Theoretical and Applied Climatology

, Volume 123, Issue 3–4, pp 757–768

Spatiotemporal characteristics of precipitation concentration and their possible links to urban extent in China

Original Paper

Abstract

Extreme precipitation has been reported to occur more frequently, and intensified extreme precipitation can cause considerable socioeconomic losses. Extreme precipitation can be measured by the concentration index (CI) and the precipitation concentration index (PCI). The former indicates the degree to which daily precipitation is unevenly distributed in the time domain, and the latter represents the degree to which monthly precipitation is unevenly distributed throughout the year. In this paper, we analyzed spatiotemporal characteristics of extreme precipitation by using CI and PCI and examined whether links exist between extreme precipitation and urban extent. We found that the spatial patterns of PCI and CI are different over China. The two are consistent in being high in Northeast China and low in Southwest China. However, they differ significantly; Northwest China is where CI is low but PCI is high, which indicates that precipitation is highly concentrated in a few months of the year, but daily precipitation is more evenly distributed during the wet season in Northwest China. The trends of both PCI and annual CI are spatially heterogeneous and are significant at the 90 % confidence level for approximately 20 % of China, and seasonal CI exhibits very different trends. Possible links between precipitation concentration and urbanization are investigated by analyzing the correlation coefficient between CI (PCI) and population density. Precipitation concentration is found positively correlated with urbanization at the 99 % confidence level in the three selected regions.

References

  1. Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank A, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Ambenje P, Rupa Kumar K, Revadekar J, Griffiths G, Vincent L, Stephenson D, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Vazquez Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res Atmos (1984–2012) 111(D5). doi:10.1029/2005JD006290
  2. Alijani B, O’Brien J, Yarnal B (2008) Spatial analysis of precipitation intensity and concentration in Iran. Theor Appl Climatol 94:107–124. doi:10.1007/s00704-007-0344-y CrossRefGoogle Scholar
  3. Cannarozzo M, Noto LV (2006) Spatial distribution of rainfall trends in Sicily (1921–2000). Phys Chem Earth 31:1201–1211CrossRefGoogle Scholar
  4. Cortesi N, Gonzalez-Hidalgo (2012) Daily precipitation concentration across Europe 1971–2010. Nat Hazards Earth Syst Sci 12:2799–2810CrossRefGoogle Scholar
  5. De Luis M, Gonzalez-Hidalgo JC, Raventos J, Sanchez JR, Cortina J (1997) Distribucion espacial de la concentracion y agresividad de la lluvia en el territorio de la Comunidad Valenciana. Cuaternarioy Geomorfologia 11:33–44Google Scholar
  6. De Luis M, Gonzalez-Hidalgo JC (2011) Precipitation concentration changes in Spain 1946–2005. Nat Hazards Earth Syst Sci 11:1259–1265CrossRefGoogle Scholar
  7. Donat MG, Peterson TC, Brunet M (2013) Changes in extreme temperature and precipitation in the Arab region: long-term trends and variability related to ENSO and NAO. Int J Climatol. doi:10.1002/joc.3707 Google Scholar
  8. Groisman PY, Knight RW (2005) Trends in intense precipitation in the climate record. J Clim 18(9):1326–1350. doi:10.1175/JCLI3339.1 CrossRefGoogle Scholar
  9. Huang J, Sun SL (2013) Detection of trends in precipitation during1960–2008in Jiangxi province, southeast China. Theor Appl Climatol 114:237–251CrossRefGoogle Scholar
  10. Hutchinson MF (1998) Interpolation of rainfall data with thin plate smoothing splines. Part II: Analysis of topographic dependence. J Geogr Inf Decis Anal 2(2):152–167Google Scholar
  11. Kašpar M, Müller M (2014) Combinations of large-scale circulation anomalies conducive to precipitation extremes in the Czech Republic. Atmos Res 138:205–212CrossRefGoogle Scholar
  12. Kenneth (1999) Temporal fluctuations in weather and climate extremes that cause economic and human health impacts: A review. Bull Am Meteorol Soc 11:1078–1099Google Scholar
  13. King AD, Alexander LV, Donat MG (2013) The efficacy of using gridded data to examine extreme rainfall characteristics: A case study for Australia. Int J Climatol 33(10):2376–2387CrossRefGoogle Scholar
  14. Knapp AK, Beier C (2008) Consequences of more extreme precipitation regimes for terrestrial ecosystems. Bioscience 58(9):811–821CrossRefGoogle Scholar
  15. Kusaka H, Nawata K, Suzuki-Parker A, Takane Y, Furuhashi N (2014) Mechanism of precipitation increase with urbanization in Tokyo as revealed by ensemble climate simulations. J Appl Meteorol Climatol 53(4):824–839CrossRefGoogle Scholar
  16. Li XM, Jiang FQ, Li LH, Wang GG (2011) Spatial and temporal variability of precipitation concentration index, concentration degree and concentration period in Xinjiang, China. Int J Climatol 31:1679–1693Google Scholar
  17. Liu W, Zhang M, Wang S, Wang B, Li F, Che Y (2013) Changes in precipitation extremes over Shanxi Province, northwestern China, during 1960-2011. Quat Int 313–314:118–129CrossRefGoogle Scholar
  18. Lorenz M (1905) Methods of measuring the concentration of wealth. Am Stat Assoc 9:209–219Google Scholar
  19. Mao R, Gong DY, Yang J, Bao JD (2012) Linkage between the Arctic Oscillation and winter extreme precipitation over central-southern China. Clim Res 50(2):187CrossRefGoogle Scholar
  20. Martin-Vide J (2004) Spatial distribution of a daily precipitation concentration index in Peninsular Spain. Int J Climatol 24:959–971CrossRefGoogle Scholar
  21. Min SK, Zhang X, Zwiers (2011) Human contribution to more-intense precipitation extremes. Nature 470(7334):378–381. doi:10.1038/nature09763 CrossRefGoogle Scholar
  22. NMIC (National Meteorological Information Center) (2012) Assessment Report of China’s Ground Precipitation 0.5° × 0.5° 0Gridded Dataset(V2.0). NMIC, BeijingGoogle Scholar
  23. Oliver JE (1980) Monthly precipitation distribution: a comparative index. Prof Geogr 32:300–309CrossRefGoogle Scholar
  24. Sang YF, Wang Z, Li Z, Liu C, Liu X (2013) Investigation into the daily precipitation variability in the Yangtze River Delta, China. Hydrol Process 27(2):175–185CrossRefGoogle Scholar
  25. Shaw G, Wheeler D (1994) Statistical Techniques in Geographical Analysis. Halsted Press, New YorkGoogle Scholar
  26. Shepherd JM (2005) A review of current investigations of urban-induced rainfall and recommendations for the future. Earth Interact 9(12):1–27CrossRefGoogle Scholar
  27. Shi P, Qiao XY, Chen X, Zhou M, Qu SM, Ma XX, Zhang ZC (2014) Spatial distribution and temporal trends in daily and monthlyprecipitation concentration indices in the upper reaches of the Huai River, China. Stoch Env Res Risk Assess 28:201–212Google Scholar
  28. Simpson IR, Jones PD (2013) Analysis of UK precipitation extremes derived from Met Office gridded data. Int J Climatol. doi:10.1002/joc.3850 Google Scholar
  29. Tao WK, Chen JP, Li Z, Wang C, Zhang C (2012) Impact of aerosols on convective clouds and precipitation. Rev Geophys 50(2). doi:10.1029/2011RG000369
  30. Vittal H, Karmakar S, Ghosh S (2013) Diametric changes in trends and patterns of extreme rainfall over India from pre-1950 to post-1950. Geophys Res Lett 40:3253–3258. doi:10.1002/grl.50631 CrossRefGoogle Scholar
  31. Wang Y, Zhou L (2005) Observed trends in extreme precipitation events in China during 1961–2001 and the associated changes in large-scale circulation. Geophys Res Lett 32, L09707. doi:10.1029/2005GL022574 Google Scholar
  32. Wang WG, Xing WQ, Yang T, Shao QX, Peng SZ, Yu ZB, Yong B (2013a) Characterizing the changing behaviors of precipitation concentration in the Yangtze River Basin, China. Hydrol Process 27:3375–3393Google Scholar
  33. Wang SJ, Zhang MJ, Sun MP, Wang BL, Li XF (2013b) Changes in precipitation extremes in alpine areas of the Chinese Tianshan Mountains, central Asia, 1961-2011. Quat Int 311:97–107Google Scholar
  34. Wang X, Liao J, Zhang J, Shen C, Chen W, Xia B, Wang T (2014) A Numeric Study of Regional Climate Change Induced by Urban Expansion in the Pearl River Delta, China. J Appl Meteorol Climatol 53(2):346–362CrossRefGoogle Scholar
  35. Yang L, Villarini G, Smith JA, Tian F, Hu H (2013) Changes in seasonal maximum daily precipitation in China over the period 1961–2006. Int J Climatol 33(7):1646–1657CrossRefGoogle Scholar
  36. Yang L, Smith JA, Baeck ML, Bou-Zeid E, Jessup SM, Tian F, Hu H (2014) Impact of urbanization on heavy convective precipitation under strong large-scale forcing: A case study over the Milwaukee–Lake Michigan region. J Hydrometeorol 15(1):261–278CrossRefGoogle Scholar
  37. Zhai P, Zhang X, Wan H, Pan X (2005) Trends in total precipitation and frequency of daily precipitation extremes over China. J Clim 18(7):1096–1108CrossRefGoogle Scholar
  38. Zhang Q, Xu CY, Marco G, Chen YP, Liu CL (2009) Changing properties of precipitation concentration in the Pearl River basin, China. Stoch Env Res Risk A 23:377–385CrossRefGoogle Scholar
  39. Zhang X, Alexander L, Hegerl GC, Jones P (2011) Indices for monitoring changes in extremes based on daily temperature and precipitation data. WIREs Clim Change 2(6):851–870. doi:10.1002/wcc.147 CrossRefGoogle Scholar
  40. Zhang K, Pan S, Cao L, Wang Y, Zhao Y, Zhang W (2014) Spatial distribution and temporal trends in precipitation extremes over the Hengduan Mountains region, China, from 1961 to 2012. Quat Int 349:346-356. doi:10.1016/j.quaint.2014.04.050
  41. Zhao Y, Zou X, Cao L, Xu X (2014) Changes in precipitation extremes over the Pearl River Basin, southern China, during 1960-2012. Quat Int 333:26–39CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2015

Authors and Affiliations

  1. 1.Department of Water Resources and Environment, School of Geography Science and PlanningSun Yat-sen UniversityGuangzhouPeople’s Republic of China
  2. 2.Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education InstituteSun Yat-sen UniversityGuangzhouPeople’s Republic of China
  3. 3.School of Urban Planning and Environmental ScienceLiaoning Normal UniversityDalianPeople’s Republic of China

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