the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 May 2024
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Abstract. Land use change, particularly deforestation, significantly influences the global climate system. While various studies have explored how deforestation affects temperature and precipitation, its impact on drought remains less explored. Understanding these effects across different climate zones and time scales is crucial for crafting effective land use policies aimed at mitigating climate change. This study seeks to investigate how changes in forest cover affect drought across different time scales and climate zones using simulated deforestation scenarios, where forests are converted to grasslands. The study utilizes data from nine global climate models participating in the Land Use Model Intercomparison Project. Drought effects are assessed by examining changes in the Standardized Precipitation Evapotranspiration Index (SPEI). The results reveal that deforestation leads to negative shifts in global SPEIs, indicating increased dryness, particularly in tropical regions, while causing wetter conditions in dry regions. Moreover, the impact on drought indices becomes more pronounced with longer time scales, underscoring the lasting effects of deforestation on drought. Seasonally, deforestation exacerbates SPEI03 shifts during autumn and winter, especially affecting tropical and northern polar regions. Continental zones experience significant seasonal changes, becoming drier in winter and wetter in summer due to global deforestation, while the northern hemisphere's dry regions see increased wetter conditions, particularly in autumn. These findings deepen our understanding of the relationship between vegetation change and climate change, offering valuable insights for better resource management and mitigation strategies against future climate change impacts.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2290 KB) - Metadata XML
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Supplement
(3927 KB) - BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1270', Wenjian Hua, 16 Aug 2024
This study investigated the global and regional response of drought to deforestation by analyzing results from CMIP6-LUMIP experiments. The authors compared the differences between the piControl and deforest-global simulations, in order to infer the impacts of deforestation. This study provides good information on the regional response of drought to idealized deforestation. However, the authors should be more cautious in their conclusions, due to the uncertainties in attributing the climatic effects of deforestation in models. There are some issues that the authors need to properly address during the revision.
- Introduction, pp.3-4, lines 65-93: Perugini et al. (2017) reviewed the existing scientific literature regarding the biophysical effects of land cover change on temperature and precipitation. I think it is inappropriate to cite this review paper in many places in the Introduction section describing the previous findings on the topic of climatic effects of forest cover change. Maybe cite and specify some classic or recent articles to illustrate the impacts of forest cover changes.
- 6-7, lines 177-187: I am intensely curious why the authors do not use the CESM and MPI-ESM1-2-LR model simulations from CMIP6-LUMIP? For example, CESM2 also have three runs, similar to IPSL-CM6A-LR, while MPI-ESM1-2-LR has seven members. Please note that climatic responses across individual runs due to model internal variability may also show considerable differences. I think single model with multiple realizations can provide a better estimate of climate responses due to deforestation. I encourage the author discussing more on these.
- Lines 248-249: The full name of the Dry_n, Dry_s, T_n, … etc should be displayed upfront when it is used for the first time.
- Sections 2.2 and 2.3: I think these two paragraphs are the core of the analysis methods section, even the core of the whole paper. However, it is not clear enough. For example, how the authors calculated the SPEI in the CMIP6-LUMIP model simulations?
- What is the rationale to perform cubic spline regression analysis? Is it sensitive to a given interval?
- Lines 284-285: One possible reason is that UKESM1-0-LL still exhibits forest cover changes after the year 50 due to its model structure? (e.g., Fig. S2 in Boysen et al., 2020).
- Section 3.1: I suggest Section 3.1 must be shortened and greater clarity in the presentation of new findings, as previous studies (e.g., Boysen et al. 2020; Luo et al. 2022) have examined the temperature and precipitation responses to idealized deforestation (i.e., deforest-global vs. piControl) in the CMIP6 models.
- Figure 2 and other similar figures: Please note that forest fractions in Antarctica did not show a change in the deforest-global experiment. Why the models exhibit few significant variations due to idealized deforestation in the SPEI in Antarctica? Please explain a little bit about it. Internal noise in models?
- The deforest-globe simulations are initialized from their pre-control runs, so the initial fraction of forest cover in each model may be different. That’s why the drought patterns (Figs. 2 and 3) and the temporal variations (Figs. 4 and 5) due to deforestation exhibit large differences (e.g., EC-Earth3-Veg and GISS-E2-1-G), in particular in the temperate and boreal regions. I think the authors should add relevant discussions on the temporal and spatial differences among the CMIP6 models.
- Authors should also pay attention to the model uncertainties (e.g., LUCID Pitman et al., 2009, also LUMIP Boysen et al., 2020). I suggest the author discussing more on these. The drought responses must be treated with caution due to lack of a sufficiently large ensemble.
- In the manuscript, I didn't see many mentions or linkages to physical and biophysical processes implemented in the nine models. Is there any chance to find an explanation of the present diagnostic results, namely, links between deforestations and drought?
Citation: https://doi.org/10.5194/egusphere-2024-1270-RC1 -
AC1: 'Reply on RC1', Bo Huang, 30 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1270/egusphere-2024-1270-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2024-1270', Anonymous Referee #2, 14 Sep 2024
Deforestation can significantly affect the climate by altering both biogeochemical and biogeophysical processes, and can also affect the drought processes across the world. While various studies have explored how deforestation affects temperature and precipitation, its impact on drought remains less explored. Based on the output from the Land Use Model Intercomparison Project (LUMIP), this study investigated the global and regional response of drought to idealized deforestation. The study presents many intriguing findings, offering a global perspective on the relationship between vegetation changes and drought, while also providing new insights. The overall structure of the article is well-organized, with clear logic and distinct layers. Here are my comments:
- This study provides many novel findings, such as “deforestation causing wetter conditions in dry regions” and “the northern hemisphere's dry regions see increased wetter conditions, particularly in autumn”. It would be even better if some mechanistic explanations could be added in the abstract.
- Line 34: Provide the full name of “SPEI03”.
- Lines 129-140: This paragraph is a bit too lengthy. You can simplify this paragraph by focusing on directly stating the scientific questions that need to be addressed while avoiding unnecessary details. Keep the language concise and clear, allowing the reader to quickly grasp the core issue.
- Line 156: Add the study period in this section.
- Lines 188-189: Why was this interpolation method chosen? Do different interpolation methods significantly affect the results?
- Lines 191-192: Many drought indices are available; could you explain some reasons for choosing the SPEI?
- Lines 222-225: What do the short-term, mid-term, and long-term mean? Why do you select two mid-terms?
- Figure 1: Combining precipitation changes with temperature changes is not intuitive enough. It is recommended to separate the two and create two subplots.
- Line 335: The font style of the titles needs to be consistent.
- Line 336: The indentation format of the paragraphs also needs to remain consistent.
- It is recommended to analyze the impact of deforestation on the spatiotemporal dynamics of drought in future studies.
Citation: https://doi.org/10.5194/egusphere-2024-1270-RC2 -
AC2: 'Reply on RC2', Bo Huang, 30 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1270/egusphere-2024-1270-AC2-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1270', Wenjian Hua, 16 Aug 2024
This study investigated the global and regional response of drought to deforestation by analyzing results from CMIP6-LUMIP experiments. The authors compared the differences between the piControl and deforest-global simulations, in order to infer the impacts of deforestation. This study provides good information on the regional response of drought to idealized deforestation. However, the authors should be more cautious in their conclusions, due to the uncertainties in attributing the climatic effects of deforestation in models. There are some issues that the authors need to properly address during the revision.
- Introduction, pp.3-4, lines 65-93: Perugini et al. (2017) reviewed the existing scientific literature regarding the biophysical effects of land cover change on temperature and precipitation. I think it is inappropriate to cite this review paper in many places in the Introduction section describing the previous findings on the topic of climatic effects of forest cover change. Maybe cite and specify some classic or recent articles to illustrate the impacts of forest cover changes.
- 6-7, lines 177-187: I am intensely curious why the authors do not use the CESM and MPI-ESM1-2-LR model simulations from CMIP6-LUMIP? For example, CESM2 also have three runs, similar to IPSL-CM6A-LR, while MPI-ESM1-2-LR has seven members. Please note that climatic responses across individual runs due to model internal variability may also show considerable differences. I think single model with multiple realizations can provide a better estimate of climate responses due to deforestation. I encourage the author discussing more on these.
- Lines 248-249: The full name of the Dry_n, Dry_s, T_n, … etc should be displayed upfront when it is used for the first time.
- Sections 2.2 and 2.3: I think these two paragraphs are the core of the analysis methods section, even the core of the whole paper. However, it is not clear enough. For example, how the authors calculated the SPEI in the CMIP6-LUMIP model simulations?
- What is the rationale to perform cubic spline regression analysis? Is it sensitive to a given interval?
- Lines 284-285: One possible reason is that UKESM1-0-LL still exhibits forest cover changes after the year 50 due to its model structure? (e.g., Fig. S2 in Boysen et al., 2020).
- Section 3.1: I suggest Section 3.1 must be shortened and greater clarity in the presentation of new findings, as previous studies (e.g., Boysen et al. 2020; Luo et al. 2022) have examined the temperature and precipitation responses to idealized deforestation (i.e., deforest-global vs. piControl) in the CMIP6 models.
- Figure 2 and other similar figures: Please note that forest fractions in Antarctica did not show a change in the deforest-global experiment. Why the models exhibit few significant variations due to idealized deforestation in the SPEI in Antarctica? Please explain a little bit about it. Internal noise in models?
- The deforest-globe simulations are initialized from their pre-control runs, so the initial fraction of forest cover in each model may be different. That’s why the drought patterns (Figs. 2 and 3) and the temporal variations (Figs. 4 and 5) due to deforestation exhibit large differences (e.g., EC-Earth3-Veg and GISS-E2-1-G), in particular in the temperate and boreal regions. I think the authors should add relevant discussions on the temporal and spatial differences among the CMIP6 models.
- Authors should also pay attention to the model uncertainties (e.g., LUCID Pitman et al., 2009, also LUMIP Boysen et al., 2020). I suggest the author discussing more on these. The drought responses must be treated with caution due to lack of a sufficiently large ensemble.
- In the manuscript, I didn't see many mentions or linkages to physical and biophysical processes implemented in the nine models. Is there any chance to find an explanation of the present diagnostic results, namely, links between deforestations and drought?
Citation: https://doi.org/10.5194/egusphere-2024-1270-RC1 -
AC1: 'Reply on RC1', Bo Huang, 30 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1270/egusphere-2024-1270-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2024-1270', Anonymous Referee #2, 14 Sep 2024
Deforestation can significantly affect the climate by altering both biogeochemical and biogeophysical processes, and can also affect the drought processes across the world. While various studies have explored how deforestation affects temperature and precipitation, its impact on drought remains less explored. Based on the output from the Land Use Model Intercomparison Project (LUMIP), this study investigated the global and regional response of drought to idealized deforestation. The study presents many intriguing findings, offering a global perspective on the relationship between vegetation changes and drought, while also providing new insights. The overall structure of the article is well-organized, with clear logic and distinct layers. Here are my comments:
- This study provides many novel findings, such as “deforestation causing wetter conditions in dry regions” and “the northern hemisphere's dry regions see increased wetter conditions, particularly in autumn”. It would be even better if some mechanistic explanations could be added in the abstract.
- Line 34: Provide the full name of “SPEI03”.
- Lines 129-140: This paragraph is a bit too lengthy. You can simplify this paragraph by focusing on directly stating the scientific questions that need to be addressed while avoiding unnecessary details. Keep the language concise and clear, allowing the reader to quickly grasp the core issue.
- Line 156: Add the study period in this section.
- Lines 188-189: Why was this interpolation method chosen? Do different interpolation methods significantly affect the results?
- Lines 191-192: Many drought indices are available; could you explain some reasons for choosing the SPEI?
- Lines 222-225: What do the short-term, mid-term, and long-term mean? Why do you select two mid-terms?
- Figure 1: Combining precipitation changes with temperature changes is not intuitive enough. It is recommended to separate the two and create two subplots.
- Line 335: The font style of the titles needs to be consistent.
- Line 336: The indentation format of the paragraphs also needs to remain consistent.
- It is recommended to analyze the impact of deforestation on the spatiotemporal dynamics of drought in future studies.
Citation: https://doi.org/10.5194/egusphere-2024-1270-RC2 -
AC2: 'Reply on RC2', Bo Huang, 30 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1270/egusphere-2024-1270-AC2-supplement.pdf
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Chunping Tan
Xia Zhang
Francesco Cherubini
Henning W. Rust
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2290 KB) - Metadata XML
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Supplement
(3927 KB) - BibTeX
- EndNote
- Final revised paper