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Seasonal Forecasts of Category 4 and 5 Hurricanes and Landfalling Tropical Cyclones using a High-Resolution GFDL Coupled Climate Model

This is a short summary of paper Murakami et al. (2016) [1].

1. Introduction

This study uses a global model recently developed by scientists at GFDL (know as HiFLOR; Murakami et al. 2015)[2] to demonstrate skill in seasonal predictions of landfalling and intense TC frequency. By quadrupling the number of horizontal grid cells of the atmosphere and land components (from a 32-mile to a 15-mile global mesh). HiFLOR leads to substantial improvements in the simulation and prediction of Atlantic TCs, relative to the FLOR model (Vecchi et al. 2014) [3] that is currently used for real-time seasonal predictions through the NMME.

Fig. 1: Clouds from a HiFLOR simulation, showing three hurricanes in the Atlantic and one in West Pacific. (Figure Remik Ziemlinski) Animation available here: http://www.gfdl.noaa.gov/video/hiflor_flat_v7_aug-dec.mp4

2. Main Results

This study focuses on seasonal predictions of TCs over the period 1990-2015, and it is found that:

  1. HiFLOR can skillfully predict year-to-year variations in intense hurricanes in the Atlantic a few months in advance (correlation 0.72 for forecasts on 1-July, with August-October being peak hurricane season, Fig. 2).
  2. The high-resolution predictions exhibited significant skill in predicting landfalling hurricanes in the Caribbean and Continental United States. (Fig. 3)
  3. Improvements in seasonal TC prediction between FLOR and HiFLOR principally due to improved simulation of TCs and the TC response to large-scale climate drivers from increased atmospheric resolution.

Fig. 2 HiFLOR shows skill at predicting year-to-year variations in Atlantic hurricanes and intense hurricanes. Left panel focuses on hurricanes, right panel on intense (Saffir-Simpson Category 4-5) hurricanes in the Atlantic. Adapted from Murakami et al. (2016)[1].


Fig. 3 HiFLOR exhibits skill in predicting year-to-year variability of U.S. and Caribbean landfalling TCs (≥34 knots). Black line shows observed landfalling TC count, green line and dots show predictions with HiFLOR. Adapted from Murakami et al. (2016)[1].

3. Summary

This is the first time that a global general circulation model has successfully demonstrated an ability to predict the observed year-by-year variations in category 4 and 5 hurricanes. These results highlight potential skill of models like HiFLOR for the subseasonal and seasonal prediction of intense TCs.

4. Reference

[1] [pdf] [doi] Murakami, H., G. A. Vecchi, T. L. Delworth, A. T. Wittenberg, S. Underwood, R. Gudgel, X. Yang, L. Jia, F. Zeng, K. Paffendorf, and W. Zhang, 2017: Dominant role of subtropical Pacific warming in extreme eastern Pacific hurricane seasons: 2015 and the future. J. Climate, 30, 243-264.
[Bibtex]
@Article{MURAKAMI2017A,
author = {H. Murakami and Gabriel A. Vecchi and Thomas L. Delworth and Andrew T. Wittenberg and Seth Underwood and Richard Gudgel and Xiaosong Yang and Liwei Jia and Fanrong Zeng and Karen Paffendorf and Wei Zhang},
title = {Dominant role of subtropical Pacific warming in extreme eastern Pacific hurricane seasons: 2015 and the future.},
year = 2017,
volume = 30,
pages = {243-264},
journal = JC,
pdf = {/hiroblog/wp-content/papercite-data/pdf_paper/Murakami_etal_2017A_JCLI.pdf},
doi = {10.1175/JCLI-D-16-0424.1},
}
[2] [pdf] [doi] Murakami, H., G. A. Vecchi, S. Underwood, T. L. Delworth, A. T. Wittenberg, W. G. Anderson, J. -H. Chen, R. G. Gudgel, L. Harris, S. -J. Lin, and F. Zeng, 2015: Simulation and prediction of Category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model. J. Climate, 28, 9058-9079.
[Bibtex]
@Article{MURAKAMI2015A,
author = {Hiroyuki Murakami and Gabriel A. Vecchi and Seth Underwood and Thomas L. Delworth and Andrew T. Wittenberg and Whit G. Anderson and J.-H. Chen and Richard G. Gudgel and Lucas Harris and S.-J Lin and Fanrong Zeng},
title = {Simulation and prediction of Category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model.},
journal = JC,
year = 2015,
volume = 28,
pages = {9058-9079},
pdf = {/hiroblog/wp-content/papercite-data/pdf_paper/Murakami_etal_2015A_JCLI.pdf},
doi = {10.1175/JCLI-D-15-0216.1},
}
[3] [pdf] [doi] Vecchi, G. A., T. Delworth, R. Gudgel, S. Kapnick, A. Rosati, A. T. Wittenberg, F. Zeng, W. Anderson, V. Balaji, K. Dixon, L. Jia, H. -S. Kim, L. Krithnamulthy, R. Msadek, W. F. Stern, S. D. Underwood, G. Villarini, X. Yand, and S. Zhang, 2014: On the seasonal forecasting of regional tropical cyclone activity J. Climate, 27, 7994-8016.
[Bibtex]
@Article{VECCHI2014,
author = {G. A. Vecchi and T. Delworth and R. Gudgel and S. Kapnick and A. Rosati and A. T. Wittenberg and F. Zeng and W. Anderson and V. Balaji and K. Dixon and L. Jia and H.-S. Kim and L. Krithnamulthy and R. Msadek and W.F. Stern and S.D. Underwood and G. Villarini and X. Yand and S. Zhang},
title = {On the seasonal forecasting of regional tropical cyclone activity },
journal = JC,
volume = {27},
pages = {7994-8016},
year = {2014},
doi = {doi:10.1175/JCLI-D-14-00158.1},
pdf = {http://journals.ametsoc.org/doi/pdf/10.1175/JCLI-D-14-00158.1},
}