MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change

Yokohata, Tokuta; Kinoshita, Tsuguki; Sakurai, Gen; Pokhrel, Yadu; Ito, Akihiko; Okada, Masashi; Satoh, Yusuke; Kato, Etsushi; Nitta, Tomoko; Fujimori, Shinichiro; Felfelani, Farshid; Masaki, Yoshimitsu; Iizumi, Toshichika; Nishimori, Motoki; Hanasaki, Naota; Takahashi, Kiyoshi; Yamagata, Yoshiki; Emori, Seita

doi:https://doi.org/10.5194/gmd-13-4713-2020

Articles | Volume 13, issue 10

https://doi.org/10.5194/gmd-13-4713-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-13-4713-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 10

Model description paper

|

02 Oct 2020

Model description paper |

| 02 Oct 2020

MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change

Tokuta Yokohata, Tsuguki Kinoshita, Gen Sakurai, Yadu Pokhrel, Akihiko Ito, Masashi Okada, Yusuke Satoh, Etsushi Kato, Tomoko Nitta, Shinichiro Fujimori, Farshid Felfelani, Yoshimitsu Masaki, Toshichika Iizumi, Motoki Nishimori, Naota Hanasaki, Kiyoshi Takahashi, Yoshiki Yamagata, and Seita Emori

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Final revised paper (published on 02 Oct 2020)
Preprint (discussion started on 29 Oct 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Referee comment', Anonymous Referee #1, 03 Dec 2019
- AC1: 'Interactive comment on “MIROC-INTEG1: A global bio-geochemical land surface model with human water management, crop growth, and land-use change” by Tokuta Yokohata et al.', Tokuta Yokohata, 31 Mar 2020
RC2: 'review', Anonymous Referee #2, 18 Dec 2019
- AC2: 'Response to Reviewer #2', Tokuta Yokohata, 31 Mar 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Tokuta Yokohata on behalf of the Authors (31 Mar 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (06 Apr 2020) by Olivier Marti

RR by Anonymous Referee #1 (10 Apr 2020)

RR by Anonymous Referee #2 (28 Apr 2020)

Suggestions for revision or reasons for rejection

Review of gmd-2019-184:
MIROC-INTEG_LAND version1: A global bio-geochemcial land surface model with human water management, crop growth, and land-use change

Overall response

This is a revision of a previously reviewed manuscript. The authors have done a good job responding to the previous review, but some further clarifications and discussions need to be made, and some additional strengthening of the results would be helpful.

1) The novelty of this work is still understated. It is shown in figure 16b, but is not explained or highlighted as such. Similar plots of irrigation demand across these same sims should show further importance of incorporating climate/co2 into the land resource allocation, which is a primary new feature of miroc-integ-land that has very limited representation in global modeling.

2) please see comments below regarding further clarification and discussion.

Specific comments and suggestions:

Abstract

page 1, line 31:
I think this should also be labelled as ‘MIROC-INTEG-LAND’ because this is what you are running here, with offline climate forcing.

page 2 line 2
You should expand on this statement. this is the real novelty of this work. The land allocation (and likely irrigation demand - do you have these outputs for figure 16?) is very different when the climate/co2 effects are included. this is what makes mirocl-integ-land different from the current IAM scenario formulation.

Introduction

Overall feature of MIROC

Model structure

It would be more clear if figure 1 included the names of the sub-models discussed here on pages 4 and 5. The names can be in the figure or in the caption.

Sub models

page 7, lines 15-27
What exactly does HiGWMAT contribute to the crop growth model and the rest of the biogeochemical and biosphysical system?
Here you mention cropping period and growth, but growth is simulated separately by PRYSBI2. And in the next section you mention only water stress from HiGWMAT, and not cropping period.
So, what does PRYSBI2 use? And are the biophysical fluxes in the land model updated after HiGWMAT determines water management/use?

page 8, lines 14-15
Does PRYSBI2 use only soil moisture from HiGWMAT, or does it use cropping period also?
Later you state that it is just soil moisture and temperature

Numerical coupling

pages 10-11
Some of the important info wanted in the previous section is here, but the overall connections are not clear. For example, some of the variables passed between models are listed. Are these complete lists?
It is still unclear which models are responsible for which overall land outputs. Does VISIT do all mass and energy land-atmosphere-flux outputs, or just the carbon and nitrogen cycles?
Figure 2 indicates that VISIT gets soil moisture and temperature from HiGWMAT, but the text states that there is no communication between these models.
What appears to take place is that TeLMO first estimates land use, then HiGWMAT estimate water use, then PRYSBI2 estimates crop growth/yields, which then feed back to TeLMO for updated future land use estimates. When does VISIT get the TeLMO outputs? Before or after being informed by the water and crop models?
And where are output water flux variables calculated?
This flow needs to be completed and made clear. Including a more detailed discussion of how the final surface model (VISIT) doesn’t use the more detailed models to determine crop growth and water exchange and eventually land-atmosphere fluxes and carbon storage, but only the land use estimated from the more detailed models.

Experimental settings

What are the historical isimip forcings? figures 3and 5 suggests that there are multiple realizations of the historical forcings.

HIstorical simulations

page 14, lines 6-7
If the model output and the reference data are on grids, why do you use another data set to aggregate to country scale? Is this just to get a ratio of physical area to harvested area to comparison with FAO?

page 15, lines 21-25
if telmo matches aim regions, why are austaralia and russia so different from aim?

page 15, lines 25-29
there are some large differences for forest in usa and australia. why is this?
With the apparent country-level differences in pasture and forest it is not correct to state that telmo, aim and fao closely agree at the regional scale. This statement needs to be tempered and the differences acknowledged.

Future simulations and interaction of submodels

The isimip1 climate forcings do not match with the SSP scenarios you use. Not only were the climate forcings created from different IAMs, but the current SSP2 formulations are different than the socio-economic scenarios used for the RCPs from isimip.
So you have inconsistencies in your forcing data. You should be using the CMIP5 SSP socio-economic drivers.
This may not be a huge issue here because the atmosphere is not coupled to the land, which means that your climate drivers are somewhat independent of the land processes.
If you cannot use the more closely matched driving data, you need to explain the mismatch and why it it exists and what impact it may have on your results.
For example, while you can examine the effects of different RCP forcings on the land surface, these forcings are not necessarily consistent with the land processes, not only because the land model is not coupled to the atmosphere, but because the climate forcings do not match the land activities to begin with.

page 16, line 6 and beyond
Figure 10, 10a, 10b, 10c

page 16, lines 16 and beyond
Your figures are out of order in referenced incorrectly. Ensure that they are numbers and referenced in order.

page 18 lines 20 forward
Do you have the irrigation results for these sims as well? figure 16b shows the real novelty of your development. The more outputs you can show that vary based on climate/co2 info and that matter for projecting human resource use, the better.

Implications and future research
So here you want to highlight how irrigation demand and cropland allocation change significantly if climate and/or CO2 effects are considered in this process. This interaction is the real novelty of miroc-integ-land. The IAMs are allocating land based on the green yield line in figure 16. But using miroc-integ-land, you get a very different allocation.

Tables and figures

Figure 8
Caption needs to be edited to state “ratio of pasture area to total area”

Figure 9
Caption needs to be edited to state “ratio of forest area to total area”

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ED: Reconsider after major revisions (18 May 2020) by Olivier Marti

ED: Reconsider after major revisions (08 Jun 2020) by Olivier Marti

AR by Tokuta Yokohata on behalf of the Authors (20 Jul 2020) Author's response Manuscript

ED: Publish as is (30 Jul 2020) by Olivier Marti

AR by Tokuta Yokohata on behalf of the Authors (07 Aug 2020) Author's response Manuscript

Short summary

The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balances, human water management, and crop growth incorporates a land-use decision-making model based on economic activities. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand.