  Spread regression is an extension of linear regression that allows for the
inclusion of a predictor that contains information about the variance. It can
be used to take the information from a weather forecast ensemble and produce a
probabilistic prediction of future temperatures. There are a number of ways
that spread regression can be formulated in detail. We perform an empirical
comparison of four of the most obvious methods applied to the calibration of a
year of ECMWF temperature forecasts for London Heathrow.
