CDAT数据集包含1979-2018年期间中国近地表气温数据，本产品集成了多个数据源，如再分析数据（ERA5、CMFD）、遥感数据 （MODIS）和原位数据，并通过结合温度策略来区分晴朗的天空和非晴朗的天空天气条件来获得。 对于Tmax，使用原位数据的验证表明，均方根误差(RMSE)范围为0.86°C至1.78°C，平均绝对误差(MAE)范围为0.63°C至1.40°C，皮尔逊系数(R2)范围为0.96至0.99。Tmin的RMSE为0.78°C ~ 2.09°C, MAE为0.58°C ~ 1.61°C, R2为0.95 ~ 0.99。对于Tavg, RMSE范围为0.35°C ~ 1.00°C, MAE范围为0.27°C ~ 0.68°C, R2范围为0.99 ~ 1.00。此外，利用多种评价指标分析Ta的时空变化趋势，Tavg增加幅度大于0.0°C/a，与全球变暖的总体趋势一致。 综上所述，该数据集具有较高的空间分辨率和可靠的精度，弥补了之前在高空间分辨率下缺失的温度值(Tmax、Tmin和Tavg)。该数据集也为研究气候变化，特别是高温干旱和低温冷害提供了关键参数。\n
XXXX_TYPE.zip：它包含CDAT的数据。它包含120个文件夹（每个文件夹代表一年的温度类型），包括Tmax，T分钟和Tavg。时间范围为1979年1月至2018年12月。\n
XXXX 是这一年。TYPE 是温度类型，命名为最大、最小、avg。每个阶段由两个文件组成，包括 *.TIF（CDAT 图像） 和 *.TFW（TIFF 图像坐标信息）。", "ds_source": "
本产品集成了多个数据源，如再分析数据（ERA5、CMFD）、遥感数据 （MODIS）和原位数据，并通过结合温度策略来区分晴朗的天空和非晴朗的天空天气条件来获得。", "ds_process_way": "
针对不同的天气条件建立了不同的Ta重建模型，并通过建立不同区域的修正方程进一步提高数据精度。", "ds_quality": "
对于Tmax，使用原位数据的验证表明，均方根误差(RMSE)范围为0.86°C至1.78°C，平均绝对误差(MAE)范围为0.63°C至1.40°C，皮尔逊系数(R2)范围为0.96至0.99。Tmin的RMSE为0.78°C ~ 2.09°C, MAE为0.58°C ~ 1.61°C, R2为0.95 ~ 0.99。对于Tavg, RMSE范围为0.35°C ~ 1.00°C, MAE范围为0.27°C ~ 0.68°C, R2范围为0.99 ~ 1.00。此外，利用多种评价指标分析Ta的时空变化趋势，Tavg增加幅度大于0.0°C/a，与全球变暖的总体趋势一致。由于南海诸岛缺乏早期气象台站观测数据，数据质量无法保证，不能在此给出。", "ds_acq_start_time": "1979-01-01 00:00:00", "ds_acq_end_time": "2018-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 136.69, "ds_acq_lat_south": 15.75, "ds_acq_lon_west": 71.28999999999999, "ds_acq_lat_north": 58.64, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "open-access", "ds_total_size": 15403317357, "ds_files_count": 122, "ds_format": "tif", "ds_space_res": "0.1°", "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "5a845a59-8d89-440f-a183-2b50fd915c59.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "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": "2023-05-29 11:17:04", "last_updated": "2025-06-30 16:24:13", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB6683.2024", "i18n": { "en": { "title": "Chinese Near Earth Surface Daily Temperature Dataset (1979-2018)", "ds_format": "tif", "ds_source": "
This product integrates multiple data sources, such as reanalysis data (ERA5, CMFD), remote sensing data (MODIS), and in-situ data, and is obtained by combining temperature strategies to distinguish between clear and non clear sky weather conditions.", "ds_quality": "
For Tmax, validation using in-situ data shows that the root mean square error (RMSE) ranges from 0.86 ° C to 1.78 ° C, the mean absolute error (MAE) ranges from 0.63 ° C to 1.40 ° C, and the Pearson coefficient (R2) ranges from 0.96 to 0.99. The RMSE of Tmin is 0.78 ° C~2.09 ° C, MAE is 0.58 ° C~1.61 ° C, and R2 is 0.95~0.99. For Tavg, the RMSE range is 0.35 ° C~1.00 ° C, the MAE range is 0.27 ° C~0.68 ° C, and the R2 range is 0.99~1.00. In addition, using multiple evaluation indicators to analyze the spatiotemporal trend of Ta, the increase in Tavg is greater than 0.0 ° C/a, which is consistent with the overall trend of global warming. Due to the lack of observation data from early meteorological stations in South China Sea Islands, the data quality cannot be guaranteed and cannot be given here.", "ds_ref_way": "", "ds_abstract": "
The CDAT dataset contains near surface temperature data of China from 1979 to 2018. This product integrates multiple data sources, such as reanalysis data (ERA5, CMFD), remote sensing data (MODIS), and in-situ data, and distinguishes between clear and non clear sky weather conditions by combining temperature strategies. For Tmax, validation using in-situ data shows that the root mean square error (RMSE) ranges from 0.86 ° C to 1.78 ° C, the mean absolute error (MAE) ranges from 0.63 ° C to 1.40 ° C, and the Pearson coefficient (R2) ranges from 0.96 to 0.99. The RMSE of Tmin is 0.78 ° C~2.09 ° C, MAE is 0.58 ° C~1.61 ° C, and R2 is 0.95~0.99. For Tavg, the RMSE range is 0.35 ° C~1.00 ° C, the MAE range is 0.27 ° C~0.68 ° C, and the R2 range is 0.99~1.00. In addition, using multiple evaluation indicators to analyze the spatiotemporal trend of Ta, the increase in Tavg is greater than 0.0 ° C/a, which is consistent with the overall trend of global warming. In summary, this dataset has high spatial resolution and reliable accuracy, which compensates for the missing temperature values (Tmax, Tmin, and Tavg) previously observed at high spatial resolution. This dataset also provides key parameters for studying climate change, especially high temperature drought and low temperature cold damage.\n
XXXXTYPE. zip: It contains data for CDAT. It contains 120 folders (each representing a temperature type for one year), including Tmax, T minutes, and Tavg. The time range is from January 1979 to December 2018.\n
XXXX is this year. TYPE is a temperature type, named as maximum, minimum avg。 Each stage consists of two files, including * TIF (CDAT image) and * TFW (TIFF Image Coordinate Information).
", "ds_time_res": "日", "ds_acq_place": "China", "ds_space_res": "0.1°", "ds_projection": "", "ds_process_way": "Different Ta reconstruction models were established for different weather conditions, and data accuracy was further improved by establishing correction equations for different regions.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [ "空气温度", "日尺度", "中国", "近地表" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 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 ], "ds_contributors": [ { "true_name": "毛克彪", "email": "maokebiao@caas.cn", "work_for": " 中国农业科学院农业资源与农业区划研究所遥感室", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "毛克彪", "email": "maokebiao@caas.cn", "work_for": " 中国农业科学院农业资源与农业区划研究所遥感室", "country": "中国" } ], "ds_managers": [ { "true_name": "毛克彪", "email": "maokebiao@caas.cn", "work_for": " 中国农业科学院农业资源与农业区划研究所遥感室", "country": "中国" } ], "category": "遥感及产品" }