陆地蒸散发（ET）在地球的水碳循环中起着至关重要的作用，准确估算全球陆地蒸散发对于促进我们对陆地-大气相互作用的理解至关重要。尽管近几十年来开发了许多蒸散发产品，但由于使用了不同的强迫输入和不完善的模型参数，广泛使用的产品仍然存在固有的不确定性。此外，由于缺乏足够的全球原位观测数据，直接评估蒸散发产品并不现实，从而阻碍了这些产品的利用和同化。因此，建立可靠的全球基准数据集和探索蒸散发产品的评估方法至关重要。\n
本研究旨在通过以下方法应对这些挑战：（1）提出一种基于对位的方法，该方法考虑了多源数据合并时的非零误差交叉相关性；（2）采用这种合并方法生成分辨率为 0.1°（2000-2020 年）和 0.25°（1980-2022 年）的长期全球每日蒸散发产品，并纳入 ERA5L、FluxCom、PMLv2、GLDAS 和 GLEAM 的输入。由此产生的产品是定位分析多源集合陆地蒸散量数据（CAMELE）。", "ds_source": "
ERA5-Land：https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview\n
GLDAS：https://disc.gsfc.nasa.gov/datasets?keywords=GLDAS\n
Global Land Evaporation Amsterdam Model 3.7 (GLEAM-3.7)：https://www.gleam.eu/\n
Penman–Monteith–Leuning version 2 global evaporation model (PMLv2)：https://developers.google.com/earth-engine/datasets/catalog/CAS_IGSNRR_PML_V2_v017\n
FluxCom：http://fluxcom.org/\n
Global in situ observation: FluxNet", "ds_process_way": "
本研究对产物的融合包括三个步骤：\n
（1）采用配准法（IVD和EIVD）计算所选输入产物的随机误差方差，确定区域最优产品，并设置误差阈值;\n
（2）以最小均方误差（MSE）为目标，计算各网格上不同产品的权重;\n
（3）根据权重融合产品，得到长序列蒸散量产品。由于 IVD 和 EIVD 是通过结合工具变量回归和扩展定位系统开发的，因此还包括对 TC 和 EC 算法的描述。", "ds_quality": "
CAMELE 在各种植被覆盖类型中表现出良好的性能，并与现场观测数据进行了验证。评估过程得出的皮尔逊相关系数（R）分别为 0.63 和 0.65。此外，比较结果表明，CAMELE 能够有效描述蒸散发的多年线性趋势、平均值和极端值。但是，它有高估季节性的倾向。总之，我们提出了一套可靠的蒸散发数据，有助于理解水循环的变化，并有可能作为各种应用的基准。", "ds_acq_start_time": "1980-01-01 00:00:00", "ds_acq_end_time": "2022-12-31 00:00:00", "ds_acq_place": "全球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": -90.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 90.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 40702489931, "ds_files_count": 68, "ds_format": "nc", "ds_space_res": "0.1度,0.25度", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "23ee4db3-6e9c-4e8f-af4a-5404ee1bd548.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2024-05-22 10:25:45", "last_updated": "2026-01-14 10:37:35", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB6472.2024", "i18n": { "en": { "title": "CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data", "ds_format": "nc", "ds_source": "
ERA5-Land： https://cds.climate.copernicus.eu/cdsapp# !/dataset/reanalysis-era5-land? tab=overview\n
GLDAS： https://disc.gsfc.nasa.gov/datasets?keywords=GLDAS\n
Global Land Evaporation Amsterdam Model 3.7 (GLEAM-3.7)： https://www.gleam.eu/\n
Penman–Monteith–Leuning version 2 global evaporation model (PMLv2)： https://developers.google.com/earth-engine/datasets/catalog/CAS_IGSNRR_PML_V2_v017\n
FluxCom： http://fluxcom.org/\n
Global in situ observation: FluxNet", "ds_quality": "
CAMELE has shown good performance in various types of vegetation cover and has been validated with field observation data. The Pearson correlation coefficients (R) obtained during the evaluation process were 0.63 and 0.65, respectively. In addition, the comparison results indicate that CAMELE can effectively describe the multi-year linear trend, average value, and extreme value of evapotranspiration. However, it tends to overestimate seasonality. In summary, we have proposed a reliable set of evapotranspiration data that can help understand changes in the water cycle and potentially serve as a benchmark for various applications.", "ds_ref_way": "", "ds_abstract": "
Land evapotranspiration (ET) plays a crucial role in the Earth's water carbon cycle, and accurate estimation of global land evapotranspiration is essential for advancing our understanding of land atmosphere interactions. Although many evapotranspiration products have been developed in recent decades, the widely used products still have inherent uncertainties due to the use of different forced inputs and imperfect model parameters. In addition, due to the lack of sufficient global in-situ observation data, it is not realistic to directly evaluate evapotranspiration products, which hinders their utilization and assimilation. Therefore, it is crucial to establish a reliable global benchmark dataset and explore evaluation methods for evapotranspiration products.\n
The aim of this study is to address these challenges through the following methods: (1) proposing an alignment based approach that considers non-zero error cross-correlation during multi-source data merging; (2) Using this merging method, long-term global daily evapotranspiration products with resolutions of 0.1 ° (2000-2020) and 0.25 ° (1980-2022) were generated and included as inputs for ERA5L, FluxCom, PMLv2, GLDAS, and GLEAM. The resulting product is CAMELE, a multi-source collection of land evapotranspiration data for location analysis.
", "ds_time_res": "年", "ds_acq_place": "Global", "ds_space_res": "0.1度,0.25度", "ds_projection": "", "ds_process_way": "The fusion of products in this study involves three steps:\n
(1) Using registration methods (IVD and EIVD) to calculate the random error variance of the selected input product, determine the optimal product in the region, and set the error threshold;\n
(2) Calculate the weights of different products on each grid with the goal of minimizing mean square error (MSE);\n
(3) Based on the weight fusion of products, obtain a long sequence evapotranspiration product. As IVD and EIVD were developed by combining instrumental variable regression and extended localization systems, they also include descriptions of TC and EC algorithms.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "CAMELE", "多源", "土地蒸散量（ET）" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [ 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 ], "ds_contributors": [ { "true_name": "杨汉波", "email": "yanghanbo@mail.tsinghua.edu.cn", "work_for": "清华大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "杨汉波", "email": "yanghanbo@mail.tsinghua.edu.cn", "work_for": "清华大学", "country": "中国" } ], "ds_managers": [ { "true_name": "杨汉波", "email": "yanghanbo@mail.tsinghua.edu.cn", "work_for": "清华大学", "country": "中国" } ], "category": "生态" }