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Title: Climate Observations in


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Climate Observations in Pacific Northwest
National Parks Kelly T. Redmond Western
Regional Climate Center Desert Research
Institute 2215 Raggio Parkway Reno Nevada
89512-1095 775-674-7011 voice 775-674-7016
fax krwrcc_at_dri.edu
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National Weather Service Cooperative Network
Approximately 5000 daily max/min temperature
stations, 8000 daily precipitation stations, 3000
automated hourly precipitation stations.
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Volunteer Observers. Standard raingage 8 wide,
20 inch capacity, This one with funnel (summer
configuration). Max/Min Temperature System (MMTS)
in background (electronic thermometers). Longest
individual observer 76 years, Cottage Grove
Oregon (not the person pictured).
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344 U.S. Climate Divisions.
http//www.wrcc.dri.edu/spi/divplot1map.html
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  • National Park Service Protocol Considerations
    (stemming from CHIS)
  • Why ? - Why are the measurements being made?
  • Immediate project needs (a few months to a few
    years duration)
  • General purpose - often turn out to be very
    important heavily used. Should assume this as
    the default case.
  • Data from many networks are being used for far
    more than their original purpose or motivation
  • Sustainability - Acquisition and deployment are
    the easy and cheap part. Think ahead Arguments
    for equipment is usually more effective than
    arguments for maintenance, quality control,
    archive, access, summary.
  • Maintenance the bane of all systematic
    measurement programs, and (the lack thereof)
    often responsible for the death of measurement
    efforts
  • Automated systems still require considerable
    human attention. Automation is not a panacea, or
    a replacement for people.
  • Automation introduces new types of errors.

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What constitutes a good climate record? - One
that records real climate variability rather than
fake climate variability. Real Climate
Variability All variations seen in the record
are due to things that happened in the
atmosphere. And, we usually hope, in the larger
scale atmosphere. (Though not always depends
on the purpose of the measurements.) Fake
Climate Variability Sensor changes Replacement
s, degradations, drift, insects, birds. Site
changes Ground cover and land use
changes Obstructions / blocking Anything
affecting the local energy balance Observer and
methodological changes How observations are
recorded (conventions followed?) a.m. / p.m.
issues. How instruments are reset.
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  • Climate quality measurements require a higher
    standard than weather quality measurements.
  • Representativeness - What spatial and temporal
    scales are the measurements intended to
    represent?
  • Siting. Choosing a site. What factors, at what
    spatial scales, will influence the measurements?
    The scales vary from millimeters to megameters.
    What is the site representative of? Practical
    and scientific considerations both matter, can be
    at odds, and often lead to compromise.
  • Precipitation Assume that all precipitation
    will occur in frozen form, even if just
    occasional. Can the equipment handle this?
  • Link into existing systems
  • Instrumentation, communication, dissemination
  • Archival, retrieval, analysis
  • Local versus external dependencies. Develop or
    rely on internal mechanisms and expertise?
    Develop relations with or rely on external
    mechanisms and expertise?

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  • Quality control begins at the station. This
    bears repeating.
  • Quality control begins at the station.
  • The best form of quality control is to not let
    bad data leave the station at all.
  • Up-front attention to equipment quality,
    installation quality, robustness to disruption,
    backup systems.
  • The weather is usually the most important
    reason that weather measurements are lost.
  • The weather that knocks out weather stations is
    often the weather we most want to know about.
    (Extremes, and disturbances.)
  • Design for the worst conditions.
  • Once the data values leave the station,
    essentially only bad things can happen them.
  • Cheap is often not cheap.
  • Two-way communication. More desirable. Enables
    re-transmission of data, resetting of data
    loggers, better debugging of problems.

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  • Documentation (Metadata data about data)
  • Need history of whatever factors that can affect
    the interpretation of the measurements. These
    include sensors, site physical circumstances
    (including vegetation), observing practices and
    reporting conventions, numerical pre-processing,
    averaging intervals, gage shielding, etc.
  • Most perishable that which is carried in human
    heads, best retrieved before or retirement, or
    more final outcomes. Filing cabinets, old
    diskettes, etc, also contain much interesting
    material, but often separated from their
    originator.
  • GPS positions.
  • Full photo sets, repeated periodically,
    approximately 1-2 years. Typically 8 point
    compass, wide angle, skylines and foreground,
    plus any other helpful angles which show local
    influences, and changes through time.
  • Changes affecting local climate, within 200-300
    meters. Irrigation starting or stopping,
    vegetative regrowth or trimming, pavement or
    change in surface status, additions or
    subtractions of obstructions.
  • Digital versions of the above, accessible with
    the data.

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  • Observing strategies
  • Is the emphasis on learning about temporal
    behavior, temporal behavior, or both at once?
  • Dependence on spatial correlation structure of
    temporal behavior of climate elements. (How well
    does time-varying behavior correlate in space, at
    various combinations of spatial and temporal
    scales?) This varies widely, depending on
    topographic complexity (height, slope, aspect),
    proximity to water bodies, as well as latitude
    and season.
  • Catch 22 Chicken and egg! We need the
    observations to tell us what observations we
    need! Solution Experience, brains,
    intuition.
  • A few very good and reliable sites, or lots of
    mediocre sites?
  • Vulnerability assessment. Where could key
    failures in measurement result in loss of
    valuable information or knowledge? Example
    manual or simple backup of automated
    precipitation gages, or, saving of water after
    initial precipitation measurement (we might lose
    the timing but know the total).
  • Redundancy is not a weakness. A degree of
    redundancy is good.

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  • Observing strategies (continued)
  • Station density. Optimum density depends on
    spatial correlation structure mentioned above.
    General consideration are all of the principal
    climate regimes adequately sampled?
  • A mixed strategy seems best A few reference
    quality sites that get lots of attention, produce
    complete records, have needed backup, and are
    thoroughly documented, interspersed with more
    numerous satellite observations of perhaps
    lesser quality, or less protected from their
    various vulnerabilities.
  • Adaptive monitoring. Smarter electronics have
    made it possible for observing systems to modify
    their sensing rate, in response to environmental
    cues. Systematic measurements are always needed,
    but these can be interspersed with rates that
    vary according to the behavior of interest. Of
    course, we dont always know what behavior will
    turn out to be of interest, especially if new.
  • Retrospective capability. We often do not learn
    that a system has experienced a change until well
    after the fact. We are therefore dependent on
    systematic measurement to reconstruct the past.

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  • Added considerations raised during meeting.
  • Public interface needed. Web access to reach
    broad range of public, research, and other user
    communities.
  • Public outreach / education. There is a great
    deal of public interest in climate. Capitalize
    on that as part of the park mission.
  • Administrative environment. Take it as given
    that personnel are busy, overwhelmed, have
    multiple duties.
  • Expectationless monitoring. The most useful
    monitoring has no special hypotheses in mind.
  • Ten commandments for climate monitoring
  • Partnering / leveraging. Why re-invent the
    wheel? Share resources and expertise. Be
    careful to pick partners with staying power.

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  • Added considerations raised during meeting
    (continued).
  • Monitoring the monitoring. Is the monitoring
    performing as needed or intended? Is it
    functioning at all? How healthy is this
    activity? Refered to as "network health.
  • Snow issues. Many of these, in higher,
    northern parks. Far more challenging, difficult,
    expensive, labor intensive, to obtain quality
    records.
  • High elevation monitoring. Badly needed. High
    elevations may not vary in time like nearby low
    elevations. Separate monitoring needed. Needs
    high standards, rugged equipment, good
    communication, highly reliable instruments.
  • The world changes. Landscape, vegetation,
    growth can alter locally measured climate
    significantly. Fires destroy, then grow backi.
    Clearcuts slow changes in small scale climate.
    Mt St Helens Destruction, then regrowth. Local
    temp precip climate will slowly change (and
    separately).

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Ten Principles for Climate Monitoring For the
past few years, with respect to climate data
issues, frequent mention is made of a set of
climate monitoring principles enunciated in 1995
by Tom Karl, director of NCDC. In some quarters
(following Gene Rasmusson, for one), they have
also been informally referred to as the "Ten
Commandments of Climate Monitoring". Both
versions are given here. collated by Kelly
Redmond, Western Regional Climate Center, August
2000. -------------------------------------------
---------------------------- ---------------------
--------------------------------------------------
Cliff's Notes version. "Ten Commandments of
Climate Monitoring" 1. Assess the impact of new
observing systems or changes to existing
systems prior to implementation. "Thou shalt
properly manage network change." (Assess effect
of proposed changes.) 2. Require a
suitable period of overlap for new and old
observing systems. "Thou shalt conduct
parallel testing." (Of old and replacement
systems.) 3. Treat the results of calibration,
validation, algorithm changes, and data
homogeneity assessments with the same care as the
data. "Thou shalt collect metadata." (Full
documentation of system and operating
prodecures.)
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\ 4. Ensure a capability for routine assessments
of quality and homogeneity, including high
resolution data for extreme events. "Thou
shalt assure data quality and continuity."
(Assess as part of routine operating
procedures.) 5. Integrate assessments, like
those of the International Panel on Climate
change, into global observing priorities.
"Thou shalt anticipate use of the data." (e.g.,
integrated environmental assessment
anticipate data use as part of operating system
plan.) 6. Maintain long-term stations.
"Thou shalt worship historical significance."
(Maintain long term observing systems which
provide homogeneous data sets.) 7. Put a high
priority on increasing observations in data-poor
regions and regions sensitive to change and
variability. "Thou shalt acquire
complementary data." (New sites to fill in
observational gaps.) 8. Provide network
operators, designers, and instrument engineers
with long-term requirements at the outset of the
design and implementation phases of new
systems. "Thou shalt specify climate
requirements." (Designers of networks be
aware of monitoring requirements for climate
usage.)
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9. Think through the transition from research
observing systems to long-term operations
carefully. "Thou shalt have continuity of
purpose." (Stable, long-term
commitments.) 10. Focus on data management
systems that facilitate access, use, and
interpretation of weather data and metadata.
"Thou shalt provide data and metadata
access. ----------------------------------------
------------------------------- ------------------
--------------------------------------------------
--- From Karl et al 1996. Full version 1.
The effects on the climate record of changes in
instruments, observing practices, observation
locations, sampling rates, etc. must be known
prior to implementing such changes. This can be
ascertained through a period of overlapping
measurements between old and new obwerving
systems or sometimes by comparison of the old and
new observing systems with a reference standard.
Site stability for in-situ measurements, both in
terms of physical location and changes in the
nearby environment, should also be a key
criterion in site selection. Thus, many synoptic
network stations, primarily used in weather
forecasting but which provide valuable climate
data, and all dedicated climatolotical stations
intended to be operational for extended periods,
must be subject to such a policy.
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2. The processing algorithms and changes in
these algorithms must be well documented.
Documentation of these changes should be
carried along with the data throughout the data
archiving process. 3. Knowledge of instrument,
station and/or platform history is essential for
data interpretation and use. Changes in
instrument sampling time, local environmental
conditions for in-situ measurements, and any
other factors pertinent to the interpretation
of the observations and measurements should be
recorded as a mandatory part of the observing
routine and be archived with the original
data. 4. In-situ and other observations with a
long uninterrupted record should be maintained.
Every effort should be applied to protect
the data sets that have provided long-term
homogeneous observations. "Long-term" for
space-based measurements is measured in decades,
but for more conventional measurements
"long-term" may be a century or more. Each
element of the observations system should develop
a list of prioritized sites or observations based
on their contribution to long-term climate
monitoring. 5. Calibration, validation and
maintenance facilities are a critical requirement
for long-term climateic data sets. Climate
record homogeneity must be routinely assessed,
and corrective action must become part of the
archived record. 6. Where feasible, some level
of "low-technology" backup to "high-technology"
observing systems should be developed to
safeguard against unexpected operational
failures.
47
7. Data poor regions, variables and regions
sensitive to change, and key measurements with
inadequate spatial and temporal resolution should
be given the highest priority in the design and
implementation of new climate observing
systems. 8. Network designers and instrument
engineers must be provided long-term climate
requirements at the outset of network design.
This is particularly important because most
observing systems have been desigined for
purposes other than long-term climate
monitoring. Instruments must have adequate
accuracy with biases small enough to document
climate variations and chaqnges. 9. Much of the
development of new observation capabilities and
much of the evidence supporting the value of
these observationss stem from research-oriented
needs or programs. A lack of stable,
long-term commitment to these observations, and
lack of a clear transition plan from research to
operations, are two frequent limitations in
the development of adequate long-term monitoring
capabilities. The difficulties of securing a
long-term commitment must be overcome if the
climate observing system is to be improved in a
timely manner with minimum interruptions. 10.
Data management systems that facilitate access,
use, and interpretation are essential. Freedom
of access, low cost, mechanisms which facilitate
use (directories, catalogs, browse
capabilities, availability of metadata on station
histories, algorithm accessibility and
documentation, etc.) and quality control should
guide data management. International cooperation
is critical for successful management of data
used to monitor long-term climate change
and variability.
48
--------------------------------------------------
--------------------- ----------------------------
------------------------------------------- Clima
te Monitoring Guidelines. Sources Thomas R.
Karl, V.E. Derr, D.R. Easterling, C.K.
Folland, D.J. Hoffman, S. Levitus, N. Nicholls,
D.E. Parker, and G.W. Withee, 1996. Critical
Issues for Long-Term Climate Monitoring. pp
55-92, in "Long Term Climate Monitoring by the
Global Climate Observing System", T.R. Karl, ed,
Kluwer, 518 pp. National Research Council, 1998.
Guidelines and Principles for Climate
Monitoring. Appendix F, p 63, in Future of the
National Weather Service Cooperative Observer
Network. National Academy Press, 65 pp. Eugene
Rasmusson, 2000. Workshop notes. Climate
Services A vision for the future.
NAS/NRC/BASC, Woods Hole MA. --------------------
--------------------------------------------------
---- Dr. Kelly T. Redmond Regional
Climatologist/Deputy Director 775-674-7011
voice Western Regional Climate Center 775-674-7016
fax Desert Research Institute email
krwrcc_at_dri.edu 2215 Raggio Parkway http//www.wr
cc.dri.edu Reno, Nevada 89512-1095 ftp.wrcc.dri.
edu/pub
49
Magnitudes and perceptions.In a relative sense,
climate change is expected to be smaller, perhaps
much smaller, than the fluctuations of climate
and weather that we already know and
love.However, it is also expected to be fairly
systematic. Thus, many causes and consequences
would likely express themselves as subtle
systematic biases in time series of properties of
the climate itself and of affected physical and
biological systems. These would be interspersed
with changes in the likelihood of more visible
and memorable occurrences of extremes and
disturbances.As cosmologist Philip Morrison
pointed out in his book Nothing is Too Wonderful
to be True, change in the universe occurs
approximately equally in quiet and unassuming
forms, and in explosive and dramatic forms. But
even the latter often build in a slow and
innocuous manner.
50
Subtle does not mean unimportant. Pr
of Mike Wallace UW Atmospheric
Sciences Seattle, July 14, 1997
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