The CNR-ISAC monthly forecasting system is involved in the joint WWRP/WCRP Subseasonal-to-Seasonal Prediction (S2S) Project.
Data are contributed in quasi real time to the S2S database since November 2015 and are available for download, through log in, at
ECMWF and
CMA.
Also, different graphical products based on the S2S forecasts are made available by dr. Mio Matsueda at http://gpvjma.ccs.hpcc.jp/S2S/.
Yan, Y., Zhu, C., & Liu, B. (2023). Subseasonal predictability of the July 2021 extreme rainfall event over Henan China in S2S operational models. Journal of Geophysical Research: Atmospheres, 128, e2022JD037879. https://doi.org/10.1029/2022JD037879, 2023
Brum, M. and Schwanenberg, D.: Long-term evaluation of the Sub-seasonal to Seasonal (S2S) dataset and derived hydrological forecasts at the catchment scale, EGUsphere [preprint],https://doi.org/10.5194/egusphere-2022-419, 2022
Chwat, D., Garfinkel, C. I., Chen, W., & Rao, J. (2022). Which Sudden Stratospheric Warming Events are Most Predictable? Journal of Geophysical Research: Atmospheres, 127, e2022JD037521. https://doi.org/10.1029/2022JD037521
Li, W., Song, J., Hsu, P., & Wang, Y. (2022). Evaluation of the Forecast Performance for Week-2 Winter Surface Air Temperature from the Model for Prediction Across Scales - Atmosphere (MPAS-A), Weather and Forecasting. https://doi.org/10.1175/WAF-D-22-0054.1
Deoras, A., Turner, A.G. and Hunt, K.M.R. (2022), The structure of strong Indian monsoon low-pressure systems in Subseasonal-to-Seasonal prediction models. Q J R Meteorol Soc. https://doi.org/10.1002/qj.4296
Wie, J.; Kang, J.; Moon, B.-K. Superensemble Approach to S2S Model for Predicting Surface Air Temperature in Summer in East Asia from 2016 to 2020. Atmosphere 2022, 13, 701. https://doi.org/10.3390/atmos13050701
Cowan, T., Wheeler, M.C., de Burgh-Day, C. et al. Multi-week prediction of livestock chill conditions associated with the northwest Queensland floods of February 2019. Sci Rep 12, 5907 (2022). https://doi.org/10.1038/s41598-022-09666-z
Lin, H., Mo, R., & Vitart, F. (2022). The 2021 western North American heatwave and its subseasonal predictions. Geophysical Research Letters, 49, e2021GL097036. https://doi.org/10.1029/2021GL097036
Lawrence, Z. D., Abalos, M., Ayarzagüena, B., Barriopedro, D., Butler, A. H., Calvo, N., de la Cámara, A., Charlton-Perez, A., Domeisen, D. I. V., Dunn-Sigouin, E., García-Serrano, J., Garfinkel, C. I., Hindley, N. P., Jia, L., Jucker, M., Karpechko, A. Y., Kim, H., Lang, A. L., Lee, S. H., Lin, P., Osman, M., Palmeiro, F. M., Perlwitz, J., Polichtchouk, I., Richter, J. H., Schwartz, C., Son, S.-W., Statnaia, I., Taguchi, M., Tyrrell, N. L., Wright, C. J., and Wu, R. W.-Y.: Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems, Weather Clim. Dynam., 3, 977-1001, https://doi.org/10.5194/wcd-3-977-2022, 2022.
Stan, C., Zheng, C., Chang, E. K., Domeisen, D. I., Garfinkel, C. I., Jenney, A. M., Kim, H., Lim, Y., Lin, H., Robertson, A., Schwartz, C., Vitart, F., Wang, J., & Yadav, P. (2022). Advances in the prediction of MJO-Teleconnections in the S2S forecast systems, Bulletin of the American Meteorological Society (2022). https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-21-0130.1/BAMS-D-21-0130.1.xml
Yan, Y., Liu, B., Zhu, C. et al.: Subseasonal forecast barrier of the North Atlantic oscillation in S2S models during the extreme mei-yu rainfall event in 2020. Clim Dyn (2021). https://doi.org/10.1007/s00382-021-06076-1
The January 2021 Sudden Stratospheric Warming and Its Prediction in Subseasonal to Seasonal Models. Jian Rao,Chaim I. Garfinkel,Tongwen Wu,Yixiong Lu,Qian Lu,Zhuoqi Liang, 2021,https://doi.org/10.1029/2021JD035057
Lin, H., Huang, Z., Hendon, H., & Brunet, G. (2021). NAO Influence on the MJO and its Prediction Skill in the Subseasonal-to-Seasonal Prediction Models, Journal of Climate, 34(23), 9425-9442. https://journals.ametsoc.org/view/journals/clim/34/23/JCLI-D-21-0153.1.xml
Schwartz, C., Garfinkel, C. I., Yadav, P., Chen, W., and Domeisen, D.: Stationary Waves and Upward Troposphere-Stratosphere Coupling in S2S Models, Weather Clim. Dynam., 3, 679-692, https://doi.org/10.5194/wcd-2021-58, 2022.
Endris, H. S., Hirons, L., Segele, Z. T., Gudoshava, M., Woolnough, S., & Artan, G. A. (2021). Evaluation of the Skill of Monthly Precipitation Forecasts from Global Prediction Systems over the Greater Horn of Africa, Weather and Forecasting, 36(4), 1275-1298. https://journals.ametsoc.org/view/journals/wefo/36/4/WAF-D-20-0177.1.xml
Pei-Ning Feng & Hai Lin (2021) Modulation of the MJO-Related Teleconnection by the QBO in Subseasonal-to-Seasonal Prediction Models, Atmosphere-Ocean, https://doi.org/10.1080/07055900.2021.1944045
Zheng, C., Kar-Man Chang, E., Kim, H., Zhang, M., & Wang, W. (2021). Subseasonal Prediction of Wintertime Northern Hemisphere Extratropical Cyclone Activity by SubX and S2S Models, Weather and Forecasting, 36(1), 75-89.https://doi.org/10.1175/WAF-D-20-0157.1
Feng, P., Lin, H., Derome, J., & Merlis, T. M. (2021). Forecast Skill of the NAO in the Subseasonal-to-Seasonal Prediction Models, Journal of Climate, 34(12), 4757-4769, https://doi.org/10.1175/JCLI-D-20-0430.1
Deoras, A., Hunt, K. M. R., & Turner, A. G. (2021). Comparison of the Prediction of Indian Monsoon Low Pressure Systems by Subseasonal-to-Seasonal Prediction Models, Weather and Forecasting, 36(3), 859-877. https://journals.ametsoc.org/view/journals/wefo/36/3/WAF-D-20-0081.1.xml
Kueh, MT., Lin, CY. The 2018 summer heatwaves over northwestern Europe and its extended-range prediction. Sci Rep 10, 19283 (2020). https://doi.org/10.1038/s41598-020-76181-4
Rao, J., Garfinkel, C. I., White, I. P., & Schwartz, C. (2020). The Southern Hemisphere minor sudden stratospheric warming in September 2019 and its predictions in S2S models. Journal of Geophysical Research: Atmospheres, 125, e2020JD032723. https://doi.org/10.1029/2020JD032723
Pan, B., K. Hsu, A. AghaKouchak, S. Sorooshian, and W. Higgins, 2019: Precipitation Prediction Skill for the West Coast United States: From Short to Extended Range. J. Climate, 32, 161-182, https://doi.org/10.1175/JCLI-D-18-0355.1
Rao, J., Garfinkel, C. I., Chen, H., & White, I. P. (2019). The 2019 New Year stratospheric sudden warming and its real-time predictions in multiple S2S models. Journal of Geophysical Research: Atmospheres, 124, 11155-11174. https://doi.org/10.1029/2019JD030826
Wang, S., Sobel, A.H., Tippett, M.K. et al. Prediction and predictability of tropical intraseasonal convection: seasonal dependence and the Maritime Continent prediction barrier. Clim Dyn 52, 6015-6031 (2019). https://doi.org/10.1007/s00382-018-4492-9
Zhou, Y., Yang, B., Chen, H. et al. Effects of the Madden-Julian Oscillation on 2-m air temperature prediction over China during boreal winter in the S2S database. Clim Dyn 52, 6671-6689 (2019). https://doi.org/10.1007/s00382-018-4538-z
Wang, S., Tippett, M. K., Sobel, A. H., Martin, Z., & Vitart, F. ( 2019). Impact of the QBO on prediction and predictability of the MJO convection. Journal of Geophysical Research: Atmospheres, 124, 11766-11782. https://doi.org/10.1029/2019JD030575
Li, W., J. Chen, L. Li, H. Chen, B. Liu, C. Xu, and X. Li, 2019: Evaluation and Bias Correction of S2S Precipitation for Hydrological Extremes. J. Hydrometeor., 20, 1887-1906, https://doi.org/10.1175/JHM-D-19-0042.1
D. I., Domeisen, Butler, A. H., Charlton-Perez, A. J., Ayarzaguena, B., Baldwin, M. P., Dunn-Sigouin, E. et al. (2020). The role of the stratosphere in subseasonal to seasonal prediction: 2. Predictability arising from stratosphere-troposphere coupling. Journal of Geophysical Research: Atmospheres, 125, e2019JD030923. https://doi.org/10.1029/2019JD030923
Domeisen, D. I. V., Butler, A. H., Charlton-Perez, A. J., Ayarzaguena, B., Baldwin, M. P., Dunn-Sigouin, E., et al (2020). The role of the stratosphere in subseasonal to seasonal prediction: 1. Predictability of the stratosphere. Journal of Geophysical Research: Atmospheres, 125, e2019JD030920.https://doi.org/10.1029/2019JD030920
Hai Lin, Ruping Mo, Frederic Vitart & Cristiana Stan (2019) Eastern Canada Flooding 2017 and its Subseasonal Predictions, Atmosphere-Ocean, 57:3, 195-207, https://doi.org/10.1080/07055900.2018.1547679
Minami, A., & Takaya, Y. (2020). Enhanced Northern Hemisphere correlation skill of subseasonal predictions in the strong negative phase of the Arctic Oscillation. Journal of Geophysical Research: Atmospheres, 125, e2019JD031268. https://doi.org/10.1029/2019JD031268
de Andrade, F.M., Coelho, C.A.S. & Cavalcanti, I.F.A. Global precipitation hindcast quality assessment of the Subseasonal to Seasonal (S2S) prediction project models. Clim Dyn 52, 5451-5475 (2019). https://doi.org/10.1007/s00382-018-4457-z
Quinting, J. F., & Vitart, F. (2019). Representation of synoptic-scale Rossby wave packets and blocking in the S2S prediction project database. Geophysical Research Letters, 46, 1070-1078. https://doi.org/10.1029/2018GL081381
Zheng, C., Chang, E. K.-M., Kim, H., Zhang, M., & Wang, W. (2019). Subseasonal to seasonal prediction of wintertime northern hemisphere extratropical cyclone activity by S2S and NMME models. Journal of Geophysical Research: Atmospheres, 124, 12057-12077. https://doi.org/10.1029/2019JD031252
Son, S.-W., Kim, H., Song, K., Kim, S.-W., Martineau, P., Hyun, Y.-K., & Kim, Y. (2020). Extratropical prediction skill of the Subseasonal-to-Seasonal (S2S) prediction models. Journal of Geophysical Research: Atmospheres, 125, e2019JD031273. https://doi.org/10.1029/2019JD031273
Lim, Y., Son, S., Marshall, A.G. et al. Influence of the QBO on MJO prediction skill in the subseasonal-to-seasonal prediction models. Clim Dyn 53, 1681-1695 (2019). https://doi.org/10.1007/s00382-019-04719-y
Lim, Y., S. Son, and D. Kim, 2018: MJO Prediction Skill of the Subseasonal-to-Seasonal Prediction Models. J. Climate, 31, 4075-4094, https://doi.org/10.1175/JCLI-D-17-0545.1
Jie, W., Vitart, F., Wu, T. and Liu, X. (2017), Simulations of the Asian summer monsoon in the subseasonal to seasonal prediction project (S2S) database. Q.J.R. Meteorol. Soc., 143: 2282-2295. https://doi.org/10.1002/qj.3085
Vitart, F. (2017), Madden-Julian Oscillation prediction and teleconnections in the S2S database.Q.J.R. Meteorol. Soc, 143: 2210-2220. https://doi.org/10.1002/qj.3079
All plots shown in these pages are created with the NCAR Command Language (Version 6.1.2) [Software]. (2013).
Boulder, Colorado: UCAR/NCAR/CISL/VETS. http://dx.doi.org/10.5065/D6WD3XH5