The National Nuclear Security Administration (NNSA) Ground-Based Nuclear Explosion Monitoring Research and Engineering (GNEM R&E) Program has made significant progress enhancing the process of deriving seismic calibrations and performing scientific integration with automation tools. We present an overview of our software automation efforts and framework to address the problematic issues of very large datasets and varied formats utilized during seismic calibration research. The software and scientific automation initiatives directly support the rapid collection of raw and contextual seismic data used in research, provide efficient interfaces for researchers to measure/analyze data, and provide a framework for research dataset integration. The automation also improves the researcher's ability to assemble quality controlled research products for delivery into the NNSA Knowledge Base (KB). The software and scientific automation tasks provide the robust foundation upon which synergistic and efficient development of seismic calibration research may be built. The task of constructing many seismic calibration products is labor intensive and complex, hence expensive. However, aspects of calibration product construction are susceptible to automation and future economies. We are applying software and scientific automation to problems within two distinct phases or "tiers" of the seismic calibration process. The first tier involves initial collection of waveform and parameter (bulletin) data that comprise the "raw materials" from which signal travel-time and amplitude correction surfaces are derived and is highly suited for software automation. The second tier in seismic research content development activities include development of correction surfaces and other calibrations. This second tier is less susceptible to complete automation, as these activities require the judgment of scientists skilled in the interpretation of often highly unpredictable event observations. Even partial automation of this second tier, through development of prototype tools to extract observations and make many thousands of scientific measurements, has significantly increased the efficiency of the scientists who construct and validate integrated calibration surfaces. This achieved gain in efficiency and quality control is likely to continue and even accelerate through continued application of information science and scientific automation. Data volume and calibration research requirements have increased by several orders of magnitude over the past decade. Whereas it was possible for individual researchers to download individual waveforms and make time-consuming measurements event by event in the past, with the Terabytes of data available today, a software automation framework must exist to efficiently populate and deliver quality data to the researcher. This framework must also simultaneously provide the researcher with robust measurement and analysis tools that can handle and extract groups of events effectively and isolate the researcher from the now onerous task of database management and metadata collection necessary for validation and error analysis. We have succeeded in automating many of the collection, parsing, reconciliation and extraction tasks, individually. Several software automation prototypes have been produced and have resulted in demonstrated gains in efficiency of producing scientific data products. Future software automation tasks will continue to leverage database and information management technologies in addressing additional scientific calibration research tasks.

This project has built a unique historic database of regional distance nuclear explosion, earthquake, and mine-related digital broadband seismograms for the western United States (US). The emphasis is on data from Lawrence Livermore National Laboratory (LLNL)-managed stations MNA, ELK, KNB and LAC that recorded many nuclear tests and nearby earthquakes in broadband digital form since 1980, along with a small number of earlier events that were digitized from tapes. Through the generous cooperation of Sandia National Laboratories (SNL) we have also included waveforms from their Leo Brady network (BMN, DWN, LDS, NEL,TON). In addition we include data from other open broadband stations in the western US with long operating histories and/or ties to the International Monitoring System (e.g. PFO, YKA, CMB, NEW, DUG, ANMO, TUC). These waveforms are associated with a reconciled catalog of events and station response information to facilitate analysis. The goal is to create a high- quality database that can be used in the future to analyze fundamental regional monitoring issues such as detection, location, magnitude, and discrimination.

LLNL has developed a robust magnitude calibration methodology for sparsely distributed regional stations using narrow band coda envelopes. This technique provides stable magnitudes for small events that make detection and identification calibration possible at low magnitudes. This approach has most recently been applied to International Monitoring System (IMS) stations located in Israel, Jordan and Egypt for events that span local and near regional distances. Our preliminary results show that a magnitude estimate from one station using the coda is equivalent to a network average of roughly 9 stations when using traditional magnitudes (e.g., mb(P), ML, Md). The stability of the coda comes from measuring a long length of coda using a calibrated synthetic envelope as an empirical metric. We relate the non-dimensional coda amplitudes to an absolute scale by tying them to independent moment estimates from larger waveform-modeled events. Unlike most narrow band magnitudes, this approach yields an azimuthally averaged, moment-rate spectrum that is completely corrected for path and site effects. The resultant magnitudes from the spectra (e.g., Mw and mb) are fully transportable and do not suffer from regional bias.

The National Nuclear Security Administration (NNSA) Ground-Based Nuclear Explosion Monitoring Research & Engineering (GNEM R&E) program provides research and development in support of U.S. nuclear explosion monitoring. Specifically, the GNEM R&E program provides products that will be utilized by the Air Force Technical Applications Center (AFTAC) in their nuclear explosion monitoring and treaty monitoring missions. To serve this role, NNSA must develop, track, and integrate products as they move from the research level to operations and must ensure that these products are reliable and technically correct. NNSA's responsibilities include: 1. Development of operationally useful products (scientific data and the tools to manipulate them) that support the U.S. nuclear explosion monitoring mission at AFTAC, 2. Integration of technical products developed by NNSA and others into a comprehensive and cohesive package (Knowledge Base) that can be readily utilized by AFTAC, 3. Technical assessment, validation, and verification of all products prior to delivery to AFTAC, and 4. Delivery and integration support of the operational Knowledge Base to AFTAC. The practical implementation of the development, integration, assessment and delivery of operational products occurs through the process of creating periodic Knowledge Base releases. Specifically, the Knowledge Base is comprised of a set of Information Products, which generally include pertinent datasets and analytical tools. In addition, each Information Product also includes critical supporting information (metadata) about the datasets and tools. This paper describes implementation of the Knowledge Base development and integration process, including the utilization of technical working groups to coordinate and evaluate Information Products.