Model Data Comparison(模型数据比较)研究综述
Model Data Comparison 模型数据比较 - Hence, the coarse ocean resolution of typical palaeo-GCMs lead to a challenge for model-data comparison in past climates. [1] Suggestions for improving standard DIC algorithms to enable quantitative model-data comparison are discussed. [2] We developed new methods for model-data comparison which help to objectively compare the stochastic results to the observations. [3] Parameters estimated with data from the 5 cm soil depth had better model-data comparisons than parameters estimated with data from the 10 cm soil depth. [4] Models’improvement relies on model-data comparisons for past periods. [5] These simulations extend the pool of current ESM simulations into the 1st millennium CE and represent an important basis to assess the models’ response to external forcing and improved model-data comparison. [6] Our aim is that the documentation of the large-scale features and model-data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability, and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols. [7] Model-data comparison shows that if that latter effect exists, it has small consequences for the observed case. [8] Proper knowledge of the dating uncertainties in paleoclimatic ice core records is important for a rigorous propagation to further analyses; for example for identification and dating of stadial-interstadial transitions during glacial intervals, for model-data comparisons in general, or to provide a complete uncertainty quantification of early warning signals. [9] Model-data comparisons show that the developed model here is potentially useful and efficient for investigating the inevitable wave-current-structure interaction problems in aquaculture technologies. [10] Our aim is that the documentation of the large scale features and model-data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability; and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols . [11] The documented distribution of facies and sequence-stratigraphic framework combined with a virtual outcrop model were used as a reference to perform geometric (quantitative) and architectural and stacking pattern (qualitative) research by model-data comparison. [12] The adjustable parameters are fixed from the comprehensive model-data comparison. [13] Results of this model-data comparison were used to assess the likely boundary conditions for the MCO and MMCT, and inferred TAM elevations of 300-500 m lower than present-day, modelled CO2 concentrations up to 780 ppm during periods of peak warmth, and a transition to lower CO2 across the MMCT. [14] The results 25 point to possible improvements in future model-data comparison studies utilizing historical written records. [15] Fay and coauthors aim to improve the global net air-sea CO2 flux estimate and ease model-data comparisons by making a diversity of pCO2 data products (n=6) with methodological differences more consistent and releasing the results as a new data product: SeaFlux. [16] Comparing these two data sources over a period with changing background conditions requires new methods for model-data comparison that incorporate multiple types and sources of uncertainty. [17] The common boundary conditions should enable consistent multi model and model-data comparisons. [18] Sea surface temperature and pseudo-δ18O are used in model-data comparisons to assess the potential influence of hydroclimate change on records. [19] Model performance was assessed based on the model-data comparisons. [20] Extensive model-data comparison demonstrated that the model could satisfactorily reproduce the oceanic structure and 137Cs concentrations in the seawater and seabed sediment. [21]因此，典型古 GCM 的粗海洋分辨率导致过去气候模式数据比较的挑战。 [1] 讨论了改进标准 DIC 算法以实现定量模型数据比较的建议。 [2] 我们开发了新的模型数据比较方法，有助于客观地将随机结果与观察结果进行比较。 [3] 用 5 cm 土壤深度的数据估计的参数比用 10 cm 土壤深度的数据估计的参数具有更好的模型数据比较。 [4] 模型的改进依赖于过去时期的模型数据比较。 [5] 这些模拟将当前 ESM 模拟池扩展到 CE 第一千年，并代表了评估模型的重要基础’对外部强迫的响应和改进的模型数据比较。 [6] 我们的目标是，本文介绍的大规模特征和模型数据比较的文档将为进一步研究铺平道路，以更详细地探索模型模拟的各个方面，例如海洋环流、水文循环和变异模式，并鼓励对古地理、轨道配置和气溶胶等方面的敏感性研究。 [7] 模型数据比较表明，如果存在后一种效应，它对观察到的情况的影响很小。 [8] 正确了解古气候冰芯记录中的测年不确定性对于进一步分析的严格传播很重要；例如，用于识别和确定冰川间隔期间的星间过渡，用于一般的模型数据比较，或提供早期预警信号的完整不确定性量化。 [9] 模型-数据比较表明，这里开发的模型对于研究水产养殖技术中不可避免的波-流-结构相互作用问题具有潜在的有用性和有效性。 [10] 我们的目标是，本文介绍的大尺度特征和模型数据比较的文档将为进一步研究更详细地探索模型模拟的各个方面铺平道路，例如海洋环流、水文循环和变异模式；并鼓励对古地理、轨道配置和气溶胶等方面的敏感性研究</div> </div> </div>。 [11] 记录的相分布和层序地层框架结合虚拟露头模型被用作参考，通过模型数据比较进行几何（定量）和建筑和堆积模式（定性）研究。 [12] 可调参数是从综合模型数据比较中确定的。 [13] 该模型-数据比较的结果用于评估 MCO 和 MMCT 可能的边界条件，并推断 TAM 海拔比现在低 300-500 m，在温暖高峰期模拟的 CO2 浓度高达 780 ppm，以及通过 MMCT 向更低的 CO2 过渡。 [14] 结果 25 指出利用历史书面记录的未来模型数据比较研究可能会有所改进。 [15] Fay 和合著者的目标是通过使方法学差异更加一致的各种 pCO2 数据产品 (n=6) 并将结果作为新数据产品发布来改进全球净海气 CO2 通量估计并简化模型数据比较：SeaFlux . [16] 将这两个数据源在一段时间内与不断变化的背景条件进行比较需要新的模型数据比较方法，该方法包含多种类型和不确定性来源。 [17] 共同的边界条件应该能够实现一致的多模型和模型数据比较。 [18] 海面温度和拟δ18O 用于模型数据比较，以评估水文气候变化对记录的潜在影响。 [19] 基于模型数据比较评估模型性能。 [20] 广泛的模型数据比较表明，该模型可以令人满意地再现海洋结构和海水和海底沉积物中的 137Cs 浓度。 [21]