Advanced Methodologies for NASA Science Missions

Most of NASA's commitment to computational space science involves the organization and processing of Big Data from space-based satellites, and the calculations of advanced physical models based on these datasets. But considerable thought is also needed on what computations are needed. The science questions addressed by space data are so diverse and complex that traditional analysis procedures are often inadequate. The knowledge and skills of the statistician, applied mathematician, and algorithmic computer scientist must be incorporated into programs that currently emphasize engineering and physical science. NASA's culture and administrative mechanisms take full cognizance that major advances in space science are driven by improvements in instrumentation. But it is less well recognized that new instruments and science questions give rise to new challenges in the treatment of satellite data after it is telemetered to the ground. These issues might be divided into two stages: data reduction through software pipelines developed within NASA mission centers; and science analysis that is performed by hundreds of space scientists dispersed through NASA, U.S. universities, and abroad. Both stages benefit from the latest statistical and computational methods; in some cases, the science result is completely inaccessible using traditional procedures. This paper will review the current state of NASA and present example applications using modern methodologies.