📝 SummarXiv

Abstract

As a demonstration of concept, quantile gradient boosting is used to forecast diurnal and nocturnal Q(.90) air temperatures for Paris, France during late the spring and summer months of 2020. The data are provided by the Paris-Montsouris weather station. Q(.90) values are estimated because the 90th percentile requires that the temperatures be relatively rare and extreme. Predictors include seven routinely collected indicators of weather conditions, lagged by 14 days; the temperature forecasts are produced two weeks in advance. Conformal prediction regions capture forecasting uncertainty with provably valid properties. For both diurnal and nocturnal temperatures, forecasting accuracy is promising, and sound measures of uncertainty are provided. Benefits for policy and practice follow.