TY - JOUR
T1 - Predicting global temperature anomaly: a definitive investigation using an ensemble of twelve competing forecasting models
AU - Hassani, Hossein
AU - Silva, Emmanuel Sirimal
AU - Gupta, Rangan
AU - Das, Sonali
N1 - Funding Information:
This work was supported by DARPA, under Grant No. F3602-97-2-0122 and NSF, under Grants No. ECS-9616879 and CCR-9988319.
Funding Information:
Philippe J. Marchand received his B.S., M.S. and Ph.D. degrees in electrical engineering from the University of Haute Alsace, Mulhouse (France) in 1986, 1987 and 1991 respectively. From 1991 through 1999, he was a research scientist and senior lecturer at the University of California, San Diego with the Optoelectronic Computing Group. His research interests included optical 2-D and 3-D storage, computer generated holography and diffractive optics, optical system design and packaging, optical free-space interconnections, parallel architectures and their applications to parallel optoelectronic computing and telecommunication switching. At UCSD, he worked on developing 3-D packaging technologies for optoelectronic systems and he concurrently worked on the development of models for optoelectronic CAD tools in relation with the University of Pittsburgh. He was a principal investigator for the DARPA funded 3D-OESP Consortium whose goal was to integrated 3D-VLSI and parallel free-space optoelectronic technologies. Since November 1999, he has joined OMM, Inc. as a project director where he is heading the R&D efforts for the development of 3D based MEMS switches. Philippe Marchand has published over 130 articles and papers in refereed journals and scientific meetings, and he holds five patents. He received a Lavoisier fellowship in 1990 from the French Foreign Ministry, the 1991 ADRERUS Thesis prize for his Ph.D. work, and a best paper award at the 1997 Design Automation Conference in Las Vegas. He is a member of IEEE, OSA, and SPIE.
PY - 2018/11/1
Y1 - 2018/11/1
N2 - In this paper we analyse whether (anthropometric) CO2 can forecast global temperature anomaly (GT) over an annual out-of-sample period of 1907–2012, which corresponds to an initial in-sample of 1880–1906. For our purpose, we use 12 parametric and nonparametric univariate (of GT only) and multivariate (including both GT and CO2) models. Our results show that the Horizontal Multivariate Singular Spectral Analysis (HMSSA) techniques (both Recurrent (-R) and Vector (-V)) consistently outperform the other competing models. More importantly, from the performance of the HMSSA-V model we find conclusive evidence that CO2 can forecast GT, and also predict its direction of change. Our results highlight the superiority of the nonparametric approach of SSA, which in turn, allows us to handle any statistical process: linear or nonlinear, stationary or non-stationary, Gaussian or non-Gaussian.
AB - In this paper we analyse whether (anthropometric) CO2 can forecast global temperature anomaly (GT) over an annual out-of-sample period of 1907–2012, which corresponds to an initial in-sample of 1880–1906. For our purpose, we use 12 parametric and nonparametric univariate (of GT only) and multivariate (including both GT and CO2) models. Our results show that the Horizontal Multivariate Singular Spectral Analysis (HMSSA) techniques (both Recurrent (-R) and Vector (-V)) consistently outperform the other competing models. More importantly, from the performance of the HMSSA-V model we find conclusive evidence that CO2 can forecast GT, and also predict its direction of change. Our results highlight the superiority of the nonparametric approach of SSA, which in turn, allows us to handle any statistical process: linear or nonlinear, stationary or non-stationary, Gaussian or non-Gaussian.
KW - CO emissions
KW - Forecasting
KW - Global temperature anomaly
KW - Univariate and multivariate models
U2 - 10.1016/j.physa.2018.05.147
DO - 10.1016/j.physa.2018.05.147
M3 - Article
AN - SCOPUS:85048585011
SN - 0378-4371
VL - 509
SP - 121
EP - 139
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -