商业文章代写:气候模型研究

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03/11/2020

商业文章代写:气候模型研究

正如前面所提到的,对这些模型、它们的比较以及其他方面的清晰理解将使气候预测比现在更准确。当前,地表平均温度、海平面压力、模型中的相关偏差以及更多的挑战对气候预测的全面理解。在对季节降水的认识和云辐射预报方面仍存在较大的误差。科学家们正在寻找减少这种错误的方法,并为此合作成立了CMIP,该机构研究耦合模型并对它们进行评估,以了解它们的比较工作、相似点、错误和发展领域。本研究对不同模型(八种模型)的比较提供了一个清晰的理解。

其次,研究工作通过其比较也告诉读者,不同的气候因素纳入模型研究如何导致其本身的错误和偏见问题。例如,一些观察到的研究工作强调了在热带海洋盆地研究时,低云层可能被低估,或者另外一些研究可能没有解释云层的缺乏等(Durrant & Greenslade, 2012)。另一方面,通过合作研究,可以得到更好的云参数化。在MOC振幅的表示上,海冰的变化越来越逼真。

商业文章代写:气候模型研究

最后,即使研究致力于理解模型比较,每天仍会增加更多无关的数据。在预测气候变化方面,大数据现象导致了前所未有的大量过剩数据。在孤立地研究气候变化的时代,许多不同的因素被包括在联合。例如,在使用这些模型时可以研究硫酸盐气溶胶的间接影响。随着时间的推移,这些研究工作的形式意味着对模型的比较分析也必须随着时间的推移而更新(Meehl等人,2009)。需要进一步的分析和调查来关注发展,因此与其他CMIP5模型的比较变得至关重要。

1.4。研究结构

本文遵循标准的论文结构。下一个重要的章节是文献综述。文献综述介绍了这八种不同模型的背景、结构细节、特点和研究观点。虽然文献综述的目的是只讨论每个模型和一些比较细节也包括在内。主要的比较作为一个单独的章节进行,根据模型的异同点和计算网格的四个参数对模型进行比较。2)时间步。3)控制方程(风分量),4)耦合(大气-海洋)。

商业文章代写:气候模型研究

As presented earlier, a clear understanding of the models, their comparison and more would make climatic prediction more accurate than what it is today. In current times, the surface mean temperature, the seal level pressure, the related biases in models and more challenges a thorough understanding of climatic prediction. There are still major errors in the understanding of seasonal precipitation, and in cloud radiative forecasts. Scientists are looking into ways to reduce such errors and to that effect have collaborated to form the CMIP which studies coupled models and assesses them to understand their comparative working, similarities, errors and areas of development. This research presents a clear understanding of the comparisons of the different models (eight models).

Secondly, the research work through its comparisons also informs the reader of how different climatic elements incorporated into the model study leads itself to errors and bias issues. For instance, some research works observed highlight how low clouds might be underestimated when studied over tropical ocean basins or alternatively some studies might not account for lack of cloudiness etc (Durrant & Greenslade, 2012). On the other hand, with a collaborative study, better cloud parametrizations are present. Representation of MOC amplitude, the sea ice and more become more realistic.

美国论文代写:气候模型研究

Finally, even with research being devoted to understanding model comparison, more extraneous data are added daily. Big data phenomenon has driven much surplus data than never before in predicting climate changes. Where climate changes were studied in isolation, in current times, many different elements are included in conjunctions. For instance, indirect effects of sulphate aerosols might be studied when using these models. These forms of research works over time means the comparative analysis of the models must also be updated over time (Meehl et al., 2009). Further analysis and investigations are needed for focusing on the developments and hence the comparison with other CMIP5 models becomes crucial.

1.4. Research Structure

A standard dissertation structure was followed here. The next important chapter is the literature review. The literature review presents the background, configuration details, features and research view on the eight different models. While the intention of the literature review is to only discuss each of the models and some comparative details are also included. The main comparison is carried out as a separate chapter in which each of the model is compared based on similarities and differences and also based on the four parameters of 1) computation grid. 2) time step. 3) governing equations (wind component), 4) coupling (Atmosphere-Ocean).

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