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Title: Final Report: Climate Variability, Stochasticity and Learning in Integrated Assessment Models, September 15, 1996 - September 14, 1999

Abstract

The focus of the work has been on climate variability and learning within computational climate-economy models (integrated assessment models--IAM's). The primary objective of the research is to improve the representation of learning in IAM's. This include's both endogenous and exogenous learning. A particular focus is on Bayesian learning about climate damage. A secondary objective is to improve the representation of climate variability within IAM's.

Authors:
Publication Date:
Research Org.:
University of California, Santa Barbara, CA (US)
Sponsoring Org.:
USDOE Office of Energy Research (ER) (US)
OSTI Identifier:
765627
DOE Contract Number:  
FG03-96ER62277
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 14 Sep 1999
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; CLIMATES; LEARNING; STOCHASTIC PROCESSES; CLIMATE MODELS

Citation Formats

Kolstad, Charles D. Final Report: Climate Variability, Stochasticity and Learning in Integrated Assessment Models, September 15, 1996 - September 14, 1999. United States: N. p., 1999. Web. doi:10.2172/765627.
Kolstad, Charles D. Final Report: Climate Variability, Stochasticity and Learning in Integrated Assessment Models, September 15, 1996 - September 14, 1999. United States. https://doi.org/10.2172/765627
Kolstad, Charles D. 1999. "Final Report: Climate Variability, Stochasticity and Learning in Integrated Assessment Models, September 15, 1996 - September 14, 1999". United States. https://doi.org/10.2172/765627. https://www.osti.gov/servlets/purl/765627.
@article{osti_765627,
title = {Final Report: Climate Variability, Stochasticity and Learning in Integrated Assessment Models, September 15, 1996 - September 14, 1999},
author = {Kolstad, Charles D},
abstractNote = {The focus of the work has been on climate variability and learning within computational climate-economy models (integrated assessment models--IAM's). The primary objective of the research is to improve the representation of learning in IAM's. This include's both endogenous and exogenous learning. A particular focus is on Bayesian learning about climate damage. A secondary objective is to improve the representation of climate variability within IAM's.},
doi = {10.2172/765627},
url = {https://www.osti.gov/biblio/765627}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Sep 14 00:00:00 EDT 1999},
month = {Tue Sep 14 00:00:00 EDT 1999}
}