the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Effects on Early Monsoon Rainfall in West Africa due to Recent Deforestation in a Convection-permitting Ensemble
- 1School of Earth and Environment, University of Leeds, UK
- 2UK Centre for Ecology and Hydrology, Wallingford, UK
- 3Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Austria
- 4National Centre for Earth Observation, Wallingford, UK
- 5National Centre for Atmospheric Science, University of Leeds, UK
- 6NORCE Norwegian Research Centre AS
- 7Laboratory of Material Sciences, Environment and Solar Energy (LASMES), University Felix Houphouet Boigny (UFHB), Abidjan, Cote d’Ivoire
- 8Geophysical Station of Lamto, BP 31, N’Douci, Cote d’Ivoire
- 1School of Earth and Environment, University of Leeds, UK
- 2UK Centre for Ecology and Hydrology, Wallingford, UK
- 3Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Austria
- 4National Centre for Earth Observation, Wallingford, UK
- 5National Centre for Atmospheric Science, University of Leeds, UK
- 6NORCE Norwegian Research Centre AS
- 7Laboratory of Material Sciences, Environment and Solar Energy (LASMES), University Felix Houphouet Boigny (UFHB), Abidjan, Cote d’Ivoire
- 8Geophysical Station of Lamto, BP 31, N’Douci, Cote d’Ivoire
Abstract. Tropical deforestation can have a significant effect on climate, but research attention has been directed mostly on Amazonian deforestation. The southern part of West Africa (a region dependent on rain-fed agriculture and vulnerable to droughts and flooding) has seen significant deforestation since the 1950s. Many previous tropical deforestation studies have used idealized and exaggerated deforestation scenarios and parameterized convection models. In this study we estimate realistic historical deforestation from the Land Use Harmonization dataset in West Africa and simulate the impacts in a 5-day ensemble forecast in June using a convection-permitting regional climate model. We find that sensible heat flux increases at the expense of latent heat flux in most deforested regions and rainfall increases by an average of 8.4 % over deforested pixels from 18:00–6:00 UTC, whereas changes are much less pronounced during the day. Over large areas of deforestation ~300 km inland (e.g., West Guinea) the roughness-length- and thermally induced enhanced convergence during the afternoon and evening occurs over the deforested areas resulting in increases in rainfall with little impact from reduced daytime humidity. In areas of coastal deforestation (e.g., Cote d’Ivoire), increased winds drive the sea breeze convection inland, resulting in evening rainfall reductions over the deforested area but increases further inland, in line with observations. We suggest our results would not be replicated in parameterized convection models, which are known to struggle with capturing peak convective activity in the late afternoon and long-lived nocturnal rainfall, and with reproducing observed surface-rainfall feedbacks.
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Julia Crook et al.
Status: open (until 08 Oct 2022)
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RC1: 'Comment on wcd-2022-49', Anonymous Referee #1, 17 Sep 2022
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Review of manuscript # wcd-2022-49 titled ‘Effects on Early Monsoon Rainfall in West Africa due to RecentDeforestation in a Convection-permitting Ensemble’
submitted to EGU Weather and Climate Dynamics – Discussions
Submitted by – Julia A. Crook et al. 2022
The study pertains to understanding how current west African deforestation impacts the regional hydroclimate as compared to the land cover in the 1950s using a cloud resolving regional atmospheric model. The pre- to early- monsoon period is simulated and various hydro-meteorological variables are analysed to understand the impacts of deforestation of convection, precipitation and underlying processes. The authors show small but significant increases in precipitation due to deforestation unlike the findings of a precipitation decrease by previous studies, which is the novelty of this result and probably also matches with some observations as claimed by the authors. It seems that the use of the cloud resolving simulations have helped the authors to achieve these similar-to-observation results. Overall I think the study and its results are important for publication. However, I do find certain issues with the writing and presentation style which have made the article a difficult read. There are also certain aspects of the study that need clarification in the paper. I suggest a revision of these aspects of the study before final acceptance. I have provided my specific comments below. I have also provided my answers to the questions provided on the journal website -
- Does the paper address relevant scientific questions within the scope of WCD? Yes
- Does the paper present novel concepts, ideas, tools, or data? No
- Are substantial conclusions reached? Yes
- Are the scientific methods and assumptions valid and clearly outlined? No
- Are the results sufficient to support the interpretations and conclusions? Yes
- Is the description of experiments and calculations sufficiently complete and precise to allow their reproduction by fellow scientists (traceability of results)? To some extent
- Do the authors give proper credit to related work and clearly indicate their own new/original contribution? Yes
- Does the title clearly reflect the contents of the paper? Yes
- Does the abstract provide a concise and complete summary? Yes
- Is the overall presentation well structured and clear? No
- Is the language fluent and precise? No
- Are mathematical formulae, symbols, abbreviations, and units correctly defined and used? Almost
- Should any parts of the paper (text, formulae, figures, tables) be clarified, reduced, combined, or eliminated? Yes
- Are the number and quality of references appropriate? Yes
- Is the amount and quality of supplementary material appropriate? Yes
Specific Reviewer Comments –
- The writing style is confusing and not succinct. At some places important information/explanation seems to be missing. At some times it even sounds more casual than expected for a scientific article. Examples – section 2.1.3, paragraph 1 of section 3.6. Some of the results need to be presented in a better way as well. For example, I found section 3.6 quite difficult to understand in the first reading probably because the results and discussion have not been presented clearly. It is hard to point at more examples, and ways in which improvements can be made, but there is nevertheless a general need for improvement on the writing style. A revision would help make the results more accessible to readers.
- A more detailed discussion of the cloud resolving model is needed. A 4 km spatial resolution falls in the grey area where clouds cannot be simulated explicitly and cannot be parameterized properly because the assumptions of regular cloud parameterizations, based on spatial statistics applicable to larger scales break. So the authors should explain in more detail why they have chosen to work in this intermediate spatial resolution.
- Some evaluation of model results with observations is needed. While there might not be in-situ observations available from this region, there are satellite data products of cloud and precipitation (on larger spatial scales) available which can be used to at least provided a qualitative comparison with observations. The authors have also mentioned some previous observational studies and that their results relating with precipitation changes agree with these observations. For example on Line 323 authors have referred to Taylor et al. 2021. It would be better if some of these observations are included in this manuscript to (1) validate the baseline simulations and (2) provide comparison to simulated changes.
- Why have the authors not analysed the changes over regions like Guinea, Sierra Leone, Cameroon and central African Republic where the change in tree cover is the maximum? Although the authors have presented some valid reasons for their choice of analysing the two regions, it is still unclear why they chose these regions over some other very interesting regions in their simulated domain where interesting and larger changes to the hydro-climate have occurred. While there might an obvious reason for this, it is not clear in the writing. Authors should point that out more clearly.
- Line 205 – it would be helpful to mention here itself which two deforested regions have been analysed.
- Line 285 – there should be more discussion around what the delta theta proxy means. The conclusions from this analysis are also not stated clearly. The usage of this proxy in the following sections is also not effective because the meaning of this proxy and implications of its change are not clearly defined.
- Figure 1 and associated text under section 2.2 can go to Supplementary Infromation.
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RC2: 'Comment on wcd-2022-49', Anonymous Referee #2, 20 Sep 2022
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The study applies a 5-day ensemble forecast over West-Africa using a convection permitting regional climate model in order to understand the effects of historical deforestation within the region. Due to the high spatial and temporal resolution of the climate model data the authors are able to dissect the processes controlling the weather response within West-Africa as a whole and within 2 subregions highlighting how different local conditions can alter the response to deforestation. Overall this is a unique approach within the research on effects of land cover change on climate and it opens a lot of interesting questions worth exploring in future studies. The study is well structured and written clearly and in a comprehensive way as it addresses several variables in order to understand the changes physically. I would recommend the journal to accept this paper after addressing some minor specific questions added here below.
- Research on deforestation in global idealised simulations studies (a.o. Winckler et al., 2017) have tried to separate local (mostly roughness and albedo effects) from remote effects (large scale circulation), as you highlight in line 109 this study mainly focusses on the local effects and the short period of simulation time does not allow (large-scale) circulation aspects to occur and to influence the results. This might be a strong assumption as these large scale effects strongly influence several variables focussed on within the study (e.g. rainfall due to shifts in ITCZ, Devaraju et al.,2015). How important do you think this bias would be for the interpretation of the results? Do you think that the lack of these large scale circulation changes could help explain the differences between your results and the 3 studies compared to in section 4? I feel these aspects although flagged at some points are not fully addressed yet.
- I’m intrigued by the approach of a 5 days forecasting ensemble, as far as I am aware this has not been used to asses effects of land cover changes which adds a strong novelty to the study. However I wonder how generalisable these results are? You highlight the importance of choice of season and month in several locations within the manuscript, but wouldn’t some effects have a delay of occurring (e.g. initial wettening due to deforestation but after while drying?). This is a known caveat of the method I presume, but I wonder if this could be overcome by for example running this ensemble longer (eg 30 days)? For clarity I do not request additional simulation, but I think some discussion on these methodological aspects would be interesting to include.
- Due to the unique setup of the study it opens a lot of questions for future research of which you highlight some in section 5. Could you go a bit further and try to give some recommendations for example : How can this study inform future work by earth system models and regional climate models? What would be priorities for development or research based on this work, should models invest in more convection permitting and/ or deeper evaluation and developments of surface scheme? I believe these kind of insights can help guide the model development community greatly. Therefore I would suggest to include something in line of a limitations and outlook section within the manuscript in order to have a general discussion on the implications and weaknesses of this study now some of these aspects are mentioned in the conclusions but I feel you could go further in this discussion.
Technical corrections:
line 49-52: There is a useful review by Perugini etal (2017) who also have a similar conclusion
line126-127: The LUCID studies by Pitman et al. 2009 indeed show this but more recently also Boysen et al. 2020 showed in the LUMIP deforest_glob runs that there still remains large issues and uncertainty within ESMs.
Line 260: More recently Duveiller et al 2020 (https://doi.org/10.1016/j.landusepol.2019.104382) have a more comprehensive dataset of near surface temperature using similar approaches as Alkama and Cescatti, 2016
Figure 9 and 11: I found it a bit unclear what all the lines were indicating on the plots (I initially overlooked the different colours of the labels) perhaps this is my own fault but to help people like me I would suggest to add the colour of the lines between brackets after the variable is introduced in the subscript (e.g. (a) number of spontaneous initiations (green) and number of storms present (blue)). Additionally I find the colours of the last panels (c in Figure 9 and c and f in Figure 11) very similar between nstorms and intensity, I would suggest to change it to a more different colour.
Julia Crook et al.
Julia Crook et al.
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