4.1 Article

A new mean-extreme vector for the trends of temperature and precipitation over China during 1960-2013

期刊

METEOROLOGY AND ATMOSPHERIC PHYSICS
卷 129, 期 3, 页码 273-282

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SPRINGER WIEN
DOI: 10.1007/s00703-016-0464-y

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资金

  1. National Natural Science Foundation of China [41330527]
  2. Natural Science Foundation of Jiangsu Province [BK20140046]
  3. priority academic program development of Jiangsu Higher Education institutions (PAPD)

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A mean-extreme (M-E) vector is defined to combine the changes of climate means and extremes. The direction of the vertical axis represents changes in means, whereas the direction of the horizontal axis represents changes in extremes. Therefore, the M-E vector can clearly reflect both the amplitude and direction of changes in climate means and extremes. Nine types of M-E vectors are defined. They are named as MuEu, MuEd, MuEz, MdEu, MdEd, MdEz, MzEu, MzEd, and MzEz. Here M and E stand for climate means and extremes, respectively, whereas u, d, and z indicate an upward, downward trend and no trend, respectively. Both temperature mean and extremely high temperature days are consistently increased (MuEu) in nearly whole China throughout four seasons. However, the MuEd-type vector dominates in some regions. The MuEd-type vector appears over the Huang Huai river basin in spring, summer and winter. For the M-E vector of temperature mean and extremely low temperature days, the MuEd-type spreads the entire China for all seasons. The M-E vector for precipitation mean and the extreme precipitation days possesses identical trends (MuEu or MdEd) despite of seasons. The MuEu-type dominates in northeastern China and west of 105A degrees E in spring, northwestern and central/southern China in summer, west of 100A degrees E and northeastern China in autumn, and nearly whole China in winter. Precipitation mean and extreme precipitation days are all decreased (MdEd) in the rest of China for all reasons. The trends relationship in means and extremes over China presented herein could provide a scientific foundation to predict change of extremes using change of mean as the predictor.

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