A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation

A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual from tree-ring records is developed tested in this paper. The principle stochastically generating assumes that temperatures any year can be approximated by a sinusoidal wave function plus perturbation the baseline. CSWG three additional assumptions: (1) In each month, total estimated if there exists relationship between monthly precipitations. If exists, then (2) number of dry days maximum month. Finally, (3) probability distribution amount wet day. These assumptions allow development constrains statistically relevant predictions specified value, thus study presents unique method used to explore historic (e.g., archeological questions) or future climate change) conditions upon values.