Academic Journal
Spatial Interpolation of Meteorological Variables with Daymet4-r2: A Self-Calibrating Algorithm for Complex Terrains.
| Title: | Spatial Interpolation of Meteorological Variables with Daymet4-r2: A Self-Calibrating Algorithm for Complex Terrains. |
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| Authors: | Fibbi, Luca, Bartolini, Giorgio, Gozzini, Bernardo, Grifoni, Daniele |
| Source: | Water (20734441); Jun2026, Vol. 18 Issue 12, p1461, 19p |
| Subject Terms: | Interpolation, Calibration, Temperature inversions, Meteorological observations, Meteorological services |
| Abstract: | High-resolution, long-term gridded meteorological datasets from in situ observations are crucial for ecosystem monitoring, soil diagnostics, hydrological modelling, and Earth system model evaluation. This study presents two enhanced real-time adaptations of Thornton's Daymet V4 interpolation method. Daymet4-r1 uses a traditional calibration strategy with exhaustive parameter search, while Daymet4-r2 applies a global optimization algorithm (find_min_global from the dlib library) to adjust parameters automatically at each time step. Both methods were tested over Tuscany using high-resolution terrain and a dense observation network. Validation with leave-one-out method was carried out for the period 1995–2011 for both versions, while Daymet4-r2 underwent extended evaluation from 1991 to 2024 to assess seasonal dynamics and long-term variability. Results show that Daymet4-r2 outperforms Daymet4-r1 and the original Daymet V4 for all variables (mean absolute error of 1.24 mm, 1.06 °C, 1.29 °C, 6.26%, 0.78 m/s, and 2.04 hPa for precipitation, maximum and minimum temperature, relative humidity, wind speed, and sea level pressure, respectively). The largest improvement was observed in minimum temperature due to an enhanced approach for detecting and modelling thermal inversions. The high performance, flexibility, and ability of Daymet4-r2 to operate without prior calibration highlight its potential for model verification, real-time environmental monitoring, and integration into climate services. [ABSTRACT FROM AUTHOR] |
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| Database: | Biomedical Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edm&genre=article&issn=20734441&ISBN=&volume=18&issue=12&date=20260615&spage=1461&pages=1461-1479&title=Water (20734441)&atitle=Spatial%20Interpolation%20of%20Meteorological%20Variables%20with%20Daymet4-r2%3A%20A%20Self-Calibrating%20Algorithm%20for%20Complex%20Terrains.&aulast=Fibbi%2C%20Luca&id=DOI:10.3390/w18121461 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Header | DbId: edm DbLabel: Biomedical Index An: 194909114 RelevancyScore: 1082 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1082.41931152344 |
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| Items | – Name: Title Label: Title Group: Ti Data: Spatial Interpolation of Meteorological Variables with Daymet4-r2: A Self-Calibrating Algorithm for Complex Terrains. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Fibbi%2C+Luca%22">Fibbi, Luca</searchLink><br /><searchLink fieldCode="AR" term="%22Bartolini%2C+Giorgio%22">Bartolini, Giorgio</searchLink><br /><searchLink fieldCode="AR" term="%22Gozzini%2C+Bernardo%22">Gozzini, Bernardo</searchLink><br /><searchLink fieldCode="AR" term="%22Grifoni%2C+Daniele%22">Grifoni, Daniele</searchLink> – Name: TitleSource Label: Source Group: Src Data: Water (20734441); Jun2026, Vol. 18 Issue 12, p1461, 19p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Interpolation%22">Interpolation</searchLink><br /><searchLink fieldCode="DE" term="%22Calibration%22">Calibration</searchLink><br /><searchLink fieldCode="DE" term="%22Temperature+inversions%22">Temperature inversions</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorological+observations%22">Meteorological observations</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorological+services%22">Meteorological services</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: High-resolution, long-term gridded meteorological datasets from in situ observations are crucial for ecosystem monitoring, soil diagnostics, hydrological modelling, and Earth system model evaluation. This study presents two enhanced real-time adaptations of Thornton's Daymet V4 interpolation method. Daymet4-r1 uses a traditional calibration strategy with exhaustive parameter search, while Daymet4-r2 applies a global optimization algorithm (find_min_global from the dlib library) to adjust parameters automatically at each time step. Both methods were tested over Tuscany using high-resolution terrain and a dense observation network. Validation with leave-one-out method was carried out for the period 1995–2011 for both versions, while Daymet4-r2 underwent extended evaluation from 1991 to 2024 to assess seasonal dynamics and long-term variability. Results show that Daymet4-r2 outperforms Daymet4-r1 and the original Daymet V4 for all variables (mean absolute error of 1.24 mm, 1.06 °C, 1.29 °C, 6.26%, 0.78 m/s, and 2.04 hPa for precipitation, maximum and minimum temperature, relative humidity, wind speed, and sea level pressure, respectively). The largest improvement was observed in minimum temperature due to an enhanced approach for detecting and modelling thermal inversions. The high performance, flexibility, and ability of Daymet4-r2 to operate without prior calibration highlight its potential for model verification, real-time environmental monitoring, and integration into climate services. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Water (20734441) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/w18121461 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 1461 Subjects: – SubjectFull: Interpolation Type: general – SubjectFull: Calibration Type: general – SubjectFull: Temperature inversions Type: general – SubjectFull: Meteorological observations Type: general – SubjectFull: Meteorological services Type: general Titles: – TitleFull: Spatial Interpolation of Meteorological Variables with Daymet4-r2: A Self-Calibrating Algorithm for Complex Terrains. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fibbi, Luca – PersonEntity: Name: NameFull: Bartolini, Giorgio – PersonEntity: Name: NameFull: Gozzini, Bernardo – PersonEntity: Name: NameFull: Grifoni, Daniele IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20734441 Numbering: – Type: volume Value: 18 – Type: issue Value: 12 Titles: – TitleFull: Water (20734441) Type: main |
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