1 / 22

Application of T382 CFS Forecasts for Dynamic Hurricane Season Prediction

Application of T382 CFS Forecasts for Dynamic Hurricane Season Prediction. J. Schemm, L. Long, S. Saha and S. Moorthi NOAA/NWS/NCEP October 21, 2008 The 33rd Climate Diagnostics and Prediction Workshop, Lincoln, NE. Outline. Description of the CFS experiment Datasets Used

donal
Download Presentation

Application of T382 CFS Forecasts for Dynamic Hurricane Season Prediction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Application of T382 CFS Forecasts for Dynamic Hurricane Season Prediction J. Schemm, L. Long, S. Saha and S. Moorthi NOAA/NWS/NCEP October 21, 2008 The 33rd Climate Diagnostics and Prediction Workshop, Lincoln, NE

  2. Outline • Description of the CFS experiment • Datasets Used • IRI Detection and Tracking Method • Analysis of storm activity statistics • Focus on the Atlantic Basin • Statistics • A look at CFS predictions for 2008 • Future plan

  3. CFST382 hurricane season experiments • One of the FY07/08 CTB internal projects • AGCM - 2007 operational NCEP GFS in T382/L64 resolution LSM - Noah LSM OGCM - GFDL MOM3 3. All runs initialized with NCEP/DOE R2 and NCEP GODAS. Initial conditions at 0Z, Apr. 19, 20, (21) and May 15(FY07) for 1981-2007. Forecasts extended to December 1. 4. For May 15 cases, runs in T62 and T126 resolutions also performed.

  4. Datasets • CFS hindcasts at T382 • May 15th Initial Condition • Output at every 3 hours • 1981-2007, 27 years • April 19th and April 20th Initial Condition • Output at every 6 hours • 1981-2008, 28 years • More appropriate ICs for CPC Operational Hurricane Season Outlook • Observations from the HURDAT and JTWC Best Track Dataset • -Tropical depressions and subtropical storms • are not included in storm counts.

  5. Tropical Cyclone Detection Method • Based on method devised by Camargo and Zebiak (2002) at IRI • Detection algorithm uses basin-dependent threshold criteria for three variables • Vorticity, xthresh xthresh = 2sx • 10-m Wind Speed, uthresh uthresh = ugl + suugl= wind speed averaged over all global basins • Vertically integrated temp anomaly, Tthresh • Tthresh = sT/2 • Calculated using only warm-core systems

  6. Eight conditions must be met for a point to be considered a tropical cyclone 1. 850-hPa relative vorticity >xthresh 2. Maximum 10-m wind speed in a 7x7 box >uthresh 3. SLP is the minimum in the centered 7x7 box 4. Temp anomaly averaged over the 7x7 box and three pressure levels (300, 500, & 700 mb) > Tthresh 5. Temperature anomaly averaged over the 7x7 box is positive at all levels (300, 500, & 700 mb) * 6. Temperature anomaly averaged over the 7x7 box at 300mb > 850mb * 7. Wind speed averaged over the 7x7 box at 850mb > 300mb 8. The storm must last for at least 6 hours. * Criteria 5 & 6 define a warm core system.

  7. Storm Tracking • Once a point is designated as a tropical cyclone, the cyclone is tracked forward and backward in time to create a full storm track. • The maximum vorticity in a 5x5 grid around the cyclone is found and a new 3x3 box is formed around it. • At the next time step, if the maximum vorticity in this new box is greater than 3.5 x 10-5 s-1, the procedure is repeated. • This point has become part of the storm track. • If two storm tracks are the same, they are considered the same cyclone and counted as one.

  8. Four NH Ocean Basins

  9. Atlantic Eastern North Pacific Western North Pacific North Indian Examples of Storm Tracks for 4 NH Basins

  10. Atlantic Basin Atlantic Tropical Storms

  11. Eastern Pacific Basin Eastern Pacific Tropical Storms

  12. T382 R2 IC=0515 0.872 IC=0419 0.722 IC=0420 0.671 JJA Nino 3.4 SST Index

  13. T382 R2 IC=0515 0.781 IC=0419 0.629 IC=0420 0.624 JJA Atlantic MDR SST Index

  14. Tropical Storm Origins, 1981-2007 ASO OBS IC=0515 IC=0419 IC=0420

  15. Total 81-93 94-06 El Nino La Nina Neutral IC=0419 0.44 -0.10 0.14 0.86 0.16 0.51 IC=0420 0.33 0.33 0.32 -0.39 0.30 IC=0515 0.35 0.18 0.40 0.55 0.85 0.08 Atlantic Basin Correlations Anomalies of Atlantic Storms N=27 N=13 N=13 N=8 N=5 N=14 0.79 Red= Statistically Significant at 0.95 Correlations based on 27-year anomaly

  16. Correlations Total 81-93 94-06 El Nino La Nina Neutral IC=0419 0.47 0.05 0.23 0.74 0.65 0.35 IC=0420 0.58 0.70 0.15 0.22 0.49 IC=0515 0.66 0.61 0.69 0.52 0.80 0.37 0.90 Red = Statistically Significant at 0.95

  17. 2008 Atlantic Season Summary As of October 17, 2008

  18. Atlantic Basin Prediction for 2008 • Two additional runs were made using July 15th and 16th initial conditions for 2008 only • Used as a trial run for the CPC Hurricane Outlook Update

  19. 2008 May Jun Jul Aug Sep Oct Nov Total 0419 1 1 5 3 2 1 1 14 0421 1 3 3 2 4 2 15 0422 1 3 3 3 1 11 ENSM 1 1.33 3.67 2.33 3 1 0.67 13.33 0715 2 4 3 9 0716 1 4 8 2 1 16 Obs 1 3 4 4 15 Atlantic BasinCFS 2008 Monthly Storm Count 3

  20. 2008 Atlantic Storm Tracks (Courtesy of Unisys) Large number of storms over the Gulf of Mexico this year

  21. Resemble Bertha and Cristobal

  22. .Summary • CFS in T382 resolution exhibits robust climatological seasonal cycle of tropical cyclone over four NH basins. • Warming trend and intensification of hurricane activity in the Atlantic basin captured in the CFS hindcasts. • Fair level of skill in predicting interannual variability of seasonal storm activities based on the limited number of forecast runs. • Continue to increase number of ensemble members for better climatology and storm statistics. Hope to provide input for 2009 Hurricane Season Outlook with real time prediction runs. • Prospect of multi-model ensemble approach for dynamical hurricane season prediction

More Related