Abstract

An experimental technique is introduced for controlling atmospheric diabatic heating in a fully-coupled climate model (NCEP Climate Forecast System version 2), with the motivation of better understanding the role of tropical forcing in modulating the Indian summer monsoon and contributing to global seasonal prediction skill. The ‘added heating’ mechanistic approach has the benefit of not interfering with any internal model feedbacks. The approach is applied in an iterative fashion to correct bias in the three-dimensional tropical heating over the Indo-Pacific, defined as the difference between the model ensemble mean heating and that estimated from ERA-Interim. The June through September seasonal mean, trend and parabolic fit in diabatic heating are corrected for each year separately over a 20-year set of seasonal re-forecasts, resulting in a 60–90% reduction in the mean-squared error of Indo-Pacific heating from an initial set of control re-forecasts, two-thirds of which is associated with the climatological bias. This results in higher skill in the climatological mean and inter-annual variability of local low-level winds and the underlying sea surface temperature (SST). Improvements are most significant over the equatorial Indian Ocean with a removal of the climatological low-level westerly bias and SST gradient bias along with substantially more skill in inter-annual variability. Although there is very little improvement in the model rainfall over India, there is improvement in the low-level circulation. The lack of significant improvement in rainfall prediction may be partly related to the representation of convection and/or the coarse resolution grid of the model.

Highlights

1. 1.

   An added heating technique is used to correct the ensemble mean atmospheric diabatic heating over the tropical Indo-Pacific in a set of climate re-forecasts.

2. 2.

   The approach in this study reduces the mean squared error in the heating by 60–90% without interfering with any internal model feedbacks.

3. 3.

   In response to heating corrections, there is significant bias correction in local low-level winds and sea surface temperature, particularly over the Indian Ocean.

4. 4.

   Despite no improvement in the simulation of rainfall over India, through teleconnections there is some improvement in the monsoon circulation.

中文翻译：

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更好地了解印度季风变异性的热带强迫成分的建模框架

摘要

引入了一种实验技术来控制全耦合气候模型中的大气非绝热加热（NCEP气候预测系统版本2），其动机是更好地了解热带强迫在调节印度夏季风中的作用并有助于全球季节性预报。“增加加热”机制的好处是不会干扰任何内部模型反馈。该方法以迭代方式应用，以校正印度洋-太平洋上三维热带加热中的偏差，该偏差定义为模型集合平均加热与ERA-Interim估算的之间的差。在20年的季节性重新预测中，每年分别校正6月至9月的非均质加热季节平均值，趋势和抛物线拟合，从而从最初的一组对照预测中得出，印度太平洋太平洋加热的均方误差降低了60-90％，其中三分之二与气候偏差有关。这样可以提高当地低水平风的气候平均值和年际变化以及海平面下温（SST）的技能。赤道印度洋的改善最为显着，它消除了气候学低水平的西风偏向和SST梯度偏向，并大大提高了年际变化的技巧。尽管印度的模型​​降雨几乎没有改善，但低空环流有所改善。降雨预报缺乏重大改进的部分原因可能与对流和/或模型的粗分辨率网格的表示有关。

强调

1. 1。

   在一系列气候重新预测中，使用了一种附加的加热技术来校正热带印度太平洋上的整体平均非绝热加热。

2. 2。

   本研究中的方法将加热的均方误差降低了60–90％，而不会干扰任何内部模型反馈。

3. 3。

   响应于加热校正，局部低层风和海面温度，特别是印度洋上空，存在明显的偏差校正。

4. 4。

   尽管印度的降雨模拟没有改善，但通过遥距连接，季风环流还是有所改善。