A major challenge facing geophysical science today is the unavailability of high-level analysis tools with which to study the massive amount of data produced by sensors or long simulations of climate models. We have developed a prototype system called QUEST to provide content-based access to massive datasets. QUEST employs workstations as well as teraFLOP computers to analyze geoscience data to produce spatial-temporal features that can be used as high-level indexes. Our first application area is global change climate modeling. In the initial prototype, the first features extracted are cyclones trajectories from the output of multi-year climate simulations produced by a General Circulation Model. We present an algorithm for cyclone extraction and illustrate the use of cyclone indexes to access subsets of GCM data for further analysis and visualization. 1 Introduction A critical challenge facing geophysical science today is the unavailability of high-level analysis tools with which to ...

Motivated by the premise that heterogeneity of software applications and hardware systems is here to stay, we are developing OASIS, a flexible, extensible, and seamless environment for scientific data analysis, knowledge discovery, visualization, and collaboration. In this paper we discuss our OASIS design goals and present the system architecture and major components of our prototype environment. 1 Introduction In the course of research activities, a scientist would like to efficiently store, retrieve, analyze and interpret selected data sets from a large collection of scientific information scattered across heterogeneous computational environments, and to share the gleaned information with other scientific communities both nationally and internationally. Consider the following prototypical interaction of a scientist with a dataset 1 . Once a scientist has located the dataset of interest, a major undertaking in its own right, a specific portion of the dataset is retrieved. Typical...