Method for a meteorological forecast of temperature, from a short term of about 1 day to a long term of about 90 days, for: - managing the trade, transport and storage of energy resources such as natural gas, electric energy, oil and refined products; - estimating the production of electric energy obtained through the combustion of natural gas in combined cycle power plants, improving efficiency and reducing environmental impact; - reducing the unbalance on the transport and distribution grids of gas and electricity; - forecasting of the industrial and civil consumptions for managing the storage of oils and refined products, and optimize the logistic of the service stations; - managing the logistic of materials and personnel in remote worksites related to exploration and production operations, construction of industrial plants or pipelines, in any geographical area; - optimizing the supply of oils and the industrial petrochemical processes lead by market trends, the method comprising the steps of: - acquiring meteorological parameters of a large-scale geographical area having a predefined extent; - decomposing the large-scale geographical area into a base area, which derives from the large-scale geographical area, and into a regional area, wherein the regional area is defined as the difference between the large-scale geographical area and the base area; - determining the temperature close to the ground surface of the base area, starting from the parameters available on the large-scale geographical area, using an empirical-statistical model which is a statistical down-scaling; - determining the tendencies of the meteorological parameters in the regional area, starting from the meteorological parameters available on the large-scale geographical area, using a dynamic numerical model which is a dynamic down-scaling, the method being characterized in that it comprises the further step of: - performing, through an applicative model, an ensemble down-scaling, which is a combination of the empirical-statistical model and of the dynamic numerical model, to obtain in continuous, from the short term of about 1 day up to the long term of about 90 days, the temperature forecast close to the ground surface, wherein said applicative model adds a statistical scaling of the data for temperatures close to the surface which are therefore re-assimilated in the regional area as new temperature values close to the ground surface of the regional area, introducing, during the dynamic down-scaling phase, a range of pseudo-observations, which properly act on the regional area. - managing the trade, transport and storage of energy resources such as natural gas, electric energy, oil and refined products; - estimating the production of electric energy obtained through the combustion of natural gas in combined cycle power plants, improving efficiency and reducing environmental impact; - reducing the unbalance on the transport and distribution grids of gas and electricity; - forecasting of the industrial and civil consumptions for managing the storage of oils and refined products, and optimize the logistic of the service stations; - managing the logistic of materials and personnel in remote worksites related to exploration and production operations, construction of industrial plants or pipelines, in any geographical area; - optimizing the supply of oils and the industrial petrochemical processes lead by market trends, - acquiring meteorological parameters of a large-scale geographical area having a predefined extent; - decomposing the large-scale geographical area into a base area, which derives from the large-scale geographical area, and into a regional area, wherein the regional area is defined as the difference between the large-scale geographical area and the base area; - determining the temperature close to the ground surface of the base area, starting from the parameters available on the large-scale geographical area, using an empirical-statistical model which is a statistical down-scaling; - determining the tendencies of the meteorological parameters in the regional area, starting from the meteorological parameters available on the large-scale geographical area, using a dynamic numerical model which is a dynamic down-scaling, - performing, through an applicative model, an ensemble down-scaling, which is a combination of the empirical-statistical model and of the dynamic numerical model, to obtain in continuous, from the short term of about 1 day up to the long term of about 90 days, the temperature forecast close to the ground surface, wherein said applicative model adds a statistical scaling of the data for temperatures close to the surface which are therefore re-assimilated in the regional area as new temperature values close to the ground surface of the regional area, introducing, during the dynamic down-scaling phase, a range of pseudo-observations, which properly act on the regional area.