1 / 22

Characterizing Multidecadal Variability in the Southeastern United States

Characterizing Multidecadal Variability in the Southeastern United States. Marcus Williams March 15, 2010. Outline. Introduction and Background Big Picture My part of the big picture Why it’s relevant Outline of Plan Results and conclusions. Introduction and Background.

emile
Download Presentation

Characterizing Multidecadal Variability in the Southeastern United States

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. Characterizing Multidecadal Variability in the Southeastern United States Marcus Williams March 15, 2010

  2. Outline • Introduction and Background • Big Picture • My part of the big picture • Why it’s relevant • Outline of Plan • Results and conclusions

  3. Introduction and Background • To predict future climate variability, and to interpret this variability with appropriate confidence, it is highly desirable to have an understanding of past variability and climate cycles. • The increased global interest in climate change and it’s impacts has made the need to understand types of long-term variability more pressing. • Regional differences exist in climate variability • Most parts of the world are considered to be warming when examined over a long enough record. • The Southeastern United States along with parts of Europe and Asia have been identified as outliers

  4. Introduction and Background • Easterling et al. 1997 • Analyzed monthly averaged min and max temperatures and DTR at 5400 observing stations around the world • Calculated anomalies from the mean of the base period of 1961 to 1985 for all station in a 5° x 5° lat-lon grid box • P.O.R. of data for study was from 1950-1993

  5. Introduction and Background • In the Southeastern United States (SE US) the El Niño- Southern Oscillation (ENSO) signal is widely recognized as the dominate mode of climate variability. • Ropelewski and Halpert provided research that showed interannual the impacts of ENSO on temperature and precipitation patterns. • Work done by the Intergovernmental Panel on Climate Change addresses climate change on interannual to multidecadal timescales.

  6. Introduction and Background • The analysis presented in this research identifies a mode of variability for the SE US that is of much larger magnitude than the trend, and is influential on a multidecadal timescale. • Analysis has identified a multidecadal regime in the long-term temperature records. • The multidecadal regime shifts from periods warmer than normal temperatures, to periods of colder than normal temperatures.

  7. Multidecadal Variability in the Southeast Alabama Annual Temperature Warm period 1920-1957 Cold period 1958-1998

  8. Multidecadal Variability in the Southeast • Same multi-decadal pattern is displayed in the raw, unadjusted station data • 1920-1957: Warm regime (WR) • 1958-1998: Cold regime (CR) Cold regime 1958-1998 Warm regime 1920-1957

  9. Introduction and Background • The mode of climate variability found in my work has been inadequately discussed in prior studies • Often times these studies describe variability is in the realm of trend analysis. • The periods over which the trends are fitted can greatly influence the significance or even the sign of the trends.

  10. Outline of Plan • Goals of my study i.e characterize the signal • seasonality, • spatial extent, and • temperature extremes • Difference in mean temperatures • PDF • Ranked sum test • Spatial correlation

  11. Key results • Significant shift in temperatures between the two regimes • Prevalent in all seasons and in all of the States of analysis(AL, FL, GA, NC, SC) • Winter minimum temperatures display the strongest shift. • Signal strongest in Alabama, signal inconsistent some seasons for different states.

  12. Difference in mean temperatures • One of the easiest ways to quantify the differences between the two regimes are to compare the mean temperatures • Add text- how was this done; spatial coherence of signal

  13. Difference of Average Maximum Temperature (1958-1998) period minus (1920-1957) period

  14. Difference of Average Minimum Temperature (1958-1998) period minus (1920-1957) period

  15. Camp Hill, AL Winter Minimum Temperature Distribution

  16. Camp Hill, AL Maximum Temperature Distributions

  17. Chapel Hill, NC Summer Maximum Temperature Distribution

  18. Camp Hill, AL Minimum Temperature Distributions

  19. Ranked Sum Test • Description of RS test • Why it’s applicable to my research • Results of RS test • Sub sampling and why

  20. Threshold occurrence • What thresholds where set and why • Results and applications

  21. Conclusions and Applications

More Related