Current challenges of implementing land - use and land - cover change in climate assessments

Current challenges of implementing land - use and land - cover change in climate assessments

Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in Dynamic Global Vegetation Models (DGVMs) and Earth System Models (ESMs), whose published results are used in major assessments of processes and impacts of global environmental change such as the reports of the Intergovernmental Panel on Climate Change (IPCC). In the absence of coupled models of climate, land use and biogeochemical cycles to explore land use – climate interactions across spatial scales, information on LULCC is currently provided as exogenous data from the land-use change modules of Integrated Assessment Models (IAMs) to ESMs and DGVMs, while data from dedicated land-use change models (LUCMs) are rarely considered. In this article, we discuss major uncertainties and existing shortcomings of current implementation strategies originating in both LULCC data-provider and LULCC data-user communities.

The authors identify, based on literature review and the analysis of empirical and modeled LULCC data, three major challenges related to LULCC representation, which are currently not or insufficiently accounted for: (1) provision of consistent, harmonized LULCC time series spanning from historical reconstructions to future projections while accounting for uncertainties due to different land-use modeling approaches, (2) accounting for sub-grid processes and bi-directional changes (gross changes) across spatial scales and (3) the allocation strategy of LULCC at the grid cell level in ESMs and DGVMs.

Based on these three challenges, the paper discusses the reasons that hamper the development of implementation strategies that sufficiently account for uncertainties in the land-use modeling process and conclude that both providers and users of LULCC data products often miss appropriate knowledge of the requirements and constraints of one another’s models, thus leading to large discrepancies between the representation of LULCC data and processes in both communities. The authors propose to focus future research on the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories.

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