42 Responses Received
Note: As a point of reference, there were two unique questionnaires that were sent out to U.S. modeling centers for the purposes of this report. One questionnaire was sent out to large and intermediate centers, and a second questionnaire was sent to small centers. 1 Thus, the ‘coding' after each question, e.g., I6L (large/intermediate), I6S (small), specifies the question number as in the surveys above and whether it was common to both questionnaires, or exclusive to one or the other. In some instances, a question was specific to only one survey as it was believed to be inappropriate to the other category of modeling centers.
What percentage of your modeling activities are devoted to operational versus research purposes? (I6L, I6S)
39 Majority research oriented
3 Majority operations oriented
Out of the responses that were majority research oriented, some stated that their research had direct operational relevance.
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An example of what is referred to in this document as a small modeling effort is one using a global, stand-alone atmospheric climate model at R15 (~4.5° × 7.5°) resolution; an example of an intermediate effort is one using a global, stand-alone atmospheric climate model at T42 (2.8° × 2.8°) resolution; an example of a large or high-end modeling effort is one using a global, coupled T42 atmospheric / 2° × 2° oceanic model (or finer resolution) for centennial-scale simulations of transient climate change. |
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Appendix E
Climate Modeling Survey: Summary Responses
42 Responses Received
Note: As a point of reference, there were two unique questionnaires that were sent out to U.S. modeling centers for the purposes of this report. One questionnaire was sent out to large and intermediate centers, and a second questionnaire was sent to small centers. 1 Thus, the ‘coding' after each question, e.g., I6L (large/intermediate), I6S (small), specifies the question number as in the surveys above and whether it was common to both questionnaires, or exclusive to one or the other. In some instances, a question was specific to only one survey as it was believed to be inappropriate to the other category of modeling centers.
What percentage of your modeling activities are devoted to operational versus research purposes? (I6L, I6S)
39 Majority research oriented
3 Majority operations oriented
Out of the responses that were majority research oriented, some stated that their research had direct operational relevance.
1
An example of what is referred to in this document as a small modeling effort is one using a global, stand-alone atmospheric climate model at R15 (~4.5° × 7.5°) resolution; an example of an intermediate effort is one using a global, stand-alone atmospheric climate model at T42 (2.8° × 2.8°) resolution; an example of a large or high-end modeling effort is one using a global, coupled T42 atmospheric / 2° × 2° oceanic model (or finer resolution) for centennial-scale simulations of transient climate change.
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Please describe groups with which you have significant collaboration and briefly describe the nature of this collaboration. (I7L, II1S)
From the responses received, there appears to be strong connections between the major centers and academia and vice-versa.
Please provide your opinion on current U.S. climate and weather modeling capabilities relative to overseas efforts. Please describe where differences in capabilities exist and what you feel are the causes for these differences. (II1L, III1S)
U.S. is:
Ahead
Behind
Comparable
Weather
2
20
6
Climate
1
21
9
Why are there differences?
Underfunded
Understaffed
Lack of computer resources
Lack of common center/coordination
Other statements:
Comparable to other countries at all but high-end
Model development is weak here and overseas
U.S. is ahead in diversity and size of effort
It is more difficult to organize the U.S. effort due to its size and diversity
If you stated that U.S. climate and weather modeling capabilities are behind those of other countries, do you have any suggestions to remedy this deficiency? (II2L, III2S)
7 Increased Funding
8 Shared Infrastructure
18 Enhanced Organization
25 Hardware
8 Adequate brainpower
Do you feel that your modeling effort would be aided by altering the organization of U.S. climate modeling resources? If so, what changes would you recommend be made? (II3S)
6 Yes
5 No
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Observations of the affirmative responses:
Too many underfunded, understaffed groups
Inadequate links to data collection
More emphasis should be placed on the vulnerability of the Earth system to the spectrum of environmental stresses, rather than focus primarily on the effects of greenhouse gases.
U.S. should take the lead in the physics of the climate system and its parameterization
Devolve computing resources away from computer centers to the users
Develop a responsive, interactive computing environment
Make it easier to access climate models for climate applications and to long-term model simulation data for analysis
What additional upgrades would be incorporated if funds were available? (III2bL, V2S)
7 Upgrades for PC clusters
2 More nodes
3 Increased bandwith
7 Increase general computational power
5 Increase disk storage
3 Increase file migration capabilities
1 Purchase Alpha-type workstations
1 Upgrade to parallel vector systems if possible
2 None
6 More processors
Does modeling capacity or capability limit your current activities or does some other factor? Could you make use of additional modeling capacity or capability for additional activities? (III3bL, V3S)
27 Yes
2 No
7 Additional human resources
18 Additional computing capabilities
Is computational time shared with the wider community? If so, how is this interaction organized? (III7L)
9 Yes
12 No
2 Yes, via scientific collaboration
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1 Only within DOD and with DOD funded scientists
3 Sharing is through a queuing system
2 Sharing through proposals for computer time
1 Sharing only within DOE
3 Via allocation process
1 Via output only
Please provide your thoughts on the relative merits and hindrances of running your models on massively parallel processing sys tems relative to parallel vector architectures. (IV1L)
4 Massively parallel architecture is better
18 Parallel vector architecture is better
MPP architecture is better but:
There are a lack of compilers for these systems
The transfer of code to MPP is not easy
Vendors are not ready to supply the needed systems
Other comments:
MPP is harder to use
MPP benefit is that the processing time is cheaper as the cost of the systems and maintenance is less than for parallel vector systems
MPP offers more CPU power and memory per dollar spent
Some new models can only be run on MPP
MPP requires longer code development
MPP is not scalable
MPP offers poor system software and is unstable
MPP requires additional personnel
MPP offers poor communication among processors
Do you use models or outputs from other facilities? If so, are any restrictions placed on the models or data? (VI3S)
12 Yes
0 No
Restrictions:
Output is restricted to research collaborators
DOE security restrictions on computing access
No restrictions
Some foreign data is restricted
Some data are restricted due to being in a pre-release state
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How “portable” is your code without experiencing major performance loss? (IV6L)
22 Very portable
2 Somewhat portable
8 Code is custom altered for specific platforms
1 Code works on MPP only
1 Code is portable to VPP and MPP with some limitation
Are you currently planning to (or intending to in the future) convert model codes to run on massively parallel machines? If cur rently converting, what experience do you have with this process? If intending to in the future, what are your plans for doing so? (V5L)
10 Already converted
12 Underway
2 Not underway
Are model results produced by your facility made available to the wider scientific community? If so, are any restrictions placed on the models or data? (VI2S)
10 Yes
0 No
Are model results produced by your facility made available to a wider scientific community? If so, are any restrictions placed on the data? (IV2L)
3 Yes with some restrictions
21 Yes
1 Yes, but only with collaborators
0 No
Additional:
2 More widely distributed if resources were available
1 Yes, through published work
Are the number of staff supporting your efforts sufficient? If not, please describe where improvements are needed. (V2L)
6 Yes
20 No
Staff needed for:
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Data interpretation and analysis
Programmers
Software engineers
Hardware maintenance
Model simulation interpretation
High-performance applications
Are the number of staff supporting your efforts sufficient? If not, please describe where improvements are needed. (VII2S)
4 Yes
8 No
Staff needed for:
Data interpretation and analysis
Programmers
Model developers
Do you feel that your efforts are being limited by access to high-end computing resources? By access to model output from large modeling centers? By availability of diagnostic tools? By any other factors? (VIII1S)
11 Yes
1 No
1 Skilled personnel are not centrally located
1 No long-term strategy
1 Data outputs need to be made more user friendly
1 Satellite data needs to be made more user friendly
9 Access to computing
1 Access to global models
1 Stable funding
Do you feel that your modeling efforts are being limited by lack of sufficient high-end computing resources? By people? By other resources? By any other factors? (VI1L)
26 Yes
27 No
Factors:
17 People
18 Computing
Other factors:
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Lack of well-documented modern model codes
Network bandwidth
Data storage
Stable funding
When staffing positions in the categories listed above, what are the main difficulties, if any, involved (i.e. level of training required, salary requirements). (V3L, VII3S)
1 Research is very specialized
16 Salary is not competitive
10 Finding funding
15 Level of training
7 Difficult to find qualified programmers
1 Navy bureaucracy
3 Difficult to find model developers
1 No difficulty
Please describe any future changes in staffing that are planned. (V4L)
7 None
8 Model/software support
8 Scientist
5 Modeler
1 Hardware
Please describe any future changes in staffing that are planned. (VI4S)
4 None
4 Model/software support
3 Scientist
0 Hardward maintenance
What is your highest priority if some of these limiting factors are removed? (VI2L)
11 Enhanced computing capabilities
8 Enhanced human resources
7 Improved physical performance of the models
1 Build a modeling system infrastructure
4 Increase the number of models
7 Increase model resolution
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1 Develop a high performance regional climate model
1 Adapt model code for parallel systems
1 Perform simulations on non-local systems
1 Additional R& D research funding
Do you feel that future modeling efforts will be hindered by the availability of quality graduate students? If so, what steps would you recommend to remedy this problem? (VI5S)
3 No
5 Yes