{"id":"https://openalex.org/W4416618443","doi":"https://doi.org/10.48550/arxiv.2510.20228","title":"Sparse Local Implicit Image Function for sub-km Weather Downscaling","display_name":"Sparse Local Implicit Image Function for sub-km Weather Downscaling","publication_year":2025,"publication_date":"2025-10-23","ids":{"openalex":"https://openalex.org/W4416618443","doi":"https://doi.org/10.48550/arxiv.2510.20228"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2510.20228","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.20228","pdf_url":"https://arxiv.org/pdf/2510.20228","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.20228","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120563426","display_name":"Yago del Valle Inclan Redondo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Redondo, Yago del Valle Inclan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120378251","display_name":"Enrique Arriaga-Varela","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arriaga-Varela, Enrique","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009463126","display_name":"Dmitry R. Lyamzin","orcid":"https://orcid.org/0000-0002-7082-2902"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyamzin, Dmitry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088477364","display_name":"Pablo Cervantes","orcid":"https://orcid.org/0000-0003-2970-1444"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cervantes, Pablo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5059552797","display_name":"Tiago Ramalho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramalho, Tiago","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.13439999520778656,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.13439999520778656,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.11789999902248383,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.08969999849796295,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/downscaling","display_name":"Downscaling","score":0.9297999739646912},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5860000252723694},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.566100001335144},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41510000824928284},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.37770000100135803},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.37560001015663147}],"concepts":[{"id":"https://openalex.org/C41156917","wikidata":"https://www.wikidata.org/wiki/Q682831","display_name":"Downscaling","level":3,"score":0.9297999739646912},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5860000252723694},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.566100001335144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.553600013256073},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41510000824928284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4147000014781952},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.36230000853538513},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35370001196861267},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29089999198913574},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2567000091075897}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.20228","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.20228","pdf_url":"https://arxiv.org/pdf/2510.20228","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.20228","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.20228","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.20228","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.20228","pdf_url":"https://arxiv.org/pdf/2510.20228","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,15,46],"introduce":[1],"SpLIIF":[2],"to":[3,39,50,53],"generate":[4],"implicit":[5],"neural":[6],"representations":[7],"and":[8,23,27,30,35,44,59,65],"enable":[9],"arbitrary":[10],"downscaling":[11,63],"of":[12],"weather":[13,21],"variables.":[14],"train":[16],"a":[17],"model":[18,49],"from":[19],"sparse":[20],"stations":[22],"topography":[24],"over":[25],"Japan":[26],"evaluate":[28],"in-":[29],"out-of-distribution":[31],"accuracy":[32],"predicting":[33],"temperature":[34],"wind,":[36],"comparing":[37],"it":[38],"both":[40,57],"an":[41],"interpolation":[42],"baseline":[43,61],"CorrDiff.":[45],"find":[47],"the":[48,60],"be":[51],"up":[52],"50%":[54],"better":[55,68],"than":[56],"CorrDiff":[58],"at":[62],"temperature,":[64],"around":[66],"10-20%":[67],"for":[69],"wind.":[70]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-25T00:00:00"}
