Abstract
This study analyzes the ability of statistical downscaling models in simulating the long-term trend of temperature and associated causes at 48 stations in northern China in January and July 1961–2006. The statistical downscaling models are established through multiple stepwise regressions of predictor principal components (PCs). The predictors in this study include temperature at 850 hPa (T850), and the combination of geopotential height and temperature at 850 hPa (H850+T850). For the combined predictors, Empirical Orthogonal Function (EOF) analysis of the two combined fields is conducted. The modeling results from HadCM3 and ECHAM5 under 20C3M and SERS A1B scenarios are applied to the statistical downscaling models to construct local present and future climate change scenarios for each station, during which the projected EOF analysis and the common EOF analysis are utilized to derive EOFs and PCs from the two general circulation models (GCMs). The results show that (1) the trend of temperature in July is associated with the first EOF pattern of the two combined fields, not with the EOF pattern of the regional warming; (2) although HadCM3 and ECHAM5 have simulated a false long-term trend of temperature, the statistical downscaling method is able to well reproduce a correct long-term trend of temperature in northern China due to the successful simulation of the trend of main PCs of the GCM predictors; (3) when the two-field combination and the projected EOF analysis are used, temperature change scenarios have a similar seasonal variation to the observed one; and (4) compared with the results of the common EOF analysis, those of the projected EOF analysis have been much more strongly determined by the observed large-scale atmospheric circulation patterns.
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References
Benestad, R. E., 2001: A comparison between two empirical downscaling strategies. Int. J. Climatol., 21, 1645–1668.
—, 2002a: Empirically downscaled multi-model ensemble temperature and precipitation scenarios for Norway. J. Climate., 15, 3008–3027.
—, 2002b: Empirically downscaled temperature scenarios for northern Europe based on a multi-model ensemble. Climatic. Res., 21(2), 105–125.
—, I. Bauer-hanssen, and D. Chen, 2008: Empirical-Statistical Downscaling. World Scientific Publishing Company, 300 pp.
Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data. J. Climate, 5, 541–560.
Fan Lijun, 2006: Statistical downscaling of local and regional climate scenarios over China. Ph. D. dissertation. Institute of Atmospheric Physics, Chinese Academy of Sciences, 32–46.
—, 2009: Statistically downscaled temperature scenarios over China. Atmospheric and Oceanic Science Letters, 2(4), 208–213.
—, Fu Congbin, and Chen Deliang, 2005: Review on creating future climate change scenarios by statistical downscaling techniques. Adv. Earth Sci., 20(3), 320–329.
—, —, and —, 2007: Estimation of local temperature change scenarios in North China using the statistical downscaling method. Chinese J. Atmos. Sci., 31(5), 887–897.
Hu, Z., S. Yang, and R. Wu, 2003: Long-term climate variations in China and global warming signals. Journal of Geophysical Research, 108(D19), 4614, doi: 10.1029/2003JD0033651.
Huth, R., 2002: Statistical downscaling of daily temperature in central Europe. J. Climate, 15, 1731–1742.
—, 2004: Sensitivity of local daily temperature change estimates to the 432 selection of downscaling models and predictors. J. Climate, 17, 640–652.
IPCC, 2007: The IPCC Fourth Assessment Report: Climate Change 2007, 918 pp.
Gao, X. J., Z. C. Zhao, and F. Giorgi, 2002: Changes of extreme events in regional climate simulations over East Asia. Adv. Atmos. Sci., 19, 927–942.
—, Z. C. Zhao, and Y, H. Ding, 2003: Climate change due to greenhouse effects in Northwest China as simulated by a regional climate model. J. Glaciol. Geocryol., 25(2), 165–169.
—, J. S. Pal, and F. Giorgi, 2006: Projected changes in mean and extreme precipitation over the Mediterranean region from a high resolution double nested RCM simulation. Geophys. Res. Lett., 33, L03706, doi:10.1029/2005GL024954.
Sun, J., H. Chen, S. Zhao, Q. Zeng, Z. Xie, J. Cui, and H. Liu, 1999: A study on the severe hot weather in Beijing and North China. Part II: Simulation and analysis. Climatic and Environmental Research, 4, 334–345.
Wilks, D. S., 1995: Statistical Methods in the Atmospheric Science. Academic Press, 467 pp.
Winkler, J. A., J. P. Palutikof, and J. A. Andresen, 1997: The simulation of daily temperature time series from GCM output. Part II: Sensitivity analysis of an empirical transfer function methodology. J. Climate, 10, 2514–2535.
Xie, Z., J. Cui, H. Liu, S. Zhao, J. Sun, H. Chen, and Q. Zeng, 1999: A study on the severe hot weather in Beijing and North China. Part I: Statistics and synoptic case study. Climatic and Environmental Research, 4, 323–333.
Xu, Y., Y. Zhang, E. Lin, W. Lin, W. Dong, J. Richard, H. David, and W. Simon, 2006: Analyses on the climate change responses over China under SRES B2 scenario using PRECIS. Chinese Science Bulletin, 51, 2260–2267.
Zhou, T., and R. Yu, 2006: Twentieth-century surface air temperature over China and the Globe simuated by coupled climate models. J. Climate, 19, 5843–5858.
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Supported by the National Natural Science Foundation of China (40705030), Knowledge Innovation Project (KZCX2-EW-202) and Strategic Priority Research Program (XDA05090103) of the Chinese Academy of Sciences.
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Fan, L., Fu, C. & Chen, D. Long-term trend of temperature derived by statistical downscaling based on EOF analysis. Acta Meteorol Sin 25, 327–339 (2011). https://doi.org/10.1007/s13351-011-0308-0
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DOI: https://doi.org/10.1007/s13351-011-0308-0