%0 Journal Article %1 Alder2015Web %A Alder, J. R. %A Hostetler, S. W. %D 2015 %J Environmental Modelling & Software %K web BigData visualisation %P 175--180 %R 10.1016/j.envsoft.2015.02.016 %T Web based visualization of large climate data sets %U http://dx.doi.org/10.1016/j.envsoft.2015.02.016 %V 68 %X Highlights • We introduce and provide an overview of the USGS National Climate Change Viewer (NCCV). • We describe the implementation and technologies used in the NCCV. • Memchached is used to improve map generation performance of THREDDS. Abstract We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

@article{Alder2015Web, abstract = {Highlights • We introduce and provide an overview of the USGS National Climate Change Viewer (NCCV). • We describe the implementation and technologies used in the NCCV. • Memchached is used to improve map generation performance of THREDDS. Abstract We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Alder, J. R. and Hostetler, S. W.}, biburl = {https://www.bibsonomy.org/bibtex/2f6e8ec391ba6a3f9338192e5c3c51059/pbett}, citeulike-article-id = {13546961}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.envsoft.2015.02.016}, doi = {10.1016/j.envsoft.2015.02.016}, interhash = {36fbd09fdb704c98c4689eeb4d0e807a}, intrahash = {f6e8ec391ba6a3f9338192e5c3c51059}, issn = {13648152}, journal = {Environmental Modelling \& Software}, keywords = {web BigData visualisation}, month = jun, pages = {175--180}, posted-at = {2015-03-11 20:40:14}, priority = {2}, timestamp = {2018-06-22T18:34:41.000+0200}, title = {Web based visualization of large climate data sets}, url = {http://dx.doi.org/10.1016/j.envsoft.2015.02.016}, volume = 68, year = 2015 }