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Abstract

Human land-use activities have  influenced the Earth’s climate system by significantly altering significantly altered biogeochemical and biogeophysical properties at local to planetary scales. To constrain the precise magnitude and characterization of land-use effects on climate and thereby reduce the uncertainty in the accuracy of future projections, the land-use harmonization (LUH2) dataset was developed to link historical land-use data and future projections in a standard format required by climate models. LUH2 includes updated inputs, higher spatial resolution (~50x the information used in CMIP5), more detailed land-use transitions, the addition of important agricultural management layers and is a part of the entry card for models participating in CMIP6. By developing , and these alterations have influenced the environment including the Earth’s climate system. The global climate modeling community recognizes these effects, and the Coupled Model Intercomparison Project (CMIP6) recently made land-use a required forcing, and endorsed the Land Use Model Intercomparison Project (LUMIP) to organize the communities’ study of the effects of land-use on climate (both activities lead by Hurtt, and supported by separate DOE-SciDAC award). Yet the precise magnitude and character of land-use effects on climate remain uncertain, and this uncertainty in turn limits the accuracy of future projections. The overall goal of this contribution is to develop an expanded and fully consistent treatment of land-use of in ACME Land Model (ALM) . Achieving such consistency will eliminate major sources of within model error/uncertainty, and will give ACME a unique capability among global models. The science questions will be focussed on assessing the sensitivity of the climate system to potentially altered land-use activities. To quantify this, model developments to enable ALM to ingest and utilize LUH2 outputs, will be specifically focused on EPIC task LG-144: 1. Splitting primary and secondary land-use classes into forested and non-forested lands; 2.Disaggregation of grazing lands into managed pasture lands and range lands and 3. Including multiple crop functional classes in ALM, and EPIC task LG-145: developing and implementing . There are two major Objectives. Objective 1 is to establish use of the new expanded land-use dataset in ACME. For CMIP6, the new required land-use forcing dataset is updated and contains ~50x the information used in CMIP5. This new information is at higher resolution over longer time domain, and includes additional new land-use transitions, crop types, crop rotations, and agriculture management information not previously available. Objective 2 is to develop and implement fully consistent (1 carbon cycle) historical land-use treatment for ACME. Global land-use history datasets are traditionally developed independently offline using best available historical information, and then used as input to global models. While useful, this separation leads to inconsistencies, as past land-use activities may be prescribed in areas inconsistent with modeled climate and vegetation. These inconsistencies in turn lead to model errors. To eliminate these errors, a fully consistent treatment of land-use in global models is needed and unique opportunity for ACME.  These objectives are ACME LG-144 and LG-145, respectively. Progress and results on these objectives will be presented.