全球地表温度观测数据集是全球变暖研究的基础。在全球变暖加剧的背景下和频繁的极端事件，必须提高覆盖率和降低全球地表温度数据集的不确定性。中国更新了全局合并地表温度临时版本 （CMST-Interim） 在本研究中达到 CMST 2.0。以前的 CMST 数据集由 将中国全球陆地地面气温（C-LSAT）与海洋合并来自扩展重建海面的表面温度 （SST） 数据温度版本 5 （ERSSTv5）。CMST 2.0 包含三种变体： CMST 2.0 − Nrec（无重建）、CMST 2.0 − Imax 和 CMST 2.0 − Imin （根据他们重建区域的海上空气温度北极地区的冰面）。重建的数据集显著提高了数据覆盖率，而 CMST 2.0 − Imax 和 CMST 2.0 − Imin 有所改善覆盖北半球，高达95%以上，因此增加了全球、半球和区域尺度的长期趋势从 1850 年到 2020 年。与 CMST-Interim、CMST 2.0 − Imax 和 CMST 2.0 − Imin 相比显示高空间覆盖范围扩展到高纬度地区，并且更多与极地地区多数据集平均值的参考一致。", "ds_source": "
1.C-LSAT2.0数据源\n
包括3个全球数据源（CRUTEM4、GHCN-V3 和 BEST）、三个区域数据源，以及8个国家原位数据源。\n
数据来源于https://www.ncei.noaa.gov/data/global-summary-of-the-day/archive/\n
2.海面温度：ERSSTv5\n
3.海冰表面空气温度：国际北极浮标计划（IABP） （http://research.jisao.washington.edu/data_sets/iabppoles/;", "ds_process_way": "
陆地和海洋部分的重建：通过对低频和高频分量求和，可以得到重建的陆地温度数据，最后对重建数据进行观测约束，以去除低质量的重建数据；用 ICOADS Release 3.0观测到的 SST anomaly 填充 1850-1853 年期间的数据，形成完整的 1850-2020 年月度 SST anomaly 数据集，然后用 Huang 等（2017 年）的 EOTs 对其进行重建，以减少缺失数据。\n
北极冰面温度重建：改进了北极地区的 ST 重建方法，将北极地区的 ST 用冰面气温来表示（考虑到冰与陆地相似的物理性质，将海冰视为陆地）。根据美国国家冰雪数据中心的数据，1980-2020 年间，3 月份海冰面积最大的年份是 1983 年，9 月份海冰面积最小的年份是 2012 年，因此我们设计了两个实验： (1) CMST 2.0 - Imax 使用 2 米气温代表北纬 65-90∘ 区域内的温度，模拟 1983 年 3 月北极海冰覆盖区域的 ST，即最大海冰范围。(2) CMST 2.0 - Imin 使用 2 米气温代表 80-90∘ N 区域内的温度，代表 2012 年 9 月北极海冰覆盖区域的 ST，即最小海冰范围。\n
重构CMST 2.0的不确定性估计：重建的 CMST 2.0 中的不确定性包括陆地和海洋的不确定性。海洋不确定性是 ERSSTv5 的不确定性。陆地不确定性基于重建的 C-LSAT2.0 组合，分为两部分：参数不确定性和重建不确定性。由于我们重建极地海冰区温度的方法与重建 LSAT 的方法相同，因此我们按照计算陆地不确定性的方法计算 CMST 2.0 - Imax 和 CMST 2.0 - Imin 的 65-90∘ N (Imax) 和 80-90∘ N (Imin) 区域的不确定性。", "ds_quality": "
由于观测资料有限，很难完全重建早期（例如 20 世纪 50 年代以前）南极上空的 SAT 和周围的 SST，这意味着 CMST 2.0 仍未实现 “全覆盖”。", "ds_acq_start_time": "1850-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 140.0, "ds_acq_lat_south": 0.0, "ds_acq_lon_west": 60.0, "ds_acq_lat_north": 60.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 85110184, "ds_files_count": 5, "ds_format": "nc", "ds_space_res": "", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "c09d62c8-98ab-4bd0-aedf-898e221c771d.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a4dd5849-78f2-44c5-b0f1-3450e952b2a2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2024-05-22 15:41:38", "last_updated": "2026-01-13 16:44:18", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.FIGSHARE.DB6475.2024", "i18n": { "en": { "title": "China Global Merged Land Surface Temperature Dataset (1850-2020)", "ds_format": "nc", "ds_source": "
1. C-LSAT2.0 Data Source\n
This includes three global data sources (CRUTEM4, GHCN-V3, and BEST), three regional data sources, and eight national in-situ data sources.\n
The data comes from https://www.ncei.noaa.gov/data/global-summary-of-the-day/archive/\n
2. Sea surface temperature: ERSSTv5\n
3. Sea ice surface air temperature: International Arctic Buoy Program (IABP)（ http://research.jisao.washington.edu/data_sets/iabppoles/ ;", "ds_quality": "
Due to limited observational data, it is difficult to fully reconstruct the early (such as before the 1950s) SAT over Antarctica and the surrounding SST, which means that CMST 2.0 has not yet achieved \"full coverage\".", "ds_ref_way": "", "ds_abstract": "
The global surface temperature observation dataset is the foundation of global warming research. Against the backdrop of intensified global warming and frequent extreme events, it is necessary to increase coverage and reduce the uncertainty of global surface temperature datasets. China has updated the Global Consolidated Surface Temperature Interim (CMST Interim) to achieve CMST 2.0 in this study. The previous CMST dataset was developed by merging China's global land surface temperature (C-LSAT) with ocean surface temperature (SST) data from extended reconstruction of sea surface temperature (ERSSTv5). CMST 2.0 includes three variants: CMST 2.0-Nrec (no reconstruction), CMST 2.0-Imax, and CMST 2.0-Imin (based on the reconstructed sea air temperature of the Arctic ice surface). The reconstructed dataset significantly improves data coverage, while CMST 2.0-Imax and CMST 2.0-Imin have improved coverage in the northern hemisphere, reaching over 95%, thus increasing long-term trends at global, hemisphere, and regional scales from 1850 to 2020. Compared with CMST Interim, CMST 2.0-Imax, and CMST 2.0-Imin, it shows that the high spatial coverage extends to high latitude regions and is more consistent with the reference of multi dataset averages in polar regions.
", "ds_time_res": "年", "ds_acq_place": "China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Reconstruction of land and ocean components: By summing the low-frequency and high-frequency components, reconstructed land temperature data can be obtained. Finally, observation constraints are applied to the reconstructed data to remove low-quality reconstruction data; Fill the data from 1850-1853 with SST anomaly observed in ICOADS Release 3.0 to form a complete monthly SST anomaly dataset from 1850-2020, and then reconstruct it using Huang et al.'s (2017) EOTs to reduce missing data.\n
Arctic ice surface temperature reconstruction: Improved the ST reconstruction method for the Arctic region, representing the ST in the Arctic region as ice surface temperature (considering the similar physical properties of ice and land, sea ice is treated as land). According to data from the National Snow and Ice Data Center in the United States, from 1980 to 2020, the year with the largest sea ice area in March was 1983, and the year with the smallest sea ice area in September was 2012. Therefore, we designed two experiments: (1) CMST 2.0- Imax uses 2-meter temperature to represent the temperature in the 65-90 ∘ north latitude region, simulating the ST of the Arctic sea ice coverage area in March 1983, which is the maximum sea ice extent. (2) CMST 2.0- Imin uses 2-meter temperature to represent the temperature within the 80-90 ∘ N region, representing the ST of the Arctic sea ice coverage area in September 2012, which is the minimum sea ice extent.\n
Estimation of Uncertainty in Reconstructed CMST 2.0: The uncertainty in reconstructed CMST 2.0 includes uncertainty in both land and ocean. Ocean uncertainty is the uncertainty of ERSSTv5. Land uncertainty is based on the reconstructed C-LSAT2.0 combination, which is divided into two parts: parameter uncertainty and reconstruction uncertainty. Since our method for reconstructing the temperature of polar sea ice is the same as that for reconstructing LSAT, we calculated the uncertainty in the 65-90 ∘ N (Imax) and 80-90 ∘ N (Imin) regions of CMST 2.0- Imax and CMST 2.0- Imin using the same method for calculating land uncertainty.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "海面温度（SST）", "地表气温2.0", "中国" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 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": "李庆祥", "email": "liqingx5@mail.sysu.edu.cn", "work_for": "中山大学大气科学学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "李庆祥", "email": "liqingx5@mail.sysu.edu.cn", "work_for": "中山大学大气科学学院", "country": "中国" } ], "ds_managers": [ { "true_name": "李庆祥", "email": "liqingx5@mail.sysu.edu.cn", "work_for": "中山大学大气科学学院", "country": "中国" } ], "category": "遥感及产品" }