在本数据集中，使用 MOD16-STM 模型，利用最近获得的土壤特性、气象条件和遥感数据集，生成了大埔 37 年（1982-2018 年）的月度蒸散发成分。整个大陆坡（海拔高于 2500m 的地区）的年平均蒸散发量（ETa）约为（1028.22±37.8）立方米/年。ETa对TP的主要贡献来自土壤，Es占ETa的84%以上。中部和东部大部分地区的 ETa 呈明显上升趋势，而西北部则呈明显下降趋势。在过去 37 年中，大埔县的蒸散发增加率约为 0.96 毫米/年。通过与现有不同数据集的交叉比较验证和独立站点数据验证，该数据集的准确性在同类数据中名列前茅。新的蒸散发数据集有助于研究土地覆被变化对水文的影响，也有助于整个大陆架的水资源管理，具有广泛的应用价值。 数据集 V1 版本的时间跨度为 2000-2018 年，包含 1076 个文件，分别为 ETa、Es、Ec 和 Ew 的模拟数据集（0.01°，月尺度），以及季节分析、趋势分析和辅助数据集。为方便用户下载使用，V2 版本增加了 0.05°数据集，时间尺度扩大到 1982-2018 年，共包含 3909 个文件。
", "ds_source": "使用 MOD16-STM 模型，利用最近获得的土壤特性、气象条件和遥感数据集，生成了大埔 37 年（1982-2018 年）的月度蒸散发成分。
", "ds_process_way": "MOD16-STM 模型依靠各种遥感数据集、再分析数据集和气象强迫数据集来估计青藏高原的每月 ET。为确保一致性，每日和 8 d 输入数据在时间尺度上取平均值，以创建月度数据集。如果任何给定月份的有效数据比率低于 90%，则平均值被视为无效。
", "ds_quality": "估算的蒸散发与 9 个通量塔的测量值相关性很好，均方根误差（RMSE=13.48 毫米/月-1）和平均偏差（MB=2.85 毫米/月-1）较低，判定系数（R2=0.83）和一致指数（IOA=0.92）较高。
", "ds_acq_start_time": "1982-01-01 00:00:00", "ds_acq_end_time": "2018-12-31 00:00:00", "ds_acq_place": "青藏高原", "ds_acq_lon_east": 104.0, "ds_acq_lat_south": 25.0, "ds_acq_lon_west": 74.0, "ds_acq_lat_north": 40.0, "ds_acq_alt_low": 2500.0, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 14421555138, "ds_files_count": 3, "ds_format": "mat", "ds_space_res": "500", "ds_time_res": "月", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "a70c2e3a-85e5-4b8d-8d92-4966a9f8102f.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "d2c052ce-d283-4a48-8962-6a3dbcb03b8e", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2025-05-29 17:22:21", "last_updated": "2026-01-14 10:43:38", "protected": false, "protected_to": null, "lang": "zh", "cstr": "https://cstr.cn/31253.11.sciencedb.00020", "i18n": { "en": { "title": "Long term variations of monthly terrestrial evapotranspiration over the Tibetan Plateau(1982-2018)", "ds_format": "mat", "ds_source": "Using the MOD16-STM model, the monthly evapotranspiration components of Dapu for 37 years (1982-2018) were generated using recently obtained soil characteristics, meteorological conditions, and remote sensing datasets.
", "ds_quality": "The estimated evapotranspiration has a good correlation with the measured values of 9 flux towers, with low root mean square error (RMSE=13.48 mm/mm-1) and average deviation (MB=2.85 mm/mm-1), high determination coefficient (R2=0.83) and consistency index (IOA=0.92).
", "ds_ref_way": "", "ds_abstract": "In this dataset, the MOD16-STM model was used to generate monthly evapotranspiration components of Dapu for 37 years (1982-2018) using recently obtained soil characteristics, meteorological conditions, and remote sensing datasets. The annual average evapotranspiration (ETa) of the entire continental slope (areas above 2500m altitude) is approximately (1028.22 ± 37.8) cubic meters per year. The main contribution of ETa to TP comes from soil, with Es accounting for over 84% of ETa. The ETa in most parts of the central and eastern regions shows a clear upward trend, while in the northwest it shows a clear downward trend. In the past 37 years, the evapotranspiration growth rate in Dapu County has been approximately 0.96 millimeters per year. Through cross comparison validation with existing datasets and independent site data validation, the accuracy of this dataset ranks among the top in the same category of data. The new evapotranspiration dataset is helpful for studying the impact of land cover change on hydrology and for water resource management throughout the continental shelf, and has broad application value. The V1 version of the dataset spans from 2000 to 2018 and contains 1076 files, including simulated datasets for ETa, Es, Ec, and Ew (0.01 °, monthly scale), as well as seasonal analysis, trend analysis, and auxiliary datasets. For the convenience of users to download and use, the V2 version has added a 0.05 ° dataset and expanded the time scale to 1982-2018, containing a total of 3909 files.
", "ds_time_res": "月", "ds_acq_place": "Qinghai-Tibet Plateau", "ds_space_res": "500", "ds_projection": "", "ds_process_way": "The MOD16-STM model relies on various remote sensing datasets, reanalysis datasets, and meteorological forcing datasets to estimate the monthly ET of the Qinghai Tibet Plateau. To ensure consistency, daily and 8-day input data are averaged on a time scale to create a monthly dataset. If the effective data ratio for any given month is below 90%, the average is considered invalid.
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [ "蒸散量", "青藏高原", "MOD16-STM" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原" ], "ds_time_tags": [ 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 ], "ds_contributors": [ { "true_name": "马耀明", "email": "ymma@itpcas.ac.cn", "work_for": "中国科学院青藏高原研究所", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "马耀明", "email": "ymma@itpcas.ac.cn", "work_for": "中国科学院青藏高原研究所", "country": "中国" } ], "ds_managers": [ { "true_name": "马耀明", "email": "ymma@itpcas.ac.cn", "work_for": "中国科学院青藏高原研究所", "country": "中国" } ], "category": "其他" }