Quantifying uncertainty in climate change science through empirical information theory

Proceedings of the National Academy of Sciences of the United States of America

Volumn 107, Issue 34, 2010, Pages 14958-14963

  Majda, Andrew J ^a   Gershgorin, Boris ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

Model errors; Practical algorithms; Unbiased empirical estimates

Indexed keywords

CARBON DIOXIDE;

ACCURACY; ARTICLE; ATMOSPHERE OCEAN SCIENCE COMPUTER MODELS; CALCULATION; CLIMATE CHANGE; COMPUTER MODEL; COVARIANCE; INFORMATION SCIENCE; LOW FREQUENCY NOISE; MEASUREMENT ERROR; OUTCOME ASSESSMENT; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; STOCHASTIC MODEL; UNCERTAINTY; ALGORITHM; COMPUTER SIMULATION; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; CLIMATE CHANGE; COMPUTER SIMULATION; INFORMATION THEORY; MODELS, STATISTICAL; STOCHASTIC PROCESSES;

EID: 77957005765     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1007009107     Document Type: Article

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