Prediction of Northern Hemisphere Regional Surface Temperatures Using Stratospheric Ozone Information
Prediction of Northern Hemisphere Regional Surface Temperatures Using Stratospheric Ozone Information
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DOI：
10.1029/2018jd029626
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发表时间：
2019-06
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影响因子：
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通讯作者：
K. Stone;S. Solomon;D. Kinnison;Cory F. Baggett;E. Barnes
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文献类型：
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作者：
K. Stone;S. Solomon;D. Kinnison;Cory F. Baggett;E. Barnes
以前曾报告过北方半球特定地点的模式和观测结果显示春季平流层臭氧极端值与随后的地表温度之间的相关性。在这里，我们第一次量化了臭氧信息在北方半球季节预报中的潜在用途，使用观测数据和一个九成员化学气候模式集合。三月总柱臭氧（TCO）和四月地面温度之间的合奏合成相关显示了类似的结构，观测，但略低的相关幅度。这可能是由于大量的情况下，平滑了模式中的采样误差，这是可见的，从个别合奏成员计算的相关性之间的差异。使用一个线性回归模型与3月TCO作为预测因子，预测以下4月的表面温度在显示大的相关性的地区是可能的4年后的回归模型结束日期在个别合奏成员，长达6年的观察。我们创建了一个经验预测模型来预测所观察到的以及使用三月TCO模拟的表面温度异常的迹象。通过三年的交叉验证方法，我们发现3月TCO可以很好地预测欧亚大陆部分地区4月地表温度异常的迹象，这些地区显示出最低的模型内部变异性。
Correlations between springtime stratospheric ozone extremes and subsequent surface temperatures have been previously reported for both models and observations at particular locations in the Northern Hemisphere. Here we quantify for the first time the potential use of ozone information for Northern Hemisphere seasonal forecasts, using observations and a nine‐member chemistry climate model ensemble. The ensemble composite correlations between March total column ozone (TCO) and April surface temperatures display a similar structure to observations, but with slightly lower correlation magnitudes. This is likely due to the larger number of cases smoothing out sampling error in the pattern, which is visible in the difference between correlations calculated from individual ensemble members. Using a linear regression model with March TCO as the predictor, predictions of the following April surface temperatures in regions that show large correlations are possible up to 4 years following the regression model end date in individual ensemble members, and up to 6 years in observations. We create an empirical forecast model to predict the sign of the observed as well as the modeled surface temperature anomalies using March TCO. Through a leave‐three‐years‐out cross‐validation method, we show that March TCO can forecast the sign of the April surface temperature anomalies well in parts of Eurasia that show the lowest model internal variability.