# Presentation: 524836

## Rapid Prototyping Capabilityfor Earth-Sun System Sciences 

- Robert J. Moorhead
- Mississippi State University

- 19 April 2006

## Approach

- Formulate architectures and develop baseline capacities that integrate applied sciences systems tools into configurations to support efficient evaluation of the prospects of integrating research results from NASA’s Earth observation systems (with emphasis on spacecraft instruments on missions recently launched or planned for near-term launch) and associated Earth system models
- systems engineering tools
- enterprise architecture tools
- information visualization and analysis tools
- uncertainty characterization tools
- performance assessment tools
- “NASA Earth Science and Space Systems benefiting Society:  Evolving Systems Engineering Capacity,” presentation by Ron Birk, August 24, 2005, SSC

- 19 April 2006

## Approach

- A systems engineering approach will be used to integrate and evolve the engineering and analysis tools necessary to efficiently evaluate candidate research results, through a **rapid prototyping capability, **to further determine potential solutions for assimilation into operational decision support processes and enable the community to propose projects for feasible solutions using innovative NASA research results.

- From “Extending NASA Earth-Sun System Research Results through a Systems Engineering Capacity,” Working Document, NASA Applied Sciences Program

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## Applied Sciences Systems Engineering Environment

- From “Extending NASA Earth-Sun System Research Results through a Systems Engineering Capacity,” Working Document, NASA Applied Sciences Program

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## Distributed Computational Simulation System:

- Interaction between users and subsystems

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## MRC Leadership Team

- Robert Moorhead, MSU, PI
- David Shaw, MSU, Co-PI
- Chuck Hill, MSU, Management
- Jim Aanstoos, MSU, Project Management
- Ed Allen, MSU, Systems Engineering
- Tomasz Haupt, MSU, System Development
- Chuck O’Hara, MSU, Ag Efficiency & Data Processing (DP)
- Valentine Anantharaj, MSU, Atmospheric Sciences & DP
- Greg Easson, UM, Evaluation, Coastal Apps & Ecological

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## NASA Partners

- Stennis
- Grant Administration (Robert Venezia, Project Manager; Greg Fletcher, Procurement Officer)
- RPC Project Team (Tom Stanley, Craig Peterson, Callie Hall,  Slawomir Blonski)
- Goddard
- Office of Science Utilization (Shahid Habib)
- Hydrological Sciences Branch (Christa Peters-Lidard)
- BASINS/HSPF project (David Toll)
- Marshall
- SPoRT Center (Gary Jedlovec)
- SERVIR Lab (Dan Irwin)
- Langley
- Chief Scientist (David Young)

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## Other Partners

- SSAI, Geoprocessing (ART)
- ITD, node deployment at SSC
- USGS Modular Modeling Group
- UAH Atmospheric Science Department
- Model Developers/Owners
- Data Providers

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## The baseline system. This four-tier architecture follows OGSA recommendations

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**Notes:**
Baseline system (Preliminary Design)
The development of CRPN will extend the current grid infrastructure developed and deployed at Mississippi State University [Haupt2002, Haupt2003], which is used to support the NEESport [Haupt2005a], SPURport [Haupt2005b] and DMEFS [Haupt2001] systems, as schematically shown in Figure 3.
The most prominent features of the baseline system are high-level grid services, or façades, that capture common patterns of accessing the Grid resources.  For example, the Data Services combine metadata, data access replica locator and file transfer services, and provide a simple interface for retrieving files of known signature but unknown location.  The user selects a file by searching the metadata repository (a keyword-based query) for the selected file and the Data Services seamlessly determine its location (i.e., URL) from the Replica Locator.  Then the URL is passed to the File Transfer Service to start streaming the data to the user.  The User Space is another application of the Data Service that allows the user to store information on his or her activities (i.e., provenance), such as job descriptors and values of parameters used for a particular run.  Provenance is critical for linking the model parameters with the model output datasets and thus achieving convergence of models and data [ESMF].  Finally, the Job Submission Services (c.f. Fig. 4) invokes several base services to stage the data, retrieves information needed for generation GRAM RSL request, set the environment on the target machine, submits the job and registers itself as a target for GRAM notifications, so that it can forward the status changes to the Job Monitoring Service. The Job Monitoring Service provides access to all jobs submitted through the portal, their status and their descriptor. Through the job descriptor, the user has access to all results generated by the job.
The Grid Services are implemented as WSDL/WSRF services, invoked by Service Providers running inside the GridSphere portal server for the Web Browser-based clients or Service Providers added as modules to stand-alone applications such as Abacus and Matlab. 

## Functional computational capabilities of the RPC system

- Evaluations leading to new understanding & ideas for ISS

**MyRPC**

**LIS**

**IGE**

**Authorization**
**Authentication**
**Notification**
**Monitoring**
**Workflow**
**Security**

**ESMF**
**GCMD**
**THREDDS**
**ESML**
**Ontology**
**Query**

**MyRPC**
**Host environment**
**GPIR**
**Execution description**
**Application description**
**Grid enabled OGC Services**

**WorldWinds**

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**Notes:**
System Capabilities and the CRPN Environments
(based on NSF LEAD approach)
CRPN comprises a “complex array of services, applications, interfaces, and local and remote computing, networking and storage resources – so-called environments – that can be used as stand-alone resources or linked together in workflows” for rapid-protyping applications.  This approach to RPC, based on the NSF LEAD, would provide  the RPC users an array of capabilities including simplified and scripted access to data, transforming and translating the data into different formats and projections, visualization of the data and results, running the models, and performing complex analysis of the results.

The complexity of the proposed RPC architecture necessitates the provision of multiple viewpoints in order to comprehend its functionalities and extensibility to accommodate changes.  Hence, a number of diagrams are provided to depict the needs of users, systems engineers and computer scientists, and other stakeholders.

At the fundamental level of functionality, CRPN enables users to accomplish the following: 
• Query for and Acquire a wide variety of information including but not limited to observational data sets (including real time streams) and gridded model output stored on local and remote servers, definitions of and interrelationships among meteorological quantities, the status of an IT resource or workflow.
• Simulate and Predict using numerical atmospheric models, particularly the Weather Research and Forecast (WRF) model system now being developed by a number of organizations. The WRF can be run in a variety of modes ranging from basic (e.g., single vertical profiles of temperature, wind and humidity in a horizontally homogeneous domain) to very complex (full physics, terrain, and inhomogeneous initial conditions in single forecast or ensemble mode). 
• Assimilate data by combining observations, under imposed dynamical constraints, with background information to create a 3D atmospheric gridded analysis. CRPN is envisioned to support the WRF-SI, and possibly the ARPS Data Assimilation System (ADAS) in collaboration with SPoRT and will incorporate the WRF 3DVAR, as necessary.
• Analyze and Mine observational data and model output to obtain quantitative information about spatio-temporal relationships among fields, processes, and features. 
• Visualize observational and remotely sensed data and model output in 1D, 2D and 3D. 

## RPC Portal

**RPC Portal**

**MyRPC**

**GCMD**

- Service oriented architecture for Computational RPC Node
- [based on NSF LEAD (Drogemeier et. al., 2006)]

**WRF, HSPF**
**LIS, RAMS**

**DAACs**
**CLASS**

**Evaluation**

**ESMF, GEOLEM**

**OGC Services**

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## Systems framework for CRPN, consisting of interacting subsystems in the

- CRPN

**WRF**

**ESMF**

**IGE**

**GCMD**

- secure and stable RPC computational grid
- [based on NSF LEAD (Drogemeier et. al., 2006)]

**MyRPC workspace**

**LIS**

**WorldWinds**

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## Slide 13

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## Slide 14

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## Slide 15

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## Management Approach:  SDM

- The Science Data Manager (SDM) accesses the data from the NASA Earth-Sun Observation Sources.
- The sources include the Distributed Active Archive Centers (DAAC’s), Observing System Simulation Experiments (OSSE’s), and other data that may be simulated through the Application Research Toolkit (ART) and similar systems.
- In this component of the architecture, the metadata will be developed and maintained and the compliance with the NASA Enterprise Architecture (EA) begun.
- The SDM will supply input to the Earth Observation section of the Earth-Sun System Architecture Tool.
- The proposed RPC will focus on spacecraft instruments on missions recently launched or planned for near-term launch.
- Lead:  Haupt
- Team:  O’Hara, Anantharaj, Easson, data providers

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## Management Approach:  IGE

- The Interoperable Geoprocessing Environment (IGE) is responsible for the development of the data products that measure the appropriate Geophysical Parameter needed for the Models and Analysis Systems being prototyped.
- The data from the NASA sources will be processed to extract the specific information needed for the prototype in development.
- The IGE includes two sub-components; Data Assimilation Tools and Model Data Resource Manager.
- This is the *critical component* in a truly Rapid Prototyping Capability.
- Lead:  O’Hara
- Team:  Haupt, Anantharaj, Easson, Yarbrough, Stennis Team, USGS

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## Management Approach:  IGE

- The IGE includes two sub-components:  Data Assimilation Tools and Model Data Resource Manager.
- The *Data Assimilation Tools* – transformation, manipulation, extraction and other pre-processing needed to produce the *Geophysical Parameter* input needed for the *Model Manager* component of the architecture.
- The requirements of the model and the processing steps required to produce the input will be stored in a database and used to ensure the quality of the data produced.
- The *Model Data Resource Manager* – documentation and cataloging of the model requirements in a database
- to identify requirements that are common to multiple models, and
- speed development of additional prototypes that require the same input data.
- The database developed will supply input to the Data Products section of the NASA EA tool.

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## Management Approach:  MM

- The *Model Manager *component of the proposed architecture also has two sub-components that correspond with the Knowledge Base: the *Model Base Manager *and *Model Results Resource Manager.*
- These components correspond to the *Model & Analysis Systems *and *Model Outputs/Predictions* parts of the Knowledge Base.
- Haupt and his team will develop this portion, but other team members will assist model owners/developers with specifying their SDM and IGE needs and prototyping their model within the RPC.
- The *Model Manager* component will be coordinated with the Earth System Modeling Framework (ESMF) to contribute to the building of an infrastructure designed to increase the performance, portability, interoperability, and coordination in the modeling community.

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## Management Approach:  MM

*Model Base Manager* manages the model runs in the prototyping process to ensure valid results.
- The manager catalogs the configuration of the model run, the other parameters that influence the model performance, and the data used in each model.
- The agency partner that developed or operates the model will supply the model configuration parameters and assist in the evaluation of model runs.
- The *Model Results Resource Manager *records and catalogs the results of the model runs and provides the information that will be needed to benchmark the improvement in the model performance.
- The outcomes from the *Model Manager* component of the architecture form the basis of input for the model outputs section of the Earth-Sun System Architecture Tool.

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## Management Approach:  PMW

*Performance Metrics Workbench* (PMW) will determine if there is significant improvement in a model’s performance.  The results of the model using NASA data will be compared to the current results and the difference evaluated.
- A key component of the *PMW *will be the visualization of the model results.
- The Model Scenario Comparison Toolkit includes the quantitative tools to evaluate model performance.  These tools include the statistical analysis of the numerical results to determine the significance of any differences in outcome.
- Lead: Moorhead
- Team: Jankun-Kelly (MSU) and Kuszmaul (UM).

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## Deliverables

- A Capabilities Document and a Preliminary Design will be developed in the first 90 days after award and delivered at least two weeks in advance of a Preliminary Design Review (PDR) to be held no sooner than 90 days from the date of award and no later than 120 days from the date of award.
- An Implementation Plan that is reflective of the reviews obtained from the PDR.  The Implementation Plan will include a means for continuous testing via application partners, will account for subsequent development activities, and will provide for the approach to transition and network the capabilities to a node for the Applied Sciences Program (ASP) at Stennis Space Center (SSC).
- System Design Document
- Test Evaluation Document

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## Deliverables

- Twelve (12) Reports evaluating the efficacy of the system design, component configurations, external interfaces and connections, and sensors, data, and/or other research capabilities. These reports will document the suitability of the RPC for further study of candidate configurations of NASA research results to serve specific National Applications.
- Monthly status reports that include task completion status will be submitted via email to the NASA Technical Monitor.
- Documents for quarterly technical design and management reviews, which will be delivered at least one week before the review.
- Quarterly status teleconferences with project team and NASA personnel.
- Participation in semi-annual peer review workshops
- Implementation of a system node at SSC
- Final Design Document

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## Preliminary Implementation Plan

|         National
             App

Evaluations | Agricultural
Efficiency Sinclair Model –  USDA PECAD
(O’Hara) | Disaster
Management Forest Fire Predictability (Cooke)
WRF/LIS
(Anantharaj) | Coastal
Management | Water Management HSPF
(McAnally & Martin) | Ecological Forecasting
SERVIR
(Easson) | Invasive Species NISFS
(Bruce) |
| --- | --- | --- | --- | --- | --- | --- |
| Baseline Evaluation | Evaluation Report 1 | Evaluation Report 2 |  | Evaluation Report 3 | Evaluation Report 4 | Evaluation Report 5 |
| Assimilation Plan and Evaluation | Evaluation Report 6 | ••• |  |  |  |  |
| Model Results Evaluation |  |  |  |  |  | Evaluation Report N |

- t

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## Models from Other National Application Areas?

- Air Quality
- Aviation
- Carbon Management
- Energy Management
- Homeland Security
- Public Health

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## Accomplishments to date

- Team kick-off meeting (Feb 6) and many meetings since to discuss how to establish optimum capability and capacity
- Visited SSC twice and hosted SSC personnel once for discussions
- Telecon with Hydrological Sciences Branch, GSFC, to discuss RPC involvement
- Visited NSSTC/UAH to discuss plans
- Ordered hardware components for local node
- Scheduled PDR
- Completed first draft of ConOp for most models
- Drafts of Capabilities Document and Preliminary Design

- 19 April 2006

## Next Steps

- Form a Working Group to determine most appropriate NASA Earth-Sun science research results and observations to evaluate – tomorrow?
- Complete PDR
- Complete Implementation Plan
- Complete System Design Document
- Complete Test Evaluation Document(s)
- Commence evaluations
- Write evaluation reports
- Publish archival articles

- 19 April 2006