical post-processing models with weighted scoring rules
• Probabilistic forecasts of temperature: measuring the utility of the ensemble spread