A Space-Time Unified Data Set of General Circulation Model Outputs for Land Surface Modeling over Amazonia

Monday, 15 December 2014
Sanaz Moghim1, Shawna L McKnight1, Ke Zhang2, Ardeshir M Ebtehaj1, Ryan G Knox3, Rafael L Bras4, Paul R Moorcroft5 and Jingfeng Wang6, (1)Georgia Institute of Technology, Atlanta, GA, United States, (2)University of Oklahoma Norman Campus, Norman, OK, United States, (3)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (4)Georgia Tech, Atlanta, GA, United States, (5)Harvard Univ, Cambridge, MA, United States, (6)GA Ins of Tech-Civil & Env Eng, Atlanta, GA, United States
This study provides bias corrected, high space-time resolution meteorological data sets for the 21st century over the Amazon Basin, which is used to drive land-surface and ecosystem models. The bias corrections and resolution adjustments are performed on the outputs of three widely-used General Circulation Models (GCMs) including the Community Climate System Model (CCSM3), the Parallel Climate Model (PCM1), and the Hadley Centre Coupled Model (HadCM3) under A2 scenario (the IPCC climate scenario). The study processes the primary GCM’s outputs including temperature, precipitation, downwelling longwave and shortwave radiation, specific humidity, horizontal wind velocities, and pressure, which are main forcing for ecosystem models to understand the consequences of climate and land-use changes in Amazonia. A series of simple but effective statistical downscaling approaches are used to properly project the data onto a unified space-time resolution at 1° by 1° grid cells and hourly temporal resolution. The bias correction step uses a quantile-based CDF matching method to adjust the model CDF for the climate projection based on the difference between the historically modeled and observed CDFs at each percentile. These improved data sets have been used as inputs to the Common Land Model (CLM), the Ecosystem Demography Model version 2 (ED2), the Integrated Biosphere Simulator Model (IBIS), and the Joint UK Land Environment Simulator (JULES) to study and predict the effects and interactions between climate, forest/deforestation, and land use in the Amazon Basin.