naa a22 4500 510774911 CHVBK 20180411083227.0 cr unu---uuuuu 180411e20130601xx s 000 0 eng 10.1007/s12210-013-0228-2 doi (NATIONALLICENCE)springer-10.1007/s12210-013-0228-2 Climate prediction: an evidence-based perspective [Elektronische Daten] [Richard Goody, Guido Visconti] This paper considers climate prediction from the perspective of the experimental, physical sciences, and discusses three ways in which the two differ. First, the construction of long-term climate series requires benchmark measurements, i.e., measurements calibrated in situ against international standards. An instrument capable of accurate, benchmark measurements of thermal, spectral radiances from space is available but has yet to be used. Second, objective criteria are needed to evaluate measurements for the purpose of improving climate predictions. Techniques based on Bayesian inference are now available. Third is the question of how to use suitable data to improve a climate prediction, when they are available. A method based on the Bayesian Evidence Function is, in principle, available, but has yet to be exploited. None of these three aspects are considered in current operational climate forecasting. All three are potentially capable of improving forecasts, and all are subjects of current research programs, with the likelihood of their eventual adoption. The Author(s), 2013 Climate predictions nationallicence Bayes inference nationallicence Climate benchmarks nationallicence Climate modeling nationallicence Goody Richard School of Engineering and Applied Science, Harvard University, 02138, Cambridge, MA, USA aut Visconti Guido Department of Physics, Center of Excellence on Integration of Remote Sensing Techniques and Numerical Modeling for the Forecast of Severe Weather (CETEMPS), University of L'Aquila, 67010, L'Aquila, Coppito, Italy aut Rendiconti Lincei Springer Milan 24/2(2013-06-01), 107-112 2037-4631 24:2<107 2013 24 12210 https://doi.org/10.1007/s12210-013-0228-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s12210-013-0228-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Goody Richard School of Engineering and Applied Science, Harvard University, 02138, Cambridge, MA, USA aut NATIONALLICENCE 700 1- Visconti Guido Department of Physics, Center of Excellence on Integration of Remote Sensing Techniques and Numerical Modeling for the Forecast of Severe Weather (CETEMPS), University of L'Aquila, 67010, L'Aquila, Coppito, Italy aut NATIONALLICENCE 773 0- Rendiconti Lincei Springer Milan 24/2(2013-06-01), 107-112 2037-4631 24:2<107 2013 24 12210 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer