Estimating present-day European seasonal mean rainfall by combining historical data and climate model simulations, for risk assessment

Building risk models for present-day climate requires an understanding of recent climate trends. To estimate the climate change driven component of recent rainfall trends in Europe, we introduce a novel methodology for combining trend estimates from observed data, a climate model ensemble and a default trend of zero. The methodology weights the different trend estimates based on their uncertainty and consistency with observations. We find that the methodology puts low weights on the observational estimates of recent rainfall trends because they are so uncertain and puts higher weights on the trends estimated using the climate model ensemble mean and the default trend of zero. This demonstrates the value of ensemble simulations of past climate for this application. The methodology we describe establishes a probabilistic framework for estimating uncertain climate change trends based on combining estimates from observed data and climate models and could be applied in many other situations.

Automated summary

Building risk models for present-day climate requires an understanding of recent climate trends. A novel methodology is introduced to estimate the climate change driven component of recent rainfall trends in Europe by combining trend estimates from observed data, a climate model ensemble, and a default trend of zero. The methodology weights the different trend estimates based on their uncertainty and consistency with observations, demonstrating the value of ensemble simulations of past climate for this application. This probabilistic framework could be applied in many other situations for estimating uncertain climate change trends.