{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T01:35:45Z","timestamp":1780364145740,"version":"3.54.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>The impacts of climate change are felt by most critical systems, such as infrastructure, ecological systems, and power-plants. However, contemporary Earth System Models (ESM) are run at spatial resolutions too coarse for assessing effects this localized. Local scale projections can be obtained using statistical downscaling, a technique which uses historical climate observations to learn a low-resolution to high-resolution mapping. The spatio-temporal nature of the climate system motivates the adaptation of super-resolution image processing techniques to statistical downscaling. In our work, we present DeepSD, a generalized stacked super resolution convolutional neural network (SRCNN) framework with multi-scale input channels for statistical downscaling of climate variables. A comparison of DeepSD to four state-of-the-art methods downscaling daily precipitation from 1 degree (~100km) to 1\/8 degrees (~12.5km) over the Continental United States. Furthermore, a framework using the NASA Earth Exchange (NEX) platform is discussed for downscaling more than 20 ESM models with multiple emission scenarios.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/759","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"5389-5393","source":"Crossref","is-referenced-by-count":57,"title":["Generating High Resolution Climate Change Projections through Single Image Super-Resolution: An Abridged Version"],"prefix":"10.24963","author":[{"given":"Thomas","family":"Vandal","sequence":"first","affiliation":[{"name":"Northeastern University, Civil and Environmental Engineering"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evan","family":"Kodra","sequence":"additional","affiliation":[{"name":"risQ Inc."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sangram","family":"Ganguly","sequence":"additional","affiliation":[{"name":"Bay Area Environmental Research Institute"},{"name":"NASA Ames Research Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Michaelis","sequence":"additional","affiliation":[{"name":"University Corporation, Monterey Bay"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramakrishna","family":"Nemani","sequence":"additional","affiliation":[{"name":"NASA Advanced Supercomputing Division"},{"name":"NASA Ames Research Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Auroop R","family":"Ganguly","sequence":"additional","affiliation":[{"name":"Northeastern University, Civil and Environmental Engineering"},{"name":"risQ Inc."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","theme":"Artificial Intelligence","location":"Stockholm, Sweden","acronym":"IJCAI-2018","number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2018,7,13]]},"end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:55:47Z","timestamp":1530755747000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/759"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/759","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}