极端气候事件定义为特定地区特定时间内天气（气候）状态严重偏离平均态的小概率事件。本数据集涵盖中国北方（35°N以北），通过R语言根据阈值法和百分位法根据气象站点数据计算了1971-2020年中国北方极端气候事件序列，包含16个极端温度指标以及11个极端降水的指标，以及极端风速指标为区域气候-灾害关联研究提供基础数据支持。", "ds_source": "
原始气象数据为中国地面气候日值数据集 (V3.0)，来自国家气象信息中心-中国气象数据网，为.txt格式，时间范围为1971-2020年，包含站点编号、观测日期、日最高温度、日最低温度、日降水量关键字段。共346个气象站点数据。", "ds_process_way": "
\"本研究严格遵循世界气象组织（WMO）《气候变化检测与指标指南》中的 ETCCDI（气候变化检测与指标专家组）指标体系，以中国北方 1971-2020 年逐日气象观测数据为基础展开研究。该数据集涵盖日最高温度、日最低温度、日降水量及沙尘暴观测记录等核心要素，研究在 R 语言环境中通过多步骤标准化流程，完成 29 类核心极端气候指标的计算。极端风速计算参考(Jiang et al. 2023)论文中的方法，包含了3种阈值计算的极端风速以及年沙尘暴发生次数。\n具体流程中，首先对原始气象站点数据实施严格的数据质量控制，剔除异常值与缺测数据，保障基础数据的可靠性；随后采用两种核心方法计算极端气候指标：其一为绝对阈值法，重点计算最大 1 日降水量（RX1day）、最大 5 日降水量（RX5day）等反映降水极值特征的指标；其二为相对百分位法，用于计算强降水量（R95p）、极端降水日数（R20mm）、降水强度（SDII）等依赖基准期气候背景的指标，确保指标计算的科学性与规范性。\"", "ds_quality": "
1971-2018年中超过5年有缺测超过60天/年；2019-2020年月缺测多于3天则剔除该月；缺测少于3天利用前/后1天数据填补", "ds_acq_start_time": "1971-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国北方气象站点", "ds_acq_lon_east": 135.0, "ds_acq_lat_south": 35.0, "ds_acq_lon_west": 73.0, "ds_acq_lat_north": 53.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 2809366, "ds_files_count": 2, "ds_format": "xlsx", "ds_space_res": "", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "998014a3-7fed-48ef-a8af-f738ff988227.png", "ds_thumb_from": 2, "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": [ "170.4510" ], "quality_level": 3, "publish_time": "2026-03-13 19:11:45", "last_updated": "2026-03-13 19:11:45", "protected": false, "protected_to": "2028-03-13 00:00:00", "lang": "zh", "cstr": "11738.11.NCDC.DESERTIFICATION.DB7165.2026", "i18n": { "en": { "title": "Dataset of Extreme Climate Events in Northern China from 1971 to 2020", "ds_format": "xlsx", "ds_source": "
The original meteorological data is the China Ground Climate Daily Value Dataset (V3.0), from the National Meteorological Information Center China Meteorological Data Network, in. txt format, with a time range of 1971-2020, including key fields such as station number, observation date, daily maximum temperature, daily minimum temperature, and daily precipitation. A total of 346 meteorological station data.", "ds_quality": "
Over 5 years from 1971 to 2018, there were more than 60 days/year of missing tests; If there are more than 3 days of missing tests in 2019-2020, that month will be excluded; Missing testing for less than 3 days, filled with data from 1 day before/after using", "ds_ref_way": "", "ds_abstract": "
Extreme weather events are defined as small probability events where the weather (climate) state in a specific region deviates significantly from the average state during a specific time period. This dataset covers northern China (north of 35 ° N). The extreme climate event sequences in northern China from 1971 to 2020 were calculated using the threshold method and percentile method based on meteorological station data using R language. It includes 16 extreme temperature indicators, 11 extreme precipitation indicators, and extreme wind speed indicators, providing basic data support for regional climate disaster correlation research.", "ds_time_res": "年", "ds_acq_place": "Meteorological stations in northern China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
This study strictly follows the ETCCDI (Expert Group on Climate Change Detection and Indicators) indicator system in the World Meteorological Organization (WMO) Guidelines for Climate Change Detection and Indicators, and is based on daily meteorological observation data from northern China from 1971 to 2020. This dataset covers core elements such as daily maximum temperature, daily minimum temperature, daily precipitation, and sandstorm observation records. Through a multi-step standardized process in the R language environment, 29 core extreme climate indicators were calculated. The extreme wind speed calculation reference (Jiang et al. 2023) paper includes three threshold calculations for extreme wind speed and the number of annual sandstorms.\nIn the specific process, strict data quality control is first implemented on the original meteorological station data, eliminating outliers and missing data to ensure the reliability of basic data; Subsequently, two core methods were used to calculate extreme climate indicators: one was the absolute threshold method, which focused on calculating indicators such as maximum 1-day precipitation (RX1-day) and maximum 5-day precipitation (RX5day) that reflect the characteristics of precipitation extremes; The second method is the relative percentile method, which is used to calculate indicators such as heavy precipitation (R95p), extreme precipitation days (R20mm), precipitation intensity (SDII) that depend on the climate background of the reference period, ensuring the scientific and standardized calculation of indicators. \"", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "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, "belong_to_nieer": false, "ds_topic_tags": [ "中国北方", "极端气候", "1971-2020" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国北方气象站点" ], "ds_time_tags": [ 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 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 ], "ds_contributors": [ { "true_name": "苗运法", "email": "miaoyunfa@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": "赵永涛", "email": "zhaoyt2018@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": "张孜越", "email": "zhangziyue22@mails.ucas.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": "赵永涛", "email": "zhaoyt2018@lzb.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": "赵永涛", "email": "zhaoyt2018@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" }