the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Apr 2025
Teleconnection of Sahara to Mediterranean Basin evidenced by consecutive dust storms
Abstract. Saharan Dust Outbreaks frequently hit the Mediterranean Basin, lasting for a few days. These phenomena have various implications for the ecosystem of the entire basin, affecting the atmosphere, lithosphere, biosphere, hydrosphere, and cryosphere. Moreover, they cause numerous hazards to human society, especially concerning the environment and health, and are particularly significant to people living in a “Dust Belt” around Sahara, including nearby areas such as the Mediterranean Basin. This study demonstrates that continuous dust intrusions from the Sahara, transported across distant geographic regions, cannot be considered random events; rather, they show long-range correlations for timescales shorter than 80 days. This behaviour generates a persistent and recurrent atmospheric pattern at inter-annual time scales and synoptic spatial scales, thus opening a new perspective for climate studies and evidencing a new kind of teleconnection between North Africa and the Mediterranean Basin.
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RC1: 'Comment on egusphere-2025-1234', Henry Schoeller, 09 May 2025
General Comments
The paper utilizes PM₁₀ time series from various Mediterranean locations to demonstrate that Saharan dust storm occurrences exhibit temporal correlation. In doing so, it introduces an intriguing and original research question, which, in my opinion, it does not fully explore. Though it touches upon the regime patterns possibly responsible for the correlation, it fails to connect the topic to the time series analysis. The reasons for and more detailed nature of the correlation structure remain, therefore, unclear. I, hence, encourage the authors to investigate further the dynamics responsible for the correlations on short time scales and develop a convincing argumentation for their plausible hypothesis, that synoptic scale circulation patterns are key to understand dust storms occurrences. In particular, a teleconnection pattern (in the meteorological sense) referred to both in the title and the abstract is not presented in the manuscript. The manuscript would also benefit from a more scientific and precise use of language throughout. Some of the analysis descriptions are not detailed enough to be reproducible and have to be made more thorough and results have to be tested against the Null Hypothesis of natural variability (see below). In terms of references, the manuscript would profit from going into more detail about papers discussing weather patterns related to Saharan dust outbreaks:
- Rodríguez, S., Cuevas, E., Prospero, J. M., Alastuey, A., Querol, X., López-Solano, J., García, M. I., and Alonso-Pérez, S.: Modulation of Saharan dust export by the North African dipole, Atmos. Chem. Phys., 15, 7471–7486, https://doi.org/10.5194/acp-15-7471-2015, 2015.
- Cuevas-Agulló, E., Barriopedro, D., García, R. D., Alonso-Pérez, S., González-Alemán, J. J., Werner, E., Suárez, D., Bustos, J. J., García-Castrillo, G., García, O., Barreto, Á., and Basart, S.: Sharp increase in Saharan dust intrusions over the western Euro-Mediterranean in February–March 2020–2022 and associated atmospheric circulation, Atmos. Chem. Phys., 24, 4083–4104, https://doi.org/10.5194/acp-24-4083-2024, 2024.
- Russo A, Sousa PM, Durão RM, Ramos AM, Salvador P, Linares C, Díaz J, Trigo RM. Saharan dust intrusions in the Iberian Peninsula: Predominant synoptic conditions. Science of The Total Environment. 2020 May 15;717:137041.
- Knippertz P, Todd MC. Mineral dust aerosols over the Sahara: Meteorological controls on emission and transport and implications for modeling. Reviews of Geophysics. 2012 Mar;50(1).
- Rodríguez, S. and López-Darias, J.: Extreme Saharan dust events expand northward over the Atlantic and Europe, prompting record-breaking PM10 and PM2.5 episodes, Atmos. Chem. Phys., 24, 12031–12053, https://doi.org/10.5194/acp-24-12031-2024, 2024.
- Silvestri, L., Petroselli, C., Saraceni, M., Crocchianti, S., Cappelletti, D., & Cerlini, P. B. (2024). The correlation of long-range Saharan dust advections with the precipitation and radiative budget in the Central Mediterranean. _International Journal of Climatology_, 44(10), 3548–3567. https://doi.org/10.1002/joc.8538
Specific Comments
- Table 1: I am not sure if this is strictly necessary; could it go into the appendix?
- 72ff: What do the sources refer to? What are they supposed to prove?
- 73: What does the $S_j(t)$ mean?
- 80: Provide a proper source for the HYSPSLIT model please.
- 82: Not sure what it means that air masses encounter Saharan dust? How is Saharan dust defined here? Please provide enough information to be able to reproduce the dataset.
- 86: Provide a source for the NCEP/NCAR data. Also, which domain, which spatial and temporal resolution did you use?
- 87: Go into more details about the cluster analysis: in which coordinate space did you cluster? How did you detect the elbow? Please show a plot of the elbow.
- 98: Why did you not use the WMO standard season definition (winter: DJF...)
- Fig. 2: Please check if the colour scheme adheres to the journals guide lines regarding colour vision deficiency friendliness. Also, are you showing the k-means centroids or are you showing the average of all instances assigned to a cluster (composites)? In the latter case, please provide some indication of within-cluster variability in the appendix or at least the number of instances in each cluster.
- 106ff: What is the time period you used for the clustering?
- 106ff: If you perform k-means clustering on the raw data for the full year, you are not controlling for the seasonal cycle of the geopotential height. In particular, the meridional variation in the ITCZ will result in higher gh850 values in summer compared to winter, which will influence the seasonal cluster occurrence. Consider controlling for this effect or comment on why you do not.
- 110: I am not sure that it is accurate to say, a specific gh850 field "shows" the Azores current, since this is more of an oceanic feature, but I might be wrong.
- 111-112: The map section does not extend to the arctic and neither does it inform about a movement, so referring to cluster 3 as an "Arctic cyclone moving toward Europe" is questionable.
- 112: Similarly, there is no way to tell in which direction the anticyclone is moving.
- 114ff: I am not sure I understand, why clusters 2 and 4 favour SDOs. In particular, the pressure pattern in cluster 2 should be associated with northerlies over spain, which should inhibit dust transport to the north, right? In addition, the pattern does not imply that "high pressure starting from Africa reaches Spain overflying the Atlantic Ocean", if anything it is the air, not the pressure that flies somewhere. Similarly, I do not understand how the high pressure system in cluster 4 should be conducive of uplift and how there should be any winds from Northern Africa to Europe. I am not saying it is not true, I just do not understand the physical reasons.
- The paragraph from 118 to 130 would profit from some kind of vizualization. At least, I had a hard time understanding, what to take home from it.
- 130ff: The whole introduction and theory of Poisson processes and persistence times belongs to the "Methods" section.
- 134: I am confused by the wording; if you are investigating the time between consecutive starting points, I would not call it persistence time, since persistence time sounds like the time an individual SDO persists, i.e. the time, the PM10 values are above a threshold. The term "waiting time" is more comprehensible.
- Are you sure the numeric values in table 2 are essential for the reader to understand the content of your paper? Again, maybe put it in the appendix.
- 156ff and table 2: How do you obtain the parameter range? Under what assumptions and to which degree of certainty do you estimate the parameter fit? Which algorithm do you use for fitting?
- Figure 3: Since you give intervals for the fitted parameters, it would be appropriate to show the same range of certainty in your plotted fit (e.g. as shading).
- 170: The sources you refer to indicate that the power law provided holds only for large waiting times. In particular, for waiting times going to zero, the probability would go to infinity.
- Figure 6: You use the data shown to prove the dust storm occurrence cannot be a Poisson process, but from the real-world realization of a Poisson process, one would expect some random departure from the expected f(H>h)= 1-h line, dependent on the number of realizations. To conclude the data plotted in figure 6 is incompatible with the hypothesis of a (local) Poisson process, please provide either an appropriate test statistic or plot the variability (expected departure from 1-h line) given the sample size.
- 196: I am not sure what you refer to as a teleconnection agrees with the common definition. In particular, the circulation patterns from 4.1. are not employed in the ensuing analysis of the (non-)Poissonian character of the SDO time series. What exactly do you mean when you mention a teleconnection?
- 200: The sources you mention cover regions different from the region you consider. The first source states, "seven or four clusters could be retained" and the second source does not justify the choice of k at all.Technical Corrections
- Across the text: article ("the") use is more frequent than necessary (11: "desert dust" instead of "the desert dust"; 28: "influenced by major climate indices" instead of "the major climate indices")
- 28: "Teleconnection patterns" is a more common term than than "climate indices"
- 39-41: The sentence seems a litte awkward; the words "impulsive" and "until" are likely mistranslations.
- 42: "transport it for a long-range" is an unusual phrasing.
- 45: "required" instead of "acquired"
- 47: "PM10" abbreviation needs to be introduced
- 54: Provide date of last access for a web source.
- The source "The European exchange of information in 2012" has the authors names mixed up. It should show up as Mol, W. and van Hooydonk, P., ...
- Figure 1: Provide a proper source for the map. Does the colour result from a satellite image or from topography?
- 60: Abbreviation "SDO" should be introduced at first occurrence.
- 62: "hence to prevent the results distortion of our analysis"; odd phrasing
- 68: Provide a source for the R package if you mention it.
- 68: "Overall the period starts ... until ..." : formally means that the start takes 20 years; rephrase either to "starts at ... and ends at ..." or "period goes from ... until ..."
- 92ff: "days with a cluster": rather "days in a cluster"?
- 132: I think \tau should also have an index i.
- 137: I suggest using p() or Pr() for any probability distribution, especially since you use f for frequencies
- 147: Do you mean "intra-seasonal" instead of "inter-seasonal"?
- 149: Do you mean "50 - 80 days"?
- 167: What exactly is meant by "rate of cloud transport"? Are you sure, the time frame you want to refer to is longer than one year?Citation: https://doi.org/10.5194/egusphere-2025-1234-RC1 -
RC2: 'Comment on egusphere-2025-1234', Anonymous Referee #2, 28 Jul 2025
General Comments:
The manuscript presents an interesting statistical analysis of Saharan dust storm occurrences over the western Mediterranean Basin using long-term PM₁₀ observations and back-trajectory validation. The finding that dust events are temporally clustered (i.e., short waiting times are more likely than expected under a Poisson process) is well supported and represents a potentially useful contribution to the understanding of sub-seasonal dust variability.
However, I have significant reservations about the interpretation of these findings as evidence of a “teleconnection” between the Sahara and the western Mediterranean. While the term is used frequently throughout the manuscript, the results presented do not satisfy the usual criteria for identifying or diagnosing teleconnections in the atmospheric sciences.
Major Concerns:
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Definition and Misuse of “Teleconnection”:
In climatology, a teleconnection typically refers to a statistically significant, often physically meaningful linkage between distant regions, frequently mediated by large-scale atmospheric or oceanic modes (e.g., NAO, ENSO). In contrast, the dust source region (Sahara) and receptor region (western Mediterranean) analyzed in this paper are adjacent, and no long-range spatial coupling is demonstrated. The observed temporal clustering is more parsimoniously explained by persistent regional-scale weather regimes (e.g., southerly flows) during certain seasons. -
Triviality of the Findings in Light of Seasonality:
The observed event clustering is expected and well understood in the context of dust seasonality. Southerly synoptic flow regimes, which are known to facilitate dust transport to the Mediterranean, often persist for several days to weeks. It is thus not surprising that consecutive dust events within ~50 days are more likely. Without explicitly controlling for or quantifying the role of seasonality and background synoptic persistence, the results risk being interpreted as novel when they may simply reflect well-documented climatological behavior. -
Lack of Evidence for Remote Forcing or Bidirectional Influence:
The paper does not show that the observed temporal clustering is modulated by or connected to remote climate drivers (e.g., NAO, MJO, AO). Nor does it analyze atmospheric fields at the necessary scale to support the existence of a dynamical teleconnection. As such, the use of “teleconnection” appears speculative and unsupported by the data.
Suggestions for Revision:
- Reframe the main findings in terms of temporal autocorrelation and synoptic regime persistence, avoiding the term “teleconnection” unless additional evidence is provided.
- Clarify that the study focuses on event timing statistics, not spatial linkages between disparate regions.
- Consider analyzing the relationship between clustered dust events and known climate modes or pressure pattern indices (e.g., NAO phase) to assess whether a teleconnection mechanism may exist.
- Discuss the potential role of seasonal forcing and event clustering in the context of expected climatology, possibly by contrasting results with synthetic seasonal Poisson processes.
The manuscript presents solid empirical evidence of non-random dust event timing over the western Mediterranean, but its interpretation overreaches in using the concept of teleconnection. With a more cautious framing and acknowledgment of known meteorological context, the paper could still offer a meaningful contribution to the understanding of dust event temporal dynamics.
Citation: https://doi.org/10.5194/egusphere-2025-1234-RC2 -
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EC1: 'Comment on egusphere-2025-1234', Harindra Joseph Fernando, 28 Jul 2025
Dear Authors, The comment period is now over, and I invite you to submit a revision. While the two referees recommend revisions, my own evaluation and reading their comments between the lines indicate the paper have substantial technical and semantic problems. Please try to address them carefully and thoroughly, as the final acceptance will be determined by their evaluation - both referees are very conversant with the topic. Best of luck in preparing a revision.
Sincerely
Joe Fernando (Handling Editor)
Citation: https://doi.org/10.5194/egusphere-2025-1234-EC1
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