Using Statistical Views of Measurements to Guide ARM Data Discovery and Access
| Giri Palanisamy | Oak Ridge National Laboratory |
| Raymond McCord | Oak Ridge National Laboratory |
| Betsy Horwedel | Oak Ridge National Laboratory |
| Richard Cederwall | Lawrence Livermore National Laboratory |
| Dale Kaiser | Oak Ridge National Laboratory |
| Sean Moore | Mission Research |
| Renata McCoy | Lawrence Livermore National Laboratory |
| Stephen Klein | Lawrence Livermore National Laboratory |
| Shaocheng Xie | Lawrence Livermore National Laboratory |
Category: Infrastructure & Outreach
The ARM Archive has been providing data access and discovery through various user interfaces based on inventories of data availability (from 3.3 million data files and hundreds of measurement types). A new Statistical Browser Interface is being developed so that users can discover and access data based on the observed results by viewing hierarchical statistical summaries. The display of statistical views allows the user to include an overview of the measured results in the process of deciding which long-term ARM data are of interest to them. This approach provides the various modeling communities with products that are easily accessible and display insights needed for research on model parameterization and validation. The prototype of statistical views currently consists of pre-computed products for nested time ranges (whole period of record, annual, seasonal, and monthly--as appropriate). For each time range and measurement, a variety of simple statistics are computed. Graphs of the statistical distribution of measurements (e.g., histograms) also are linked to the statistical results. The graphs are available through a web-based interface. Users select a location and measurement and then drill down through time scales ranging from the full period of record to individual months. Currently, statistical graphs are available for the Best Estimate Product, Data Quality Assessment for ARM Radiation Data (QCRAD) and Long-Term Continuous Forcing Data from Variational Analysis (CONSTRVARANA). While viewing the graphs displayed by the user interface, users will be able to extract the data behind the statistical graphs, or the measurement data used in calculating the statistics, or order the ARM data files using the ARM data cart.
http://www.archive.arm.gov/arm/stattnb1.jsp
This poster will be displayed at ARM Science Team Meeting.
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