Presentation of Kevin Trenberth NCAR' From "Interactions between Data, Observations, and Modeling,"

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Strategic Plan for the Climate Change Science
Program
Session morning Dec 5, 2002 Interactions
between Data, Observations and Modeling
(should be
among?) Chapter 3 Climate quality
observations, monitoring and data
management Chapter 12 Grand Challenges in
Modeling, Observations, and Information Systems
IMPORTANT Reminder To be effective in improving
the Strategic Plan, comments should be submitted
electronically according to instructions on the
website www.climatescience.gov follow links to
Strategic Plan)
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There have already been sessions on Chapters 3
and 12, and even parts of these. Accordingly, I
am not inclined to duplicate those sessions, but
rather to focus here on the interactions and the
document as a whole the true Grand Challenge.
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THE NEED FOR A SYSTEMS APPROACH TO
CLIMATE OBSERVATIONS BY KEVIN E. TRENBERTH,
THOMAS R. KARL, AND THOMAS W. SPENCE Because
climate is changing, we need to determine how and
why. How do we best track and provide useful
information of sufficient quality on
climate? Bulletin of the American
Meteorological Society November 2002, 83,
1593-1602
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• Chapter 3 (CCRI)
• CLIMATE QUALITY OBSERVATIONS, MONITORING, AND
  DATA MANAGEMENT
• This chapters contents
• How did the global climate vary and change over
  the past fifty years and beyond, what were the
  climate forcings over the past 50 years and
  beyond, and what level of confidence do these
  data provide in attributing change to natural and
  human causes?
• 2. What is the current state of the climate, how
  does it compare with the past, and how can
  observations be improved to better initialize
  models for prediction?
• 2a. How can we improve analyses of observations
  into globally gridded products?
• 2b. How can we ensure that future observations
  can be compared with past?
• 3. How real are the differences in surface and
  tropospheric temperature trends? What is the
  vertical structure of climate change in the
  atmosphere, and how well do models reproduce it?
• 4. How do we improve observations of biological
  and ecological systems to understand their
  response and feedback to climate variability and
  change?
• 5. How accessible is the climate record?
• How do we make the climate record more
  accessible?

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Chapter 3 comments Some nice discussion but not
followed up with items in Research Needs. 1.
go beyond observations to include the processing
and support system that leads to reliable and
useful products No item on analysis and four
dimensional data assimilation Does include
Reanalyses Does not deal with variability,
forcings, full fields needed for understanding
causes, relationships and feedbacks.
(Attribution) 2. Discusses scientific
stewardship monitoring performance of system and
taking corrective actions. No item on required
infrastructure. Deals only with baseline
networks. Does not deal with synthesis, esp.
satellite and in situ (for ocean). Does not deal
with understanding. 3. Satellite vs surface
Separate topic. Whole issue of satellite data!
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We do NOT have an adequate Climate Observing
System! Instead we rely on an eclectic mix of
observations taken for other purposes. But we
can not create an observing system just for
Climate! Observations MUST serve multiple
purposes.
In the United States multiple Federal Agencies
make observations for all sorts of purposes.
Many could be useful for climate (with a bit more
care). Coordination among agencies should be a
high priority. Building knowledge of just what
observations are made (as done for the UNFCCC in
preparation for the 2nd adequacy report) is a key
first step to better management. In addition,
real time knowledge of how the observing system
is performing is essential. Along with the
wherewithal to fix problems promptly.
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Climate Data Records A major effort is required
to produce satisfactory climate data records from
operational data. Over the past decade a
number of basic principles have been endorsed by
the National Research Council (NRC) in 1999, the
United Nations Framework Convention on Climate
Change, and in recommendations for a Global
Climate Observing System.
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1. Management of Network Change Assess how and
the extent to which a proposed change could
influence the existing and future climatology. 2.
Parallel Testing Operate the old system
simultaneously with the replacement
system. 3. Metadata Fully document each
observing system and its operating procedures 4.
Data Quality and Continuity Assess data quality
and homogeneity as a part of routine
operation procedures. 5. Integrated
Environmental Assessment Anticipate the use of
data in the development of environmental
assessments. 6. Historical Significance
Maintain operation of observing systems that have
provided homogeneous data sets over a
period of many decades to a century or
more. 7. Complementary Data Give the highest
priority in the design and Implementation
of new sites or instrumentation within an
observing system to data-poor regions,
poorly observed variables, regions sensitive to
change, and key measurements with
inadequate temporal resolution. 8. Climate
Requirements Give network designers, operators,
and instrument engineers climate
monitoring requirements at the outset of network
design. 9. Continuity of Purpose Maintain a
stable, long-term commitment to these
observations, and develop a clear transition plan
from serving research needs to serving
operational purposes. 10. Data and Metadata
Access Develop data management systems that
facilitate access, use, and interpretation of
data and products by users.
1. Management of Network Change 2. Parallel
Testing 3. Metadata 4. Data Quality and
Continuity 5. Integrated Environmental
Assessment 6. Historical Significance
7. Complementary Data 8. Climate
Requirements 9. Continuity of Purpose 10.
Data and Metadata Access
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Furthermore, satellite systems for monitoring
climate should adhere to the following specific
principles  11. Rigorous station keeping should
be maintained to minimize orbital drift.  12.
Overlapping observations ensured to determine
inter-satellite biases.  13. Satellites replaced
within their projected operational lifetime
(rather than on failure) to ensure continuity (or
maintain in-orbit replacements).  14. Rigorous
pre-launch instrument calibration should be
ensured.  15. On-board calibration and means to
monitor instrument characteristics in space
should be ensured.  16. Product development and
operational production.  17. Data access to
climate products, metadata and raw data,
including key data for delayed-mode analysis,
should be established and maintained. 18.
Continuing use of still-functioning baseline
instruments on otherwise de-commissioned
satellites should be considered. 19. Ground
truth The need for complementary in-situ
baseline observations for satellite measurements
should be appropriately recognized.  20.
Monitoring systems of network performance to
identify both random errors and time-dependent
biases in satellite observations.
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CHAPTER 12 GRAND CHALLENGES IN MODELING,
OBSERVATIONS, AND INFORMATION SYSTEMS This
chapters contents 1. Observations 2. Modeling
capabilities 3. Data and Information
Management _______________________________________
_
Comments 1 Where is the topic Analysis of
observations (into gridded global products)? 2
Where are the observations made into an
observing system? 3 Where are the linkages
between observations and modeling? 4 Where is
the Grand Challenge?
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• Observing system means a comprehensive approach,
  including
• Climate observations from both space-based and in
  situ platforms taken in ways that address climate
  needs and adhere to the ten principles outlined
  by the NRC (1999).

• A global telecommunications network and
  satellite data telemetry
• capacity to enable data and products to be
  disseminated.

• A climate observations analysis capability that
  produces global
• and regional analyses of products for the
  atmosphere,
• oceans, land surface and hydrology, and the
  cryosphere.
• Four dimensional data assimilation capabilities
  that process the
• multivariate data in a physically consistent
  framework to enable
• production of the analyses for the atmosphere
  and oceans, land surface etc.

• Global climate models that encompass all parts
  of the climate system
• and which are utilized in data assimilation and
  in making ensemble
• predictions.

• A climate observations oversight and monitoring
  center that tracks the performance of
  observations, the gathering of the data, and the
  processing system. This center must have
  resources and influence to fix problems and be a
  prominent climate voice when observational
  systems are established, such as for weather
  purposes or in establishing requirements for
  instruments on satellites.

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• Chapter 12 nicely pulls together all the items
  from previous chapters on
• Observations, and
• Modeling.
• Atmospheric composition (Ch. 5)
• Climate variability and change (Ch. 6)
• Water Cycle (Ch. 7)
• Land Use and Land Cover (Ch. 8)
• Carbon Cycle (Ch. 9)
• Ecosystems (Ch. 10)

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• The plan notes that some new sensors and networks
  need to be developed and implemented with
  continuity in mind.
• The road forward
• Stabilize existing observational capabilities
• Identify and implement critical measurement
  improvements.
• Incorporate climate and global change observing
  requirements in operational programs at the
  appropriate level.
• Continue intensive field missions
• Continue a vigorous program in data reanalysis to
  ensure the time consistency and spatial
  homogeneity of global change data sets.

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• Some Questions
• Where are the linkages among these components?
• water cycle and ocean
• carbon and water,
• aerosols and water vapor/cloud,
• carbon, ecosystems and land cover,
• climate variability and change, and land
• Where is blend of in situ and space-based obs
• (esp. water cycle)?
• Where are they all coupled to deal with the
  energy cycle?

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Water Cycle Hydrological Cycle Units Storage
Thousand cubic km Exchanges Thousand cubic km/yr
Where is the ocean? (Freshwater transports in
ocean and atmosphere, ocean density,
precipitation, evaporation) No complete
hydrological cycle here or elsewhere! Issues of
things like frequency and intensity of
precipitation ? extremes.
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Observing System Prioritization Criteria The
following prioritization criteria should be
considered in selecting CCSP observing
program initiatives Scientific Return
significance of the expected increase in
fundamental knowledge. Benefit to Society
extent to which the outcome may be utilized for
great societal benefit. Mandated Programs
support of programs mandated by law.
Partnership Opportunities the extent to which
needed work can be carried out with partners in
the United States and abroad. Technology
Readiness the extent to which current technology
enables a question to be productively
addressed. Program Balance distribution of
resources to ensure scientific progress is
not impeded by the lack of key information. First
is about scientific justification and
rationale? Also Scientific readiness (in
addition to technical feasibility and cost)
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Modeling Priorities and Linkages in CCSP Program
Elements

• Nice preamble
• Models as essential tools for synthesizing
  observations, theory, experimental results.
• Retrospective compare to observations
• Prognostic future projections
• Only quantitative tool
• Expand to become Earth System models
• Need for computational capabilities
• Quasi-operational activity
• Research activity

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• Links to Climate Modeling and Prediction
• The monitoring program must be combined with
• analysis and generation of products, including
  assimilation of the data into an operational
  climate model. Provides
• Quality Control,
• Feedback to the monitoring program,
• Optimization of design of observing system and
• Expert information on the data for the climate
  services.
• So where, under modeling, is role of models in
  4DDA and analysis?
• atmosphere
• ocean
• land surface
• coupled

All models are wrong, some are useful! Need for
assessment of models along with all
products Chapter 4?
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• Initializing Operational Climate Prediction
• The analyzed observations are vital to establish
  the initial state of the climate system monthly.
• The Earth is not in radiative balance and some
  predictability arises from changes in radiative
  forcing that has already happened.This is not
  dealt with anywhere (e.g., Chapters 4, 6). Issues
  of climate drift and spin up (esp. of oceans) to
  be solved.
• Similarly, where is predictability dealt with?
• Major issue for regional climate (can you ever
  expect to predict regional climate without
  predicting ENSO?)

For climate predictions, the initial state of the
atmosphere is less critical. Needed for
predictions of a season to a year or so upper
ocean heat content soil moisture, state of
surface vegetation the mass, extent, thickness
and state of sea ice and snow cover. On longer
time scales, information throughout the ocean is
essential. Information on systematic changes to
the atmosphere (especially its composition and
influences from volcanic eruptions) as well as
external forcings, such as from changes in the
sun, is also needed.
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• Data and Information Management
• Good discussion of
• Access, harnessing advanced technologies
• Metadata, Q/C
• Ocean observing system
• Challenges discussed
• Integration
• Archival
• Distributed system
• Interoperability
• Data rescue
• User friendly

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Stewardship of the data is needed establish an
organization with responsibilities for
operational climate monitoring and prediction.
Essential infrastructure has to be established to
ensure the integrity and continuity of the
observations, their analysis into products, and
links to modeling and research activities.
Needed a central facility with oversight of
the health of the observing system and resources
to build and sustain a climate observing system
operating under the guideline principles. It
would have a new management structure, authority
and infrastructure and should be responsible for
a line of products for use in all aspects of
climate, and oversight of management, access and
archival of the data.
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So what are the grand challenges?
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Integrating themes Climate change arises from
changes in the energy budget. MISSING theme on
the energy cycle? Kiehl and Trenberth 1997
IPCC has used radiative forcing at TOA works for
global T for global forcings. Assumes linearity.
BUT some effects are not linear. AND this
greatly oversimplifies the system (e.g., solar
which affects shortwave, vs CO2 which affects
longwave and so diurnal cycle, land-sea
differences matter.) ALSO clouds and absorbing
aerosols have great impact but may have no TOA
radiative forcing.
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Energy cycle
NEED to come to grips with bottom of atmosphere
radiative forcing (I.e. the surface heat
budget) INVOLVES oceans through uptake of heat
(heat storage) INCLUDES all feedbacks CRITICAL
for hydrological cycle AND local vs global
effects. This integrating theme places all
feedbacks into a coherent framework. New way to
analyze and look at models and data
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The climate is changing It is likely to continue
to change! Regardless of the success of
mitigation actions We need a comprehensive
information system to

• Observe and track the climate changes and
  forcings as they occur.
• Analyze global products (with models)
• Understand the changes and their origins
• Validate and improve models
• Initialize models predict future developments
• Assess impacts regionally on environment, human
  activities and sectors such as agriculture,
  energy, fisheries, water resources, etc.
• Such a system will be invaluable regardless of
  magnitude of global warming

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• Grand Challenges
• Integrate the science under a banner e.g.,
  focused on energy.
• Establish an end-to-end information system
  involving Observations, Analysis, Modeling,
  Prediction, and Assessment. To make music out
  of the din of observations that currently fall on
  the floor an interagency conductor for the
  orchestra is needed.
• 3. Make the case and establish adequate funding
  to do this

Ramping up to 1B per year after 10 years 100M
each in situ atmosphere, oceans, land (carbon,
hydrology, land use, paleo), data stewardship,
computing, modeling and analysis, 200M
satellite obs for climate 200M operation of
satellites (hot spare in orbit, orbit control)