Historical snowfall measurements in the Central and Southern Apennine Mountains: climatology, variability and trend

Capozzi, Vincenzo; Serrapica, Francesco; Rocco, Armando; Annella, Clizia; Budillon, Giorgio

doi:https://doi.org/10.5194/egusphere-2024-1056

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https://doi.org/10.5194/egusphere-2024-1056

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05 Jun 2024

| 05 Jun 2024

Historical snowfall measurements in the Central and Southern Apennine Mountains: climatology, variability and trend

Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon

Abstract. This work presents an analysis of historical snow precipitation data collected in the period 1951–2001 in Central and Southern Apennines (Italy), an area scarcely investigated so far. To pursue this aim, we used the monthly observations of the snow cover duration, number of days with snow and total height of new snow collected at 129 stations located between 288 and 1750 m a.s.l.. Such data have been manually digitized from the Hydrological Yearbooks of the Italian National Hydrological and Mareographic Service. The available dataset has been primarily analyzed to build a reference climatology (related to 1971–2000 period) for the considered Apennine region. More specifically, using a methodology based on Principal Component Analysis and k-means clustering, we have identified different modes of spatial variability, mainly depending from the elevation, which reflect different climatic zones. Subsequently, focusing on the number of days with snow and snow cover duration on the ground, we have carried out a linear trend analysis, employing the Theil-Sen estimator and the Mann-Kendall test. An overall negative tendency has been found for both variables. For clusters including only stations above 1000 m a.s.l., a significant (at 95 % confidence level) decreasing trend has been found in winter season (i.e. from December to February): −3.2 [−6.0 to 0.0] days/10 years for snow cover duration and −1.6 [−2.5 to −0.6] days/10 years for number of days with snow. Moreover, in all considered seasons, a clear direct relationship between trend magnitude and elevation has emerged. In addition, using a cross wavelet analysis, we found a close in-phase linkage on decadal time scale between the investigated snow indicators and the Eastern Mediterranean Pattern. For both snow cover duration and number of days with snow, such connection appears to be more relevant in full (i.e. from November to April) and in late (i.e. from February to April) seasons.

Received: 08 Apr 2024 – Discussion started: 05 Jun 2024

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Journal article(s) based on this preprint

05 Feb 2025

Historical snow measurements in the central and southern Apennine Mountains: climatology, variability, and trend

Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon

The Cryosphere, 19, 565–595, https://doi.org/10.5194/tc-19-565-2025,https://doi.org/10.5194/tc-19-565-2025, 2025

Short summary

Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon

Interactive discussion

Status: closed

CC1:
'Comment on egusphere-2024-1056', Danilo Godone, 05 Jun 2024
Dear Authors,
thanks for the interesting work. If I may, I would like to report two papers that are very similar and may provide useful insights:
https://doi.org/10.1016/j.jhydrol.2022.128532

http://dx.doi.org/10.1088/1748-9326/acdb88

Moreover, I would like to suggest avoiding the translation "Arm of Carabineers" thus favoring the notation in Italian such as "Carabinieri" or "Carabinieri Corps" which should be the official one.
Citation: https://doi.org/10.5194/egusphere-2024-1056-CC1
- AC1: 'Reply on CC1', Vincenzo Capozzi, 06 Jun 2024
  
  Dear Dr. Godone,
  thank you very much for the comment and for your interest in our paper.
  In the framwork of the review process, we'll take into consideration your suggestions.
  Kind regards,
  Vincenzo Capozzi
  On behalf of all Co-Authors
  
  Citation: https://doi.org/10.5194/egusphere-2024-1056-AC1
RC1:
'Comment on egusphere-2024-1056', Anonymous Referee #1, 05 Jul 2024

This paper presents a valuable collation of historical snow records for an understudied region. As such, the authors should fully document and deposit the data in a public repository, in compliance with the Copernicus Publications data policy: https://www.the-cryosphere.net/policies/data_policy.html

The cluster analysis is detailed, but I am not sure that the discussion reveals much more than could have been illustrated by plotting the snow metrics against elevation and examining the outliers. Although the wavelet analysis is rather preliminary and descriptive, it presents results and so should be moved to the Results section.

15
The difference between “snow cover duration” and “number of days with snow” is not clear, and is not made clear until line 183. State “number of days with snowfall” throughout.

31
Snowfall is certainly an essential climate variable, but it is not a GCOS Essential Climate Variable distinct from precipitation, so do not use that specific term.

257-300
The description of Climatol tests is barely comprehensible without reading the references.

360
Relationships of PCs to geographical features are stated but not made clear to the reader.

Figure 5
There is some appeal to having elevation on the y-axis, but it would conventional for it to be on the x-axis as the independent variable. This would also better show the overlap in elevation between clusters and the increasing gradient. Rather than the generic x = ay^b, it would be better to show the power fit equations as SCD = az^b.

464
“subset” would be a more widely comprehensible term than “aliquot”.

Figure 11
Does this contradict recovery of NDS in the Southern Apennines cited in the introduction?

593
XX century?

Figures 12 and 13
The captions should state that arrows pointing to the right indicate that signals are in phase.

675
When claiming 90% confidence, it would make more sense to quote the 90% confidence interval.

Citation: https://doi.org/10.5194/egusphere-2024-1056-RC1
- AC2: 'Reply on RC1', Vincenzo Capozzi, 27 Aug 2024
  
  Dear Referee, we are grateful for the time dedicated to the revision of our manuscript and for the suggestions, which will help us to improve our paper. Here we provide a point-by-point response to his/her comments. All required changes will be included in the new manuscript version.
  You can find our replies in the attached pdf document.
  Kind regards,
  Vincenzo Capozzi
  on behalf of all Co-Authors
  
  Citation: https://doi.org/10.5194/egusphere-2024-1056-AC2
RC2:
'Comment on egusphere-2024-1056', Anonymous Referee #2, 08 Oct 2024

Dear Authors, dear Editor,

Thank you for proposing this study. The topic is interesting and timely, the methods used are sound, and the focus on the Appenine area is a valuable complement to pre-existing work and snow data analyses.
Therefore I find the presented work very valuable and worth publishing - but naturally, I have some suggestions to try to improve it :

General comments

1 / I join referee one in his/her concern that the data should be made openly accessible (for instance via a doi associated to the present paper) to comply with Copernicus guidelines.

2/ As also assessed by referee 1, "Number of days with Snow" / NDS is too vague (notably L55) and the description comes too late in the paper. As I understand from L 183 it could be formulated as Number of days with fresh snow accumulation on the ground.

3/ The Standard Normal Homogeneity Test procedure is barely understandable the way it is currently presented without reading further reference. I suggest to explain the general philosophy underlying the test.

4/ More generally, the use of the terms "snow" is sometimes misleading throughout the paper, as illustrated in the expression "number of days with snow" . We don't know wether this is atmospheric snow (snowfall) or ground covering snow. Please be more specific.

5/ Both the title and the abstract draw the focus on snow *precipitation* or *snowfall*. However, based on the variables analyzed (snow cover duration, number of days with snow, total height of new snow) the focus is at least equally on snow on the ground as on snowfall. This should be revised in order to convey a more precise message.

Minor comments :
L 43-44 : please aknowledge recent work that expands in time the MODIS time-series through the use of older satellite archives or reanalyses, and machine learning

Dumont, Z. B., Gascoin, S., & Inglada, J. (2024). Snow and cloud classification in historical SPOT images: An image emulation approach for training a deep learning model without reference data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Gascoin, S., Monteiro, D., & Morin, S. (2022). Reanalysis-based contextualization of real-time snow cover monitoring from space. Environmental Research Letters, 17(11), 114044.

L 172 : snow-to-liquid equivalent : the proper name of this quantity is snow water equivalent (SWE). See the International Classification of snow (Fierz et al., 2009) here : https://unesdoc.unesco.org/ark:/48223/pf0000186462

In one of the authors' previous work mentioned in the Introduction, a recent recovery of snow cover duration, HN and NDS is mentioned in the Southern Appenines (L 67 68). Unfortunately the present study ends by 2000 while the recovery at Montevergine Observatory appears after 2000. Would it be possible to bridge the gap between both studies and mention this in the discussion, enlightening the dependence of trends to timeframe/period length, and also the connection with AO/NA that was seen in this previous study but found not relevant in the present one ?

Edits :

L61 : clear -> clearly

L 106 : ad -> an

L 115 : southwest -> south east

L 223 : quote -> quite

L 263 : use -> uses

L 355 : scree -> screen

L 511 : second "in" -> and

L 539 one word is missing (likely "to" before "contextualize").

L 559 : stations -> station

L 689 : means -> by means

Citation: https://doi.org/10.5194/egusphere-2024-1056-RC2
- AC3: 'Reply on RC2', Vincenzo Capozzi, 15 Oct 2024
  
  Dear Referee, we are very grateful for the positive evaluation of our manuscript and for the comments and the suggestions, which help us to improve our paper. Here we provide a point-by-point response to his/her comments. All required changes will be included in the new manuscript version.
  You can find the replies to your comments in the attached pdf document.
  
  Kind regards.
  
  Citation: https://doi.org/10.5194/egusphere-2024-1056-AC3

Interactive discussion

Status: closed

CC1:
'Comment on egusphere-2024-1056', Danilo Godone, 05 Jun 2024
Dear Authors,
thanks for the interesting work. If I may, I would like to report two papers that are very similar and may provide useful insights:
https://doi.org/10.1016/j.jhydrol.2022.128532

http://dx.doi.org/10.1088/1748-9326/acdb88

Moreover, I would like to suggest avoiding the translation "Arm of Carabineers" thus favoring the notation in Italian such as "Carabinieri" or "Carabinieri Corps" which should be the official one.
Citation: https://doi.org/10.5194/egusphere-2024-1056-CC1
- AC1: 'Reply on CC1', Vincenzo Capozzi, 06 Jun 2024
  
  Dear Dr. Godone,
  thank you very much for the comment and for your interest in our paper.
  In the framwork of the review process, we'll take into consideration your suggestions.
  Kind regards,
  Vincenzo Capozzi
  On behalf of all Co-Authors
  
  Citation: https://doi.org/10.5194/egusphere-2024-1056-AC1
RC1:
'Comment on egusphere-2024-1056', Anonymous Referee #1, 05 Jul 2024

This paper presents a valuable collation of historical snow records for an understudied region. As such, the authors should fully document and deposit the data in a public repository, in compliance with the Copernicus Publications data policy: https://www.the-cryosphere.net/policies/data_policy.html

The cluster analysis is detailed, but I am not sure that the discussion reveals much more than could have been illustrated by plotting the snow metrics against elevation and examining the outliers. Although the wavelet analysis is rather preliminary and descriptive, it presents results and so should be moved to the Results section.

15
The difference between “snow cover duration” and “number of days with snow” is not clear, and is not made clear until line 183. State “number of days with snowfall” throughout.

31
Snowfall is certainly an essential climate variable, but it is not a GCOS Essential Climate Variable distinct from precipitation, so do not use that specific term.

257-300
The description of Climatol tests is barely comprehensible without reading the references.

360
Relationships of PCs to geographical features are stated but not made clear to the reader.

Figure 5
There is some appeal to having elevation on the y-axis, but it would conventional for it to be on the x-axis as the independent variable. This would also better show the overlap in elevation between clusters and the increasing gradient. Rather than the generic x = ay^b, it would be better to show the power fit equations as SCD = az^b.

464
“subset” would be a more widely comprehensible term than “aliquot”.

Figure 11
Does this contradict recovery of NDS in the Southern Apennines cited in the introduction?

593
XX century?

Figures 12 and 13
The captions should state that arrows pointing to the right indicate that signals are in phase.

675
When claiming 90% confidence, it would make more sense to quote the 90% confidence interval.

Citation: https://doi.org/10.5194/egusphere-2024-1056-RC1
- AC2: 'Reply on RC1', Vincenzo Capozzi, 27 Aug 2024
  
  Dear Referee, we are grateful for the time dedicated to the revision of our manuscript and for the suggestions, which will help us to improve our paper. Here we provide a point-by-point response to his/her comments. All required changes will be included in the new manuscript version.
  You can find our replies in the attached pdf document.
  Kind regards,
  Vincenzo Capozzi
  on behalf of all Co-Authors
  
  Citation: https://doi.org/10.5194/egusphere-2024-1056-AC2
RC2:
'Comment on egusphere-2024-1056', Anonymous Referee #2, 08 Oct 2024

Dear Authors, dear Editor,

Thank you for proposing this study. The topic is interesting and timely, the methods used are sound, and the focus on the Appenine area is a valuable complement to pre-existing work and snow data analyses.
Therefore I find the presented work very valuable and worth publishing - but naturally, I have some suggestions to try to improve it :

General comments

1 / I join referee one in his/her concern that the data should be made openly accessible (for instance via a doi associated to the present paper) to comply with Copernicus guidelines.

2/ As also assessed by referee 1, "Number of days with Snow" / NDS is too vague (notably L55) and the description comes too late in the paper. As I understand from L 183 it could be formulated as Number of days with fresh snow accumulation on the ground.

3/ The Standard Normal Homogeneity Test procedure is barely understandable the way it is currently presented without reading further reference. I suggest to explain the general philosophy underlying the test.

4/ More generally, the use of the terms "snow" is sometimes misleading throughout the paper, as illustrated in the expression "number of days with snow" . We don't know wether this is atmospheric snow (snowfall) or ground covering snow. Please be more specific.

5/ Both the title and the abstract draw the focus on snow *precipitation* or *snowfall*. However, based on the variables analyzed (snow cover duration, number of days with snow, total height of new snow) the focus is at least equally on snow on the ground as on snowfall. This should be revised in order to convey a more precise message.

Minor comments :
L 43-44 : please aknowledge recent work that expands in time the MODIS time-series through the use of older satellite archives or reanalyses, and machine learning

Dumont, Z. B., Gascoin, S., & Inglada, J. (2024). Snow and cloud classification in historical SPOT images: An image emulation approach for training a deep learning model without reference data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Gascoin, S., Monteiro, D., & Morin, S. (2022). Reanalysis-based contextualization of real-time snow cover monitoring from space. Environmental Research Letters, 17(11), 114044.

L 172 : snow-to-liquid equivalent : the proper name of this quantity is snow water equivalent (SWE). See the International Classification of snow (Fierz et al., 2009) here : https://unesdoc.unesco.org/ark:/48223/pf0000186462

In one of the authors' previous work mentioned in the Introduction, a recent recovery of snow cover duration, HN and NDS is mentioned in the Southern Appenines (L 67 68). Unfortunately the present study ends by 2000 while the recovery at Montevergine Observatory appears after 2000. Would it be possible to bridge the gap between both studies and mention this in the discussion, enlightening the dependence of trends to timeframe/period length, and also the connection with AO/NA that was seen in this previous study but found not relevant in the present one ?

Edits :

L61 : clear -> clearly

L 106 : ad -> an

L 115 : southwest -> south east

L 223 : quote -> quite

L 263 : use -> uses

L 355 : scree -> screen

L 511 : second "in" -> and

L 539 one word is missing (likely "to" before "contextualize").

L 559 : stations -> station

L 689 : means -> by means

Citation: https://doi.org/10.5194/egusphere-2024-1056-RC2
- AC3: 'Reply on RC2', Vincenzo Capozzi, 15 Oct 2024
  
  Dear Referee, we are very grateful for the positive evaluation of our manuscript and for the comments and the suggestions, which help us to improve our paper. Here we provide a point-by-point response to his/her comments. All required changes will be included in the new manuscript version.
  You can find the replies to your comments in the attached pdf document.
  
  Kind regards.
  
  Citation: https://doi.org/10.5194/egusphere-2024-1056-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Publish subject to revisions (further review by editor and referees) (11 Nov 2024) by Melody Sandells

AR by Vincenzo Capozzi on behalf of the Authors (19 Nov 2024) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (11 Dec 2024) by Melody Sandells

AR by Vincenzo Capozzi on behalf of the Authors (13 Dec 2024) Manuscript

Journal article(s) based on this preprint

05 Feb 2025

Historical snow measurements in the central and southern Apennine Mountains: climatology, variability, and trend

Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon

The Cryosphere, 19, 565–595, https://doi.org/10.5194/tc-19-565-2025,https://doi.org/10.5194/tc-19-565-2025, 2025

Short summary

Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon

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https://doi.org/10.5194/egusphere-2024-1056-supplement

Vincenzo Capozzi, Francesco Serrapica, Armando Rocco, Clizia Annella, and Giorgio Budillon

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Short summary

This study offers a “journey through time” to discover historical information about snow precipitation in the Italian Apennines. In this area, in the second half of past century, a gradual decline in snow persistence on the ground as well as in the frequency of occurrence of snowfall events has been observed, especially in sites located above 1000 m a.s.l.. The old data rescued in this study strongly enhances our knowledge about past snowfall variability and climate in the Mediterranean area.


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