{"id":"https://openalex.org/W7170163294","doi":"https://doi.org/10.48550/arxiv.2607.20230","title":"PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling","display_name":"PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling","publication_year":2026,"publication_date":"2026-07-22","ids":{"openalex":"https://openalex.org/W7170163294","doi":"https://doi.org/10.48550/arxiv.2607.20230"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.20230","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.20230","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.20230","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5143480571","display_name":"Shiyuan Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Shiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767610","display_name":"Runlong Yu","orcid":"https://orcid.org/0000-0003-4080-2377"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Runlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090105992","display_name":"Chonghao Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Chonghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143482038","display_name":"Yue Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143511159","display_name":"Rahul Ghosh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ghosh, Rahul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014901624","display_name":"Robert Ladwig","orcid":"https://orcid.org/0000-0001-8443-1999"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ladwig, Robert","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041638098","display_name":"Paul C. Hanson","orcid":"https://orcid.org/0000-0001-8533-6061"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanson, Paul C.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143516029","display_name":"Yiqun Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yiqun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5143513988","display_name":"Xiaowei Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Xiaowei","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/T14427","display_name":"Environmental Monitoring and Data Management","score":0.20909999310970306,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"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/T14427","display_name":"Environmental Monitoring and Data Management","score":0.20909999310970306,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"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/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.17020000517368317,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.11900000274181366,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7192999720573425},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.3555000126361847},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.3262999951839447},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.32420000433921814},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.28999999165534973}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7192999720573425},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6532999873161316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.376800000667572},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34279999136924744},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31439998745918274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30880001187324524},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.20230","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.20230","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":"doi:10.48550/arxiv.2607.20230","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.20230","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"modeling":[1],"of":[2,44],"environmental":[3],"systems":[4],"is":[5],"fundamental":[6],"to":[7,31],"scientific":[8],"understanding":[9],"and":[10,19,136,140],"decision-making,":[11],"yet":[12],"remains":[13],"challenging":[14],"because":[15],"observations":[16],"are":[17],"limited":[18],"physical":[20,46],"dynamics":[21],"vary":[22],"across":[23,34,119,147],"systems.":[24],"Retrieval-augmented":[25],"approaches":[26],"offer":[27],"a":[28,65,73,143],"natural":[29],"path":[30],"transfer":[32],"knowledge":[33],"systems,":[35],"but":[36],"standard":[37],"embedding-based":[38,70],"retrieval":[39,71,106],"does":[40],"not":[41],"guarantee":[42],"consistency":[43,81],"underlying":[45,57],"processes,":[47],"since":[48],"scenarios":[49],"with":[50,72,82],"similar":[51],"embeddings":[52],"may":[53],"arise":[54],"from":[55],"different":[56],"mechanisms.":[58],"We":[59],"propose":[60],"Physics-Informed":[61],"Environmental":[62],"Retrieval":[63],"(PIER),":[64],"model-agnostic":[66],"framework":[67],"that":[68,76,101,128],"augments":[69],"physics-aware":[74],"stream":[75],"scores":[77],"candidates":[78],"by":[79],"flux-response":[80],"the":[83,104,120],"target,":[84],"using":[85],"local":[86],"verifiers":[87],"trained":[88],"on":[89,109,116],"physics-derived":[90],"flux":[91],"features.":[92],"A":[93],"weight":[94],"adjustment":[95],"mechanism":[96],"then":[97],"learns":[98],"per-scenario":[99],"weights":[100],"adaptively":[102],"balance":[103],"two":[105],"streams":[107],"based":[108],"diagnostic":[110],"features":[111],"summarizing":[112],"physics-stream":[113],"reliability.":[114],"Experiments":[115],"356":[117],"lakes":[118],"Midwestern":[121],"United":[122],"States":[123],"spanning":[124],"41":[125],"years":[126],"show":[127],"PIER":[129],"consistently":[130],"outperforms":[131],"baselines":[132],"for":[133],"water":[134],"temperature":[135],"dissolved":[137],"oxygen":[138],"prediction,":[139],"serves":[141],"as":[142],"general":[144],"augmentation":[145],"strategy":[146],"diverse":[148],"backbones.":[149]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-24T00:00:00"}