The Global Change Assessment Model (GCAM): An overview and applications скачать в хорошем качестве

The Global Change Assessment Model (GCAM): An overview and applications

Pralit Patel @ Pacific Northwest National Lab https://www.pnnl.gov/science/staff/st... Slides: https://sites.google.com/modelingtalk... Abstract: This seminar introduces the Global Change Assessment Model (GCAM), an integrated human-Earth systems model, and analyzes a range of scenarios that estimate the future evolution of the energy, agriculture, and water system calculating the resulting green house gases as well. GCAM has been widely used for analysis of these systems individually, and the feedbacks between them. GCAM has been used to produce scenarios for national and international assessments ranging from the very first IPCC scenarios (Response Strategies Working Group, 1990) through the present Shared Socioeconomic Pathways (Calvin et al., 2017). GCAM is increasingly being used in multi-model, multi-scale analysis, in which it is either soft- or hard-coupled to other models with different focuses and often greater resolution in key sectors. For example, a range of downscaling tools have been developed for use with GCAM to be able to land and water outputs at a grid resolution. Similarly, it has been coupled to a state of the art Earth system model (Collins, et al., 2015). Hundreds of papers have been published in peer-reviewed journals using GCAM over its lifetime and the GCAM system continues to be an important international tool for scientific inquiry. GCAM is also a community model being used by researchers across the globe, creating a shared global research enterprise and is open source and freely available. Bio: Pralit Patel is a Computational Scientist at the Joint Global Change Research Institute (JGCRI), a joint institute with the Pacific Northwest National Laboratory (PNNL) and the University of Maryland (UMD), in College Park Maryland. Pralit’s focus is developing simulation and emulation based models in a wide range of fields including energy, agriculture, water, and climate. His background is in Computer Science and Mathematics with a Bachelor’s degree from the University of Maryland.