Climate Modeling

Approximately 80-85 attendees (more than a full house)

# Salient Points 

*Presenter* -- Ants Leetma

Seasonal forecasting -- project what climatologies will look like

Reduce uncertainty by systematic model testing

How do we resolve and identify differences (sensitivities)?

Characterize a source of uncertainty from feedback mechanisms but need
to determine consensus on which mechanisms are key, compare with obs.

What measurements are absolute? (not subject to differences in
satellites)

Will centers use climate variability and change models for
seasonal-interannual forecasting?

Systematic change detection and attribution needed

Two center strategy buttressed by common modeling (software)
infrastructure and access to computational capability

MOU with NCAR for intercomparison between CCSM and GFDL codes

Community input on modeling mentioned in two-center strategy

## Panelists

Jim Hansen:

\- Added level of bureaucracy that presumes scientific progress can be
ordered

\- More bureaucracy takes away science time

\- Notes issue of model sensitivity and proposes resolving it via
comparison of models but this won't reveal underlying issues of climate
sensitivity

\- Appears to be two different documents

Dan Cayan:

-   Plan shortfall: regional scale not well developed, topography
    matters

-   Water issues imperative, topography plays a role in this as well
    (snow pack, precipitation, low frequency drought signals that are
    highly impactful regionally but not generally thought of in "climate
    variability")

-   Short-term events impactful (local high peaks in sea level exceed
    trends)

-   Application models needed

-   Need regional scale observational programs as well as mandated
    observations for global scale

Linda Mearns:

-   Characterization of uncertainty could benefit from more attention-
    especially in climate projections and socio-economic assumptions

-   Uncertainty never defined and there are several types

-   Characterizing and reducing uncertainty are different activities

-   Elucidate then reduce uncertainty

-   False certainty a consequence and concern for not characterizing and
    quantifying uncertainty correctly

-   No plan for how to improve the quality of the data at higher
    resolution

-   Uncertainty increases as we go to a finer-scale; work has been done
    on a global scale.

-   Consideration for resource management has different time-cycles for
    decisions (5-10 year resolutions, for 20-100 years) affects
    information needs

> Bob Friedman

-   How is the plan being responsive to users? It is sketchy on how and
    how much (resources, which elements of plans)

-   No cross-check with users needs

-   Likes two-center approach with differing foci

-   Delivery to users important but not clear how users on different
    scales are served

-   Identify decision makers needs by giving assessment primacy

-   Feedback from decision support and assessments to CCSP not clear;
    also not clear how resources budget will be distributed

-   Caution on running out of time on important assessment issues

-   Assess early, assess often

# Major Issues and Concerns

*Anthes (UCAR):* Two centers should not imply 2 and only 2 models in the
US; these centers should, could, would have different models for
different purposes.

Concern about drawing line between assessments, applications and
research, both centers should do some of each.

*Colburn (NESCOM-air programs in NE states):* Emphasize need for
regional climate model (watershed-watershed basis); Economies will be
tuned on regional climate modeling.

*Coakley (OSU):* Concerned that the 2-center strategy doesn't make sense
and also feels that the problems have been around for a while. Questions
how observations are married to models, especially on the regional scale
(water vapor and clouds specifically). Can old satellite data be used?
Not clear how bureaucratic structure will help the problems be solved,
really need more resources and manpower on existing problems.

*Shukla (COLA)*: Comments on uncertainty, is it really that large? It
never goes negative and there is some convergence within a given range
already...should we really postpone dealing with the existing knowledge
about change?

The focus on 100 years is too shortsighted.

Concern with the 2-center strategy, it is not a solution to the problem.
Also concerned with labeling centers/models as research or assessment
because the two activities are inter-related. Different emphasis is
acceptable, but both modeling centers should address the complete
problem in order to capture the improvements to assessments by research
and the guidance of research by doing the assessments.

Patz (JHU-Public Health): Echo emphasis on communication between
applications modelers and decision makers. Encourage continued dialog,
but encourage more applied modeling especially on small scales
interfacing with regional models. Gap is in the bottom-up connection
between model output-applications.

Kenneth Green (Frazer Institute, Vancouver Canada, emphasis on policy).
Modeling community tends to focus only on the worst-case scenario.
Expressing and communicating uncertainty pushes back against an untoward
focus on worst-case.

Branscome: Lacks connection to the private sector, such as re-insurance
sector. Climate change affects long-term investments. Operational
products delivery in aviation may be a reasonable model for outreach to
private sector.

Takle (Iowa State University): Do regional modeling for the science
component as well as the assessment needs; it is important for
understanding water vapor and cloud feedbacks on regional scales, as
this directly to aids global parts. Add regional modeling to science
component.

Greg Greenwood (Dep. Ass. Sec. For Resources in California) Emphasis on
regional need for assessments and regional climate models to support
decision-making. Would like to see the report reconstructed to emphasize
service to regional managers. Would like to see more information about
the computational capacity...plea for big iron...we should be ahead
given our technology.

Neil Wood (International Institute for Climate Prediction --Columbia?):
Running the models in real time needed for learning about modal
variability.

Phil Merilees (NCAR): Is the present range of assessments (1.5-4.5) good
enough? How do the regions and countries evaluate what this assessment
means to them? Demand for information will grow as science becomes
credible. We don't have the tools to provide the information. No one has
asked the modelers what they need to deliver the information. What about
the role of ocean mixing? What is the role of high-resolution eddy
activity in the global ocean in the climate assessment? Need a 5 year
dedicated 3 Tera-flop machine to do this...where will this tool come
from? Where will the people come from to do this work? Example of the
length of the code (500,000) lines...how many people needed to maintain
this code? The two-center strategy can bring together a critical mass of
people to address these problems. NWP has shown that more you examine
individual areas, the more science you learn.

Ming Ji (NOAA OGP): Needs are at regional level, credible regional
simulations need credible global simulations for boundary conditions. Or
increase resolution to regional scale...this has computational and
scientific needs...the plan should address the path to this goal of
credible regional simulations.

? (Director Hadley Center of UK). Need care in how global model output
is used. Regional detail doesn't translate to regional
information...need care, skill and training.

Sheila. Lynch (NE Vehicle Consortium) Need time scale information about
cycle's....relationships between paleo- climate-microscale, mesoscale,
etc.

K. Forbes (Climate Change in Portugal): Dichotomy between regional and
global models. For small countries, regional models are critical needs.

# Panel Responses

LM: Some other session may address the private sector concerns.

LM: Agrees with needs for global models to support regional models but
thinks the resolution of global models will be limiting within the
context of this fast track plan.

LM: If your country isn't represented in a global model, then it is hard
for the country to feel invested in the assessments.

BF: Modeling community should identify what assessments they are unable
to do (through limitations of technology and knowledge?) Institutions
should be set up so scientists can say this.

JH: Primacy of assessment should drive a natural mesh of research and
assessment

DC: Agrees with Ming Ji's point about the critical need for global
models feeding regional models; need a sustained program because the
problems of modeling and monitoring are not going to be solved in 4
years. Systematic climate data collection is needed (data now tends to
be data of opportunity). Need data quality, scrutiny, control for the
right kind of data.

**Major Themes**

**THERE IS A COMPELLING NEED FOR A REGIONAL CLIMATE MODELING PLAN.
REGIONAL DECISION MAKERS ARE NOT SERVED BY GLOBAL ASSESSMENT BUT
(DESPERATELY) NEED ASSESSMENTS THAT ARE TUNED TO THEIR SPATIAL SCALES,
TEMPORAL SCALES (OF DECISION-MAKING), AND APPLICATIONS. THE PRESENT
STRATEGY DOCUMENT IS LACKING IN A REGIONAL STRATEGY.**

**TWO-CENTERS STRATEGY: EACH CENTER SHOULD HAVE PRIMARY FOCUS BUT SHOULD
ALSO DO THE WHOLE PROBLEM BECAUSE OF THE INTERACTIONS BETWEEN RESEARCH,
ASSESSMENT, and OPERATIONS**

**CENTER STRATEGY SHOULD HAVE A SELECTION OF MODELS SOME OF WHICH SHOULD
BE SPECIALIZED; TWO-CENTERS DOESN'T EQUAL TWO MODELS**

**REGIONAL SCALE MODELING WILL NEED GLOBAL MODELING TO SUPPORT IT BUT IT
MUST BE DONE SKILLFULLY**

**HOW IS THE RANGE OF VALUES INTERPRETED AS UNCERTAINTY, BOTH FOR
DIFFERENT APPLICATIONS AND ASSESSMENTS AND DIFFERENT SCALES?**

**IN GENERAL UNCERTAINTY IS NOT WELL DEFINED NOR IS THE STRATEGY CLEAR
ON THE IDENTIFICATION,\
CHARACTERIZATION, QUANTIFICATION, or REDUCTION STRATEGIES.**

**CONTINUED COMMUNICATION NEEDED BETWEEN DECISION MAKERS (ESPECIALLY
REGIONAL DECISION MAKERS) AND MODELERS ON NEEDS, ASSESSMENT SCENARIOS,
AND WHAT TYPES OF APPLICATION MODELS AND ASSESSMENTS ARE FEASIBLE**