Drought Causes,Prediction

1
Drought Causes,Prediction
Causes and Prediction of Drought
Randall M. Dole NOAA-CIRES Climate Diagnostics
Center
Drought in Great Plains, ca. 1935
Fires in the West, 2002
2
Drought context
Context Importance of Drought
North Platte river, May 22, 2002 Mean flow 1310
cu. ft/sec Observed flow 0 cu. ft/sec.

• Droughts are not simply climate phenomena they
  have profound societal, economic, and
  environmental consequences.
• Traditional federal/state response to drought has
  been reactive. We are moving toward a more
  proactive approach - National Drought
  Preparedness Act of 2003. Implications for NOAA
  wx/climate services --

3
Drought characteristics - definitions and types
Drought characteristics
a. Definition(s) No unique definition. National
Drought Policy Commission a persistent and
abnormal moisture deficiency having adverse
impacts on vegetation, animals, and people. b.
Types Meteorological - rainfall deficit (better
P - E ( supply-demand)) Agricultural - topsoil
moisture deficit crop impacts. Hydrological -
surface or sub-surface water supply
shortage. Typically, meteorological
agricultural
hydrological. Similar sequence for recovery. For
more info, on defintions, see National Drought
Mitigation Center website http//www.drought.unl.
edu/index.htm/ .
4
Drought time scales

c. Time scales Droughts span a broad
range of time scales, from short-term flash
droughts that may have significant agricultural
impacts, to multi-year or even decadal droughts
(1930s, 1950s, etc.) Paleoclimate evidence
suggests that in the last 1000 years parts of the
U.S. have experienced mega-droughts that
persisted for decades.
Droughts
5
Drought Indices

• d. Drought indices
• Numerous drought measures - all have strengths
  and shortcomings. Some of the most common
  measures
• Percent of normal precipitation (problem
  non-normal dist.)
• Standardized precipitation index, or SPI (only
  considers P)
• Crop Moisture Index, CMI - simple water balance,
  top layer
• Palmer Drought Severity Index (PDSI) - responds
  slowly
• Deciles or quintiles - lowest quintile much
  below normal, need fairly long, stable climate
  record.

6
SPI

Examples - 2002 Case Standardized
Precipitation Index (June 2002)
7
SPI time series
SPI local time history (created from WRCC website
- 08/02)
Standardized Precipitation Index Northern New
Mexico
Normal
Drought
Severe
1
2
3
4
6
5
Current
Years before present
8
CMI

Crop Moisture Index (CMI) - 2002 Case (from CPC -
24 August 2002)
The CMI is most useful for short-term monitoring
(e.g., for ag.)
9
PDSI

Palmer Drought Severity Index - 2002 Case (from
CPC - 24 August 2002)
The PDSI is more useful for monitoring long-term,
hydrological drought.
10
PDSI time series -area coverage
PDSI- area coverage of severe drought
Percent area under severe or worse drought in
western US and for Contiguous US. Black curve
based on 5-month running mean of monthly PDSI
values. Red curve shows 5-year running mean
values.
11
U.S. Drought Monitor.
National Drought Monitor -2002 case represents
synthesis of inputs
Most direct impacts on water supply
(and demand), agriculture, fire risk. But
manifold indirect impacts as well, e.g., on
recreation, energy production, water quality, air
quality, ecosystems, endangered species.
12
Current CMI
Current Crop Moisture Index (for period ending
7/26/2003)

13
Current CMI
Current Palmer Drought Severity Index (for
period ending 7/26/2003)

14
U.S. Drought Monitor - current.
Current Drought Monitor (7/22/2003)

15
Take home points - monitoring
Drought Monitoring - take home points

• There is no unique definition of drought, nor is
  there a best drought index - all have strengths
  and limitations.
• Consider impacts - the human dimension.
• Keep in mind the types of drought, and their lag
  relationships.
• Be wary of calling a premature end to the
  drought hydrological impacts may persist well
  after precipitation has returned to near normal.
• Key factors to monitor in drought include
  severity, longevity, spatial pattern and scale.
  Impacts will vary regionally and depending on
  time of year.
• There are a number of excellent web resources
  available.

16
Monitoring -Key web resources.
Drought monitoring - some key resources

• Climate Prediction Center - http//www.cpc.ncep.n
  oaa.gov/
• NDMC - http//www.drought.unl.edu/index.htm
• Climate Diagnostics Center - http//www.cdc.noaa.
  gov/
• Western Region Climate Center -
  http//wrcc.sage.dri.edu/

17
Drought causes - intro.
Drought Causes
You are asked, What is the cause of this
drought?
And your answer is
18
Anticyclone effects
An unusually persistent upper-level ridge over
the region.

• General contributing factors are anomalous
  subsidence, changes in horizontal moisture
  transports, and shifts in the storm tracks.
• Persistent upper-level ridges are often
  identified as the proximate cause of drought
  conditions. Subsidence occurs downshear of ridge
  axis. Suppresses precipitation in several ways
• Adiabatic warming inhibits large-scale
  condensation
• Mid-tropospheric warming produces static
  stabilization
• Low-level divergence inhibits moisture
  convergence, is frontolytical.
• Even relatively weak subsidence can strongly
  suppress precipitation.

19
Role of Moisture transports
Role of Anomalous Moisture transports 1988
Drought
850 mb Mean Moisture Flux (April - June)
850 mb Anomalous Flux (April-June, 1998)
(from Lyon and Dole, 1995)
20
What causes the anticyclone?
Next question
What is the cause of this unusual flow pattern?
21
Drought causes - spatial patterns
An important diagnostic clue spatial pattern
The 1998-2002 drought was part of a larger global
pattern.
22
Perfect Ocean for Drought
During the same time - persistent tropical SST
anomalies
Pacific sea surface temperature on the equator,
1998-2002
Unusual warmth of the warm pool
Multi-year La Niña since 1998
23
La Nina impacts
La Niña Effects on U. S. Precipitation
La Niña Composite (Oct.-May) (created off
of CDC web site)
La Niñas effects on precipitation are most
robust in SW and SE.
24
Oct.-May P-T anomalies
U.S. Oct-May Precipitation and Temp
Anomalies Averaged for the Period 1998-2002
Temperature Precipitation
gt2F
lt-5
lt-10
25
Simulating Joint Impacts
Idealized experiments to test sensitivity to
tropical SSTs (Hoerling and Kumar, 2003)
Simulating the Joint Impacts of Warm Indian
Ocean and La Niña U.S. Oct-May Temperature And
Precipitation
Temperature
Precipitation
lt-7
gt3F
26
Observed and AGCM anomalies - specified
SSTs(Hoerling and Kumar, 2003)
Observed Temperature and Precipitation
anomalies (June 1998 - May 2002)
Model-simulated Temperature and Precipitation
Anomalies given observed SSTs over this period
27
Land Surface Intro.
Land Surface effects

• Why consider?
• Like SSTs, LS has a memory beyond synoptic
  scales
• After SSTs, it is most likely source for
  seasonal climate predictability.
• Influence on T
• Influence on P

28
Role of land surface processes
Drought changes evapotranspiration rates
(ET) Example Southern Plains, Summer 1980
drought (Lyon and Dole, 1995)
ET decreases during drought. Estimated anomalous
heating rates 1-2 C/ day. Increases likelihood
of heat waves. High Ts increase drought impacts
(demand side).
29
Role of land surface processes - P
LS effects on precipitation

• Studies suggest a link between precipitation and
  anomalous LS conditions, especially for major
  droughts and floods, such as 1980, 1988 droughts,
  1993 floods.
• LS conditions do not initiate droughts. They may
  perpetuate drought conditions, increase the
  likelihood of drought recurrence (midwest), and
  certainly increase drought impacts.
• Main LS effects on p are likely to be in warm
  season.
• Mechanisms are elusive local moisture recycling,
  non-local effects.
• Non-local effects T induces PV flow, moisture
  transport, convergence,stability change changes
  in the elevated mixed layer.

30
Varying effects of remote forcing during drought
Effects of remote and local land surface
processes likely vary during droughts
Studies of various droughts, and mechanistic
experiments suggest that the role of remote and
land surface processes varies during the course
of drought evolution.
(From Hong and Kalnay, 2002, for 1998 drought)
31
Take home points - LS processes
LS effects Summary

• LS processes directly impact weather and climate
  through the surface heat and moisture budgets. ET
  is the key connecting variable, and is strongly
  modulated by soil moisture. At present ET is
  poorly observed is estimated from models.
• The strongest and most direct LS impacts are on
  T, through changes in the surface energy budget.
  Impacts on P are weaker, and may be due to local
  moisture recycling or more subtle non-local
  effects.
• LS climate influences are most evident in warm
  season, when dynamics are relatively weak. LS
  processes are likely increase the probability of
  summer heat waves and may increase the duration
  of droughts.
• Regions that are characterized by large soil
  moisture variance, high ET rates, and a dominance
  of convective precipitation are most likely to be
  sensitive to LS processes (e.g., much of the
  southern and central U.S. in summer).
• There is increasing evidence that deep soil
  moisture may be significant in maintaining
  multi-year droughts over the Great Plains (e.g.,
  in the 1930s).

32
Other factors
Other factors

• Random component - droughts happen.
• Forcing from other ocean regions
  (extratropics, Atlantic)
• Other large scale modes of variability (AO?)
• Solar variations

33
Other factors
The Climate - Weather Connection

• Understanding the links between climate and
  weather (precipitation) variability is vital to
  identifying the causes of droughts.
• To understand droughts, need to understand
  dominant regional and seasonal precipitation
  mechanisms (synoptic-scale, convective,
  orographic --)
• As droughts evolve, they may have feedback
  effects on T and precip., both locally and
  non-locally, that effect the weather
• - T higher maxs., larger diurnal cycles -
• - P In times of drought, all signs of rain
  fail.
• May see higher convective cloud bases, other
  effects.Non-local effects e.g., on dryline,
  convective cap locations?
• Possible development of biases in MOS wx.
  products?

34
Take home points - Causes of Drought
Take home points - Drought Causes

• To understand droughts, it is vital to know the
  processes that produce precipitation and how
  they are influenced by climate variability. This
  will vary regionally and seasonally.
• Time scales and spatial patterns provide
  important clues on drought causes.
• Several factors are likely contribute to severe
  and sustained droughts, such as tropical SST
  forcing, land surface processes, etc. Major
  factors contributing to the 1998-2002 drought
  were the persistent La Niña conditions and a
  record warm Indian Ocean.

35
Causes of drought -Key web resources.
Causes of drought - key web resources

• Climate Prediction Center - http//www.cpc.ncep.n
  oaa.gov/
• -- See expert assessments, discussions,
  long-lead briefings, etc.
• Climate Diagnostics Center - http//www.cdc.noaa.
  gov/
• -- Applications of diagnostic tools for
  interpretations.

36
Drought predictions - basis
Drought Prediction

• For operational purposes, the drought prediction
  problem is to forecast the probability
  distribution of some quantitative drought measure
  or index over a given region and time period.
• Relationship to other operational products
• Very short term - apply weekly outlooks and
  hazards assessments.
• CMI responds relatively rapidly - weekly to
  monthly forecasts relevant.
• PDSI responds slowly - monthly to seasonal and
  longer - seasonal forecasts.
• Consider T forecasts as well as P forecasts.

37
El Nino vs. La Nina

Key point Climate forecasts are always
probabilistic. Model-derived Seasonal
Precipitation probabilities for New Mexico
La Niña
El Niño

• The model results illustrate how wet La Niña
  conditions or dry
• El Niño conditions in New Mexico are both
  possible, but unlikely.

38
Extreme event risks

Empirical estimates of changes in risks of
seasonal precipitation extremes March-May (constr
ucted from CDC website http//www.cdc.noaa.gov/Cl
imaterisks/)
El Niño
La Niña
39
Drought predictions - outlook
Drought Outlook
The current drought outlook (Climate Prediction
Center)
40
Take home points
Drought prediction - take home points

• Climate forecasts are intrinsically probability
  forecasts.
• Beyond a few weeks, the major source for
  predictive skill is related to changes in the
  distribution of tropical heating, particularly
  over the Pacific and Indian Oceans. Most models
  do not simulate this well.
• Users are interested in weather/climate
  information and predictions across a broad range
  of time scales. For up to a few weeks out, use
  model forecasts (consider ensembles, not just
  control) plus CPCs hazard assessment product
  CMI (ag. impacts) responds on these time scales.
• For longer-term conditions, use Drought Outlook
  and monthly and seasonal forecasts. Look at IRI
  and CDCs experimental forecast pages to compare
  similarities and differences among seasonal
  forecast models.

41
Causes of drought -Key web resources.
Drought prediction - key resources

• Climate Prediction Center - http//www.cpc.ncep.n
  oaa.gov/
• Hazards assessment, monthly and seasonal
  forecasts, drought outlooks, experimental
  prediction of PDSI, etc.
• International Research Institute for Climate
  Prediction (IRI) - http//iri.ldeo.columbia.edu/
  
• Climate Diagnostics Center - http//www.cdc.noaa.
  gov/
• Experimental forecast products week two to
  multi-season, model-intercomparisons,
  ENSO-extreme event risks, etc.

42
The End
The End