Speaker:
Prof. Yongkang Xue
Department of Geography
University of California, Los Angeles, CA
Time:
1:00 - 2:00 pm EST, 5 December 2017
Location:
NOAA
Center for Weather and Climate Prediction, Conference Room 3159
5830
University Research Court, College Park, MD 20740
Remote Access: GOTO meeting:
https://global.gotomeeting.com/join/621184917
Meeting ID: 621-184-917
The Dial-in number: 1-877-680-3341
The Participant passcode: 858747
ABSTRACT
Extreme climate events, such as droughts and floods, are important features
of Earth’s climate and have large impacts on society. While studies have
shown connections between sea surface temperature (SST) variability and land
precipitation, they also suggest that SSTs are unable to fully predict these
extreme events. The remote effects of large-scale land surface temperature
(LST) and subsurface temperature (SUBT) anomalies in geographical areas
upstream and closer to the areas of drought and flood have largely been
ignored. Here, evidence from climate observations and model simulations
addresses these effects. Evaluation of observational data using Maximum
Covariance Analysis identifies significant correlations between springtime
LST cold (warm) anomalies in both the northwest U.S. and the Tibetan Plateau
and downstream drought (flood) events in late spring/summer. To support
these observational findings, climate models are used to demonstrate a
causal relationship for two important cases: between spring warm LST/SUBT
anomalies in northwest U.S. and the extraordinary 2015 flood in Southern
Great Plains and adjacent regions; and between spring cold LST/SUBT
anomalies in the Tibetan Plateau and the severe 2003 drought south of the
Yangtze River. The LST/SUBT downstream effects are associated with a
large-scale atmospheric stationary wave extending eastward from the LST/SUBT
anomaly region. The effects of SST in these cases are also tested and
compared with the LST/SUBT effects. These results suggest that consideration
of LST/SUBT anomalies have the potential to add value to intraseasonal
prediction of dry and wet conditions, in particular extreme drought and
flood events.
( Flyer
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Presentation pdf)
