Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability.
Saved in:
| Title: | Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability. |
|---|---|
| Authors: | Chu, Yufei1 (AUTHOR), Lin, Guo2,3 (AUTHOR), Deng, Min4 (AUTHOR), Xue, Lulin5 (AUTHOR), Li, Weiwei5 (AUTHOR), Shin, Hyeyum Hailey5 (AUTHOR), Zhang, Jun A.2,3 (AUTHOR), Guo, Hanqing6 (AUTHOR), Wang, Zhien1 (AUTHOR) zhien.wang@stonybrook.edu |
| Source: | Atmospheric Chemistry & Physics. 2026, Vol. 26 Issue 2, p1415-1434. 20p. |
| Database: | Environment Complete |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: eih DbLabel: Environment Complete An: 191385023 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chu%2C+Yufei%22">Chu, Yufei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lin%2C+Guo%22">Lin, Guo</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Deng%2C+Min%22">Deng, Min</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xue%2C+Lulin%22">Xue, Lulin</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Weiwei%22">Li, Weiwei</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shin%2C+Hyeyum+Hailey%22">Shin, Hyeyum Hailey</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Jun+A%2E%22">Zhang, Jun A.</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Hanqing%22">Guo, Hanqing</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Zhien%22">Wang, Zhien</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zhien.wang@stonybrook.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Atmospheric+Chemistry+%26+Physics%22">Atmospheric Chemistry & Physics</searchLink>. 2026, Vol. 26 Issue 2, p1415-1434. 20p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=191385023 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5194/acp-26-1415-2026 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 1415 Titles: – TitleFull: Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chu, Yufei – PersonEntity: Name: NameFull: Lin, Guo – PersonEntity: Name: NameFull: Deng, Min – PersonEntity: Name: NameFull: Xue, Lulin – PersonEntity: Name: NameFull: Li, Weiwei – PersonEntity: Name: NameFull: Shin, Hyeyum Hailey – PersonEntity: Name: NameFull: Zhang, Jun A. – PersonEntity: Name: NameFull: Guo, Hanqing – PersonEntity: Name: NameFull: Wang, Zhien IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 01 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 16807316 Numbering: – Type: volume Value: 26 – Type: issue Value: 2 Titles: – TitleFull: Atmospheric Chemistry & Physics Type: main |
| ResultId | 1 |
