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Enregistrement W4393562101 · doi:10.5281/zenodo.5113734

Nodal tide components for the PSMSL annual and monthly dataset (preliminary)

2021· dataset· en· W4393562101 sur OpenAlexaboutno aff
Jelmer Veenstra, Fedor Baart, Martin Verlaan, Willem Stolte

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Langueen
DomaineEarth and Planetary Sciences
ThématiqueOceanographic and Atmospheric Processes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésNODALClimatologyGeographyEnvironmental scienceOceanographyGeologyBiology

Résumé

récupéré en direct d'OpenAlex

Nodal tide components for the PSMSL annual and monthly dataset (preliminary) This preliminary dataset contains the tidal component for the mean sea level for the tide gauges in the Permanent Service for Mean Sealevel dataset. These files can be used to subtract the long term tide of the mean sea level. Authors and contact This dataset is created by Jelmer Veenstra, Martin Verlaan, Fedor Baart, and Willem Stolte. You can contact Jelmer Veenstra or Fedor Baart for more information. Files You can find the following files in this dataset. monthlymean_gtsm_psmsl-{id}.csv: monthly tidal corrections for mean sea level. yearlymean_gtsm_psmsl-{id}.csv: annual tidal corrections for the mean sea level. yearlymeanOLS_gtsm_psmsl-{id}.csv: annual tidal corrections based on a harmonic analysis through the reanalysis data (see details below). df_OLSmodelstats_year.csv: an overview of the phase and amplitude of the harmonic analysis of all the stations, also includes the equilibrium tidal amplitude. All files are stored in .csv files, using a , as field separator and . as decimal separator. Time is stored as YYYY for the annual series and as YYYY-MM for the monthly series. The file df_OLSmodelstats_year.csv also contains the list of all stations for which we provide information. More information on these stations can be found at [1]. Data specific information The file monthlymean_gtsm_psmsl-{id}.csv contains the following columns: - time [year-month] : year-month for which the mean tidal level is determined - sea_surface_height_due_to_tide [m]: mean sea surface level due to tidal waves [m] The file yearlymean_gtsm_psmsl-{id}.csv contains the following columns: - time [year]: year for which the mean tidal level is determined - sea_surface_height_due_to_tide [m]: mean sea surface level due to tidal waves [m] The file yearlymeanOLS_gtsm_psmsl-{id}.csv contains the following columns: - time [year]: year for which the mean tidal level is determined - sea_surface_height_due_to_tide_fitted [m]: mean sea surface level due to tidal waves, harmonic fit [m] The file df_OLSmodelstats_year.csv contains the following columns: longitude [degrees east]: longitude of the station latitude [degrees north]: latitude of the station station_name: station name nodal tide U [m]: linearized fit of the nodal cycle (A/U/cos term) (relative to 1970) [m] nodal tide V [m]: linearized fit of the nodal cycle (B/V/sin term) (relative to 1970) [m] nodal amplitude [m]: amplitude of the fitted nodal cycle, sqrt(A2 + B2) [m] nodal phase [radians since 1970-01-01]: phase of the fitted nodal cycle arctan2(B, A) [rad, epoch 1970] mean sea surface height of nodal fit [m]: mean tidal level over the fitted time window [m] nodal amplitude fitted with nodal epoch [m]: amplitude of the fitted nodal tide with epoch at the start of the phase of the nodal tide. Note that the amplitude here can be negative. [m] nodal amplitude of equilibrium tide [m]: equilibrium amplitude of the nodal tide [m] Methods To generate this dataset we have run a tidal model (GTSM v4.0) for 19 years. This multi-decadal reanalysis of tides allows separating the tidal component from other sea-level fluctuations. The purpose of this computation is to correct yearly mean and monthly mean tide gauge records for this tide constituent. See [1, 2] for a discussion on this topic. The equilibrium ampltiude is computed as: abs(0.69 * 20 * (3 * sin(deg2rad(lat))**2 - 1)) / 1000 This assumes an all water, elastic earth, and no self attraction. In this simulation, all tidal forcings (~400) are active. Thus the estimates also contain indirect non-linear effects, such as the nodal modulation on the amplitude of M2 interacting with itself. This allows the computation to deviate from the equilibrium tide. The tidal potential, corrections for solid earth tide (through Love numbers), and self attraction and loading are included. Using this dataset we fit, using an ordinary least squares approach, the nodal tidal amplitude, and phase. Details of this analysis can be found in the corresponding notebook [3]. The results have not been validated or published, so please use this dataset with caution. See the details in the section preliminary results. Preliminary results These are preliminary results, intended for evaluation with other scientists. Make sure you take into account the following: These results are based on GTSM 4.0, we expect to create an updated version based on 4.1. Version 4.1 should have a better internal tide model, which should improve reanalysis results in general. The following regions are not reliable: Black Sea, due to a limited topological relation with the rest of the grid. These stations are excluded. Regions in inlets have not been validated The reanalysis amplitude is lower than expected from equilibrium tide (about a factor 2 lower). Research into the cause of this is pending (love numbers, self attraction can be considered). The phase of the nodal tide is not yet validated. Some stations have deviating mean sea levels. A few examples: psmsl-173: station in the river mound the St. Lawrence River in Quebec. Not enough resolution psmsl-1067: Anchorage in Alaska, in an inlet psmsl-495: inlet psmsl-1908: bathymetry/bridge psmsl-2285: bathymetry resolution/bridge General remark: resolution in narrow tidal inlets and stations up rivers are not accurate. In an updated version we might be able to use cells just outside the inlet. Tide in narrow inlets can be quite different from outside. Sharing and Access information This dataset is available under a CC-BY-SA license [3]. See the link below for details. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Please make sure you refer to the preliminary status of this dataset if you use it. [0] https://www.psmsl.org [1] https://doi.org/10.2112/JCOASTRES-D-11-00169.1 [2] https://doi.org/10.2112/JCOASTRES-D-11A-00023.1 [3] http://creativecommons.org/licenses/by-sa/4.0/

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,183
Score d'incertitude au seuil0,613

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0010,000
Communication savante0,0020,002
Science ouverte0,0020,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,1830,182

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,221
Écart entre enseignants0,196 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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