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Enregistrement W4232236262 · doi:10.5194/tc-2015-216-ac2

Response to Referee #2

2016· peer-review· en· W4232236262 sur OpenAlexaboutno aff

Notice bibliographique

Revuenon disponible
Typepeer-review
Langueen
DomaineEarth and Planetary Sciences
ThématiqueCryospheric studies and observations
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBusiness

Résumé

récupéré en direct d'OpenAlex

This study concerns the application of the cosmic-ray neutron method to monitor snow water equivalent.The authors performed neutron count measurements over two winters (2013/2014 and 2014/2015) in an agricultural field in Saskatoon (Canada).Based on this data, they developed an empirical equation to provide estimates of average SWE which were compared with continuous snow depth measurements.This paper is an interesting presentation of a snow application of the cosmic-ray neutron method.It is also well written and fits well to the scope of Cryosphere Journal.However, some methodological improvements need to be undertaken as outlined in my C1 TCD Interactive commentPrinter-friendly version Discussion paper specific comments.In addition, I am not convinced that the presented method is able to provide quantitative estimates of SWE that are more accurate than the traditional snow depth measurements.Thus, the study should be more critical and should better discuss the potential drawbacks of the method.Author response: Thank you for the excellent comments.As shown in our measured SWE data using snow tube, the point measurements are highly spatially variable.It is impossible to obtain accurate areal SWE without a large number of point measurements.Therefore, a point measurement of continuous snow depth can cause accuracy issues if wanting to upscale the measurement to represent a larger area.For example, melting can occur below the depth sensor or snow could preferentially accumulate around the depth sensor from wind redistribution.Thus, the CRP method should provide a better estimate of average SWE in the area since it does integrate over a larger area.As Anonymous Referee 1 mentioned, it is not very practical to compare the CRP accuracy to an array of continuous measurements since it is not common to have an intensive set up of continuous SWE measurement instruments in the field.Printer-friendly version Discussion paper L184: The value of 4.53 cm suggests that the soil porosity must be at least 0.453.This is extremely high, e.g.sandy soils have typically porosities in the range of 0.30-0.35(Nimmo, 2004).Thus, this value is may be overestimated (see comment above).Author reply: The soil at our site has a fine texture (silt loam) and the top 10 cm of the soil profile had crop residue from previous years incorporated into the soil surface.The fine texture and crop residue caused the bulk density for 0 -10 cm to be 1.01 g cm-3 and the total porosity to be 0.61 cm3.This porosity would allow the value of 4.53 cm to be relevant.L225-229: Such scaling is unnecessary in the case of this study.Scaling would be necessary in case absolute neutron count rates would be important, e.g. in case neutron count measurements from different locations would be compared among each other.However, in this study the neutron counts are converted to snow water equivalents, which is inherently a sort of scaling.Author response: We will remove this scaling from the final corrected neutron counts.Changed in manuscript: Line 259 -263 "The corrected moderated neutron counts were then averaged over 13 hours.A 13-hour running average was used for the moderated neutron intensity counts in order to reduce the inherent noise of the hourly moderated neutron data and reduce measurement uncertainty, yet still allow responses to precipitation events to be observed (Zreda et al., 2008)."L240: This spacing is not appropriate (see comment L114).Add a discussion on the consequences.Author reply: We developed this study before the Köhli et al. (2015) paper came out so we used the spacing of 25, 75, and 200 m based on the original soil sampling schemes for the CRP when a footprint of 300 m was assumed.Changed in manuscript: Line 270 "This sampling scheme is based on a CRP footprint of ∼300 m radius.According to Köhli et al. (2015), the CRP footprint might be smaller C6 TCD Interactive comment Printer-friendly version Discussion paper(∼200 m radius).This study was performed prior to the new estimations of the CRP footprint so a radius of ∼300 m was still assumed and samples along the 200 m radial were included in the snow surveys."L256-259: How did your snow height and SWE data compare with predictions of this equation?Author reply: Our measurements of snow depth and SWE closely matched predictions with the equation proposed by Shook and Gray (1994).We did not include figures showing the comparison between our sampled SWE and predictions based on snow depth because our CRP predicted SWE matched closely to our sampled SWE.Thus it would be as though we were displaying the same info twice on the figures where we compare our CRP-predicted SWE and snow depth estimated SWE.L296: You should also present scatter-plots of the correlations (without the soil water storage adjustment).Author reply: We included the correlation of neutrons and SWE without the soil water storage offset in Figure 3. L321-324: This is very unlikely, since modelling of neutron transport of nonhomogenous environmental conditions have shown that only extreme cases, e.g.discrete objects like tree trunks, may have an influence on neutron intensity (e.g.Franz et al., 2015).In any case, such assumptions would need to be substantiated by a dedicated neutron transport modelling study.Author reply: We do not have neutron transport simulations to back up our statement regarding the penetration of neutrons in snow so we will remove our claim.Changed in manuscript: Line 376 -377 "However, we observed a CRP response to SWE values of greater than 70 mm, when including antecedent soil water in the upper soil profile, during the 2014/15 winter.It is not completely clear why distinct CRP responses occurred at SWE values greater than 70 mm."C7 TCD

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)0,007
score de la tête « metaresearch » (Gemma)0,064
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: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,142
Score d'incertitude au seuil0,474

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,064
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0020,002
Études des sciences et des technologies0,0030,001
Communication savante0,0040,003
Science ouverte0,0030,003
Intégrité de la recherche0,0170,010
Charge utile insuffisante (le modèle a refusé de juger)0,1420,075

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 Opus0,059
Tête enseignante GPT0,286
Écart entre enseignants0,227 · 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
GenreAutre

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
Publié2016
Routes d'admission1
Résumé présentoui

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