Three papers authored by GES DISC scientific staff members appear in the September 2010 issue of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, commonly known as JSTARS. (IEEE stands for the Institute of Electrical and Electronics Engineers, but the organization is much better known simply as "I triple-E" in the scientific community).
Aijun Chen of the GES DISC and George Mason University is the first author of the paper "Using KML and Virtual Globes to Access and Visualize Heterogeneous Datasets and Explore Their Relationships Along the A-Train Tracks." The paper demonstrates the use of KML files, which are visualized in Google Earth, to examine vertical atmospheric data profiles (called "curtain plots"). The data files are from the satellites orbiting in the A-Train constellation. (Formation Flying: The Afternoon "A-Train" Satellite Constellation fact sheet, in PDF). The A-Train orbital configuration allows data to be collected nearly simultaneously from several different satellites, allowing multiple complementary observations of atmospheric phenomena. The vertical atmospheric profiles can be examined with data mapped on the Earth's surface, providing a three-dimensional perspective. Chen's co-authors on this paper are Gregory Leptoukh, GES DISC Science Data Manager, and Steven Kempler, GES DISC Head.
The paper "Access, Visualization, and Interoperability of Air Quality Remote Sensing Data Sets via the Giovanni Online Tool" was authored by a collaborative team headed by Ana Prados (GES DISC / University of Maryland-Baltimore County). Her co-authors are Gregory Leptoukh, and Christopher Lynnes (GES DISC/ NASA), James Johnson (GES DISC/ Wyle IS LLC), Hualan Rui (GES DISC/ Adnet Inc.), and Rudolf "Rudy" Husar (Washington University of St. Louis). In this paper, the capability of Giovanni to display air quality related parameters (such as ozone concentration, NO2 concentration, SO2 concentration, aerosol optical depth, and surface PM2.5 data) is highlighted. Giovanni allows collocation of datasets to enable the examination of events impacting air quality, and also accelerates comparisons of satellite and surface monitoring data, as well as aerosol intercomparison studies.
William Teng of the GES DISC is a co-author of a third paper in this issue, "Analysis of Spatial Similarities Between NEXRAD and NLDAS Precipitation Data Products," with first author Zhuotong Nan (Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences) and co-authors Shugong Wang, Xu Liang (University of Pittsburgh), Thomas E. Adams (NOAA National Weather Service, and Yao Liang (Indiana University-Purdue University, Indianapolis, Indiana). This paper examines precipitation data generated by the Multisensor Precipitation Estimator (MPE) from NEXRAD (Next Generation Radar) and the NLDAS (North American Land Data Assimilation System) precipitation data. The research showed significant differences between the spatial distribution of precipitation estimates from these two systems, and attempted to identify the primary reasons for these differences. The paper demonstrates that the use of multiple metrics provided a better characterization of the similarities and dissimilarities between the two precipitation products.
Link to the JSTARS Volume 3, Issue 3 Table of Contents, with links to paper abstracts (full text of articles is available to subscribers):
IEEE Journal of Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 3, Issue 3