1. Current and emerging developments in subseasonal to decadal prediction
- Author
-
Barcelona Supercomputing Center, Merryfield, William J., Baehr, Johanna, Batté, Lauriane, Becker, Emily J., Butler, Amy H., Coelho, Caio A.S., Danabasoglu, Gorkhan, Dirmeyer, Paul A., Doblas-Reyes, Francisco, Domeisen, Daniela I.V., Ferranti, Laura, Ilynia, Tatiana, Kumar, Arun, Müller, Wolfang A., Rixen, Michel, Robertson, Andrew W., Smith, Doug M., Takayaka, Yuhei, Tuma, Matthias, Vitart, Frederic, White, Christopher J., Alvarez, Mariano S., Ardilouze, Constantin, Attard, Hannah, Baggett, Cory, Balsameda, Magdalena A., Beraki, Asmeron F., Bhattacharjee, Partha S., Bilbao, Roberto, Andrade, Felipe M. de, DeFlorio, Michael J., Díaz, Leandro B., Ehsan, Muhammad Azhar, Fragkoulidis, Georgios, Grainger, Sam, Green, Benjamin W., Hell, Momme C., Infanti, Johanna M., Isensee, Katharina, Kataoka, Takahito, Kirtman, Ben P., Klingaman, Nicholas P., Lee, June-Yi, Mayer, Kristen, McKay, Roseanna, Mecking, Jennifer V, Miller, Douglas E., Neddermann, Nele, Justin Ng, Ching Ho, Ossó, Albert, Pankatz, Klaus, Peatman, Simon, Pegion, Kathy, Perlwitz, Judith, Recalde-Coronel, G. Cristina, Reintges, Annika, Renkl, Christoph, Solaraju-Murali, Balakrishnan, Spring, Aaron, Stan, Cristiana, Sun, Y. Qiang, Tozer, Carly R., Vigaud, Nicolas, Woolnough, Steven, Yeager, Stephen, Barcelona Supercomputing Center, Merryfield, William J., Baehr, Johanna, Batté, Lauriane, Becker, Emily J., Butler, Amy H., Coelho, Caio A.S., Danabasoglu, Gorkhan, Dirmeyer, Paul A., Doblas-Reyes, Francisco, Domeisen, Daniela I.V., Ferranti, Laura, Ilynia, Tatiana, Kumar, Arun, Müller, Wolfang A., Rixen, Michel, Robertson, Andrew W., Smith, Doug M., Takayaka, Yuhei, Tuma, Matthias, Vitart, Frederic, White, Christopher J., Alvarez, Mariano S., Ardilouze, Constantin, Attard, Hannah, Baggett, Cory, Balsameda, Magdalena A., Beraki, Asmeron F., Bhattacharjee, Partha S., Bilbao, Roberto, Andrade, Felipe M. de, DeFlorio, Michael J., Díaz, Leandro B., Ehsan, Muhammad Azhar, Fragkoulidis, Georgios, Grainger, Sam, Green, Benjamin W., Hell, Momme C., Infanti, Johanna M., Isensee, Katharina, Kataoka, Takahito, Kirtman, Ben P., Klingaman, Nicholas P., Lee, June-Yi, Mayer, Kristen, McKay, Roseanna, Mecking, Jennifer V, Miller, Douglas E., Neddermann, Nele, Justin Ng, Ching Ho, Ossó, Albert, Pankatz, Klaus, Peatman, Simon, Pegion, Kathy, Perlwitz, Judith, Recalde-Coronel, G. Cristina, Reintges, Annika, Renkl, Christoph, Solaraju-Murali, Balakrishnan, Spring, Aaron, Stan, Cristiana, Sun, Y. Qiang, Tozer, Carly R., Vigaud, Nicolas, Woolnough, Steven, and Yeager, Stephen
- Abstract
Climate prediction on subseasonal to decadal time scales is a rapidly advancing field that is synthesizing improvements in climate process understanding and modeling to improve and expand operational services worldwide. Weather and climate variations on subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus broadly remains similar, (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these area, The International Conferences on Subseasonal to Decadal Prediction on which this paper is based were sponsored by: US CLIVAR, NSF, UCAR, NCAR and its Climate and Global Dynamics Laboratory (CGD), NOAA’s Climate Variability and Predictability (CVP) and Modeling, Analysis, Predictions and Projections (MAPP) Programs, Copernicus Climate Change Service, IPSL, and WWRP/WCRP’s Subseasonal-to-Seasonal (S2S) Prediction Project., Postprint (author's final draft)
- Published
- 2020