{"id":"https://openalex.org/W2884498293","doi":null,"title":"Model uncertainty estimation in data assimilation for multi-scale systems with partially observed resolved variables","display_name":"Model uncertainty estimation in data assimilation for multi-scale systems with partially observed resolved variables","publication_year":2018,"publication_date":"2018-07-24","ids":{"openalex":"https://openalex.org/W2884498293","mag":"2884498293"},"language":"en","primary_location":{"id":"mag:2884498293","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/pdf/1807.09621.pdf","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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/1807.09621.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087316749","display_name":"Sahani Pathiraja","orcid":"https://orcid.org/0000-0002-0114-3164","observed_orcids":["https://orcid.org/0000-0002-0114-3164"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sahani Pathiraja","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0114-3164","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063378345","display_name":"Peter Jan van Leeuwen","orcid":"https://orcid.org/0000-0003-2325-5340","observed_orcids":["https://orcid.org/0000-0003-2325-5340"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Jan van Leeuwen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2325-5340","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":1,"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":0.9965999722480774,"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":0.9965999722480774,"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/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.002199999988079071,"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/T11206","display_name":"Model Reduction and Neural Networks","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/model-uncertainty-quantification","display_name":"model uncertainty quantification","score":0.8799999952316284},{"id":"https://openalex.org/keywords/data-assimilation","display_name":"data assimilation","score":0.9629999995231628},{"id":"https://openalex.org/keywords/model-error-estimation","display_name":"model error estimation","score":0.7070000171661377},{"id":"https://openalex.org/keywords/stochastic-parameterization","display_name":"stochastic parameterization","score":0.7480000257492065},{"id":"https://openalex.org/keywords/subgrid-scale-processes","display_name":"subgrid-scale processes","score":0.8820000290870667},{"id":"https://openalex.org/keywords/conditional-density","display_name":"conditional probability density","score":0.8149999976158142},{"id":"https://openalex.org/keywords/non-gaussian-uncertainty","display_name":"non-Gaussian uncertainty","score":0.8130000233650208},{"id":"https://openalex.org/keywords/multiscale-systems","display_name":"multiscale systems","score":0.875},{"id":"https://openalex.org/keywords/lorenz-96-model","display_name":"Lorenz 96 model","score":0.9079999923706055},{"id":"https://openalex.org/keywords/timescale-separation","display_name":"time-scale separation","score":0.7039999961853027}],"concepts":[{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.7613562345504761},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5683168172836304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5063894987106323},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.49714210629463196},{"id":"https://openalex.org/C179024874","wikidata":"https://www.wikidata.org/wiki/Q5395728","display_name":"Errors-in-variables models","level":2,"score":0.493554949760437},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4688362181186676},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4256068766117096},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3803100287914276},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3766421675682068},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30221349000930786},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.10124695301055908},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2884498293","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/pdf/1807.09621.pdf","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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2884498293","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/pdf/1807.09621.pdf","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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1587348082","https://openalex.org/W1959024134","https://openalex.org/W1962855533","https://openalex.org/W1987315804","https://openalex.org/W1996786220","https://openalex.org/W2035933721","https://openalex.org/W2067409914","https://openalex.org/W2087070363","https://openalex.org/W2090955752","https://openalex.org/W2103757834","https://openalex.org/W2109005173","https://openalex.org/W2118428107","https://openalex.org/W2126202478","https://openalex.org/W2146803308","https://openalex.org/W2148474597","https://openalex.org/W2152599715","https://openalex.org/W2154358707","https://openalex.org/W2157098139","https://openalex.org/W2157499377","https://openalex.org/W2160811279","https://openalex.org/W2161691942","https://openalex.org/W2173190456","https://openalex.org/W2174784159","https://openalex.org/W2175913405","https://openalex.org/W2179584279","https://openalex.org/W2274190189","https://openalex.org/W2461562005","https://openalex.org/W4390461978"],"related_works":["https://openalex.org/W3171334681","https://openalex.org/W2994881203","https://openalex.org/W3020098949","https://openalex.org/W2789558175","https://openalex.org/W2242762476","https://openalex.org/W2995396760","https://openalex.org/W2790650361","https://openalex.org/W1936777844","https://openalex.org/W4392677857","https://openalex.org/W3071685551"],"abstract_inverted_index":{"Model":[0,29,153],"uncertainty":[1,262],"quantification":[2],"is":[3,82,120,172],"an":[4],"essential":[5],"component":[6],"of":[7,37,51,65,74,98,111,128,135,192,201,215],"effective":[8],"Data":[9],"Assimilation":[10],"(DA),":[11],"although":[12],"it":[13],"can":[14,141],"be":[15,142],"a":[16,92,159],"challenging":[17],"task":[18],"for":[19,94,102,189,258,260],"complex":[20,193],"partially":[21],"observed":[22],"non-linear":[23],"systems":[24],"with":[25,32,207,222,249],"highly":[26],"non-Gaussian":[27,194],"uncertainties.":[28],"errors":[30,131,175],"associated":[31],"sub-grid":[33,68,99],"scale":[34,69,77,100,114,228],"processes":[35,101],"are":[36,45,60,79,116,156,176,220,247],"particular":[38],"interest":[39],"in":[40,87,263],"meteorological":[41],"DA":[42],"studies;":[43],"these":[44,174],"often":[46],"represented":[47],"through":[48,204],"Stochastic":[49,57],"Parameterizations":[50],"the":[52,66,75,85,96,103,112,124,133,136,180,185,190,199,202,208,216,250],"unresolved":[53],"process.":[54],"Many":[55],"existing":[56,256],"Parameterization":[58],"schemes":[59],"only":[61,108],"applicable":[62],"when":[63],"knowledge":[64],"true":[67],"process":[70,78,115],"or":[71],"full":[72],"observations":[73,110],"coarse":[76,113],"available,":[80],"which":[81,139],"typically":[83],"not":[84],"case":[86,106],"real":[88],"applications.":[89],"We":[90,197],"present":[91],"methodology":[93],"estimating":[95],"statistics":[97],"more":[104],"realistic":[105],"that":[107,173,241],"partial":[109],"available.":[117],"The":[118],"aim":[119],"to":[121,144,254],"first":[122],"estimate":[123],"conditional":[125,165],"probability":[126],"density":[127],"additive":[129],"model":[130,146,182,219,261],"given":[132],"state":[134,183],"system,":[137],"from":[138],"samples":[140],"generated":[143],"simulate":[145],"error":[147,154,195,243],"within":[148],"any":[149],"ensemble-based":[150],"assimilation":[151],"framework.":[152],"realizations":[155],"estimated":[157],"over":[158],"training":[160],"period":[161],"by":[162,168],"minimizing":[163],"their":[164],"variance,":[166],"constrained":[167],"available":[169],"observations.":[170],"Special":[171],"binned":[177],"conditioned":[178],"on":[179],"previous":[181],"during":[184],"minimization":[186],"process,":[187],"allowing":[188],"recovery":[191],"structures.":[196],"demonstrate":[198],"efficacy":[200],"approach":[203],"numerical":[205],"experiments":[206],"multi-scale":[209],"Lorenz":[210,217],"96":[211],"system.":[212],"Various":[213],"parameterizations":[214],"96'":[218],"considered":[221],"both":[223,242],"small":[224],"and":[225,234,245],"large":[226],"time":[227],"separations":[229],"between":[230],"slow":[231],"(coarse":[232],"scale)":[233,237],"fast":[235],"(fine":[236],"variables.":[238],"Results":[239],"indicate":[240],"estimates":[244],"forecasts":[246],"improved":[248],"proposed":[251],"method":[252],"compared":[253],"two":[255],"methods":[257],"accounting":[259],"DA.":[264]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2018-08-03T00:00:00"}
