改进频率分布和风速纠正的青藏高原格点降水数据集是一套适合青藏高原,经过风引起的降水观测损失订正和降水频率分布优化后的数据集。数据为NETCDF格式，时间分辨率为1天，水平空间分辨率10km。该数据可作为数值模式降水频率纠正的参考数据源。
\n该数据集使用了164个来自中国气象局和GSOD的日观测数据作为数据源。数据的生成分为4步：（1）首先对观测数据进行了质量控制，包括异常值和坏值去除等。（2）进行主要由风引起的观测损失补偿。（3）分别采用考虑海拔的样条函数插值月降水总量，普通克里金法插值日降水与月降水的比值，将两部分相乘得得到1km空间分辨率的数据。（4）将1km空间分辨率数据均值聚合到10km空间分辨率，得到最终数据。
\n相比国际同类格点降水数据，该数据进行了风引起的降水观测损失订正，同时通过插值方法的优化使其在降水量频率分布上更佳准确。该数据适合用于数值模式输出降水的统计偏差纠正或分析格点上的降水频率特征。
", "ds_source": "该数据集使用了164个来自中国气象局和GSOD的日观测数据作为数据源。数据的生成分为4步：（1）首先对观测数据进行了质量控制，包括异常值和坏值去除等。（2）进行主要由风引起的观测损失补偿。（3）分别采用考虑海拔的样条函数插值月降水总量，普通克里金法插值日降水与月降水的比值，将两部分相乘得得到1km空间分辨率的数据。（4）将1km空间分辨率数据均值聚合到10km空间分辨率，得到最终数据。投影信息：兰伯特等角圆锥投影（+proj=lcc +lat_1=30 +lat_2=35 +lat_0=30 +lon_0=87 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs）
", "ds_quality": "数据质量良好
", "ds_acq_start_time": "1980-01-01 00:00:00", "ds_acq_end_time": "2009-12-31 00:00:00", "ds_acq_place": "青藏高原", "ds_acq_lon_east": 99.0, "ds_acq_lat_south": 25.0, "ds_acq_lon_west": 70.0, "ds_acq_lat_north": 41.0, "ds_acq_alt_low": 30.0, "ds_acq_alt_high": 8844.0, "ds_share_type": "login-access", "ds_total_size": 1937465336, "ds_files_count": 2, "ds_format": "NC", "ds_space_res": "1000", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "兰伯特等角圆锥投影", "ds_thumbnail": "e02da0b1-28bd-4790-9adf-d39c4f355b49.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "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": "2020-11-16 08:15:34", "last_updated": "2023-06-13 09:53:47", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.nieer.2020.1686", "i18n": { "en": { "title": "Improved frequency distribution and wind speed correction for the Tibetan Plateau grid point precipitation dataset (1980-2009)", "ds_format": "NC", "ds_source": "Good data quality
", "ds_ref_way": "", "ds_abstract": "The Improved Frequency Distribution and Wind Corrected Precipitation Dataset for the Qinghai-Tibet Plateau is a dataset for the Qinghai-Tibet Plateau that has been revised for wind-induced precipitation losses and optimised for precipitation frequency distribution. The data is available in NETCDF format with a temporal resolution of 1 day and a horizontal spatial resolution of 10 km, and can be used as a reference data source for numerical model precipitation frequency correction.
\nThe dataset uses 164 daily observations from CMA and GSOD as the data source. The data were generated in four steps: (1) Firstly, quality control of the observations was performed, including outliers and bad value removal. (2) Compensation for observation losses mainly caused by wind was performed. (3) The monthly precipitation totals were interpolated using a spline function considering elevation, and the ratio of daily to monthly precipitation was interpolated using ordinary kriging, and the two parts were multiplied to obtain the 1km spatial resolution data. (4) Aggregate the 1km spatial resolution data to 10km spatial resolution to obtain the final data.
\nCompared to international comparable grid point precipitation data, this data has been revised for wind-induced precipitation observation losses and optimised for accuracy in precipitation frequency distributions through interpolation methods. The data are suitable for correcting statistical biases in the numerical model output of precipitation or for analysing the frequency characteristics of precipitation at grid points.
", "ds_time_res": "日", "ds_acq_place": "Qinghai Tibet Plateau", "ds_space_res": "1000", "ds_projection": "Lambert projection", "ds_process_way": "The dataset uses 164 daily observations from CMA and GSOD as the data source. The data were generated in four steps: (1) Firstly, quality control of the observations was performed, including outliers and bad value removal. (2) Compensation for observation losses mainly caused by wind was performed. (3) The monthly precipitation totals were interpolated using a spline function considering elevation, and the ratio of daily to monthly precipitation was interpolated using ordinary kriging, and the two parts were multiplied to obtain the 1km spatial resolution data. (4) Aggregate the 1km spatial resolution data to 10km spatial resolution to obtain the final data. Projection information: Lambert equirectangular conic projection (+proj=lcc +lat_1=30 +lat_2=35 +lat_0=30 +lon_0=87 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs)
", "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": [ "降水", "风速损失校正", "格点降水", "降水频率分布" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原" ], "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 ], "ds_contributors": [ { "true_name": "马佳培", "email": "jiapeima@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": "李弘毅", "email": "lihongyi@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_meta_authors": [ { "true_name": "马佳培", "email": "jiapeima@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": "马佳培", "email": "jiapeima@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" }