1. business and industrial
2. agriculture and forestry
3. crops and seed

Facilitating the Use of Drought Early Warning
Information through Interactions with
Stakeholders
Jason Otkin
University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies
Mark Shafer
University of Oklahoma, Oklahoma Climatological Survey
Mark Svoboda
University of Nebraska-Lincoln, Drought Mitigation Center
Brian Wardlow
University of Nebraska-Lincoln, CALMIT
Martha Anderson
USDA-Agricultural Research Service, Hydrology and Remote Sensing Laboratory
Funding: NOAA Climate Program Office Sectoral Applications
Research Program (SARP) and NOAA Climate Program Office
Modeling Analysis, Predictions and Projections (MAPP)
Evaporative Stress Index (ESI)
•  Remotely sensed land surface temperatures retrieved from GOES
thermal infrared imagery can provide a reliable signal of incipient
drought stress
•  As root zone soil moisture decreases, canopy temperatures
rise in comparison to unstressed vegetation because less
energy is being used for evaporation
•  The ALEXI land surface energy balance model uses this
relationship to estimate evapotranspiration (ET) at high resolution
•  Drought severity is inferred from reductions in the ratio of real
to potential ET, as expressed by the Evaporative Stress Index
•  Negative ESI anomalies indicate drier than average conditions,
whereas positive anomalies indicate wetter conditions
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
2011 Flash Drought – Domain Images
USDM
USDM
ESI
Rainfall
ESI_04WK
PRECIP_04WK
May
May
April
April
•  Highly variable
rainfall during April
and May (wet in the
east, dry in the west)
June
June
•  Drought conditions
rapidly expanded
northward during June
and July
July
July
•  USDM indicates that
parts of OK and AR
experienced up to a 3
category increase in
drought severity
during July
D0 D1 D2 D3 D4
Drought Category
-2.0
-1.0
0
1.0
ESI Anomaly
2.0
0
5
10
15
20
Accumulated Precipitation (cm)
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
2011 Flash Drought – Time Series
•  Time series of surface
weather conditions across
eastern OK and western AR
DRIVERS
RESPONSE
•  Hot temperatures, strong
winds and diminished cloud
cover anomalies developed
by the end of May and then
persisted all summer
•  Strongly negative ESI
values by the middle of
June indicate that the
vegetation was unable to
adequately respond to the
extreme conditions
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
2011 Flash Drought – “Plume” Diagram
Current
Changes
•  Change indicators
show that conditions
were already starting
to rapidly deteriorate
at the end of May
•  Rapid deterioration
began one month
before similar large
changes occurred in
the USDM
•  First three columns show the USDM, weekly rainfall, and 3-month SPI
•  Next three columns show 2, 4, and 8 week ESI composites
•  Last twelve columns show weekly ESI change variables
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
Rapid Change Index
•  The Rapid Change Index (RCI) was developed to encapsulate the
accumulated rate of moisture stress change occurring during the
full duration of a rapid change event
•  It is designed to identify areas experiencing either rapid increases
or rapid decreases in moisture stress
•  It is computed using “standardized change anomalies” depicting
how rapidly the ESI is changing with time
•  Negative RCI values correspond to periods of rapidly drying
conditions while positive values indicate improving conditions
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
2012 Central U.S. Flash Drought
Rainfall
ESI
RCI
USDM
•  Large negative RCI values
in the top row indicate that
moisture stress was rapidly
increasing at the beginning
of summer
•  Impressive scope of the
unusually rapid decrease in
the ESI anomalies is clearly
depicted by the large area
of negative RCI values
•  Initial appearance of
negative RCI values led the
introduction of severe
drought in the USDM by
more than 4 weeks
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
Focus Group Meeting Description
•  Meetings convened with stakeholders from NIDIS Southern Plains
(Norman, OK) and Missouri River Basin (Lincoln, NE) pilot regions
in August 2014
•  All attendees invited based on prior interest in drought mitigation
•  30 people with diverse backgrounds attended the meetings
•  70% researchers, 20% government, and 10% agriculture
•  Each meeting included an interactive discussion on the common
characteristics of flash drought events and their societal impacts
•  Attendees were introduced to the ESI and associated drought
monitoring products such as the RCI and ESI change anomalies
•  Attendees were asked to assess utility of these datasets through
group discussions, analysis of drought events, and a questionnaire
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
ESI Drought Early Warning Assessment
•  Most attendees had a favorable opinion of the ESI (89%) and RCI
(68%) datasets
•  Attendees generally preferred to view these variables in map form
when assessing current drought conditions
•  Most helpful when used together because ESI shows current
conditions, whereas RCI shows how they have changed
•  Feedback was less favorable when assessing the ESI change
anomalies because they found them more difficult to interpret
•  Standardized change anomalies, not numerical differences
•  Preferred the RCI even though it is computed using the ESI
change anomalies
•  Indicates that the RCI formulation adds value
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
ESI Drought Early Warning Assessment
•  Mixed reaction to the “plume” diagrams – opinion would likely
improve after they gain more experience using them
•  Many people appreciated how they provide a concise view of the
current drought status and how things are changing with time
•  Feedback was unfavorable (31% liked them) at the first meeting,
but much more positive (80%) at the second meeting
•  Better response at the second meeting was mostly due to the
presenters taking more time to explain how to use them
•  Shows the need to allow sufficient time to thoroughly explain
new visualization methods to the general public
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
Potential Drought Early Warning Applications
•  Ranchers could use early warning of worsening conditions to preemptively move livestock or purchase supplemental feed
•  Farmers could use drought early warning when making marketing
decisions or to decide whether to plant a cover crop
•  Government agencies use information to reposition resources to
better prepare for drought in specific regions
•  Incorporation of drought early warning indicators in the USDM
could lead to earlier drought declarations
•  Could lead to earlier implementation of emergency farm
programs that would promote more timely drought relief
measures when flash droughts occur
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015
Flash Drought References
Otkin, J. A., M. Shafer, M. Svoboda, B. Wardlow, M. C. Anderson, C. Hain, and J.
Basara, 2015: Facilitating the use of drought early warning information through
interactions with stakeholders. Bull. Am. Meteorol. Soc., in press.
Otkin, J. A., M. C. Anderson, C. Hain, and M. Svoboda, 2015: Using temporal
changes in drought indices to generate probabilistic drought intensification
forecasts. J. Hydrometeor., 16, 88-105.
Otkin, J. A., M. C. Anderson, C. Hain, and M. Svoboda, 2014: Examining the
relationship between drought development and rapid changes in the Evaporative
Stress Index. J. Hydrometeor., 15, 938-956.
Otkin, J. A., M. C. Anderson, C. Hain, I. Mladenova, J. Basara, and M. Svoboda,
2013: Examining flash drought development using the thermal infrared based
Evaporative Stress Index. J. Hydrometeor., 14, 1057-1074.
Anderson, M. C., C. Hain, J. A. Otkin, X. Zhan, K. Mo, M. Svoboda, W. Dulaney,
and A. Pimstein, 2013: An intercomparison of drought indicators based on thermal
remote sensing and NLDAS-2 simulations with U.S. Drought Monitor
classifications. J. Hydrometeor., 14, 1035-1056.
Climate Prediction Applications Science Workshop, Las Cruces, NM, 25 March 2015