Assessing the land-use harmonization (LUH) 2 dataset in Central Asia for regional climate model projection

Abstract

Although the land-use harmonization (LUH) datasets have been widely applied in regional climate model (RCM) projections for investigating the role of the land-use forcing in future climate changes, few studies have thoroughly assessed them on local scale, which may bring large uncertainties in the resultant climate information for designing adaption and mitigation measures of climate change. The authors use a local land-use dataset (referred to as Li-LU) as the benchmark to assess the latest version of the LUH datasets, LUH2, in Central Asia (CA) which has undergone extensive land-use changes (LUCs) and might undergo extensive LUCs in the future. The results show that LUH2 has large biases in depicting the historical land-use states in CA for 1995–2015. For instance, the area of grassland (cropland) in LUH2 is about 1.4–1.5 (0.4–0.5) times of that of Li-LU. Moreover, the future LUCs predicted by LUH2 for 2045 (relative to 2005) are much smaller than those of Li-LU and these two datasets generally have opposite signals in changes. In addition, the predicted LUCs of LUH2 do not follow the causal mechanisms [the causal connections between the key drivers (e.g. population, economy, and environment) and land use] behind the LUCs in the past. If the future scenario of LUH2 is used for RCM projection in CA with the historical land-use information from Li-LU, the simulation results could be misleading for understanding the impacts of LUCs on future climate changes there. This study suggests that the LUH datasets should be carefully assessed before using them for regional studies and provides practical notes for selecting the appropriate land-use dataset for RCM projections in other areas around the world.

Keywords

• regional climate model (RCM) projection
• land use and land cover
• the land-use harmonization (LUH) datasets
• Central Asia