Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
Description: These data represent gridded monthly SST anomalies for 399 consecutive months from January 1970 through March 2003. The data were obtained from the IRI/LDEO Climate Data Library at Columbia University (http://iridl.ldeo.columbia.edu/). The data are gridded at a 2 degree by 2 degree resolution and represent anomalies from a January 1970 - December 1985 monthly (average) climatology. A more complete description can be found at http://iridl.ldeo.columbia.edu/SOURCES/.CAC/ References: In addition to Chapter 5 and 9 of Cressie and Wikle (2011), these data have been described and modeled in the following: Berliner, L.M., Wikle, C.K. and N. Cressie, (2000). Long-lead prediction of Pacific SSTs via Bayesian Dynamic Modeling. Journal of Climate, 13 , 3953-3968. Wikle, C.K. and M.B. Hooten, 2010: A general science-based framework for spatio-temporal dynamical models. Invited discussion paper for Test. 19, 417-451. Wikle, C.K. and S.H. Holan, 2011: Polynomial nonlinear spatio-temporal integro-difference equation models Journal of Time Series Analysis. DOI: 10.1111/j.1467-9892.2011.00729.x
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
Description: These data represent gridded monthly SST anomalies for 399 consecutive months from January 1970 through March 2003. The data were obtained from the IRI/LDEO Climate Data Library at Columbia University (http://iridl.ldeo.columbia.edu/). The data are gridded at a 2 degree by 2 degree resolution and represent anomalies from a January 1970 - December 1985 monthly (average) climatology. A more complete description can be found at http://iridl.ldeo.columbia.edu/SOURCES/.CAC/ References: In addition to Chapter 5 and 9 of Cressie and Wikle (2011), these data have been described and modeled in the following: Berliner, L.M., Wikle, C.K. and N. Cressie, (2000). Long-lead prediction of Pacific SSTs via Bayesian Dynamic Modeling. Journal of Climate, 13 , 3953-3968. Wikle, C.K. and M.B. Hooten, 2010: A general science-based framework for spatio-temporal dynamical models. Invited discussion paper for Test. 19, 417-451. Wikle, C.K. and S.H. Holan, 2011: Polynomial nonlinear spatio-temporal integro-difference equation models Journal of Time Series Analysis. DOI: 10.1111/j.1467-9892.2011.00729.x
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Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
Description: These data represent gridded monthly SST anomalies for 399 consecutive months from January 1970 through March 2003. The data were obtained from the IRI/LDEO Climate Data Library at Columbia University (http://iridl.ldeo.columbia.edu/). The data are gridded at a 2 degree by 2 degree resolution and represent anomalies from a January 1970 - December 1985 monthly (average) climatology. A more complete description can be found at http://iridl.ldeo.columbia.edu/SOURCES/.CAC/ References: In addition to Chapter 5 and 9 of Cressie and Wikle (2011), these data have been described and modeled in the following: Berliner, L.M., Wikle, C.K. and N. Cressie, (2000). Long-lead prediction of Pacific SSTs via Bayesian Dynamic Modeling. Journal of Climate, 13 , 3953-3968. Wikle, C.K. and M.B. Hooten, 2010: A general science-based framework for spatio-temporal dynamical models. Invited discussion paper for Test. 19, 417-451. Wikle, C.K. and S.H. Holan, 2011: Polynomial nonlinear spatio-temporal integro-difference equation models Journal of Time Series Analysis. DOI: 10.1111/j.1467-9892.2011.00729.x