GECCO3 Ocean Synthesis (nativ grid 41S6m)
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The GECCO3 ocean synthesis is the German contribution of the Estimating the Circulation and Climate of the Ocean project (ECCO, see references) and is the new version of the GECCO2 synthesis already available at ICDC. The synthesis also uses the adjoint method to adjust the initial temperature and salinity in 1948 together with the air temperature, humidity, precipitation, shortwave radiation, and zonal and meridional wind every 10 days to bring the model into consistency with the data, which derive from the EN4.2.1 data base AVISO along track SLA, DTU10 mean sea surface minus GOCO5s geoid to yield the mean dynamic topography, HadISST SST, and the WOA18 climatology. The global model is based on the MITgcm model, has 40 levels, and uses the horizontal and vertical grid of the ocean component of MPI-ESM in the MR/HR configuration, which is with nominally 0.4° resolution eddy-permitting. The bathymetry is also adopted from this configuration. The background atmospheric state is taken from the 6 hourly NCEP/NCAR Reanalysis 1. <strong>GECCO3 and GECCO3S6m</strong> The GECCO3 synthesis covers the period 1948-2018 and, unlike GECCO2, is optimized over only one assimilation window. The state after 41 iterations is available. There are two versions of the synthesis, which differ in the time constant of the relaxation of the surface salinity. For the present version 41S6m a time constant of 180 days was used. Globally and averaged over all data types, there is a slight advantage for the stronger relaxation. However, an evaluation with ESA-CCI surface salinity data for the years 2011-2018 showed a somewhat more realistic variability with less relaxation. In other variables that were examined, mainly differences between the two products on multi-decade time scales were found. The difference between the products gives an impression of the robustness of the estimate, but it must be taken into account that only one aspect was changed. Overall, the GECCO3S6m version can be recommended. <strong>Model:</strong> MITgcm <br> <strong>Resolution:</strong> 0.4°, 40 z-levels, partial cells <br> <strong>Data assimilated:</strong> EN4.2.1 T/S (XBT corrected)+ AVISO along track SLA , GOCO5s MDT, HadISST SST, WOA18 climatology <br> <strong>Assimilation method: </strong>4D-VAR (adjoint) method <br> <strong>Forcing and relaxation used:</strong> NCEP RA1 atm. Fields, Bulk formulae, Large and Yeager, 2009 <strong>Coverage, spatial and temporal resolution</strong> Period and temporal resolution: 1948-2018 monthly SSH (daily upon request) Coverage and spatial resolution: Global Spatial resolution: curvilinear nativ model grid Dimension: 800x400x40 Altitudes: 40 depth levels Format: NetCDF4 <strong>Data quality</strong> Variational methods fit the trajectory best during the middle section of the assimilation period. During the first few years spin-up effects are noticeable such that the variability during this period should be considered with care. Changes in the densities and type of assimilated data leave signatures in the product, in particular noticeable in year 1992 and at the beginning of the 2000s during the advent of altimeter and Argo data. <strong>References</strong> Köhl, A. (2020), Evaluating the GECCO3 1948-2018 Ocean Synthesis - a configuration for initializing the MPI-ESM climate model, Q. J. R. Met. Soc., doi: 10.1002/qj.3790. https://doi.org/10.1002/qj.3790
GECCO3海洋合成数据集是海洋环流与气候估算计划（Estimating the Circulation and Climate of the Ocean，简称ECCO，详见参考文献）的德国贡献成果，亦是已在国际气候数据中心（ICDC）发布的GECCO2合成数据集的全新版本。该合成数据集同样采用伴随方法，于1948年对初始温度与盐度，以及每10天更新一次的气温、湿度、降水、短波辐射、纬向与经向风进行调整，以使模型与观测数据相一致，所用数据源自EN4.2.1数据库、AVISO沿轨海平面高度异常（SLA）、基于DTU10平均海平面减去GOCO5s大地水准面得到的平均动力地形、HadISST海表温度（SST）以及WOA18气候态数据。该全球海洋模型基于MITgcm模型构建，包含40个垂直层，采用MPI-ESM海洋分量在MR/HR配置下的水平与垂直网格，该配置的名义分辨率为0.4°，具备涡旋分辨能力。地形数据同样源自该配置。背景大气状态取自每6小时一次的NCEP/NCAR再分析1数据集（NCEP/NCAR Reanalysis 1）。 **GECCO3与GECCO3S6m版本** GECCO3合成数据集的时间覆盖范围为1948-2018年，与GECCO2不同，其仅在单个同化窗口内完成优化。迭代41次后的模型状态可供使用。该合成数据集包含两个版本，二者的核心差异在于表层盐度松弛的时间常数不同。本版本41S6m采用了180天的时间常数。从全球尺度及所有数据类型的平均表现来看，更强的松弛方案具备小幅优势。然而，针对2011-2018年ESA-CCI表层盐度数据的评估显示，采用更弱松弛方案的版本呈现出更贴近真实的变率特征。在其余被考察的变量中，两类产品的差异主要体现在年代际时间尺度上。二者的差值可用于评估估算结果的鲁棒性，但需注意仅改变了表层盐度松弛这一个参数。总体而言，推荐使用GECCO3S6m版本。 **模型：** MITgcm **分辨率：** 0.4°，40个Z型垂直层，部分单元格 **同化数据：** EN4.2.1温盐数据（经XBT校正）、AVISO沿轨海平面高度异常数据、GOCO5s平均动力地形（MDT，基于DTU10平均海平面与GOCO5s大地水准面计算得到）、HadISST海表温度数据以及WOA18气候态数据 **同化方法：** 四维变分（4D-VAR，伴随）方法 **所用强迫与松弛方案：** NCEP RA1大气场、Bulk通量公式（Large和Yeager, 2009） **覆盖范围与时空分辨率** 时间范围与时间分辨率： 1948-2018年，月均数据；海平面高度（SSH）数据可按需提供日尺度数据 空间覆盖范围与空间分辨率： 全球范围；空间分辨率：曲线原生模型网格；维度：800×400×40；垂直深度层数：40层 **数据格式：** NetCDF4 **数据质量** 变分同化方法在同化周期的中段能够最佳匹配观测轨迹。在初始数年，模型会出现显著的自旋调整效应，因此需谨慎对待该时段内的变率特征。同化数据的密度与类型变更会在产品中留下特征信号，这在1992年以及21世纪初（高度计与Argo浮标数据投入使用的时期）尤为显著。 **参考文献** Köhl, A. (2020), 评估GECCO3 1948-2018海洋合成数据集——一种用于初始化MPI-ESM气候模型的配置方案，《皇家气象学会季刊》（Q. J. R. Met. Soc.），doi: 10.1002/qj.3790. https://doi.org/10.1002/qj.3790
