This work examines the process that anomalous heating over the tropical-subtropical western North Pacific can affect European temperature variability, with the modulation from the North Atlantic SST, on subseasonal timescales in the summer season. The authors defined a West Pacific Dipole (WPD) index to characterize the combined zonal and meridional heating contrast in the western North Pacific. They found that positive WPD can trigger teleconnections towards Europe, leading to warm T2m anomalies over western Europe in 3-6 weeks. They also found that the negative phase of WPD has become more frequent since 1980, consistent with the “Western Pacific warming mode”. However, the summertime temperature over western Europe has not shown any cooling trend since 1980. The authors argued that the North Atlantic SST also plays an important role in modulating the teleconnections.

The results in this manuscript potentially present valuable improvement to our understanding of subseasonal climate predictability and prediction. I have some major comments and clarification questions, hopefully could help to improve the manuscript.

Major comments:

1. A large portion of the manuscript depends on connecting the warming SST trends in the western Pacific to the increasing occurrences of negative WPD. I am not familiar with the “Western Pacific warming mode”, but my understanding is that this is for a long-term warming trend in the SST (basic-state shifts). On the other hand, the WPD phases and their teleconnections to the European T2m characterized in this manuscript are subseasonal variability.
   
   I guess I am confused the connection here: one is change in the mean (shift in the distribution) and another one is change in the standard deviation (change in the shape of the distribution). For example, in L285-289, the authors stated: though negative WPD has occurred more frequently, western Europe has not experienced a relative cooling as expected. Based on the results shown here, WPD affects the “subseasonal variability” in western European t2m. More frequent of this event is not necessarily equal to change in seasonal mean temperature, if the standard deviation has become larger (e.g., more frequent cold subseasonal events, but also more frequent and stronger warm subseasonal events).
   
   In short, it would be helpful if the authors clarify the different timescales across the phenomena they have mentioned in the manuscript. Also, in L290-296, the authors examined that the positive WPD phase has become more likely to result in positive t2m anomalies in western Europe. It is also helpful to shown the negative WPD phase: has negative WPD phase become less likely to result in negative t2m anomalies in western Europe?
2. Also relevant to the timescale issue. In Fig. 4, WPD index is not detrended, but t2m over western Europe is detrended. As the main purpose is to examine how WPD affect western European t2m on subseasonal timescales, why the inconsistency here?
3. The “Western Pacific warming mode” frequently mentioned in this manuscript (Funk and Hoell, 2015) characterizes the warming extending from the subtropical North Pacific to the subtropical South Pacific. On the other hand, the “La Nina-like warming” has been commonly referred to the trend in the zonal SST gradient in the equatorial Pacific, especially the cooling over the equatorial eastern Pacific (e.g., Seager et al. 2022; Lee et al. 2022). It would be better to distinguish these two. I don’t think the “Western Pacific warming mode”, “La Nina-like warming” or the cooling over the equatorial eastern Pacific are interchangeable. (e.g., L146-149)
4. Statistical significance tests should be included in the composite plots (Figs. 5 and 7). Also, whether the differences in Figs. 5 and 7 are statistically significant should be addressed.
5. The teleconnection patterns shown in Figure 5 is quite similar to the circumglobal teleconnection pattern shown in Ding et al. (2011). As mentioned in L194, Ding et al. (2011) also showed similar heating dipole pattern. Furthermore, Ding et al. (2011) also suggested this pattern is more frequent in the developing ENSO summer (Fig. 11a in Ding et al. 2011). I am wondering how much the patterns shown in this manuscript are similar to the CGT pattern in Ding et al. (2011). Is it possible there are actually the same thing?
6. Throughout the manuscript (especially in Section 5), the authors mentioned other studies frequently, e.g., Ding et al. (2011), Vijverberg and Coumou (2022), SEA pattern, Behera et al. 2013, O’Reilly et al. (2018) etc. The authors should provide more background information regarding these studies. Also, there are lots of consistency between your work and previous results. Which part of their results support the element you mentioned here? What are the unique parts of your results? We should not assume all the readers have read all these references or will read all of them along the way.

Minor comments:

L94-97: Please include the longitudinal ranges of Nino3 and Nino4 regions. Also, how about the climatology? Or SST anomalies are relative to zonal mean (between 20N-20S), rather than relative to any climatology?

L122: “eastern” edge of the Nino4 area: “western”

L124-125: please provide the lon/lat ranges of the components 1 and 2.

L194: “Both types of heating contrasts were found to be important by Ding et al. (2011)” -> important to what?

L208-209 & L283: why not include t2m anomalies over Eastern Europe and Russia in Figure 5?

L250-254 & Fig. 7: it would be helpful to also include wave patterns (Z300 anomalies) in Figure 7.

L281-284: Are there any evidences supporting that the more frequent warming & high pressure over Eastern Europe and Russia are statistically significant related to the increasing WPD negative phase?

The study by van Straaten et al investigates the link between sub-seasonal variability in tropical Pacific convection, closely related to ENSO, and summertime circulation over the Euro-Atlantic. The study shows that SST gradients associated with the dipole represent a combination of ENSO variability and West Pacific warming. These gradients in the West Pacific are followed by quasi-stationary waves that linger for multiple weeks. Situations with La Niña-like gradients are followed by high-pressure centers over Eastern Europe and Russia, three to six weeks later. The study also confirms earlier findings that the summertime connectivity between the Pacific and Europe has shifted in recent decades and partly explains the increased occurrence of high sea level pressures and summer temperatures over the European continent. The evidence the authors show is compelling and extends to sub-seasonal scales the findings reported by other authors who have analysed teleconnections from the Pacific towards Europe. I think the study is worth publishing after minor amendments to the text and figures.

Minor comments:

Line 44: There is a typo in consequence.

Lines 69-71 Even when a two weeks lag has been used, I consider it important to show that this is the optimal time lag since it is not so obvious that the signals arrive with the same lag.

Line 86-87: A clear reason should be stated on why the different times for averaging the different variables are used. The authors provide citations to other works, but still in my view, for clarity's sake, the authors should mention in this paper the reason for using different time lengths for averaging.

Figure 4B. It would be better to show the result in frequency, meaning the occurrences are divided by the total amount of occurrences and not occurrences.

The paper by Van Straaten et al. studies the connectivity between the western Pacific and Western Europe, with a focus on the sub-seasonal predictability of summer European temperatures related to tropical Pacific sea surface temperatures (SSTs) as well as the modulation of the teleconnection by north Atlantic SSTs. The authors base their analysis on the ERA5 reanalysis and other observed sea surface temperature datasets.

I have a few comments that need to be addressed before a possible publication of the paper in Weather and Climate Dynamics.

Major Comments:

1. My first comment is that the study is based on one reanalysis only (ERA5) while other reanalyses do exist and could be used to assess the sensitivity of the results to the choice of ERA5. Given that they use the 1950-2021 period for ERA5, I am also assuming that the authors have used the preliminary ERA5 back-extension (1950-1978) and not the final ERA5 recent release since 1940. If it is not too cumbersome, I would suggest to update the analysis with the new ERA5 data (at least for the figures using years before 1979).
2. In addition to spatial aggregation for the predictand, the authors use a monthly (4 weeks) aggregation for t2m and 3 weeks for SSTs. It would be interesting to see the results with a shorter temporal aggregation (10-15 days for instance, as the authors explicitly mentioned this period in their introduction as the time needed for the waves to establish) and comment on the potential differences. If these long averaging periods are required to obtain significant results (albeit with low amplitude for the correlations, 0.15–0.2), it is an interesting information.
3. Statistical significance: no statistical significance of the composites is provided for figures 5 and 7. They need to be performed with an appropriate method (for a cautionary note about t-test, see “The Use of t values in Composite Analyses” by Brown, T.J., and Hall, B.L., Journal of climate, vol. 12. 2941-2944, 1999). It would be nice to have more details in the paper about the method used to derive statistical significance for Figure2 (without having to go to a previous publication). In relation to the false discovery rate procedure, it is not clear to me what alpha (page 6, line 119) is (in Wilks BAMS2016, alpha is the nominal level of the statistical test).
4. Figure 2 and the definition of the WPD index: as it is now, there seems to be a lot of subjectivity in the choice of the two boxes (comp_1 and comp_2). For instance, one could have extended the comp_1 westward and southward (including regions with significant correlations). Similarly, the comp_2 box could have been slightly extended eastward and southward. Is it possible to present a rationale for the choice of the boxes? Or at least, one would like to see a sensitivity analysis regarding the definition of the WPD index.  It is a bit surprising to notice that a large spatial aggregation is performed for the predictand (t2m in Europe), contrasting with the small spatial extent of the regions used to estimate the WPD index.

Minor comments:

• Page 2, line 34: Many studies suggest that the contribution of ocean SSTs (including therefore La Niña) to the Russian heatwave is very weak (see Dole et al., 2011; Hauser et al. 2016; Wehrli et al. 2019)
• Page 2, line 51: this is a reference to a paper under review, I am not sure about the WCD policy about that.
• Page 4, line 100: using this PDO definition where global mean SSTs are removed might not be the best option This assumes that any anthropogenic influence on PDO behavior is fully removed by subtracting the time evolving changes in global mean SSTs from local SST changes in the PDO region. This is unlikely as it is known that there are different forced warming rates between the PDO region SSTs and the global mean SSTs. This means that an anthropogenic signal is likely to be aliased when using this PDO index definition (see Bonfils and Santer, 2011).
• Page 4: there is no reference to figure 1A, perhaps add it line 109.
• Page 6, lines 126–129: I think that this statement (that the WPD captures the combined heating contrast …) need a bit more details, or maybe even an additional figure. It is written as if it is an obvious fact, but it is not.
• Page 6, figure 3 caption: why do you use 4 weeks instead of 3 for PDO and Niño indices?
• Page 6, lines 131–134: I do not understand the logic here. The WPD index is based on two boxes that are located in the Western Pacific, and one of the boxes is outside the equatorial region. It is not clear to see how this can be related to the equatorial SST gradient across the whole Pacific basin. Please explain.
• Page 7, lines 155–159: why not using the “detrending” approach outlined for Figure 2 instead of using a 21-yr rolling window?
• Page 7, lines 163–165: please specify what are exactly the equatorial (SST?) gradients you are talking about.
• Figure 7: the contours are very difficult to see, can you enlarge the plots and make thicker contours ?

References:

Bonfils C, Santer BD (2011) Investigating the possibility of a human component in various Pacific Decadal Oscillation indices. Clim Dyn 37:1457–1468. https://doi.org/10.1007/s00382-010-0920-1

Dole, R., Hoerling, M., Perlwitz, J., Eischeid, J., Pegion, P., Zhang, T., et al. (2011).Was there a basis for anticipating the 2010 Russian heat wave? Geophysical Research Letters, 38, L06702. https://doi.org/10.1029/2010GL046582

Hauser, M., Orth, R., & Seneviratne, S. I. (2016). Role of soil moisture versus recent climate change for the 2010 heat wave in western Russia. Geophysical Research Letters, 43, 2819–2826. https://doi.org/10.1002/2016GL068036

Wehrli, K., Guillod, B. P., Hauser, M., Leclair, M., & Seneviratne, S. I. (2019). Identifying key driving processes of major recent heat waves. Journal of Geophysical Research: Atmospheres, 124, 11,746–11,765. https://doi.org/10.1029/2019JD030635