Land-use harmonization datasets for annual global carbon budgets
Land-use harmonization datasets for annual global carbon budgets
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DOI：
10.5194/essd-13-4175-2021
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发表时间：
2021-08-26
影响因子：
11.4
通讯作者：
Poulter, Benjamin
中科院分区：
文献类型：
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作者：
Chini, Louise;Hurtt, George;Poulter, Benjamin
在历史时期的大部分时间里，土地利用变化一直是人为碳排放的主要来源，目前是全球碳循环中最大和最不确定的组成部分之一。推动对这一主题的科学理解需要将最佳数据用作组织良好的科学评估中最先进的模型的投入。土地利用协调2数据集(LUH2)以前开发并用作第六次耦合模式相互比较项目(CMIP6)模拟的输入，已每年更新，以便为年度全球碳预算评估中的土地模型提供所需的输入。在这里，我们讨论编制这些LUH2-GCB年度更新和延伸的方法，其中纳入联合国粮食及农业组织(粮农组织)关于2015年后数据集年份的年度木材收获数据更新，以及全球环境历史数据库(HYDE)关于2012年后数据集年份的格网农田和牧区数据更新(基于粮农组织农田和牧区数据的年度更新)，以及由于粮农组织数据发布滞后1年或更多而外推到当前年份。由此产生的更新的LUH2-GCB数据集提供了与农业扩张、毁林、木材采伐、轮作种植、再生和造林、作物轮作和牧场管理有关的全球年度网格化土地利用和土地利用变化数据，并被GCB的簿记模型和动态全球植被模型(DGVM)使用。对于GCB 2019年，对LUH2进行了更重要的更新，LUH2-GCB2019(https://doi.org/10.3334/ORNLDAAC/1851，Chini等人，2020b)，以利用早在1950年就纠正了巴西这一全球重要地区的农田和牧区的新数据输入。从1951年到2012年，LUH2-GCB2019数据集开始偏离用于世界气候研究计划CMIP6的LUH2版本，巴西的牧场差异在2000年达到峰值(相差10万公里(2))，农田在2009年达到峰值(相差77000公里(2))，同时巴西境内的农业土地利用模式发生了重大的次国家重组。LUH2-GCB2019数据集为未来的LUH2-GCB更新提供了基础，包括最近的LUH2-GCB2020数据集，并为这些数据集的创建提供了一个可操作的起点，以减少由于多输入数据集和模型延迟而造成的时间滞后。
Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to state-of-the-art models in well-organized scientific assessments. The Land-Use Harmonization 2 dataset (LUH2), previously developed and used as input for simulations of the 6th Coupled Model Intercomparison Project (CMIP6), has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2-GCB updates and extensions which incorporate annual wood harvest data updates from the Food and Agriculture Organization (FAO) of the United Nations for dataset years after 2015 and the History Database of the Global Environment (HYDE) gridded cropland and grazing area data updates (based on annual FAO cropland and grazing area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of 1 or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use-change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, crop rotations, and pasture management and are used by both bookkeeping models and dynamic global vegetation models (DGVMs) for the GCB. For GCB 2019, a more significant update to LUH2 was produced, LUH2-GCB2019 (https://doi.org/10.3334/ORNLDAAC/1851, Chini et al., 2020b), to take advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil as far back as 1950. From 1951 to 2012 the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for the World Climate Research Programme's CMIP6, with peak differences in Brazil in the year 2000 for grazing land (difference of 100 000 km(2)) and in the year 2009 for cropland (difference of 77 000 km(2)), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates, including the recent LUH2-GCB2020 dataset, and presents a starting point for operationalizing the creation of these datasets to reduce time lags due to the multiple input dataset and model latencies.