最根本的区别在于,你是比较一个预测高再分析产品。这里的假设是,再分析提供最好的信息基于所有可用的测量使用最先进的造型。预测高另一方面模拟预测过程基于当前的模型和所有可用的观测,即它只利用观测预报的基础,然后运行一个预测在现实生活中就像一个预测系统。这可能还不错,但你看着预测交货时间为0到24小时如果您使用的是第一天。此外,gef是一个整体系统。这意味着它执行相同的预估几天开始使用不同的参数。通过这种方式,可以估计的不确定性预测系统。例如,如果某一天可用预测偏离很多,你可以假定有更高的预测不确定性。作为总结,我认为使用预测高数据比使用再分析数据需要更多的理由。使用整体信息可能是一个很好的理由使用gef预测高但也增加了一层复杂性。 Finally, allow me some general comments: - Have you considered using data from other services, most notably ECMWF? The [ERA-Interim][1] reanalysis is quite commonly used and has very good reputation. Or, as gansub pointed out, you can consider the [reanalysis by JMA][2]. - No matter which product you are using, do not take the results as "truth". You may find that interpolating down to an individual location requires more thought than people usually expect. For example, what happens if your location is a land location but falls into a sea pixel? This would greatly affect simulated 2m temperatures and the diurnal cycle. Using a neighbouring pixel in such cases may get you better results. - Speaking of the diurnal cycle, do you really care about daily means? In this kind of studies, I have seen people distinguish between day and night-time temperatures, which appeared to me as quite crucial. [1]: http://www.ecmwf.int/en/research/climate-reanalysis/era-interim [2]: http://jra.kishou.go.jp/JRA-55/index_en.html