Rainfall predictive model

Rainfall simulation is key problem for the evaluation of the energy saving potential of passive cooling by natural rainfall evaporation in humid and hot areas. This paper used a set of monthly, daily and hourly rainfall data in Guangzhou Area to identify the statistic feathers and distribution of the monthly, daily and hourly rainfall. A one-order AR model was found to be suitable for monthly rainfall estimation by AIC criterion judgment. Using a Gamma distribution model and monthly rainfall, daily rainfall was estimated by stochastically assignment.

Rainfall simulation is a key problem for the evaluation of the energy saving potential of passive cooling by natural rainfall evaporation in humid and hot areas. Using a set of data in Guangzhou Area from weather bureau as the training sample, and the data generated by Medpha (Meteorological Data Producer for HVAC Analysis) as the testing sample, distance discriminant analysis was applied to identify the rainy time.