August 10, 1998




Dr. Aristedes Patrinos
Department  of Energy
Associate Director
Biological and Environmental Research ER-70
19901 Germantown Road
Germantown, MD   20874-1290

Dear Ari:

        This letter is in response to your request that JASON review plans for
the 
Advanced Climate Prediction Initiative.  Specifically, your request was that 

. JASON undertake a study to determine whether the pace of 
computational technology development (computers, networks, software, etc) 
will be sufficient to perform century long simulations of climate change with 
weather-scale resolution.  Additionally, JASON should provide advice on 
how best to utilize this technology to link the scientific resources of the DOE 
laboratories and the US Global Change Research Program to produce 
unprecedented climate change projections, including measures of climate 
variability, by the middle of the next decade when greenhouse gas 
stabilization policies are enacted.

        To respond to this request, we and the USGCRP jointly convened a
workshop at 
SIO from July 1-3, 1998.  Speakers included representatives from the climate
modeling 
community, the high-performance computing community (including the ASCI
program), 
and several users of climate models.  Beyond this input, we also reviewed
extensive 
written material and drew upon our own prior experience with climate and high-
performance computing, as well as the management of large-scale technical
enterprises.

        The "executive summary" of our response is captured by the following two

observations:

1. Substantial increases in the computational power available to US 
researchers are well-warranted and can contribute to a better 
understanding of the climate system.
 
2. Computational power alone will not greatly improve our abilities to 
predict climate.  Linked observational programs and process studies are 
essential for a balanced global change effort. 

We elaborate on these points in turn.

The rationale for increased computational power

        Understanding the earth's climate is one of today's most challenging
scientific 
problems.  Multiple components are involved, including the atmosphere, the
ocean, the 
cryosphere, the land surface, and the biosphere.  These vary and interact with
one another 
on diverse spatial and temporal scales.  

        Models of the climate embody and test our understanding of this system.
They 
also allow us to assimilate observational data ("fill in the gaps").  Ideally,
they allow us 
to forecast changes in the climate system (both due to natural variability and
to 
anthropogenic response) and the likely effects of various mitigation strategies.

        Fundamental physical considerations set the spatial and temporal
resolutions 
needed for a realistic climate model.  These, together with the necessity for
century-to-
millennium scale runs to quantify the response to anthropogenic forcing or the
natural 
variability imply, at a minimum, terascale computing resources.  ACPI is a step
toward 
meeting that need.

        Successful climate modeling will find utility in a number of different
modes.  On 
short timescales, one may expect some improvement in numerical weather
prediction 
(NWP), although this is quite a distinct problem from climate (because of the
very 
different timescales involved) and most of the improvement is expected from
better 
observational data.  Over somewhat longer intervals, seasonal to interannual
climate 
prediction will likely be a real benefit.  [The improved agricultural response
of Peru to El 
Ni$o forecasts during the last decade clearly demonstrates the benefits
possible.]  
Accurate descriptions on decade-to-century scales are necessary to evaluate the
likely 
impacts of anthropogenic activities and the likely efficacy of various
responses.  And 
simulations involving many millennia are required to describe paleoclimates.
These 
diverse needs imply the need for flexible simulation capability that can be used
in new 
and imaginative ways.

        Many other nations have realized the importance of sustained and focused

investment in climate modeling, the European Center for Medium-range Weather 
Forecasting (ECMWF) perhaps being the outstanding example.  These organizations 
benefit from sustained funding, state-of-the-art technology, and strong
intellectual 
leadership.  Surprisingly, although the US has led world in climate observations
and in 
pursuing the science embodied in the models, it lags significantly in the
exploitation of 
modeling capabilities.  Greater computing power will help to address this
deficiency.  
Among other benefits, it will enable objective testing of simulations with
diverse 
assumptions and process descriptions.

Organization, management, and implementation of the ACPI

        In considering how additional computing power might best be applied to
climate 
modeling, it is important to realize that the science is as yet uncertain, and
controversial 
in parts.  Further,  any successful modeling effort will need to closely
integrate diverse 
disciplines, including computer and computational science, applied mathematics,
fluid 
dynamics, chemistry, weather, biology, and climatology.  There is also the
obvious need 
to harness the creative energy and talents of the university community. 

        The basic question in organizing the ACPI is whether to simply supply
more 
computational capability to the diverse US modeling community, or to create a
more 
centralized structure for a coherent attack on climate simulation.  Our
inclination is 
toward the latter.  Strong scientific leadership must be identified early in the
project and 
charged with managing the computational and scientific resources.  Science must
be at 
the center of the enterprise, with technology as a means to an end, not an end
in itself.

        However ACPI is implemented, we urge a close coupling with NWP.  The 
necessity of continually confronting detailed observations can only be a bracing

experience for the modeling community, as has been shown by the ECMWF
experience. 
A USCMWF or organization similar to NCAR but focused on climate are notions that

capture many attractive organizational aspects. 

        We believe that the case is strong for the ACPI proceeding
expeditiously.  It will 
address serious deficiencies in climate computing and will allow climate
modelers to 
efficiently refine and exploit their models.  However, as the benefits of
terascale climate 
computing are some years off, there are some short term steps that could be
considered, 
including a reallocation of existing computing resources or the purchase of a
100-1000 
Gflop capacity. 

ACPI is only a part of the Global Change program

        As noted above, ACPI in and of itself will not greatly improve our
abilities to 
predict climate.  Success will require that modeling be integrated with
observational 
programs and process studies.  Indeed, it is essential that all three of these
elements work 
together. Such coordination is rare within the global change research program,
the 
DOE's on-going ARM program being a conspicuous exception. 

        It is encouraging that ACPI includes a substantial outreach component to
make 
modeling results more widely available.  However, even before ACPI begins, it is

important to educate the public and policy makers about the nature of climate
science and 
the real scientific uncertainties and deficiencies the field is trying to
address (in part 
through efforts like ACPI).  Among these are: 

? the unphysical drift in virtually all coupled climate models (the NCAR CSM 
being the sole exception we are aware of), 
? the lack of spontaneous ENSO events in all coupled models (despite the fact
that 
this is the dominant mode of variability in the real climate) 
? the general absence in simulations of the ubiquitous marine stratus near
Western 
South America 
? the inability to satisfactorily balance the global carbon cycle 
? the anomalous shortwave absorption of the atmosphere amounting to 30 W/m2 (to 
be compared with the increase of approximately 6 W/m2 expected from doubling 
CO2) 
? the failure of the oceanic equator-pole heat flux to converge with increasing 
model resolution 
? the failure to observe the predicted increase of upper tropospheric water
vapor 
? the lack of agreed-upon model metrics or of climate variables most indicative
of 
change. 

        I hope that these thoughts will be of use to you and others as you plan
and 
implement the ACPI.  Please don't hesitate to contact me if you would like any 
clarification or amplification of these points.


                                                Sincerely,



                                                Dr. Steven E. Koonin




                                                
Study Contributors:
H. Abarbanel, K. Case, F. Dyson, S. Flatte, N. Fortson, E. Frieman, M. Gregg, M.
Goldgerger, 
W. Happer, R. Jeanloz, W. Munk, W. Nierenberg, O. Rothaus, M. Ruderman, R.
Schwitters, P. 
Weinberger, F. Zachariasen