the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The potential of an increased deciduous forest fraction to mitigate the effects of heat extremes in Europe
Marcus Breil
Annabell Weber
Joaquim G. Pinto
Abstract. Deciduous forests are characterized by a higher albedo, a reduced stomatal resistance and a deeper root system in comparison to coniferous forests. As a consequence, less solar radiation is absorbed and evapotranspiration is potentially increased, making an increase in the deciduous forest fraction potentially a promising measure to mitigate the burdens of heat extremes for humans and nature. We analyze this potential by means of an idealized 30 years long regional climate model experiment, in which all coniferous forests in Europe are replaced by deciduous forests and compared to a simulation using the actual forest composition.
Results show that an increase in the deciduous forest fraction significantly reduces the heat intensity during heat periods in most regions of Europe. In mean, a slight reduction of the daily maximum 2 m temperatures about 0.2 K is simulated locally, and 0.1 K non-locally during heat periods. Regions with a high cooling potential are south-western France and northern Turkey, where heat period intensities are reduced up to 1 K. Negative effects are simulated in Scandinavia and Eastern Europe.
Although the cooling effect on heat period intensities is statistically significant over large parts of Europe, the magnitude of the temperature reduction is small. An increase in the deciduous forest fraction has consequently only a limited potential to reduce heat period intensities in Europe and can therefore only be considered as a supporting mitigation measure to complement more effective mitigation strategies.
Marcus Breil et al.
Status: final response (author comments only)
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RC1: 'Comment on bg-2023-18', Anonymous Referee #1, 20 Feb 2023
Comment on bg-2023-28 by Breil et al.
This paper plays with the idea that all coniferous forests in Europe are replaced by deciduous forests. The climatic response to this vegetation change is simulated by one RCM. As such this is an interesting exercise since different kind of afforestation or vegetation alterations are discussed as mitigation methods. The effect of changing the type of forest is, however, mostly small and statistically insignificant.
The experiment is well organised and executed, but there I have some concerns about the methods and the conclusions that I would like to raise. My main concern is that the results, or the implications of the results, is a bit exaggerated. The effects are small and mostly insignificant, i.e. changing conifers to deciduous is not a viable mitigation strategy. This also an interesting result. I don’t see the need of exaggerating the model response, or trying to see connections between e.g. evaporation in western Europe and precipitation in eastern Europe. I don’t think that the authors in a satisfactory way should that the model response is due to these proposed mechanisms and not just random. The difference between the first 15 years and the last 15 years of the REF simulations could be bigger than the difference between REF and BROAD. Natural variability is large and I don’t see why the difference between REF and BROAD could just be random variability. I still think the paper is worth publishing, and therefore I don’t see the need of making a large effort to try to explain all differences between REF and BROAD. Especially since these differences are mostly small and insignificant.
Major comments
L112, and Table 1: What do these classes represent? The difference in characteristics are large between e.g. birch and oak. Also, not the same kinds of tress grow in northern Turkey and northern Norway. Please describe the forest types a little better.
L114: You call the simulation BROAD, by you constantly use the term deciduous forest, not broadleaved. Consider renaming the simulation to something more corresponding, e.g. DECID.
L117: Is the 90th percentile calculated on all days of the year? This would mean that on average 36 days per year pass the threshold, more than a month. In that case you don’t study intense heat but rather summer conditions. Please clarify.
L118: “analyzed” How do you analyse them? Do you compare the means of the warm days of the different simulations?
L118: “duration” and “number of periods” If you count the number of periods, you are not studying the duration. Duration is the length of the events not how many they are.
L133-135: This is a description that is a bit backwards. It’s a bit strange to describe Scandinavia as the exception, when in fact this is the largest and most obvious change. This description also mainly applies to Fig 4b, it’s not the most appropriate to but it after “(Fig 2c)”.
L138-139: Maximum 2 m temperature is not necessarily the same as heat period intensities (but again it’s not entirely clear how you define heat intensity). Did you also look at Tmax? It would be interesting to see how the signal in Tmax compares to the signal in heat intensity.
L140: “notably Norway” Here one might add also the northern half of Sweden and large parts of Finland.
L175: Is it really correct to call a correlation of 0.2-0.4 high?
L179-184: I would suspect that this is very model sensitive, and sensitive to the exact vegetation description used. I think this should be mentioned, either here or in the Discussion.
L203: I find it a bit strange that you support the small changes with the statement that the signal is statistically significant in 45 % of the grid cells. This means that the local effect is small and insignificant in more than half of the grid cells.
L203: “all grid cells” Do you mean *all* grid cells, all grid cells with vegetation changes or all grid cells with with reduced daily maximum 2 m temperature? Please rephrase and clarify.
L207: “95 % of the areas” Do you mean grid cells? If not, please explain what these areas are.
L222-223: Do you actually mean that the precipitation sum is driving the temperature increase? Please explain.
L227: “Spatial precipitation” Do you mean the mean precipitation over a particular area, or do you mean spatial changes in precipitation? Please explain or rephrase.
L240: The band from Greece to the Baltics is very narrow, and the changes in evaporation in western Europe is very small. How can you know that this is the connection? Especially since precipitation sums are reduced also to the west of this band. Without a proper explanation I would say that this is a random effect.
L249-251: This could as well be used as an argument for that all differences are random.
L251: “several parts of Europe” Which parts are these, are they defined?
L251-251: “95 % of these regions” Do you mean regions or grid cells?
L252: “the rest of Europe” How large proportion of Europe is this? Is this actually the dominating effect?
L254: The sentence reads like you only looked at grid cells with reduced Tmax. I guess this is not what you did. Please rephrase.
L257-260. Is the threshold calculated from the 90th percentile in REF of per simulation? See also the comment on L118.
L272-274: How does this relate to observations and actual conditions? I guess that there are data. It would be good to check whether the models give expected results.
L293: This depends on how you define drought conditions. In summer in northern Europe precipitation will not decrease, but not increase that much either. Agricultural drought might increase anyway because of increasing evaporation.
L297: It’s not true that the water availability will not decrease in Scandinavia in summer. The projected change in summer precipitation is small. This combined with increased evaporation because of higher temperature will lead to decreased soil moisture.
https://interactive-atlas.ipcc.ch/permalink/iUVVp1nj
L319-322: The best model study of this is probably Belusic et al. (2019). They show that changes in roughness length alone can explain a large part of the precipitation changes. It may be worth having a look at that. It also worth noting that Strandberg & Kjellström (2019, already cited in the manuscript) hardly find any significant down-wind non-local effects on precipitation at all.
L348-355: One could add that the response to vegetation changes differs between models. Please add a note on that.
L371: “significant effects” I guess you mean insignificant effects given what you write on lines 203, 210, 251 and 254.
L375: You don’t study the duration of heat periods, but the number of heat periods.
L393-394: “Positive impact” Do you mean ‘improvement’ or increased temperature? Please explain.
Figs 3 & 5: Just to clarify. Is Fig 3 the same as Fig 2d, and Fig 5 the same as Fig 4a, only with grey points? If that is the case I would suggest that you mark the significant results in a more visible way. The grey dots are really difficult to see. Why don’t use hatching, or borders around significant grid cells, or something like that.
Fig 4b: It very non-intuitive to show increasing precipitation with red and decreasing with blue. Please reverse or change colourscale.
Minor comments
L24: (see also L382 and more). It is not always to understand what positive/negative effects are. It is often better to use increase/decrease or similar.
L100: “yearly updated maps”. Does this mean that the land cover is changed in every simulated year in the model? If not, rephrase. If this is what you do, how does the changing vegetation in the REF simulations affect the results?
L166: “due the generally” -> “due to the generally”
L215: “non-locally simulated” I think you mean that the simulations give no non-local effects. Please rephrase.
L290: “in future” -> “in the future”
L305: “in future” -> “in the future”
References
Belušić, D., Fuentes-Franco, R., Strandberg, G.and Jukimenko, A., 2019: Afforestation reduces cyclone intensity and precipitation extremes over Europe. Environ. Res. Lett. 14,https://doi.org/10.1088/1748-9326/ab23b2
Citation: https://doi.org/10.5194/bg-2023-18-RC1 -
RC2: 'Comment on bg-2023-18', Anonymous Referee #2, 24 Feb 2023
Review for Breil and Coauthors
“The potential of an increased deciduous forest fraction to mitigate the effects of heat extremes in Europe”
Submitted to Biogeosciences
https://doi.org/10.5194/bg-2023-18
Overview:
Breil et al. present research on modeling the local and non-local climate effects of afforesting existing coniferous forest in Europe with deciduous forest. They hypothesize that deciduous forest may help mitigate warming during periods of extreme heat through increased evapotranspiration and/or increased surface albedo. They run two model scenarios – one with present day forest annual changing forest cover and a second with all coniferous forest replaced with deciduous forest types. The results indicate that there is a slight cooling effect, but it is marginal and unlikely to serve as a single solution to reducing the duration and magnitude of extreme heat. Instead, they suggest that afforestation of coniferous forest with deciduous forest would serve as one of several efforts that could complement rather than completely mitigate future warming.
While the results do not show a large cooling effect of replacing coniferous forest with deciduous forest, I still believe it is an important addition to the peer-reviewed literature. Please address the major and minor comments below in a revised submission.
Major Comments:
The introduction could use more context on the history and current state of forest types in Europe. How did we arrive at present-day forest cover distribution? Why does Europe’s forest cover today differ so much from potential vegetation that would grow there if it otherwise hadn’t been cleared for agriculture, timber, and fuelwood? Wouldn’t beech and oak, two broadleaved species, dominate European forests were it not for forest management and harvest practices? Isn’t secondary regrowth and forest succession part of the story? I would like to see this contextualized beyond the single sentence in lines 72-73 that states “the current composition of European forests is dominated by coniferous forests (Bartholome & Belward, 2005), due to forestry reasons.”
I would also like to see a discussion paragraph on the feasibility of growing deciduous forests in Scandinavia and other regions in the modeling domain that have limited potential to be afforested into a deciduous forest. It seems soil nutrient availability and chemistry, specifically N-limited and acidic soils, would limit deciduous forest afforestation in the boreal forest biomes dominant in Fennoscandia.
Minor Comments:
Lines 72-73: Please include more recent references, such as Sabatini et al. (2021) and Ceccherini et al. (2020).
Sabatini et al. (2021): https://onlinelibrary.wiley.com/doi/full/10.1111/ddi.12778
Ceccherini et al. (2020): https://www.nature.com/articles/s41586-020-2438-y
Lines 93-99: Please confirm and specify that two-way coupling is used between the land and atmosphere models.
Line 109: Remove unnecessary comma after CCLM-VEG3D
Figures:
Figure 2f. Please use a monochromatic (light green to dark green for example) rather than rainbow scale bar.
Citation: https://doi.org/10.5194/bg-2023-18-RC2
Marcus Breil et al.
Marcus Breil et al.
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