AeroStat: NASA Giovanni Tool for Statistical Intercomparison of Aerosols
Abstract
Giovanni is a NASA's interactive online visualization and analysis tool for exploring very large global Earth science datasets. One of the new Giovanni analytical and statistical tools is called AeroStat, and it is designed to perform the direct statistical intercomparison of global aerosol parameters. Currently, we incorporate the MAPSS (A Multi-sensor Aerosol Products Sampling System) data that provides spatio-temporal statistics for multiple spatial spaceborne Level 2 aerosol products (MODIS Terra, MODIS Aqua, MISR, POLDER, OMI and CALIOP) sampled over AERONET ground stations. The dataset period, 1997-2011 (up to date), is long enough to encompass a number of scientifically challenging cases of long-term global aerosol validation from multi-sensors. AeroStat allows users to easily visualize and analyze in details the statistical properties of such cases, including data collected from multiple sensors and quality assurance (QA) properties of these data. One of the goals of AeroStat is to also provide a collaborative research environment, where aerosol scientists can share pertinent research workflow information, including data cases of interest, algorithms, best practices, and known errors, with the broader science community and enable other users of the system to easily reproduce and independently verify their results. Furthermore, AeroStat provides an easy access to the data provenance (data lineage) and quality information, which allows for a convenient tracing of scientific results back to their original input data, thus further ensuring the reliability of these results. Case studies will be presented to show the described functionality and capabilities of AeroStat, and possible directions of the future development.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFMIN51C1604W
- Keywords:
-
- 0305 ATMOSPHERIC COMPOSITION AND STRUCTURE / Aerosols and particles;
- 1900 INFORMATICS;
- 1984 INFORMATICS / Statistical methods: Descriptive