气象数据是理解区域荒漠化情况的重要指标。目前，敦煌面临着严峻的荒漠化态势，但区域内的气象数据仍较为零散。本研究基于敦煌地区自然数据统计年鉴，系统总结了21世纪以来当地气温、降水等关键数据。该数据将有助于对敦煌生态环境进行评估，并提出适宜的方案以遏制荒漠化。", "ds_source": "
本研究所用气象数据来源于《敦煌地区自然数据统计年鉴》，涵盖自21世纪以来的长期观测记录。数据指标包括平均气温、日最高气温、日最低气温、日照时数、降水量及平均风速等，反映了区域的主要气候特征。年鉴数据经过官方统计与审核，具有较高的可靠性与可追溯性，可为分析敦煌地区的气候变化趋势及荒漠化过程提供基础支撑。此外，数据以年度和日度尺度记录，便于进行时间序列分析和跨年度比较。", "ds_process_way": "
所收集的气象数据经数字化处理后导入计算机进行整理。数据处理包括统一时间尺度、缺失值填补及必要的单位转换，例如将温度转换为摄氏度、降水量转换为毫米等。对日度观测数据可进一步汇总计算月度或年度平均值，以便进行长期气候趋势分析。数据还经过时间序列整理和初步统计分析，包括最大值、最小值、平均值及标准差的计算，以保证数据可直接用于荒漠化过程评估和相关模型研究。", "ds_quality": "
所有数据均来源于官方统计年鉴，经过严格的统计和审核程序，可靠性高。采集过程中对异常值、缺测值进行了标记和处理，缺失数据通过线性插值或邻近年份平均值进行补充。对重复观测和长期趋势进行比对，确保数据的连续性和一致性。经过处理的数据已统一格式存储，并保留原始数据备份，以保证数据可追溯性和长期使用的稳定性。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2010-12-31 00:00:00", "ds_acq_place": "中国敦煌", "ds_acq_lon_east": 95.0, "ds_acq_lat_south": 39.66694444444444, "ds_acq_lon_west": 93.66694444444445, "ds_acq_lat_north": 40.33305555555556, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 26418, "ds_files_count": 2, "ds_format": "Excel", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "b3a1b37d-670d-455f-a7e9-36a1fb792873.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "6d0aa454-9b64-4be5-b0cd-4cc796e6aea0", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 0, "publish_time": "2026-03-13 18:43:51", "last_updated": "2026-03-13 18:43:51", "protected": false, "protected_to": "2028-03-01 00:00:00", "lang": "zh", "cstr": "11738.11.NCDC.DESERTIFICATION.DB7166.2026", "i18n": { "en": { "title": "Dunhuang Meteorological Dataset", "ds_format": "Excel", "ds_source": "
The meteorological data used in this study is sourced from the Dunhuang Natural Data Statistical Yearbook, covering long-term observation records since the 21st century. The data indicators include average temperature, daily maximum temperature, daily minimum temperature, sunshine hours, precipitation, and average wind speed, reflecting the main climatic characteristics of the region. The yearbook data has undergone official statistics and review, and has high reliability and traceability, providing basic support for analyzing climate change trends and desertification processes in the Dunhuang region. In addition, the data is recorded on an annual and daily scale, which facilitates time series analysis and cross year comparisons.", "ds_quality": "
All data is sourced from official statistical yearbooks and has undergone strict statistical and auditing procedures, ensuring high reliability. During the collection process, outliers and missing measurements were marked and processed, and missing data was supplemented through linear interpolation or the average of adjacent years. Compare repeated observations with long-term trends to ensure data continuity and consistency. The processed data has been stored in a unified format and the original data backup has been retained to ensure data traceability and long-term stability.", "ds_ref_way": "", "ds_abstract": "
Meteorological data is an important indicator for understanding regional desertification. At present, Dunhuang is facing a severe desertification situation, but meteorological data in the region is still relatively scattered. This study is based on the Dunhuang Natural Data Statistical Yearbook and systematically summarizes key data such as local temperature and precipitation since the 21st century. This data will help evaluate the ecological environment of Dunhuang and propose appropriate solutions to curb desertification.", "ds_time_res": "", "ds_acq_place": "Dunhuang, China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
The collected meteorological data is digitized and imported into a computer for organization. Data processing includes unifying time scales, filling missing values, and necessary unit conversions, such as converting temperature to degrees Celsius and precipitation to millimeters. Daily observation data can be further summarized and calculated as monthly or annual averages for long-term climate trend analysis. The data has also undergone time series sorting and preliminary statistical analysis, including the calculation of maximum, minimum, mean, and standard deviation, to ensure that the data can be directly used for desertification process assessment and related model research.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "ds_topic_tags": [ "气象", "统计年鉴", "荒漠", "绿洲", "过渡带" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国敦煌" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010 ], "ds_contributors": [ { "true_name": "张克存", "email": "kecunzh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "潘加朋", "email": "panjiapeng@nieer.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "潘加朋", "email": "panjiapeng@nieer.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "张克存", "email": "kecunzh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "气象" }