1 / 18

Seasonal Predictability of the North American Monsoon using the Combined Pacific Variability Mode

Stephen W. Bieda III ATMO 529: OBJ ANALY/ATMO+REL SCI 5 December 2007. Seasonal Predictability of the North American Monsoon using the Combined Pacific Variability Mode. Motivation for Research.

hetal
Download Presentation

Seasonal Predictability of the North American Monsoon using the Combined Pacific Variability Mode

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. Stephen W. Bieda III ATMO 529: OBJ ANALY/ATMO+REL SCI 5 December 2007 Seasonal Predictability of the North American Monsoon using the Combined Pacific Variability Mode

  2. Motivation for Research • The Combined Pacific Variability Mode (henceforth CPVM) has a known relationship with NAMS variability at onset. (referenced in Castro et al. 2007, J. Climate) • Further research by Bieda et al. 2007 suggests that the CPVM has a known relationship with transient inverted troughs during the North American Monsoon Season (NAMS). Negative (positive) CPVM provides more (less) of these transient features during the season, with more (less) precipitation falling over a northward (southward) deviated track. • A predictive seasonal parameter for the NAMS still has yet to be found.

  3. NAME Regions Tier I and II Source: NAME Science Plan 2004

  4. Definition • CPVM – Combined Pacific Variability Mode: uses the two (2) rotated EOFs of global SSTs which are associated with interannual and interdecadal variability in the tropical Pacific Ocean. (referenced in Castro et al. 2007, J. Climate)

  5. CPVM Source: Castro et al. (2007)

  6. Model Precip w/CPVM (Castro et al. 2007) CPVM Positive – CPVM Negative Years showing the basic principle of onset relationship.

  7. Datasets • Time Frame: All year for ocean, JJA for Precipitation • Years covered: 1979 - 2006 • Datasets Used: • International Comprehensive Ocean-Atmosphere Data Set (1979-2007): 1°x1° dataset of monthly Ocean SSTs • North American Regional Reanalysis (1979- 2006): 0.3°x0.3° dataset of monthly precipitation • Region covered: • NARR - boundaries were 10N – 42N, 122W – 90W (NAME Tier II).

  8. Methods of Analysis • Convert the summer precipitation totals to SPI over the Tier II domain. • Perform the REOF analysis of global SSTs by the methods of Castro et al. (2007a,b). • Lag the dominant modes of SSTs (i.e. JFM, FMA, etc.), to perform a “hindcast” of an averaged monsoon season.

  9. Results – NDJ CPVM Corr.

  10. Results – DJF CPVM Corr.

  11. Results – JFM CPVM Corr.

  12. Results – FMA CPVM Corr.

  13. Results – MAM CPVM Corr.

  14. Results – AMJ CPVM Corr.

  15. Discussion • I’m not convinced that I personally calculated the CPVM correctly, due to the results that were generated. • The reason is that the correlation should be increasing over the area as we approach the NAM season, rather than remaining steady.

  16. Continued Work • Work will continue to correct the mistakes made, and generate composites that will hopefully be more convincing.

  17. References • Castro, C.L. R.A. Pielke Sr., J.O. Adegoke, 2007: Investigation of the Summer Climate of the Contiguous U.S. and Mexico Using the Regional Atmospheric Modeling System (RAMS). Part A: Model Climatology (1950-2002). J. Clim.,20, 3844-3865.   • Castro, C.L., R.A. Pielke Sr., J.O. Adegoke, S.D. Schubert, P.J. Pegion, 2007: Investigation of the Summer Climate of the Contiguous U.S. and Mexico Using the Regional Atmospheric Modeling System (RAMS). Part B: Model Climate Variability. J. Clim., 20, 3866-3887. • Mesinger, F., G. DiMego, E. Kalnay, K. Mitchell, P.C. Shafran, W. Ebisuzaki, D. Jovic, J. Woollen, E. Rogers, E.H. Berbery, M.B. Ek, Y. Fan, R. Grumbine, W. Higgins, H. Li, Y. Lin G. Manikin, D. Parrish, W. Shi, 2006: North American Regional Reanalysis. Bull. AMS, 87, 343-360. • North American Monsoon Experiment: Science and Implementation Plan 2004: NAME Science Working Group [Available on line at http://www.cpc.ncep.noaa.gov/products/precip/monsoon/NAME.html]. • Worley, S.J., S.D. Woodruff, R.W. Reynolds, S.J. Lubker, and N. Lott, 2005: ICOADS Release 2.1 data and products. Int. J. Climatol. (CLIMAR-II Special Issue), 25, 823-842 (DOI: 10.1002/joc.1166).

  18. Questions or Comments • Thank you for your time.

More Related