the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Mar 2024
Global terrestrial moisture recycling in Shared Socioeconomic Pathways
Abstract. Many areas across the globe rely on upwind land areas for their precipitation supply through terrestrial precipitation recycling. Global warming and land-use changes may affect the future patterns of terrestrial precipitation recycling, but where and to which extent remains unclear. To study how the global patterns of precipitation recycling may change until the end of the 21st century we present a new forward-tracking version of the three-dimensional atmospheric moisture tracking model UTrack that is forced by output of the Norwegian Earth System model (NorESM2). We simulate global precipitation recycling in four Shared Socioeconomic Pathways (SSPs), which are internally consistent combinations of climate- and land-use scenarios used in the sixth phase of the Coupled Model Intercomparison Project. The scenarios range from mild to severe: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. We compare results for the middle of the century (2050–2059) and end of the century (2090–2099) with a 2015–2024 baseline. We similarly also calculate basin precipitation recycling for the 26 major river basins of the world. We find that the global terrestrial moisture recycling ratio decreases with the severity of the SSPs and estimate a decrease in this ratio of 2.1 % with every degree of global warming. However, we find differences among regions and river basins in trends in precipitation recycling and whether projected drying or wetting is mainly contributed by land or ocean. Our results give critical insight into the relative contributions of global warming and land use changes on global precipitation changes over the course of this century. In addition, our model paves the way for more detailed regional studies of future changes in terrestrial moisture recycling.
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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.
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RC1: 'Comment on egusphere-2024-790', Anonymous Referee #1, 05 Apr 2024
Summary
The authors use future projections from the NorESM2 climate model to drive the atmospheric moisture tracking model UTrack. The future projections represent four possible socioeconomic scenarios of varying severity, with the aim of estimating global responses in terrestrial precipitation recycling to different emissions pathways. The authors present their new version of the UTrack model in a Github repository. The paper is well written and a valuable addition to the literature. The introduction and discussion sections were especially good, however, the description of the results could be improved to help the reader make links between the text and the figures more readily, and to ensure your findings come across in the clearest possible way.
Line by line comments
Line 74 – add some examples of studies that use moisture tracking models to assess precipitation recycling
Line 97 – can you add further explanation for why 100 parcels are released at random locations above the starting area? For evaporation, shouldn’t parcels come from the surface, and precipitation higher up in the atmosphere? You say further up in the paragraph that the number of parcels that is tracked from a certain area and time step depends on the evaporation…or precipitation… from the respective location or area at the respective time step. Is the number of parcels 100 or does it vary? Would be good to make this paragraph a bit clearer to fully understand what’s happening in the lagrangian model. Could consider adding in a schematic figure?
You add further information under the ‘Simulation settings’ section. Perhaps these sections could be combined / adjacent for clarity?
Line119 – did you calculate vertically integrated moisture fluxes?
Line 158 – can you add more information on this basin-level analysis. Do you calculate trajectories for multiple locations within each basin? How does this differ from the rest of your analysis. E.g. couldn’t you just subset your existing trajectories you calculated for the whole globe? Add a statement on what additional insight this basin-level analysis provides.
Line 159 – 100 parcels vs 1000 parcels mentioned in line 152. Is that correct? If so, why the difference?
Line 171 – add definition of evaporation recycling and how this differs from P recycling
Line 213 – here you discuss changes in precipitation, but the figure you point to (Fig. 3a) shows changes in precipitation recycling, which isn’t the same thing. Maybe double check.
Having read further on in the paper – you show the annual P changes in Figure A1. Would be good to direct to this in relevant parts of the text. In fact, it might be better to move A1 to the main paper given its importance to the rest of your results – it will allow the reader to identify drying and wetting areas more easily. Make sure all supplementary figures are referenced somewhere so they don’t get overlooked.
“In 45.4% of the grid cells that are projected to become drier (representing 1.1% of all land grid cells)” are these figures correct? Does this mean that in 1.1 % of land grid cells the drying is caused by a reduction in P recycling? This value seems quite low looking at the shaded areas in Fig 3, but perhaps that’s because you’re showing significant and no-significant changes, but only talking about the significant changes. Maybe consider rewording this paragraph and subsequent paragraphs or at least clarify in the text that only a very small land fraction shows statistically significant changes.
Line 214 “…this drying is dominated by a decrease in the precipitation that originates from land.” Point to a figure / evidence for this.
Lines 211-245 I wonder if the information presented in these paragraphs would be better summarised in a table? The text gets a bit repetitive here and it might be more useful to focus the reader’s attention on your most important findings, e.g. perhaps the worst case scenario of SSP5-8.5 could be highlighted in the text? Just an idea.
Line 248 – Are you considering ‘all global grid cells’ or just land? As all your figures show land only, perhaps it makes sense to only refer to results over land throughout your description of your results. Check here and elsewhere.
Line 255 – please indicate a figure after the first sentence so the reader immediately knows where to look for evidence for this statement.
Line 264 – again please be clearer with your figure indications. How is it possible for recycling to exceed actual precipitation? You indicate the regions where this occurs but would be useful to add a line to explain if this is simply an artefact of the model or if this is a physical result (and if so how that might arise).
Line 270 – consider removing the word ‘one’ or even the whole phrase in brackets – not sure if it’s needed here and sounds a bit confusing
Line 272 – ‘In SSP2-4.5, global forest cover remains 25%’ insert ‘at’ after ‘remains’
Line 279 – ‘a larger proportion of the 26 major…’
Line 280 – unclear what the distinction is between basin precipitation recycling ratio and terrestrial precipitation recycling ratio. In line 165 you state: “We calculate the global terrestrial precipitation recycling ratio as the percentage of precipitation on land that evaporated from land.” Can you also clarify in caption for Table 2?
Line 289 – “Both changes in basin recycling ratio increases in SSP1-2.6 are an increase.” Not sure what you mean here. Possibly: “The two basins that showed statistically significant changes in basin recycling ratio by the end of the century in SSP1-2.6 both showed increases from the baseline”?
Line 289 – From Table 2 it looks like the change is from 19 % to 20% for Amur? Similarly it looks like Ob changed from 11 % to 13 % ( not 11 to 12 as written in the text). Possibly double check these and other values referenced in the text in case the numbers have updated since an earlier draft of the paper.
Table 2 – It might be nice to somehow indicate (possibly through additional columns, or by colouring the numbers red and blue) which basins were showing statistically significant increases and which decreases in P recycling. At present the reader can quickly pick out the values with asterisks next to them but not the direction of changes.
Line 302 – check the wording here as it seems a bit contradictory. You say that Chad has an “increase in basin recycling ratio between the middle and end of the century” but in the next sentence you say “the Chad basin does not have a significant decrease by the end of the century”. This whole paragraph might be a bit clearer if you first focus on the changes by the middle of the century, and then subsequently describe the changes that occur from mid to late century. I appreciate there is a lot of detail to try to capture, but at the moment it gets a bit muddled and the message gets lost.
Line 319 – I’m not familiar with the expression “the one percentage point level” which comes up here and elsewhere. Is the point you want to make that in some instances there are changes in P recycling where there are no changes in forest cover or cropland cover? Possibly rewording could improve clarity.
Line 321 – where land cover changes are small and P recycling changes are high, is this related to changes in e.g. plant stomatal conductance in response to rising atmospheric CO2? Or other aspects of climate? I know this is only the results section, not results and discussion, but might be nice to just add in a line or so to briefly explain this finding.
Lines 317-330 Maybe restructure this paragraph or split into multiple paragraphs. For example, the first line of the paragraph really relates to what is described in the second half of the paragraph – i.e. regions where changes in recycling are related to changes in land cover
Line 345 – missing word ‘relative’ for panel a description. Could start the paragraph with the current second sentence (rephrased!) and focus on areas with no LCC that see changes in recycling, then have a separate paragraph that looks at areas that do see large differences in LCC.
Lines 332-336 Maybe reword. I think the point you are trying to get across is: “In the Amazon and Congo river basins, end-of-century recycling ratios are the same in SSPs with different land cover distributions. For example, in the Amazon under SSP 3-7.0 and SSP5-8.5 the estimated basin recycling ratio is 24% and the terrestrial recycling ratio is 40%, despite forest cover of 75% in SSP3-7.0 and 82% in SSP5-8.5. Similarly in the Congo…. etc. etc.”
Line 349 – specify ‘absolute’ differences in ∆TPR
Line 355 – missing word ‘ratio’ after recycling. Not sure if this is intended given the change in units from Figure 2 to Figure 3?
Line 420 – can you speculate on why the Danube might show opposite behaviour?
Line 423 – consider citing papers by Christopher Skinner and Rob Chadwick here. E.g. DOI: https://doi.org/10.1175/JCLI-D-16-0603.1
Line 444 – underestimated…. In the current generation of climate models? Or specifically in this study?
Line 461 “We call drying land-dominated if it coincides with a significant increase in terrestrial precipitation recycling ratio and we call it ocean-dominated if it coincides with a significant decrease in terrestrial precipitation recycling ratio.” This definition could come earlier as it would help understand the description of these results.
Line 524 – maybe repeat here that NorESM2 was the only model that provided the required variables at the time frequency required for your moisture tracking model.
Citation: https://doi.org/10.5194/egusphere-2024-790-RC1 -
AC1: 'Reply on RC1', Arie Staal, 12 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-790/egusphere-2024-790-AC1-supplement.pdf
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AC1: 'Reply on RC1', Arie Staal, 12 Jun 2024
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RC2: 'Comment on egusphere-2024-790', Anonymous Referee #2, 23 Apr 2024
This paper addresses the question how moisture recycling ratios change under different future SSP scenarios. The authors study this question by running the UTrack moisture tracking model forced with the NorESM climate model and analyse 10-years of future climate slices under different SSP scenarios. This study on moisture recycling changes towards the future is very relevant and timely, however I have some major comments on the methodology and the reporting of the results. In short, my major concerns are 1) regarding the fact that only 10-year simulations are analysed (10-years is not a climatology), 2) that the changes in the model are not well described and not validated, 3) that present climate simulations are not validated well with literature or ERA5, 4) that relevant literature is missing in the introduction, and 5) that the results section reads as a bookkeeping exercise (of which the information can be put into a table) rather than a story highlighting the main results. I have described my major concerns in more detail below, and have also included substantial and minor comments that I encountered while reading the paper.
Major comments
10-years of simulations do not present a climatology
The results of this study are based on moisture recycling ratios calculated for slices of 10years of climate data (present and future). In climate terms, this is a very short period to draw conclusions from, taking into account the internal variability of our climate. By only analysing 10 years, it could happen that your results are biased to multiple dry or wet years present in the data. While the authors address the fact that they do not study interannual variability (although presenting standard deviations around moisture recycling ratios, which is an indication of interannual variability), they do not acknowledge the short 10-year timeseries as serious constrain to base their conclusions on. Further they do not compare their 10-year land precipitation and land evaporation results with a wider range of models to validate if the 10-years is a good representation of (present) climatology.
No validation is performed for present climate and with the new model set-up
To continue on the previous comment, one way to verify if present climate from the NorESM simulations is actually representing our current present climate, one could validate the moisture recycling ratios from NorESM baseline with moisture recycling ratios from ERA5.
The authors have published simulations with the UTrack model forced with ERA5, which is the perfect reference dataset for this study, and I am surprised to see no validation is done at all. Validation is recommended in two ways: a) to validate how well NorESM performs in representing moisture recycling ratios in current climate (2015-2024) and b) to validate the described model changes. With the latter I mean that a different model set-up is described based on the constrains of available data from NorESM and the impacts of using only limited input data (daily timestep, only eight pressure levels in the atmosphere). The impact of using daily data and limited information in the vertical (and horizontal) can be perfectly validated with the ERA5 dataset. One can run the UTrack model in the standard ERA5 set-up, and run the UTrack model with the input from ERA5 based on the constrains of NorESM, This will allow to illustrate the impacts of using limited data resources, which is currently not addressed in the paper at all. The fact that there are some grid cells that show higher precipitation recycling then precipitation itself (lines 264-269), might be related to the fact that only daily data or few vertical levels are used.
In addition, daily data from NorESM is used to force the UTrack model (Line 118: has a temporal resolution of one day). I assume that for wind fields and specific humidity instantaneous data is used and I wonder at which timestep of the day this data is taken? This is not stated in the methods and influences your results. If instantaneous wind fields are taken at midnight, features like a low level jet will enhance moisture transport, compared to instantaneous wind fields taken at noon. Opposite, sea-breeze features which enhance ocean-to-land moisture transport are mostly present during the day and thus will also influence your results when only one timestep during the day is used. This issue can be addressed by running UTrack with hourly ERA5 forcing, and with daily ERA5 forcing (as suggested in the previous point).
Last, I am a bit confused why the authors use a forced climate scenario to analyse past climate. I can follow the logic to take the scenario that is following the trajectory that the world is currently on (Fricko et al., 2017) (line 165), though citing a paper from 7 years ago feels a bit odd then. Wouldn’t it be much more logic to use climate data forced with observed CO2 levels and observed SSTs?
Introduction does not include all relevant literature and hypothesis
In the introduction the authors state that (line 50): “However, where, how, and to which extent terrestrial moisture recycling will change in the future remains unclear.” Although I agree there is still research to be done on how moisture recycling is changing to the future, there is also literature available already that addresses and (partly) answers this statement, and this literature is only cited in the discussion. An introduction needs to state the relevant literature on the topic and this is currently not done. Examples of literature that addresses the changes in moisture sources or moisture recycling in a future climate (Benedict et al., 2020; Findell et al., 2019; Fernandez-Alvarez et al., 2023). Furthermore, the introduction is also the moment to state hypothesis based on current literature, for example addressing the impacts of land-use change versus climate change. Currently the introduction provides more insights on the methods, describing the SSP scenarios and different moisture tracking methods which I found more relevant for the method section, or can be reduced.
Improve results and discussion section
In the first section of the results (line 187-192) the absolute and relative changes in land precipitation and land evaporation are given from NorESM. It would be very good to put these numbers in the perspective of a multi-model mean, for example given in Table 8.1 of Chapter 8 of the IPCC 2021 report, Douville et al., (2021). This indicates if the precipitation and evaporation averages from NorESM2 fall within or outside of the range of the CMIP6 multi-model mean.
The result section reads as a bookkeeping exercise, where multiple alinea’s (four alinea’s from line 210 to line 245) have exactly the same structure but different numbers inserted for the different scenario’s. This makes the result section dry and hard to read. This information suits well for a table instead, while in the text rather the interesting findings of the table can be reported.
Further, my suggestion would be to combine the results and discussion section to allow for direct comparison with literature. Currently, the result section is very dry as it is a sum-up of numbers and scenario’s. By directly comparing moisture recycling ratios with the literature (combining results and discussion) allows for more perspective. At the moment, in the discussion the numbers from the result section are not repeated, which makes it very hard to put literature results next to the results of this study, which I think is very important to do. The same holds for the results on the major river basins, which could include more references to current literature.
On the discussion on the impact of land-use change and climate change on recycling ratio. I think this is a very interesting discussion point which is now addressed only shortly, I would dedicate a whole section on this. Are their different ways forward to test this influence? Some arguments that are provided later in the text (line 411) could potentially also be used to study impact land-use change vs climate change.
Substantial comments
Line 40-50: Besides including relevant literature that assessed moisture recycling under a warming climate it is also good to address the impact of circulation changes on moisture recycling, such as changes in location of the ITCZ, Hadley cells, storm tracks, as this will affect the moisture transport as well.
Section 2.3 Simulations settings; I already addressed the issue of daily data in the major comments, but the limitation of only having limited pressure levels as input is not discussed at all. What is the impact of this on your results?
Line 176-184: Can the significant increases and decreases be quantified? Did you use a threshold to call it a significant increase or decrease?
Section 2.4: When is the model initialized? As already mentioned I am a bit surprised that for current climate a scenario is used, while we already have the observations of current climate as the boundary conditions of the model. I could imagine this is done for consistency, but it would be nice to check how well the baseline run represent the actual conditions. Further, are these atmosphere only runs? So SST is prescribed?
Line 174: Do I understand correctly that also for the SSP3-7 and SSP1-2.6 and SSP 3-7.0 you use the same climate sensitivity as SSP5-8.5? The approach here is unclear but you would expect that the climate sensitivity is used per SSP scenario to calculate changes in moisture recycling per degree warming.
Further, we are currently already warmer than the 1976-2005 baseline that is mentioned for which the 3.26 degrees is determined for. In the results a 3.26 change in temperature is used to move from the SSP2-4.5 (baseline; 2015-2024) to the SSP5-8.5, but I assume there is already some warming in the SSP2-4.5 baseline run for 2015-2024, which is now not taken into account. Thus if I understand the taken approach well, using the 3.26 degrees warming is incorrect.
Results
Line 177: “wetting, land dominated” if a significant increase in precipitation coincides with a significant decrease in terrestrial precipitation recycling --> should this not be exactly opposite? An increase in terrestrial precipitation recycling? Line 461-462 also states that land-dominated means increase in terrestrial precipitation recycling
I would suggest to leave the min and max value of moisture recycling out of the text to make it more readable. Those min and max values could be reported in a table. By providing the std you give an idea of the interannual variability in the text.
Line 213-215; How relevant is it to give this information if it only concerns such a small percentage of land grid cells (1.1% and 1.3%)? Instead, it would be nice if some words are dedicated on where those 8.7% of land grid cells are on the globe that show a significant change in precipitation. And do you mean with precipitation absolute precipitation or precipitation recycling? In line 170 it is stated that statistical significance is tested for precipitation recycling, but from the result section it reads as if it is checked for absolute precipitation changes, which is confusing. I read in the caption of Figure 2 and 3 it is about significant differences in precipitation recycling, it would be nice to have those regions that show a significant change are hatched in figure 2 and 3.
Line 279-277: I am not sure about the purpose of this alinea. Are these findings of this study? Or are these numbers given here to indicate the impact of land-use change on moisture recycling? If so, I would discuss them in combination with the discussion section 4.1.
Minor comments / typos / small unclarities:
Define precipitation recycling in abstract
Line 20: moisture recycling ratio--> do you mean with moisture recycling precipitation recycling? Terms are used throughout it each other but it is unclear what is what
Line 108: For equations --> equations of what? Of the moisture tracking model?
Line 134: ‘There is some overestimation of global mean temperature’ --> this is very vaguely stated, can you quantify?
Line 148: ‘We used these forcing data directly without interpolation’ --> How can you have daily data and run the model on 4-hourly timesteps, without interpolation?
Line 159: In Line 153 it says 1000 parcels per mm, and here 100 parcels per mm
3.1 Global land --> can you make the headers more self-explanatory? The result section will also benefit from more section and section headings to illustrate the red-threat
Line 492: less clouds but more rain? Maybe I misunderstand
Line 499: ‘Around one-fifth of global precipitation is attributed to vegetation’ --> to me it is not clear what is meant with this sentence
Conclusions
Line 538-539: ‘widespread drying accompanied by disproportional reductions of moisture supply over land’ à this sentence counteracts the argument of global greening and increased evaporation (stated in the discussion)
Here the word disproportional is often used, what is meant with that?
Line 541-542: can you back-up this last sentence by findings from the study?
Figures
Figure 2 to 6: These figures can be improved and made more readable by only displaying one legend (colorbar) per figure, and not for all subfigures. In this way the figures can be enlarged.
Citation: https://doi.org/10.5194/egusphere-2024-790-RC2 -
AC2: 'Reply on RC2', Arie Staal, 12 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-790/egusphere-2024-790-AC2-supplement.pdf
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AC2: 'Reply on RC2', Arie Staal, 12 Jun 2024
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-790', Anonymous Referee #1, 05 Apr 2024
Summary
The authors use future projections from the NorESM2 climate model to drive the atmospheric moisture tracking model UTrack. The future projections represent four possible socioeconomic scenarios of varying severity, with the aim of estimating global responses in terrestrial precipitation recycling to different emissions pathways. The authors present their new version of the UTrack model in a Github repository. The paper is well written and a valuable addition to the literature. The introduction and discussion sections were especially good, however, the description of the results could be improved to help the reader make links between the text and the figures more readily, and to ensure your findings come across in the clearest possible way.
Line by line comments
Line 74 – add some examples of studies that use moisture tracking models to assess precipitation recycling
Line 97 – can you add further explanation for why 100 parcels are released at random locations above the starting area? For evaporation, shouldn’t parcels come from the surface, and precipitation higher up in the atmosphere? You say further up in the paragraph that the number of parcels that is tracked from a certain area and time step depends on the evaporation…or precipitation… from the respective location or area at the respective time step. Is the number of parcels 100 or does it vary? Would be good to make this paragraph a bit clearer to fully understand what’s happening in the lagrangian model. Could consider adding in a schematic figure?
You add further information under the ‘Simulation settings’ section. Perhaps these sections could be combined / adjacent for clarity?
Line119 – did you calculate vertically integrated moisture fluxes?
Line 158 – can you add more information on this basin-level analysis. Do you calculate trajectories for multiple locations within each basin? How does this differ from the rest of your analysis. E.g. couldn’t you just subset your existing trajectories you calculated for the whole globe? Add a statement on what additional insight this basin-level analysis provides.
Line 159 – 100 parcels vs 1000 parcels mentioned in line 152. Is that correct? If so, why the difference?
Line 171 – add definition of evaporation recycling and how this differs from P recycling
Line 213 – here you discuss changes in precipitation, but the figure you point to (Fig. 3a) shows changes in precipitation recycling, which isn’t the same thing. Maybe double check.
Having read further on in the paper – you show the annual P changes in Figure A1. Would be good to direct to this in relevant parts of the text. In fact, it might be better to move A1 to the main paper given its importance to the rest of your results – it will allow the reader to identify drying and wetting areas more easily. Make sure all supplementary figures are referenced somewhere so they don’t get overlooked.
“In 45.4% of the grid cells that are projected to become drier (representing 1.1% of all land grid cells)” are these figures correct? Does this mean that in 1.1 % of land grid cells the drying is caused by a reduction in P recycling? This value seems quite low looking at the shaded areas in Fig 3, but perhaps that’s because you’re showing significant and no-significant changes, but only talking about the significant changes. Maybe consider rewording this paragraph and subsequent paragraphs or at least clarify in the text that only a very small land fraction shows statistically significant changes.
Line 214 “…this drying is dominated by a decrease in the precipitation that originates from land.” Point to a figure / evidence for this.
Lines 211-245 I wonder if the information presented in these paragraphs would be better summarised in a table? The text gets a bit repetitive here and it might be more useful to focus the reader’s attention on your most important findings, e.g. perhaps the worst case scenario of SSP5-8.5 could be highlighted in the text? Just an idea.
Line 248 – Are you considering ‘all global grid cells’ or just land? As all your figures show land only, perhaps it makes sense to only refer to results over land throughout your description of your results. Check here and elsewhere.
Line 255 – please indicate a figure after the first sentence so the reader immediately knows where to look for evidence for this statement.
Line 264 – again please be clearer with your figure indications. How is it possible for recycling to exceed actual precipitation? You indicate the regions where this occurs but would be useful to add a line to explain if this is simply an artefact of the model or if this is a physical result (and if so how that might arise).
Line 270 – consider removing the word ‘one’ or even the whole phrase in brackets – not sure if it’s needed here and sounds a bit confusing
Line 272 – ‘In SSP2-4.5, global forest cover remains 25%’ insert ‘at’ after ‘remains’
Line 279 – ‘a larger proportion of the 26 major…’
Line 280 – unclear what the distinction is between basin precipitation recycling ratio and terrestrial precipitation recycling ratio. In line 165 you state: “We calculate the global terrestrial precipitation recycling ratio as the percentage of precipitation on land that evaporated from land.” Can you also clarify in caption for Table 2?
Line 289 – “Both changes in basin recycling ratio increases in SSP1-2.6 are an increase.” Not sure what you mean here. Possibly: “The two basins that showed statistically significant changes in basin recycling ratio by the end of the century in SSP1-2.6 both showed increases from the baseline”?
Line 289 – From Table 2 it looks like the change is from 19 % to 20% for Amur? Similarly it looks like Ob changed from 11 % to 13 % ( not 11 to 12 as written in the text). Possibly double check these and other values referenced in the text in case the numbers have updated since an earlier draft of the paper.
Table 2 – It might be nice to somehow indicate (possibly through additional columns, or by colouring the numbers red and blue) which basins were showing statistically significant increases and which decreases in P recycling. At present the reader can quickly pick out the values with asterisks next to them but not the direction of changes.
Line 302 – check the wording here as it seems a bit contradictory. You say that Chad has an “increase in basin recycling ratio between the middle and end of the century” but in the next sentence you say “the Chad basin does not have a significant decrease by the end of the century”. This whole paragraph might be a bit clearer if you first focus on the changes by the middle of the century, and then subsequently describe the changes that occur from mid to late century. I appreciate there is a lot of detail to try to capture, but at the moment it gets a bit muddled and the message gets lost.
Line 319 – I’m not familiar with the expression “the one percentage point level” which comes up here and elsewhere. Is the point you want to make that in some instances there are changes in P recycling where there are no changes in forest cover or cropland cover? Possibly rewording could improve clarity.
Line 321 – where land cover changes are small and P recycling changes are high, is this related to changes in e.g. plant stomatal conductance in response to rising atmospheric CO2? Or other aspects of climate? I know this is only the results section, not results and discussion, but might be nice to just add in a line or so to briefly explain this finding.
Lines 317-330 Maybe restructure this paragraph or split into multiple paragraphs. For example, the first line of the paragraph really relates to what is described in the second half of the paragraph – i.e. regions where changes in recycling are related to changes in land cover
Line 345 – missing word ‘relative’ for panel a description. Could start the paragraph with the current second sentence (rephrased!) and focus on areas with no LCC that see changes in recycling, then have a separate paragraph that looks at areas that do see large differences in LCC.
Lines 332-336 Maybe reword. I think the point you are trying to get across is: “In the Amazon and Congo river basins, end-of-century recycling ratios are the same in SSPs with different land cover distributions. For example, in the Amazon under SSP 3-7.0 and SSP5-8.5 the estimated basin recycling ratio is 24% and the terrestrial recycling ratio is 40%, despite forest cover of 75% in SSP3-7.0 and 82% in SSP5-8.5. Similarly in the Congo…. etc. etc.”
Line 349 – specify ‘absolute’ differences in ∆TPR
Line 355 – missing word ‘ratio’ after recycling. Not sure if this is intended given the change in units from Figure 2 to Figure 3?
Line 420 – can you speculate on why the Danube might show opposite behaviour?
Line 423 – consider citing papers by Christopher Skinner and Rob Chadwick here. E.g. DOI: https://doi.org/10.1175/JCLI-D-16-0603.1
Line 444 – underestimated…. In the current generation of climate models? Or specifically in this study?
Line 461 “We call drying land-dominated if it coincides with a significant increase in terrestrial precipitation recycling ratio and we call it ocean-dominated if it coincides with a significant decrease in terrestrial precipitation recycling ratio.” This definition could come earlier as it would help understand the description of these results.
Line 524 – maybe repeat here that NorESM2 was the only model that provided the required variables at the time frequency required for your moisture tracking model.
Citation: https://doi.org/10.5194/egusphere-2024-790-RC1 -
AC1: 'Reply on RC1', Arie Staal, 12 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-790/egusphere-2024-790-AC1-supplement.pdf
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AC1: 'Reply on RC1', Arie Staal, 12 Jun 2024
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RC2: 'Comment on egusphere-2024-790', Anonymous Referee #2, 23 Apr 2024
This paper addresses the question how moisture recycling ratios change under different future SSP scenarios. The authors study this question by running the UTrack moisture tracking model forced with the NorESM climate model and analyse 10-years of future climate slices under different SSP scenarios. This study on moisture recycling changes towards the future is very relevant and timely, however I have some major comments on the methodology and the reporting of the results. In short, my major concerns are 1) regarding the fact that only 10-year simulations are analysed (10-years is not a climatology), 2) that the changes in the model are not well described and not validated, 3) that present climate simulations are not validated well with literature or ERA5, 4) that relevant literature is missing in the introduction, and 5) that the results section reads as a bookkeeping exercise (of which the information can be put into a table) rather than a story highlighting the main results. I have described my major concerns in more detail below, and have also included substantial and minor comments that I encountered while reading the paper.
Major comments
10-years of simulations do not present a climatology
The results of this study are based on moisture recycling ratios calculated for slices of 10years of climate data (present and future). In climate terms, this is a very short period to draw conclusions from, taking into account the internal variability of our climate. By only analysing 10 years, it could happen that your results are biased to multiple dry or wet years present in the data. While the authors address the fact that they do not study interannual variability (although presenting standard deviations around moisture recycling ratios, which is an indication of interannual variability), they do not acknowledge the short 10-year timeseries as serious constrain to base their conclusions on. Further they do not compare their 10-year land precipitation and land evaporation results with a wider range of models to validate if the 10-years is a good representation of (present) climatology.
No validation is performed for present climate and with the new model set-up
To continue on the previous comment, one way to verify if present climate from the NorESM simulations is actually representing our current present climate, one could validate the moisture recycling ratios from NorESM baseline with moisture recycling ratios from ERA5.
The authors have published simulations with the UTrack model forced with ERA5, which is the perfect reference dataset for this study, and I am surprised to see no validation is done at all. Validation is recommended in two ways: a) to validate how well NorESM performs in representing moisture recycling ratios in current climate (2015-2024) and b) to validate the described model changes. With the latter I mean that a different model set-up is described based on the constrains of available data from NorESM and the impacts of using only limited input data (daily timestep, only eight pressure levels in the atmosphere). The impact of using daily data and limited information in the vertical (and horizontal) can be perfectly validated with the ERA5 dataset. One can run the UTrack model in the standard ERA5 set-up, and run the UTrack model with the input from ERA5 based on the constrains of NorESM, This will allow to illustrate the impacts of using limited data resources, which is currently not addressed in the paper at all. The fact that there are some grid cells that show higher precipitation recycling then precipitation itself (lines 264-269), might be related to the fact that only daily data or few vertical levels are used.
In addition, daily data from NorESM is used to force the UTrack model (Line 118: has a temporal resolution of one day). I assume that for wind fields and specific humidity instantaneous data is used and I wonder at which timestep of the day this data is taken? This is not stated in the methods and influences your results. If instantaneous wind fields are taken at midnight, features like a low level jet will enhance moisture transport, compared to instantaneous wind fields taken at noon. Opposite, sea-breeze features which enhance ocean-to-land moisture transport are mostly present during the day and thus will also influence your results when only one timestep during the day is used. This issue can be addressed by running UTrack with hourly ERA5 forcing, and with daily ERA5 forcing (as suggested in the previous point).
Last, I am a bit confused why the authors use a forced climate scenario to analyse past climate. I can follow the logic to take the scenario that is following the trajectory that the world is currently on (Fricko et al., 2017) (line 165), though citing a paper from 7 years ago feels a bit odd then. Wouldn’t it be much more logic to use climate data forced with observed CO2 levels and observed SSTs?
Introduction does not include all relevant literature and hypothesis
In the introduction the authors state that (line 50): “However, where, how, and to which extent terrestrial moisture recycling will change in the future remains unclear.” Although I agree there is still research to be done on how moisture recycling is changing to the future, there is also literature available already that addresses and (partly) answers this statement, and this literature is only cited in the discussion. An introduction needs to state the relevant literature on the topic and this is currently not done. Examples of literature that addresses the changes in moisture sources or moisture recycling in a future climate (Benedict et al., 2020; Findell et al., 2019; Fernandez-Alvarez et al., 2023). Furthermore, the introduction is also the moment to state hypothesis based on current literature, for example addressing the impacts of land-use change versus climate change. Currently the introduction provides more insights on the methods, describing the SSP scenarios and different moisture tracking methods which I found more relevant for the method section, or can be reduced.
Improve results and discussion section
In the first section of the results (line 187-192) the absolute and relative changes in land precipitation and land evaporation are given from NorESM. It would be very good to put these numbers in the perspective of a multi-model mean, for example given in Table 8.1 of Chapter 8 of the IPCC 2021 report, Douville et al., (2021). This indicates if the precipitation and evaporation averages from NorESM2 fall within or outside of the range of the CMIP6 multi-model mean.
The result section reads as a bookkeeping exercise, where multiple alinea’s (four alinea’s from line 210 to line 245) have exactly the same structure but different numbers inserted for the different scenario’s. This makes the result section dry and hard to read. This information suits well for a table instead, while in the text rather the interesting findings of the table can be reported.
Further, my suggestion would be to combine the results and discussion section to allow for direct comparison with literature. Currently, the result section is very dry as it is a sum-up of numbers and scenario’s. By directly comparing moisture recycling ratios with the literature (combining results and discussion) allows for more perspective. At the moment, in the discussion the numbers from the result section are not repeated, which makes it very hard to put literature results next to the results of this study, which I think is very important to do. The same holds for the results on the major river basins, which could include more references to current literature.
On the discussion on the impact of land-use change and climate change on recycling ratio. I think this is a very interesting discussion point which is now addressed only shortly, I would dedicate a whole section on this. Are their different ways forward to test this influence? Some arguments that are provided later in the text (line 411) could potentially also be used to study impact land-use change vs climate change.
Substantial comments
Line 40-50: Besides including relevant literature that assessed moisture recycling under a warming climate it is also good to address the impact of circulation changes on moisture recycling, such as changes in location of the ITCZ, Hadley cells, storm tracks, as this will affect the moisture transport as well.
Section 2.3 Simulations settings; I already addressed the issue of daily data in the major comments, but the limitation of only having limited pressure levels as input is not discussed at all. What is the impact of this on your results?
Line 176-184: Can the significant increases and decreases be quantified? Did you use a threshold to call it a significant increase or decrease?
Section 2.4: When is the model initialized? As already mentioned I am a bit surprised that for current climate a scenario is used, while we already have the observations of current climate as the boundary conditions of the model. I could imagine this is done for consistency, but it would be nice to check how well the baseline run represent the actual conditions. Further, are these atmosphere only runs? So SST is prescribed?
Line 174: Do I understand correctly that also for the SSP3-7 and SSP1-2.6 and SSP 3-7.0 you use the same climate sensitivity as SSP5-8.5? The approach here is unclear but you would expect that the climate sensitivity is used per SSP scenario to calculate changes in moisture recycling per degree warming.
Further, we are currently already warmer than the 1976-2005 baseline that is mentioned for which the 3.26 degrees is determined for. In the results a 3.26 change in temperature is used to move from the SSP2-4.5 (baseline; 2015-2024) to the SSP5-8.5, but I assume there is already some warming in the SSP2-4.5 baseline run for 2015-2024, which is now not taken into account. Thus if I understand the taken approach well, using the 3.26 degrees warming is incorrect.
Results
Line 177: “wetting, land dominated” if a significant increase in precipitation coincides with a significant decrease in terrestrial precipitation recycling --> should this not be exactly opposite? An increase in terrestrial precipitation recycling? Line 461-462 also states that land-dominated means increase in terrestrial precipitation recycling
I would suggest to leave the min and max value of moisture recycling out of the text to make it more readable. Those min and max values could be reported in a table. By providing the std you give an idea of the interannual variability in the text.
Line 213-215; How relevant is it to give this information if it only concerns such a small percentage of land grid cells (1.1% and 1.3%)? Instead, it would be nice if some words are dedicated on where those 8.7% of land grid cells are on the globe that show a significant change in precipitation. And do you mean with precipitation absolute precipitation or precipitation recycling? In line 170 it is stated that statistical significance is tested for precipitation recycling, but from the result section it reads as if it is checked for absolute precipitation changes, which is confusing. I read in the caption of Figure 2 and 3 it is about significant differences in precipitation recycling, it would be nice to have those regions that show a significant change are hatched in figure 2 and 3.
Line 279-277: I am not sure about the purpose of this alinea. Are these findings of this study? Or are these numbers given here to indicate the impact of land-use change on moisture recycling? If so, I would discuss them in combination with the discussion section 4.1.
Minor comments / typos / small unclarities:
Define precipitation recycling in abstract
Line 20: moisture recycling ratio--> do you mean with moisture recycling precipitation recycling? Terms are used throughout it each other but it is unclear what is what
Line 108: For equations --> equations of what? Of the moisture tracking model?
Line 134: ‘There is some overestimation of global mean temperature’ --> this is very vaguely stated, can you quantify?
Line 148: ‘We used these forcing data directly without interpolation’ --> How can you have daily data and run the model on 4-hourly timesteps, without interpolation?
Line 159: In Line 153 it says 1000 parcels per mm, and here 100 parcels per mm
3.1 Global land --> can you make the headers more self-explanatory? The result section will also benefit from more section and section headings to illustrate the red-threat
Line 492: less clouds but more rain? Maybe I misunderstand
Line 499: ‘Around one-fifth of global precipitation is attributed to vegetation’ --> to me it is not clear what is meant with this sentence
Conclusions
Line 538-539: ‘widespread drying accompanied by disproportional reductions of moisture supply over land’ à this sentence counteracts the argument of global greening and increased evaporation (stated in the discussion)
Here the word disproportional is often used, what is meant with that?
Line 541-542: can you back-up this last sentence by findings from the study?
Figures
Figure 2 to 6: These figures can be improved and made more readable by only displaying one legend (colorbar) per figure, and not for all subfigures. In this way the figures can be enlarged.
Citation: https://doi.org/10.5194/egusphere-2024-790-RC2 -
AC2: 'Reply on RC2', Arie Staal, 12 Jun 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-790/egusphere-2024-790-AC2-supplement.pdf
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AC2: 'Reply on RC2', Arie Staal, 12 Jun 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
Global terrestrial moisture recycling in Shared Socioeconomic Pathways Arie Staal, Pim Meijer, Maganizo Kruger Nyasulu, Obbe Tuinenburg, and Stefan Dekker https://zenodo.org/records/10650579
Model code and software
UTrack-NorESM2_global_land Arie Staal, Pim Meijer, Maganizo Kruger Nyasulu, Obbe Tuinenburg, and Stefan Dekker https://github.com/ArieStaal/UTrack-NorESM2_global_land
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Pim Meijer
Maganizo Kruger Nyasulu
Obbe A. Tuinenburg
Stefan C. Dekker
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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