Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation

• Published in: Journal of applied meteorology and climatology Vol. 60; no. 5; pp. 695 - 710
• Main Authors: Lai, Yuchuan, Dzombak, David A.
• Format: Journal Article
• Language: English
• Published: Boston American Meteorological Society 01.05.2021
• Subjects: Autoregressive models; Bias; Cities; Climate change; Climate models; Daily temperatures; Deviation; Engineering; Global climate; Global climate models; Infrastructure; Mathematical models; Modelling; Precipitation; Precipitation-temperature relationships; Regional studies; Simulation; Statistical analysis; Statistical methods; Temperature; Time series; Trends; Weather forecasting; United States > US; Pittsburgh Pennsylvania

An integrated technique combining global climate model (GCM) simulation results and a statistical time series forecasting model [the autoregressive integrated moving average (ARIMA) model] was developed to bring together the climate change signal from GCMs to city-level historical observations as an...