the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Aug 2021
High-resolution land-use land-cover change data for regional climate modelling applications over Europe – Part 2: Historical and future changes
Abstract. Anthropogenic land-use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently extensively investigated within the WCRP CORDEX Flagship Pilot Study (FPS) LUCAS – "Land Use and Climate Across Scales" using an ensemble of different Regional Climate Models (RCMs) coupled with diverse Land Surface Models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM-LSM simulations. To account for these needs, we generated the LUCAS LUC Version 1.0 at 0.1° resolution for Europe Hoffmann et al. (2021b,c). The plant functional type distribution for the year 2015 (i.e. LANDMATE PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details about the conversion method based on a cross-walking procedure and the evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (submitted). Subsequently, we applied the land-use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25° resolution as input for CMIP6 experiments, to derive realistic LULC distribution at high spatial resolution and at annual timesteps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a Land Use Translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to remotely-sensed PFT time series. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the Coupled Modelling Intercomparison Project Phase 6 (CMIP6). The resulting LULCC maps can be applied as land use forcing to the next generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions world-wide.
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EC1: 'Review link for essd-2021-252', David Carlson, 10 Aug 2021
For purposes of review and comment, please use this link:
user: referee@copernicus.org
password: bG538M1TtThank you!
Citation: https://doi.org/10.5194/essd-2021-252-EC1 -
RC1: 'Comment on essd-2021-252', Anonymous Referee #1, 28 Oct 2021
The authors have implemented a massive amount of data analysis in teh field of land cover/land use change. They explain that the exercise serves requirements by teh regional climate modeling community for more detailed data at teh geospatial level in order to improve downscaled simulations and predictions. This is of course a valuable goal. However, the authors fail in my view to characterixe the quality of the data they produced for use by another community -- in terms of underlying uncertainties and limitations.
Overall, even if this was done in a companion paper, the authors should repeat or at least summarize findings on uncertainty that may be used as guide (or warning) by the modelers. Everybody wants to improve simulations, and everyone wants more detailed data of some sort--but the data provided need to come with full descriptors.
In the specific, it is well known that land cover and land use data are very uncertain, and even more so when differencing the input land data as done here. In other words, take any two established products such as MODIS and ESA CCI (as done here), and you'll see that their differences in terms of derives land cover changes are huge and hardly explainable in a consistent manner. THough explained they should be so that others can ue them with a grain of salt.
At the outset and even before discussinn uncertainty and limitations, teh manuscript would benefit from clearly defininig what is meant bby land cover and land use -- key differences in the concepts etc. Then I think there should be a valiant effort to use more homogenized land use/cover categories rather than inventing yet another set of new ones (proliferation in this fiels is an enemy to improved understanding) as done in the manuscript. I would start by looking at the available internatoinal definitions of land use (IPCC, FAO) and use those of FAO/UN for land cover. This would have the added advantage of gaining an understanding audience, plus ensure that the climate results obtained by the modelers can be presented in understandable IPCC/FAO language. This effort is important because a good part of teh úncertainties'' in the derived products actually stem from usage of different names and classifications -- and there is no need for that.
Secondly, the authors should attempt at computing uncertainty values in order to scientifically communicate their results. There is guidance in many places in the literature for this, from IPCC guidelines all the way to the remote sensing literature on this topic.
Regardless of the degree of success of the two requests above, which I recommend strongly, at a minimum the authors should clearly discuss teh implications of using their data for modeling, with big warning signs to potential users of where they see the reasonable space of applications (i.e., clearly stating the boundaries outside of which ''garbage in = garbage out'').
I am attaching a number of more detailed comments in an annotated pdf of the submitted manuscript.
Best Regards,
- RC2: 'Comment on essd-2021-252', Anonymous Referee #2, 08 Jan 2022
Status: closed
-
EC1: 'Review link for essd-2021-252', David Carlson, 10 Aug 2021
For purposes of review and comment, please use this link:
user: referee@copernicus.org
password: bG538M1TtThank you!
Citation: https://doi.org/10.5194/essd-2021-252-EC1 -
RC1: 'Comment on essd-2021-252', Anonymous Referee #1, 28 Oct 2021
The authors have implemented a massive amount of data analysis in teh field of land cover/land use change. They explain that the exercise serves requirements by teh regional climate modeling community for more detailed data at teh geospatial level in order to improve downscaled simulations and predictions. This is of course a valuable goal. However, the authors fail in my view to characterixe the quality of the data they produced for use by another community -- in terms of underlying uncertainties and limitations.
Overall, even if this was done in a companion paper, the authors should repeat or at least summarize findings on uncertainty that may be used as guide (or warning) by the modelers. Everybody wants to improve simulations, and everyone wants more detailed data of some sort--but the data provided need to come with full descriptors.
In the specific, it is well known that land cover and land use data are very uncertain, and even more so when differencing the input land data as done here. In other words, take any two established products such as MODIS and ESA CCI (as done here), and you'll see that their differences in terms of derives land cover changes are huge and hardly explainable in a consistent manner. THough explained they should be so that others can ue them with a grain of salt.
At the outset and even before discussinn uncertainty and limitations, teh manuscript would benefit from clearly defininig what is meant bby land cover and land use -- key differences in the concepts etc. Then I think there should be a valiant effort to use more homogenized land use/cover categories rather than inventing yet another set of new ones (proliferation in this fiels is an enemy to improved understanding) as done in the manuscript. I would start by looking at the available internatoinal definitions of land use (IPCC, FAO) and use those of FAO/UN for land cover. This would have the added advantage of gaining an understanding audience, plus ensure that the climate results obtained by the modelers can be presented in understandable IPCC/FAO language. This effort is important because a good part of teh úncertainties'' in the derived products actually stem from usage of different names and classifications -- and there is no need for that.
Secondly, the authors should attempt at computing uncertainty values in order to scientifically communicate their results. There is guidance in many places in the literature for this, from IPCC guidelines all the way to the remote sensing literature on this topic.
Regardless of the degree of success of the two requests above, which I recommend strongly, at a minimum the authors should clearly discuss teh implications of using their data for modeling, with big warning signs to potential users of where they see the reasonable space of applications (i.e., clearly stating the boundaries outside of which ''garbage in = garbage out'').
I am attaching a number of more detailed comments in an annotated pdf of the submitted manuscript.
Best Regards,
- RC2: 'Comment on essd-2021-252', Anonymous Referee #2, 08 Jan 2022
Data sets
LUCAS LUC historical land use and land cover change dataset (Version 1.0) Hoffmann, Peter; Reinhart, Vanessa; Rechid, Diana https://doi.org/10.26050/WDCC/LUC_hist_landCovChange_v1.0
LUCAS LUC future land use and land cover change dataset (Version 1.0) Hoffmann, Peter; Reinhart, Vanessa; Rechid, Diana https://doi.org/10.26050/WDCC/LUC_future_landCovChange_v1.0
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Cited
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- Future heat extremes and impacts in a convection-permitting climate ensemble over Germany M. Hundhausen et al. 10.5194/nhess-23-2873-2023