• Energy Research

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow‐on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

A statement in this recently published paper makes a point that is largely at odds with the main point of the paper that is cited. Stating that higher air temperatures lead to greater evapotranspiration is an oversimplification; the true story is more complex. Although this is by no means central to the conclusions of the paper being commented on, we have demonstrated the danger in taking too literally the idea that air temperature determines potential evapotranspiration.

Abstract The questions of how land use change affects climate, and how climate change affects land use, require examination of societal and environmental systems across space at multiple scales, from the global climate to regional vegetative dynamics to local decision making by farmers and herders. It also requires an analysis of causal linkages and feedback loops between systems. These questions and the conceptual approach of the research design of the Climate–Land Interaction Project (CLIP) are rooted in the classical human–environment research tradition in Geography. This paper discusses a methodological framework to quantify the two-way interactions between land use and regional climate systems, using ongoing work by a team of multi-disciplinary scientists examining climate–land dynamics at multiple scales in East Africa. East Africa is a region that is undergoing rapid land use change, where changes in climate would have serious consequences for people’s livelihoods, and requiring new coping and land use strategies. The research involves exploration of linkages between two important foci of global change research, namely, land use/land cover (LULC) and climate change. These linkages are examined through modeling agricultural systems, land use driving forces and patterns, the physical properties of land cover, and the regional climate. Both qualitative and quantitative methods are being used to illustrate a diverse pluralism in scientific discovery.