In usual pricing approaches for weather derivatives, forward-looking information such as meteorological weather forecasts is not considered. Thus, important knowledge used by market participants is ignored in theory. By extending a standard model for the daily temperature, this article allows the incorpo-ration of meteorological forecasts in the framework of weather derivative pricing and is able to esti-mate the information gain compared with a bench-mark model without meteorological forecasts. This approach is applied for temperature futures referring to New York, Minneapolis, and Cincinnati with meteorological forecast data 13 days in advance. Despite this relatively short forecast horizon, the models using meteorological forecasts outperform the classical approach and more accurately forecast the market prices of the temperature futures traded at the Chicago Mercantile Exchange (CME). Moreover, a concentration on the last two months or on days with actual trading improves the results, whereas an inclusion of hypothetical perfect forecasts worsens them.