SM2RAIN-CCI (1 Jan 1998 – 31 December 2015) global daily rainfall dataset

A NEW GLOBAL SCALE RAINFALL PRODUCT obtained from satellite soil moisture data through the SM2RAIN algorithm (<em>Brocca et al., 2014</em>), at 0.25 degree/daily spatial-temporal resolution, has been delivered (Ciabatta et al., 2018). The SM2RAIN method was applied to the ESA CCI soil moisture Active and Passive products (<em>Liu et al., 2011, 2012; Wagner et al., 2012</em>) for the period from January 1998 to December 2015 (18 years). The CCI-derived rainfall datasets (in mm/day) is gridded over a 0.25-degree grid on a global scale. The number of dates is 6574 (1998/01/01 – 2015/12/31). The product represents the cumulated rainfall between the 00:00 and the 23:59 UTC of the indicated day. A climatological correction has been applied to the data at monthly scale. The rainfall dataset is provided in netCDF format. A total of 18 netCDF files, one per year, are provided. The rainfall dataset is obtained by applying the SM2RAIN algorithm to the ESA CCI soil moisture Active and Passive products at version 03.1 separately. Then, an integration procedure based on a weighted average is applied in order to obtain the rainfall estimate. The algorithm has been calibrated during three different periods (1998-2001, 2002-2006 and 2007-2013) against the Global Precipitation Climatology Centre Full-Data daily dataset (GPCC-FDD, Schamm et al., 2015). The quality flag provided within the raw soil moisture observations has been used to mask out low quality data, as well as the areas characterized by high topographic complexity, high frozen soil and snow probability and presence of tropical forests. <strong>References</strong> Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. <em>Journal of Geophysical Research</em>, 119(9), 5128-5141, doi:10.1002/2014JD021489. Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S., Paulik, C., Dorigo, W., Kidd, R., and Wagner, W.: SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture, Earth Syst. Sci. Data, 10, 267-280, https://doi.org/10.5194/essd-10-267-2018, 2018. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436, doi:10.5194/hess-15-425-2011. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M., Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014. Schamm, K., Ziese, M., Raykova, K., Becker, A., Finger, P., Meyer-Christoffer, A., Schneider, U. (2015). GPCC Full Data Daily Version 1.0 at 1.0°: Daily Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data. DOI: 10.5676/DWD_GPCC/FD_D_V1_100. Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E., Ertl, M. (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321.本数据集为通过SM2RAIN算法（Brocca等，2014）由卫星土壤湿度数据反演得到的全球尺度降雨产品，时空分辨率为0.25°逐日，相关成果发表于Ciabatta等（2018）的研究中。 本研究将SM2RAIN方法应用于欧洲空间局气候变化倡议（ESA CCI）主动与被动微波土壤湿度产品（Liu等，2011、2012；Wagner等，2012），反演时段为1998年1月至2015年12月，共计18年。由ESA CCI土壤湿度数据反演得到的降雨数据集（单位：毫米/日）以0.25°网格实现全球网格化布设，时间序列共包含6574天，覆盖1998年1月1日至2015年12月31日。 该产品的降雨值为对应日期协调世界时（UTC）00:00至23:59的累积降雨量。已对数据集进行月度尺度的气候学校正。 本降雨数据集以网络通用数据格式（netCDF）存储，共包含18个单年度的netCDF文件。具体构建流程为：分别对版本号为03.1的ESA CCI主动与被动微波土壤湿度产品运行SM2RAIN算法，再基于加权平均的融合流程得到最终降雨反演结果。 本算法以全球降水气候学中心全数据逐日数据集（GPCC-FDD，Schamm等，2015）为参照标准，在1998-2001、2002-2006及2007-2013三个时段完成校准。原始土壤湿度观测数据中附带的质量标记已被用于剔除低质量观测，同时也对地形复杂度较高、冻土与积雪概率较高以及存在热带雨林的区域进行了掩膜处理。 ### 参考文献 1. Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). 以土壤作为天然雨量计：基于卫星土壤湿度数据反演全球降雨. *地球物理研究期刊*, 119(9), 5128-5141, doi:10.1002/2014JD021489. 2. Ciabatta, L., Massari, C., Brocca, L., Gruber, A., Reimer, C., Hahn, S., Paulik, C., Dorigo, W., Kidd, R. 及Wagner, W.: SM2RAIN-CCI：一款基于ESA CCI土壤湿度数据构建的全球长期降雨数据集, *地球系统科学数据*, 10, 267-280, https://doi.org/10.5194/essd-10-267-2018, 2018. 3. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). 融合主动与被动微波卫星反演数据构建改进型土壤湿度数据集. *水文学与地球系统科学*, 15, 425-436, doi:10.5194/hess-15-425-2011. 4. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M., Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 保留趋势的主动与被动微波土壤湿度反演数据融合方法, *环境遥感*, 123, 280-297, doi:10.1016/j.rse.2012.03.014. 5. Schamm, K., Ziese, M., Raykova, K., Becker, A., Finger, P., Meyer-Christoffer, A., Schneider, U. (2015). 1.0°分辨率GPCC全数据逐日版本1.0：基于全球电信系统（GTS）与历史雨量站数据构建的逐日陆地表面降雨数据集. DOI: 10.5676/DWD_GPCC/FD_D_V1_100. 6. Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E., Ertl, M. (2012). 融合主动与被动微波观测以构建土壤湿度关键气候变量数据记录, *国际摄影测量与遥感学会摄影测量、遥感与空间信息科学年报*, 第I-7卷, 第22届国际摄影测量与遥感学会大会, 澳大利亚墨尔本, 2012年8月25日-9月1日, 315-321.