Theme 4: Scales and Sustainability

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Theme 4 Scales and Sustainability Ecological
Effects of Climate Driven Processes Through
Time Kelly T. Redmond Western Regional Climate
Center Desert Research Institute Reno
Nevada Mojave Desert Science Symposium University
of Redlands Redlands California November 16-18,
2004
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Some general points about climate Climate and
fluctuation Fluctuation and variability
an inherent property of climate
Energy and mass Reservoirs
Flows
Typically driven by spatial gradients
Thresholds (including phase changes of key
constituents) Temporal scales
Microseconds to eons - approx 16 orders of
magnitude Boundary conditions on
one scale are initial conditions at others
High and low pressure areas for the
next five minutes Sea
surface temperature for tomorrows forecast
Continental positions for the next
millennium Spatial scales
Microns to planetary - approx 10 orders of
magnitude Climate entails constant
fluctuation, at all scales Fluctuation at
one scale is stasis at another scale
Snail vs turtle perspective
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Change and fluctuation in desert environments
Deserts are defined by aridity, but water is
the major driver of change Highly skewed
precipitation statistics Yuma 17 days per
year with precipitation (every 21 days) 51
hours of precipitation annually (0.6 of the
time) 12 percent of the annual average falls
during the wettest hour Annual average falls
in one day about once per hundred years
Very unlikely that these are stationary
statistics What is a sufficient averaging
interval for calculating event rates?
Deserts spend most of their time in waiting
mode military analogy Wind somewhat
less troublesome, statistically, but still not
easy Temperature more tractable. Temp,
Wind, Rel Hum always present. Recharge
highly nonlinear, mountains and heavy
thunderstorms Climate behavior in driest
environments is tied to wettest areas
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14 Nov 2004 Water Vapor 2100 GMT
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CA Stovepipe Wells 1 SW, Death Valley National
Park (Climate Reference Network) 36.6 N 117.1
W 80 May 6, 2004
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Reanalysis Resolution
Global
Regional (slightly smaller pixel resolution)
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Annual Precipitation PRISM - OSU
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Mean July Max Temperature PRISM - OSU
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Oct-Mar Apr-May-June Fraction of
Annual Total Precipitation, by Season July-Aug
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Jan
Feb
Percent of Annual Precipitation
Mar
Apr
12
May
Jun
Percent of Annual Precipitation
Aug
Jul
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Sep
Oct
Percent of Annual Precipitation
Nov
Dec
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Chaos and nonlinear dynamics Does this subject
have a role? On the face of it,
immediate practical applications seem
elusive. However, there seems much to
offer in terms of appreciating limitations of
knowledge of behavior of system
components. Fundamental and theoretical
limitations, what is simply not
possible. Practical limitations, so we dont
waste our time on the wrong things. The subject
seems to have a great deal of value in informing
us how strongly to hold on to certain beliefs
about our ability to direct events in preferred
directions. It also brings up the subject of
predictability Under what circumstances is
prediction even possible? What situations might
be more predictable than others? (more
predictable greater likelihood of correct
outcome) When should we refrain from prediction,
when should we try? This is a major area of
inquiry in climate and atmospheric
science. Combined physical and biological
systems are incredibly complicated. How
predictable is the evolution of ecological
systems?
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Life must be lived forward, but it can only be
understood backward. - Soren Kierkegaard
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Sat 2004 Nov 14 00 GMT - 000 hr
Sat 2004 Nov 14 0000 GMT - 000 hr
Ensemble Forecasting - 23 members
NOAA Climate Diagnostics Center
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000 Hr Forecast
NOAA Climate Diagnostics Center
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Sat 2004 Nov 14 0000 GMT - 024 hr
Sat 2004 Nov 14 0000 GMT - 048 hr
NOAA Climate Diagnostics Center
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Sat 2004 Nov 14 0000 GMT - 072 hr
Sat 2004 Nov 14 0000 GMT - 120 hr
NOAA Climate Diagnostics Center
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120 Hr Forecast
Wed Eve Nov 24 2004 00 GMT 5 PM PST
NOAA Climate Diagnostics Center
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Sat 2004 Nov 14 0000 GMT - 168 hr
Sat 2004 Nov 14 0000 GMT - 240 hr
NOAA Climate Diagnostics Center
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Sat 2004 Nov 14 0000 GMT - 360 hr
Sat 2004 Nov 14 0000 GMT - 360 hr
NOAA Climate Diagnostics Center
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360 Hr Forecast
NOAA Climate Diagnostics Center
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Sea Surface Temperature Departure from Average
Week of 2004 Oct 31 Nov 06
NOAA Climate Diagnostics Center
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Seasonal precipitation outlook
Nov-Dec-Jan 2004-05 EC means Equal Chances (no
forecast !)
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Six models, 12 opinions, for Northern California.
1900-2100
Precipitation
Temperature
Thanks to Mike Dettinger, Scripps / USGS
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Trends 1966 Feb-Mar-Apr
Trends 1966 Annual, Full Year.
Source Climate Prediction Center
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1 oC
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75 mm
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1 oC
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1 oC
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1 oC
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10 mm
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Southern Nevada Climate Division Nov-April
Precipitation 1895-2004
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Southern Nevada Climate Division Nov-April
Temperature 1895-2004
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For sustainability The climate backdrop may be
changing.
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Desert Drought How do you recognize it
???
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Standardized Precipitation Index Percentile 01
Month thru Oct 2004
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Standardized Precipitation Index Percentile 12
Month thru Oct 2004
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Standardized Precipitation Index Percentile 72
Month thru Oct 2004
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Standardized Precipitation Index
Percentiles Southern Nevada All Time Scales
01 72 months
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14 Nov 2004 Water Vapor 2100 GMT
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Courtesy of Nate Mantua, U Washington
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Positive
Negative
Mantua et al.
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Time scales of atmospheric variability Turbulent
scale variability Hourly scale
variability Weekly scale variability Monthly
scale variability Seasonal scale
variability Annual scale variability ENSO scale
variability Decadal scale variability Century
scale variability Millennium scale
variability Orbital scale variability Geological
scale variability
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Time scales of atmospheric variability Turbulent
scale variability Hourly scale
variability Weekly scale variability Monthly
scale variability Seasonal scale
variability Annual scale variability ENSO scale
variability Decadal scale variability Career
scale variability Century scale
variability Millennium scale variability Orbital
scale variability Geological scale variability
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Sea Surface Temperature Departure from Average
Week of 2004 Oct 31 Nov 06
NOAA Climate Diagnostics Center
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Thru Oct 2004
Courtesy Klaus Wolter Mike Timlin, Climate
Diagnostics Center
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Washington
Redmond Koch, 1991, updated.
ENSO
Arizona
Central Sierra
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Data Van West Altschul, 1997
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Figure 10 from K.T. Redmond, Y.Enzel, P.K.
House, and F. Biondi, 2002. Climate variability
and flood frequency at decadal to millennial time
scales. pp 21-45, in Ancient Floods, Modern
Hazards Principles and Applications of
Paleoflood Hydrology, editors P.K. House, R.H.
Webb, V.R. Baker, and D.R. Levish. American
Geophysical Union, 385 p.
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Climate Stationarity The history of climate is
a non-stationary time series. There are no
true climatic normals (states to which the
climate must return). Climate never repeats
itself exactly. Climate is always fluctuating, on
all scales. There are always surprises
remaining. We can thus never stop observing or
monitoring. The Paradigm of Climatology An
Essay Reid A. Bryson, Bulletin of the American
Meteorological Society, 1997, 78(3), 449-455
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Sustainability What is it that we want to
sustain? The process or the outcome? What do
we value? How something looks, or acts, or
is? or How it got that way? What enabled a
system to get to the state it is in? These
processes usually involve climate and other
aspects of the physical environment. The
climate processes at work span scales from
turbulence to tectonics, from seconds to
millenia. Is the same mix of causative forces
still at work? A la Thomas Wolfe We cant go
home again. can we? The key question What
do we value?
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A few thoughts on management We cannot really
manage natural systems themselves. We have
limited understanding of how these systems
work. We have limited knowledge of the full
status of all relevant pieces. We have limited
control over certain inputs and boundary
conditions. We have limited ability to predict
the consequences of actions. Ecological
forecasting much more difficult than weather
forecasting. We have limited ability to evaluate
consequences. We have limited ability to
correctly ascribe consequences to causes. All we
can manage is our interaction with those
systems. This is all we really have control
over. All of our understanding points to Nature
as fundamentally probabilistic. We should learn
to work and think in this mode as much as we
can. This is the current mode for the prediction
of climate. Decision-making under uncertainty
We do have piecewise understanding of internal
workings, status, boundary conditions, and
predictability, and of some of the probability
distributions. Despite uncertainty, we have to
make decisions anyway.
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Climate Monitoring as a Priority Need
long, continuous, homogeneous time series
Keep present monitoring going For
automated equipment, basic scale typically
hourly Maintenance is crucial, and
neglected far too often So is
documentation Siting and exposure need
attention, documentation, constancy
Hypothesis-driven monitoring?
Hypothesis Huge demand for climate data.
Conclusion Yes. P lt
0.00000000001 Need context for short term
field programs and process studies. Many
key relationships only discovered in retrospect,
after the fact Access to climate
information vital Ecological scales
small long-term clusters much needed
CEMP, NTS, TREX
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Design Considerations for Weather and Climate
Monitoring in Channel Islands National
Park Kelly Redmond and Greg McCurdy
November 2004  Western Regional Climate
Center Desert Research Institute 2215 Raggio
Parkway Reno Nevada 89512-1095
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Representativeness of measurements In
space In time Consistency versus accuracy
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www.calclim.dri.edu
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Southern California
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TREX Terrain Induced Rotors Experiment
Independence CA Owens Valley
www.trex.dri.edu
6 mi
10 km
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TREX Terrain Induced Rotors Experiment
Independence CA Owens Valley
1 km
1 mile
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Community Environmental Monitoring Program
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Yucca Mountain Network
Nevada Test Site Network
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ACIS Applied Climate Information
System Available daily from HPRCC
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Southern Nevada Climate Division October
Precipitation 1895-2004
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CA Southeast Desert Climate Division October
Precipitation 1895-2004
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CA South Coast Climate Division October
Precipitation 1895-2004
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ACIS Applied Climate Information
System Available daily from HPRCC
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Experimental OSU / WRCC Prism 1 km Monthly
Climate Products
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Experimental OSU / WRCC Prism 1 km Monthly
Climate Products
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Experimental OSU / WRCC Prism 1 km Monthly
Climate Products
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Experimental OSU / WRCC Prism 1 km Monthly
Climate Products
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You can observe a lot, just by watching. -
Yogi Berra