The important scientific challenge of understanding global climate change is one that clearly requires the application of knowledge discovery and datamining techniques on a massive scale. Advances in parallel supercomputing technology, enabling high-resolution modeling, as well as in sensor technology, allowing data capture on an unprecedented scale, conspire to overwhelm present-day analysis approaches. We present here early experiences with a prototype exploratory data analysis environment, CONQUEST, designed to provide content-based access to such massive scientific datasets. CONQUEST (CONtent-based Querying in Space and Time) employs a combination of workstations and massively parallel processors (MPP's) to mine geophysical datasets possessing a prominent temporal component. It is designed to enable complex multi-modal interactive querying and knowledge discovery, while simultaneously coping with the extraordinary computational demands posed by the scope of the datasets involved. A...

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 ...

The present study examines the simulation of the number of tropical storms produced in GCM integrations with a prescribed SST. A 9-member ensemble of 10-yr integrations (1979–88) of a T42 atmospheric model forced by observed SSTs has been produced; each ensemble member differs only in the initial atmospheric conditions. An objective procedure for tracking-model-generated tropical storms is applied to this ensemble during the last 9 yr of the integrations (1980–88). The seasonal and monthly variations of tropical storm numbers are compared with observations for each ocean basin. Statistical tools such as the Chi-square test, the F test, and the t test are applied to the ensemble number of tropical storms, leading to the conclusion that the potential predictability is particularly strong over the western North Pacific and the eastern North Pacific, and to a lesser extent over the western North Atlantic. A set of tools including the joint probability distribution and the ranked probability score are used to evaluate the simulation skill of this ensemble simulation. The simulation skill over the western North Atlantic basin appears to be exceptionally high, particularly during years of strong potential predictability. 1.

A probabilistic clustering technique is developed for classification of wintertime extratropical cyclone (ETC) tracks over the North Atlantic. We use a regression mixture model to describe the longitude-time and latitude–time propagation of the ETCs. A simple tracking algorithm is applied to 6-hourly mean sea-level pressure fields to obtain the tracks from either a general circulation model (GCM) or a reanalysis data set. Quadratic curves are found to provide the best description of the data. We select a three-cluster classification for both data sets, based on a mix of objective and subjective criteria. The track orientations in each of the clusters are broadly similar for the GCM and reanalyzed data; they are characterized by predominantly south-to-north (S–N), west-to-east (W–E), and southwest-to-northeast (SW–NE) tracking cyclones, respectively. The reanalysis cyclone tracks, however, are found to be much more tightly clustered geographically than those of the GCM. For the reanalysis data, a link is found between the occurrence of cyclones belonging to different clusters of trajectory-shape, and the phase of the North Atlantic Oscillation (NAO). The positive

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This paper investigates an episode of three successive cold outbreak events that took place over southeast Australia during May-June 2000. Of these three cold events, the most intense occurred on 27-28 May and was associated with a Melbourne maximum temperature of only 10.2°C. This is the second lowest daily maximum temperature recorded in Melbourne for May since 1958. The other two events, with slightly higher daily maximum temperatures, followed the first event closely. Various data processing techniques along with an air-parcel trajectory model and a sophisticated vortex tracking scheme are utilised to examine several aspects of these cold events, with a particular emphasis on the major event of 27 May. Results show that the synoptic pattern and its temporal evolution leading to the major event were characterised by a persistent anticyclone-cyclone dipole, located south of Australia. On the onset day, the configuration and position of this anticyclone-cyclone pair was such that a strong cold advection from the interior of Antarctica was implied, which was confirmed by

Detection, tracking and event localization of jet stream features in 4-D atmospheric data