Storm tracking with remote data and distributed computing Export

@article{Froude2008CaGeo, abstract = {Meteorological datasets are continuously getting larger, as a result of increasing computer power allowing models to be run at higher resolutions and for longer time periods. This is making it increasingly difficult to analyse these datasets at a single location. A web application has been developed to address this problem. The web application allows storm identification and tracking software to be executed from a web browser. It accesses remote datasets using the OPeNDAP protocol and makes use of distributed computing techniques with Condor. The web application currently enables users to compute storm tracks from the National Centers for Environmental Prediction (NCEP) re-analysis and ensemble prediction datasets, which are both archived in the USA. A list of jobs can be constructed and executed across multiple computers to reduce computation time. The progress of each job can be monitored and once completed, the computed storm tracks can be downloaded and plotted in a web browser. Applications of the web application are also discussed.}, author = {Froude, Lizzie S.}, citeulike-article-id = {3114853}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.cageo.2007.11.004}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6V7D-4RXJYR2-2/2/165d3975690c17d988861ea95e912e2a}, doi = {10.1016/j.cageo.2007.11.004}, journal = {Computers \& Geosciences}, keywords = {diss-lit-pa, gis-meteorology, gis-opendap, gis-web}, month = {November}, number = {11}, pages = {1621--1630}, posted-at = {2008-08-13 10:03:57}, priority = {3}, title = {Storm tracking with remote data and distributed computing}, url = {http://dx.doi.org/10.1016/j.cageo.2007.11.004}, volume = {34}, year = {2008} }

TY - JOUR ID - Froude2008CaGeo L3 - citeulike-article-id:3114853 N2 - Meteorological datasets are continuously getting larger, as a result of increasing computer power allowing models to be run at higher resolutions and for longer time periods. This is making it increasingly difficult to analyse these datasets at a single location. A web application has been developed to address this problem. The web application allows storm identification and tracking software to be executed from a web browser. It accesses remote datasets using the OPeNDAP protocol and makes use of distributed computing techniques with Condor. The web application currently enables users to compute storm tracks from the National Centers for Environmental Prediction (NCEP) re-analysis and ensemble prediction datasets, which are both archived in the USA. A list of jobs can be constructed and executed across multiple computers to reduce computation time. The progress of each job can be monitored and once completed, the computed storm tracks can be downloaded and plotted in a web browser. Applications of the web application are also discussed. IS - 11 JF - Computers & Geosciences EP - 1630 TI - Storm tracking with remote data and distributed computing VL - 34 SP - 1621 KW - diss-lit-pa KW - gis-meteorology KW - gis-opendap KW - gis-web AU - Froude, Lizzie PY - 2008/11// UR - http://dx.doi.org/10.1016/j.cageo.2007.11.004 ER -