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Arctic summer storm track in CMIP3/5 climate models

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Abstract

Model performance and future projection of Arctic summertime storm-track activity and associated background states are assessed on the basis of Coupled Model Intercomparison Project Phase 3 (CMIP3)/5 (CMIP5) climate models. Despite some improvement in the CMIP5 models relative to the CMIP3 models, most of the climate models underestimate summertime storm-track activity over the Arctic Ocean compared to six reanalysis data sets as measured locally as the variance of subweekly fluctuations of sea level pressure. Its large inter-model spread (i.e., model-to-model differences) is correlated with that of the intensity of the Beaufort Sea High and the lower-tropospheric westerlies in the Arctic region. Most of the CMIP3/5 models project the enhancement of storm-track activity over the Arctic Ocean off the eastern Siberian and Alaskan coasts, the region called the Arctic Ocean Cyclone Maximum, in association with the strengthening of the westerlies in the warmed climate. A model with stronger enhancement of the storm-track activity tends to accompany stronger land-sea contrast in surface air temperature across the Siberian coast, which reflects greater surface warming over the continent and slower warming over the Arctic Ocean. Other processes, however, may also be likely to contribute to the future changes of the storm-track activity, which gives uncertainty in the projection by multiple climate models. Our analysis suggests that further clarification of those processes that influence storm-track activity over the Arctic is necessary for more reliable future projections of the Arctic climate.

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Notes

  1. A recent study found a maximum also in winter around the same domain based on the Arctic System Reanalysis (ASR) interim, which are not clear in global reanalysis data (Tilinina et al. 2014).

  2. We only use CMIP5 models because some of data are not available for some of CMIP3 models.

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Acknowledgments

KN and HN are supported in part by the Japanese Ministry of Environment through the Environment Research and Technology Development Fund A-1201 and by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) through a Grant-in-Aid for Scientific Research in Innovative Areas 2205. KN is supported by MEXT also through the GRENE Arctic Climate Change Research Project. YO is supported by the Norwegian Research Council East Asian DecCen Project (193690). We acknowledge the World Climate Research Program’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank all contributing climate modeling groups. The U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provided coordination and support for CMIP, and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We also acknowledge the “Data Integration and Analysis System” Fund (DIAS) for National Key Technology and the Innovative Program of Climate Change Projection for the 21st Century (“Kakushin” program) from MEXT.

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Authors and Affiliations

  1. Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8904, Japan

    Kazuaki Nishii & Hisashi Nakamura

  2. NILU - Norwegian Institute for Air Research, Instituttveien 18, 2027, Kjeller, Norway

    Yvan J. Orsolini

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  1. Kazuaki Nishii
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Correspondence to Kazuaki Nishii.

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Appendix: Partial correlation and regression

Appendix: Partial correlation and regression

Consider three variables of X i , Y i , and Z i , and linear regression equations among them:

$$X_{i} = a_{x} Z_{i} + b_{x} + \in_{xi} ,$$
$$Y_{i} = a_{y} Z_{i} + b_{y} + \in_{yi} ,$$

where a x , b x , a y , and b y are constant. Then residuals ε xi and ε yi are not correlated with Z i . Correlation between ε xi and ε yi is the partial correlation between X i and Y i without influence of Z i . Regression coefficient of ε yi onto ε xi is partial regression of Y i onto X i without influence of Z i .

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Nishii, K., Nakamura, H. & Orsolini, Y.J. Arctic summer storm track in CMIP3/5 climate models. Clim Dyn 44, 1311–1327 (2015). https://doi.org/10.1007/s00382-014-2229-y

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