Spring surface temperature anomalies in the western U.S. and summer droughts
in the Southern Plains
The Southern Plains (SP) are one of the most drought-prone regions in the United States.
In the summer of 2011, Texas and parts of several surrounding states suffered a drought nearly as severe
as some of the world's previous worst. The observational evidence has suggested that conditions with
colder spring surface temperature in the Western U.S. have a high probability of association with drier
summer in the SP. Based on this observed association, we have conducted a preliminary modeling study
to explore the relationship between spring land surface temperature (LST) and subsurface temperature
(SUBT) anomaly in the Western U.S. and June precipitation in the Southern U.S. and possible
mechanisms. The imposed SUBT anomaly in the simulation is used to generate the observed LST
anomaly, which directly effects the land/atmosphere interaction. The Rossby wave propagation in
westerly mean flow generated by the surface heating and the steering flow have been identified as
contributing to the LST/precipitation relationship.
Scientific Merit: In this proposal, we will extend our previous exploratory case study to
investigate the impact of SUBT over the Western U.S. during the spring on the SP summer drought using
a general circulation model (GCM) and a nested regional climate model (RCM). The RCM will
downscale the GCM simulation with high resolution. We conjecture that the low LST over the high
elevation area in the Western U.S. during the spring contributed to the summer droughts, including the
extraordinary 2011 Texas drought, in the SP. The SUBT memory prolongs the snow effect and plays
an important role in producing LST anomaly and teleconnections to summer drought in the SP
(Hypothesis I). Furthermore, the observational data show that the LST anomaly could last as long as four
months, but our current land soil scheme with no frozen soil processes was only able to hold the LST and
SUBT anomalies for much shorter time periods, which would undermine the LST and SUBT effect in
model simulations. Evidence has suggested that past soil temperature anomalies are stored as variations
in the amount of ground ice and that a deep soil column is needed to capture variability in the frozen
layer. We conjecture that ignoring frozen soil processes and deep soil heat storage in the model
substantially undermines the effect of spring SUBT memory in the Western U.S. and its impact on the
SP regional climate and the summer drought. Frozen soil processes and adequate soil depth are
required in the simulation to capture proper variability associated with the time-delayed
LST/SUBT/snow/atmosphere feedbacks (Hypothesis II). Sea surface temperature (SST) anomalies have
been considered as a major cause of the drought in the Great Plains. The local soil moisture and
vegetation feedbacks have also been studied for their roles in the drought. SST as well as local soil
moisture and vegetation will also be included for the SP drought study for comparison with the SUBT
effect. We conjecture that all four of these factors have to be included to obtain a comprehensive
understanding of the drought in SP and to produce a robust and reliable prediction of the drought
(Hypothesis III). A set of experiments will be conducted to test these hypotheses, and analyses will be
conducted to understand the mechanisms. These hypotheses, which are based on observational data and
our preliminary case study, have never been proposed or tested before.
Broad Impact: Episodes of extreme drought and heat can have serious societal, agricultural,
economic, and ecological impacts across the U.S. This proposal is very timely in response to the
extraordinary and disastrous 2011 Texas drought event that has caught national public and scientific
attention, with the causes still largely unknown. With projections suggesting that climate change may
become more extreme in the 21st century, it is imperative to understand the cause of the drought. The
results from this study should provide useful information for disaster prediction, prevention, and
mitigation. The results from this research will also help in understanding the land memory effect due to
snow, frozen soil, and SUBT in teleconnection and will provide useful information for seasonal
prediction. Through presentation, publications, and online approaches, the results from this project will
be presented to other researchers and public.