本数据是基于GLEAM4.2全球0.1°分辨率蒸散发和土壤湿度栅格数据提取的新疆和中亚五国的数据，保留原数据的分辨率精度、文件格式，空间分辨率0.1°，时间分辨率每日、每月、每年，数据格式nc文件，按照新疆和中亚五国分别存放文件夹。
\n数据变量：实际蒸发量（E ）、蒸腾量（E t ）、截留损失（E i ）、土壤蒸发量（E b ）、Ep_aero、Ep_rad、雪的升华（E s ）、地表凝结（E c ）、开放水面蒸发（E w ）、潜在蒸发（E p ）、蒸腾胁迫（S）、根区土壤湿度（SM rz ）、表层土壤湿度（SM s ）、感热通量 (H )。
", "ds_source": "GLEAM4.2全球0.1°分辨率蒸散发和土壤湿度栅格数据，空间分辨率0.1°，时间分辨率每日、每月、每年，数据格式nc文件，记录了从2018年至今的数据，2025年6月已更新完2024年的数据。数据是由比利时根特大学极端水文气候实验室（H-CEL）发布的，官网下载地址https://www.gleam.eu/?spm=a2ty_o01.29997173.0.0.693c570b1fEaPT。\nGLEAM 提供陆地蒸发（或称'蒸散'）的不同组成部分的数据：蒸腾作用、裸土蒸发、截留损失、开敞水面蒸发和升华，此外还包括其他相关变量，如地表和根区土壤湿度、感热通量、潜在蒸发和蒸发胁迫条件。\nGLEAM4生成了两个数据集，GLEAM4.2a是基于再分析辐射和气温，结合了基于雨量计、再分析和卫星的降水，以及基于卫星的植被光学深度的数据，GLEAM4.2b是一个涵盖 2003 年至 2023 年 21 年期间的全局数据集。该数据集（主要）由卫星数据驱动得到的，根据官网信息，数据发布者后续将会发布GLEAM4.2b数据。\n所有 GLEAM4 数据集均以 0.1°×0.1°的纬度-经度网格和每日时间分辨率提供。\n更多信息可参考官网、README_GLEAM4.2说明文件或数据论文中的信息。
", "ds_process_way": "GLEAM 中的 Penman 方程使用地表净辐射（R n ）、近地表气温（T a ）、风速（u ）、叶面积指数（LAI）和蒸汽压亏缺（VPD）的观测值来计算潜在蒸发（E p ）。裸土、高植被冠层和低植被冠层土地分区的 E p 估算值通过深度神经网络训练的乘法蒸发胁迫因子（S）转换为裸土蒸发（E b ）和蒸腾（E t ）。胁迫预测因子包括土壤湿度、VPD、[CO 2 ]、T a 以及植被状况（VOD、LAI）。根区土壤湿度（SM rz ）使用多层运行水平衡计算。为校正随机强迫误差，将卫星观测的地表土壤湿度（SM s ）同化到土壤剖面中。截留损失（E i ）在 GLEAM 中使用由降水（P ）和植被特性驱动的解析模型单独计算。最后，使用改进的 Penman 方程导出水体（E w ）和被冰和/或雪覆盖区域（E s ）的实际蒸发估算值
", "ds_quality": "GLEAM 自 2011 年首次发布以来一直在不断修订和更新，当前版本 GLEAM4.2 于 2025 年 6月发布.
", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 2188686889, "ds_files_count": 33068, "ds_format": "", "ds_space_res": "0.1°", "ds_time_res": "日，月，年", "ds_coordinate": "WGS84", "ds_projection": "GCS_WGS84", "ds_thumbnail": "5b50a3f3-0947-45d1-b906-d5d08d5c776a.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 1, "publish_time": "2025-08-10 00:30:14", "first_publish_time": null, "last_updated": "2025-08-10 00:30:14", "protected": false, "protected_to": null, "lang": "zh", "cstr": null, "license": null, "extra": null, "files_shape": [ { "name": "Log_file_GLEAM4.2.pdf", "size": 57834, "is_dir": false }, { "name": "README_GLEAM4.2.pdf", "size": 101540, "is_dir": false }, { "name": "s41597-025-04610-y.pdf", "size": 3584872, "is_dir": false }, { "name": "变量中英文对照.txt", "size": 715, "is_dir": false }, { "name": "daily_KAZ", "size": null, "is_dir": true }, { "name": "daily_KGZ", "size": null, "is_dir": true }, { "name": "daily_TJK", "size": null, "is_dir": true }, { "name": "daily_TKM", "size": null, "is_dir": true }, { "name": "daily_UZB", "size": null, "is_dir": true }, { "name": "daily_XJ", "size": null, "is_dir": true }, { "name": "monthly_KAZ", "size": null, "is_dir": true }, { "name": "monthly_KGZ", "size": null, "is_dir": true }, { "name": "monthly_TJK", "size": null, "is_dir": true }, { "name": "monthly_TKM", "size": null, "is_dir": true }, { "name": "monthly_UZB", "size": null, "is_dir": true }, { "name": "monthly_XJ", "size": null, "is_dir": true }, { "name": "yearly_KAZ", "size": null, "is_dir": true }, { "name": "yearly_KGZ", "size": null, "is_dir": true }, { "name": "yearly_TJK", "size": null, "is_dir": true }, { "name": "yearly_TKM", "size": null, "is_dir": true }, { "name": "yearly_UZB", "size": null, "is_dir": true }, { "name": "yearly_XJ", "size": null, "is_dir": true } ], "features": null, "data_level": 0, "i18n": { "en": { "title": "GLEAM4.2 0.1° resolution evapotranspiration and soil moisture grid data across Xinjiang and five Central Asian countries (1980-2024)", "ds_abstract": "This data is data from Xinjiang and five Central Asian countries extracted based on GLEAM4.2 global 0.1° resolution evapotranspiration and soil moisture grid data. The resolution accuracy and file format of the original data are retained. The spatial resolution is 0.1° and the temporal resolution is daily, monthly, and annually. The data format is nc file, which is stored in folders according to Xinjiang and the five Central Asian countries.
\nData variables: Actual evaporation (E), transpiration (Et), interception loss (Ei), soil evaporation (Eb), Ep_aero, Ep_rad, sublimation of snow (Es), surface condensation (Ec), open water surface evaporation (Ew), potential evaporation (Ep), transpiration stress (S), root zone soil moisture (SMrz), surface soil moisture (SMs), sensible heat flux (H ).
", "ds_source": "GLEAM4.2 global 0.1° resolution evapotranspiration and soil moisture grid data, spatial resolution 0.1°, temporal resolution daily, monthly, and annual, data format nc file, records data from 2018 to the present, 2024 data has been updated in June 2025. The data was released by the Extreme Hydroclimate Laboratory (H-CEL) at the University of Ghent, Belgium, and the official website is downloaded from www.gleam.eu/? spm=a2ty_o01.29997173.0.0.693c570b1fEaPT。\nGLEAM provides data on different components of land evaporation (or 'evapotranspiration'): transpiration, bare soil evaporation, interception losses, open water evaporation and sublimation, in addition to other related variables such as surface and root zone soil moisture, sensible heat fluxes, potential evaporation and evaporation stress conditions.\nGLEAM4 generates two datasets, GLEAM4.2a is based on reanalysis of radiation and temperature, combining rain gauge, reanalysis and satellite-based precipitation, and satellite-based vegetation optical depth data, and GLEAM4.2b is a global dataset covering a 21-year period from 2003 to 2023. This dataset is (mainly) driven by satellite data. According to official website information, the data publisher will later release GLEAM4.2b data.\nAll GLEAM4 datasets are provided on a latitude-longitude grid of 0.1°×0.1° and a daily time resolution.\nFor more information, please refer to the official website, README_GLEAM4.2 documentation or data papers.
", "ds_process_way": "The Penman equation in GLEAM uses observations of net surface radiation (Rn), near-surface air temperature (Ta), wind speed (u), leaf area index (LAI), and vapor pressure deficit (VPD) to calculate potential evaporation (Ep). Estimates of Ep for bare soil, high vegetation canopy and low vegetation canopy land divisions were converted into bare soil evaporation (Eb) and transpiration (Et) using multiplicative evaporation stress factors (S) trained by deep neural networks. Predictors of stress include soil moisture, VPD,[CO2], Ta, and vegetation status (VOD, LAI). Root zone soil moisture (SMrz) was calculated using multi-layer running water balance. To correct for random forcing errors, satellite observed surface soil moisture (SMs) were assimilated into soil profiles. Interception losses (Ei) were calculated separately in GLEAM using analytical models driven by precipitation (P) and vegetation characteristics. Finally, estimates of actual evaporation for water bodies (E w) and areas covered by ice and/or snow (Es) were derived using the modified Penman equation
", "ds_quality": "GLEAM has been continuously revised and updated since it was first released in 2011, with the current version of GLEAM 4.2 released in June 2025.
", "ds_projection": "GCS_WGS84", "ds_space_res": "0.1°", "ds_time_res": "Day, month, year" } }, "license_type": null, "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "土壤湿度", "蒸散发" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "乌兹别克斯坦", "土库曼斯坦", "吉尔吉斯斯坦", "新疆", "塔吉克斯坦", "哈萨克斯坦" ], "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, 2023, 2024 ], "ds_contributors": [ "李锦" ], "ds_meta_authors": [ "李锦" ], "ds_managers": [ "李锦" ], "category": "气象" }