the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Extreme blocking ridges are associated with large wildfires in England
Abstract. Persistent positive anomalies in 500 hPa geopotential heights (PPAs) are an event-based paradigm for tracking specific large scale atmospheric patterns that often correspond to blocking events. PPAs are associated with hot, dry surface weather conditions that promote fuel aridity and wildfire activity. We examine the importance of PPA events for surface fire weather across the UK and wildfires in England, a temperate, emerging fire prone region. Surface fire weather is more extreme under PPAs, characterised by reduced precipitation and anomalously high temperatures. Overall, 34 % of England’s burned area and 16 % of all wildfire events occur during or up to five days following the presence of a PPA event. PPAs are generally more strongly associated with wildfire burned area than ignition frequency. The percentage of PPAs associated with wildfire events increases with increasing fire size, with PPAs being associated with half of wildfire events > 500 ha. PPAs are most important for heathland/moorland (40 % burned area) followed by grassland (30 % burned area) wildfires and are more important during the summer wildfire season. Synoptic-scale indicators of wildfire activity like PPAs may improve longer-term fire weather forecasts beyond surface fire weather indices alone, aiding wildfire preparedness and management decision-making. This is particularly important in emerging fire prone regions where wildfire risk is increasing but established tools for assessing fire danger may not yet exist.
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RC1: 'Comment on nhess-2024-161', Anonymous Referee #1, 03 Dec 2024
Little et al. explore the relationship between persistent high-pressure systems, surface weather conditions, fire indicators and actual wildfires using a dataset which ranges from March – October 2001-2021 (UK) and 2010-2020 (England), respectively. They find significant relationships between high pressure systems and local weather conditions and wildfire characteristics across seasons. This is an interesting assessment, which could be further improved by accounting for following comments:
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Minor:
1.     Fig. 1 this is a very informative figure. It could be improved even further, by adding information on months and seasons by e.g. dashed vertical lines or shaded background.
2.     L. 144 is this the best way to implement this? Wouldn’t daily max. Temperatures be more informative? Or is this essentially the same value for most of the days.
3.     L. 245 do these numbers refer to each grid-cell individually or are events defined based on some sort of spatial integration (all anomalous neighboring grid-cells are counted as one event)?
4.     This does not refer to the content, but rather to the way the paper is structured. Data and Methods sections seem to include some results already, which is why the results section is fairly short (mostly the figure, the figure caption and 1-2 sentences of description). The manuscript would be easier to follow if methods and related results were merged.Â
5.     Figure 3. It would be helpful (also for the description of the results in the paragraph before and for the caption) to have the subplot labeled with e.g. letters a-i. Abbreviations should be written out fully in the caption.Â
6.     Figure 4. The subplot labeling and the figure caption could be made more intuitive by labeling each plot separately. Abbreviated variables should be written out. A clear description of what the boxplot boundaries, whiskers and dots refer to is missing.Â
7.     I would suggest to merge the conclusions into the discussion section and possibly add a bit more context.Â
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Major:Â
1.     How are PPA events being associated with surface anomalies? Are relationships being quantified for events that are detected over the same grid-point, during the same time period only? How are the lead lag relationships accounted for and how are vertical shears in PPAs and surface response integrated in the regression shown in Fig. 4?
2.     The Dataset is fairly short for a trend analysis, but it would be very insightful to acknowledge and assess changes in wildfire characteristics over the past decade(s). Have increased temperatures, precipitation or landcover changes led to significant increases (or decreases in regional wildfires?). An increased threat from Wildfires to the UK is mentioned in l.363 but is not backed up with any quantitative results.
3.     Various fire weather indicators were calculated in this study. Which indicator is best suited to predict actual fires in the UK?
Citation: https://doi.org/10.5194/nhess-2024-161-RC1 -
RC2: 'Comment on nhess-2024-161', Anonymous Referee #2, 21 Jan 2025
First of all, I would like to apologize for the long delay in providing the revision of the manuscript.
The authors investigate the occurrence of extreme blocking ridges associated with large wildfires in England. For that they use a method to identify atmospheric blocking patterns for the pan-European spatial domain. The method is based on persistent positive anomies of 500 hPa geopotential height.
Main issues:
- The data provided by the Home Office for England, covering the period between March and October 2010–2020, requires careful consideration. First, the analysis should be restricted to fires exceeding 10 hectares, or preferably, 50 hectares. Fires below these thresholds generally have a minimal or negligible impact. If such thresholds are applied, the majority of the analysis and conclusions will be based on a limited number of cases, which restricts the generalizability of the findings.
- Introduction: The introduction lacks clarity in several places. For example, lines 39–41 and 44–46 are vague and read more like a report rather than scientific writing. These sections should be rewritten to align with scientific standards, ensuring precision and focus.
- Blocking Paragraph (Lines 65–70): The explanation of blocking is not presented correctly. The paragraph begins with a discussion of the 500 hPa level, followed by a description of what blocking is. This structure is unclear and suggests a lack of understanding of the concept. A more structured and detailed explanation of atmospheric blocking is required, ensuring the authors demonstrate a thorough grasp of the subject.
- Section 1.3. Antecedent conditions are crucial for understanding most fire behavior. These conditions, including prolonged dry periods, accumulated fuel loads, and seasonal trends, significantly influence fire behavior and severity. The section should emphasize the role of these pre-existing factors in shaping fire activity.
- L97 Does it really matters analyzing fires below 30ha or even 50ha?
- Why is this study important and why is different from Little et al 2024??
- L126 The analysis raises the question of why wildfires in built-up areas and gardens are being included. Are these incidents truly wildfires? By definition, wildfires typically occur in natural or semi-natural landscapes, and including these cases may lead to misleading interpretations or dilute the focus of the study.
- Figure 1. The total burnt area of specific large wildfires dominates the results, overshadowing smaller events and potentially skewing the analysis. A more detailed breakdown or normalization of the data might help clarify the trends and improve the interpretability of the figure.
- Re-grid: I don´t understand how did you re-grid the data? Specially for the wild fires. If there is one wild fire with 1ha within a certain 1x1 degree box then you count this grid point with a wildfire? Do you think that´s a fair thing to do? If this is the case, I don´t agree with the methodology since a single wildfire with a 1ha is not meaningful on a 1x1 degree box.
- I have another major issue using the specific detection blocking method. Using this specific method, you only have a yes or no analysis. My suggestion is to use Weather Regimes (Grams et al., 2017) instead of your blocking method. This as many advantages: 1) The use of weather regimes gives more opportunity to study other meteorological patterns that can be important for wildfires which you cannot do it in the present form. 2) the authors mentioned several times, that this study would be important for helping in forecasting wildfires. It the PPAs operational forecast in use? Another advantage of using Weather regimes is that they are operational forecasted at the ECMWF (https://www.ecmwf.int/en/newsletter/165/meteorology/how-make-use-weather-regimes-extended-range-predictions-europe). The authors could consider combining the Fire Weather Index (FWI) forecasts from Copernicus with weather regime forecasts to enhance wildfire predictability in England. This integrated approach could improve the accuracy of forecasting wildfire risks by leveraging the strengths of both systems, providing valuable insights for prevention and mitigation strategies.
Grams, C., Beerli, R., Pfenninger, S. et al. Balancing Europe’s wind-power output through spatial deployment informed by weather regimes. Nature Clim Change 7, 557–562 (2017). https://doi.org/10.1038/nclimate3338
Considering these significant major issues, I recommend the rejection of the manuscript in its current form. I also suspect that the use of wildfires only above 10ha or 50ha and excluding in built-up areas and gardens areas will give a very limited sample for analysis which will limited the findings of the study. The points outlined above highlight critical flaws in the analysis, interpretation, and presentation of results, which need substantial revision before the work can be reconsidered again for publication.
Citation: https://doi.org/10.5194/nhess-2024-161-RC2
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