Spatiotemporal extremes of temperature and precipitation during 1960–2015 in the Yangtze River Basin (China) and impacts on vegetation dynamics

  • Lifang Cui
  • Lunche Wang
  • Sai Qu
  • Ramesh P. Singh
  • Zhongping Lai
  • Rui Yao
Original Paper

Abstract

Recently, extreme climate variation has been studied in different parts of the world, and the present study aims to study the impacts of climate extremes on vegetation. In this study, we analyzed the spatiotemporal variations of temperature and precipitation extremes during 1960–2015 in the Yangtze River Basin (YRB) using the Mann-Kendall (MK) test with Sen’s slope estimator and kriging interpolation method based on daily precipitation (P), maximum temperature (Tmax), and minimum temperature (Tmin). We also analyzed the vegetation dynamics in the YRB during 1982–2015 using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) datasets and investigated the relationship between temperature and precipitation extremes and NDVI using Pearson correlation coefficients. The results showed a pronounced increase in the annual mean maximum temperature (Tnav) and mean minimum temperature (Txav) at the rate of 0.23 °C/10 years and 0.15 °C/10 years, respectively, during 1960–2015. In addition, the occurrence of warm days and warm nights shows increasing trends at the rate of 1.36 days/10 years and 1.70 days/10 years, respectively, while cold days and cold nights decreased at the rate of 1.09 days/10 years and 2.69 days/10 years, respectively, during 1960–2015. The precipitation extremes, such as very wet days (R95, the 95th percentile of daily precipitation events), very wet day precipitation (R95p, the number of days with rainfall above R95), rainstorm (R50, the number of days with rainfall above 50 mm), and maximum 1-day precipitation (RX1day), all show pronounced increasing trends during 1960–2015. In general, annual mean NDVI over the whole YRB increased at the rate of 0.01/10 years during 1982–2015, with an increasing transition around 1994. Spatially, annual mean NDVI increased in the northern, eastern, and parts of southwestern YRB, while it decreased in the YRD and parts of southern YRB during 1982–2015. The correlation coefficients showed that annual mean NDVI was closely correlated with temperature extremes during 1982–2015 and 1995–2015, but no significant correlation with precipitation extremes was observed. However, the decrease in NDVI was correlated with increasing R95p and R95 during 1982–1994.

Notes

Acknowledgements

We would like to thank the China Meteorological Administration (CMA) for providing the meteorological and radiation data.

Funding Information

This work was financially supported by the National Natural Science Foundation of China (No. 41601044); the Special Fund for Basic Scientific Research of Central Colleges, China University of Geosciences, Wuhan (No. CUG150631, CUGL170401, and CUGCJ1704); and the 111 Project (Grant No. B08030).

References

  1. Aguilar E, Peterson TC, Obando PR, Frutos R, Retana JA, Solera M, Soley J, García IG, Araujo RM, Santos AR (2005) Changes in precipitation and temperature extremes in central America and northern South America, 1961–2003. J Geophys Res 110(D23):3233–3250CrossRefGoogle Scholar
  2. Aguilar E, Barry AA, Brunet M, Ekang L, Fernandes A, Massoukina M, Mbah J, Mhanda A, Nascimento DJD, Peterson TC (2009) Changes in temperature and precipitation extremes in western central Africa, Guinea Conakry, and Zimbabwe, 1955–2006. J Geophys Res Atmos 114(D2):356–360CrossRefGoogle Scholar
  3. Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Tank AMGK, Haylock M, Collins D, Trewin B, Rahimzadeh F (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res Atmos 111(D5):1042–1063CrossRefGoogle Scholar
  4. Alexander LV, Hope P, Collins D, Trewin B, Lynch A, Nicholls N (2012) Trends in Australia’s climate means and extremes: a global context. Aust Meteorol Mag 56(1):1–18Google Scholar
  5. Chaudhuri S, Dutta D (2014) Mann–Kendall trend of pollutants, temperature and humidity over an urban station of India with forecast verification using different ARIMA models. Environ Monit Assess 186(8):4719–4742CrossRefGoogle Scholar
  6. Chen B, Zhang X, Tao J, Wu J, Wang J, Shi P, Zhang Y, Yu C (2014a) The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau. Agric For Meteorol 189–190(189):11–18CrossRefGoogle Scholar
  7. Chen J, Wu X, Finlayson BL, Webber M, Wei T, Li M, Chen Z (2014b) Variability and trend in the hydrology of the Yangtze River, China: annual precipitation and runoff. J Hydrol 513(5):403–412CrossRefGoogle Scholar
  8. Chen YD, Zhang Q, Xiao M, Singh VP, Leung Y, Jiang L (2014c) Precipitation extremes in the Yangtze River Basin, China: regional frequency and spatial–temporal patterns. Theor Appl Climatol 116(3–4):447–461CrossRefGoogle Scholar
  9. Cui LF, Wang LC, Lai ZP, Tian Q, Liu W, Li J (2017) Innovative trend analysis of annual and seasonal air temperature and rainfall in the Yangtze River Basin, China during1960–2015. J Atmos Sol Terr Phys 164:48–59CrossRefGoogle Scholar
  10. Deng H, Chen Y, Shi X, Li W, Wang H, Zhang S, Fang G (2014) Dynamics of temperature and precipitation extremes and their spatial variation in the arid region of northwest China. Atmos Res 138(3):346–355CrossRefGoogle Scholar
  11. Ding Y, Chan JCL (2005) The east Asian summer monsoon: an overview. Meteorog Atmos Phys 89(1–4):117–142Google Scholar
  12. Duan H, Yan C, Tsunekawa A, Song X, Li S, Xie J (2011) Assessing vegetation dynamics in the Three-North Shelter Forest region of China using AVHRR NDVI data. Environ Earth Sci 64(4):1011–1020CrossRefGoogle Scholar
  13. Easterling DR, Alexander LV, Mokssit A, Detemmerman V (2003) CCI/CLIVAR workshop to develop priority climate indices. Bull Am Meteorol Soc 84(10):1403–1407CrossRefGoogle Scholar
  14. Frich P, Alexander L, Dellamarta P, Gleason B, Haylock M, Klein Tank A, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res 19(3):193–212CrossRefGoogle Scholar
  15. Fu G, Yu J, Yu X, Ouyang R, Zhang Y, Ping W, Liu W, Min L (2013) Temporal variation of extreme rainfall events in China, 1961–2009. J Hydrol 487(487):48–59CrossRefGoogle Scholar
  16. Guan Y, Zhang X, Zheng F, Wang B (2015) Trends and variability of daily temperature extremes during 1960–2012 in the Yangtze River Basin, China. Glob Planet Chang 124:79–94CrossRefGoogle Scholar
  17. Hamed KH (2008) Trend detection in hydrologic data: the Mann–Kendall trend test under the scaling hypothesis. J Hydrol 349(3–4):350–363CrossRefGoogle Scholar
  18. Juan D, Jie W, Wei Z (2012) Changes of climate extremes of temperature and precipitation in summer in eastern China associated with changes in atmospheric circulation in East Asia during 1960–2008. Sci Bull 57(15):1856–1861CrossRefGoogle Scholar
  19. Katz RW, Brown BG (1992) Extreme events in a changing climate: variability is more important than averages. Clim Chang 21(3):289–302CrossRefGoogle Scholar
  20. Kendall MG (1934) Rank correlation methods. Br J Psychol 25(1):86–91Google Scholar
  21. Kendall MG (1938) A new measure of rank correlation. Biometrika 30(1/2):81–93CrossRefGoogle Scholar
  22. Klein Tank AMG, Können GP (2003) Trends in indices of daily temperature and precipitation extremes in Europe, 1946–99. J Clim 16(22):3665–3680CrossRefGoogle Scholar
  23. Lehner B, Döll P, Alcamo J, Henrichs T, Kaspar F (2006) Estimating the impact of global change on flood and drought risks in Europe: a continental, integrated analysis. Clim Chang 75(3):273–299CrossRefGoogle Scholar
  24. Li Q, Yu M, Lu G, Cai T, Bai X, Xia Z (2011) Impacts of the Gezhouba and Three Gorges reservoirs on the sediment regime in the Yangtze River, China. J Hydrol 403(3–4):224–233CrossRefGoogle Scholar
  25. Li, Z., He, Y., Wang, P., Theakstone, W. H., An, W., Wang, X., Lu, A., Zhang, W. & Cao, W. (2012). Changes of daily climate extremes in southwestern China during 1961–2008. Glob Planet Chang, 80–81(80-81), 255–272Google Scholar
  26. Liang K, Peng B, Li J, Liu C (2014) Variability of temperature extremes in the Yellow River basin during 1961–2011. Quat Int 336(336):52–64CrossRefGoogle Scholar
  27. Lim YK, Schubert SD (2011) The impact of ENSO and the Arctic oscillation on winter temperature extremes in the southeast United States. Geophys Res Lett 38(15):98–106CrossRefGoogle Scholar
  28. Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245–259CrossRefGoogle Scholar
  29. Marengo JA, Jones R, Alves LM, Valverde MC (2010) Future change of temperature and precipitation extremes in South America as derived from the PRECIS regional climate modeling system. Int J Climatol 29(15):2241–2255CrossRefGoogle Scholar
  30. Milliman, J. D. & Farnsworth, K. L. (2011). River discharge to the coastal ocean—a global synthesisGoogle Scholar
  31. Pan WH, Li LA, Tsai MJ (1995) Temperature extremes and mortality from coronary heart disease and cerebral infarction in elderly Chinese. Lancet 345(8946):353–355CrossRefGoogle Scholar
  32. Pang, G., Wang, X. & Yang, M. (2016). Using the NDVI to identify variations in, and responses of, vegetation to climate change on the Tibetan Plateau from 1982 to 2012. Quaternary InternationalGoogle Scholar
  33. Peng SS, Chen AP, Xu L, Cao CX, Fang JY, Myneni RB, Pinzon JE, Tucker CJ, Piao SL (2011) Recent change of vegetation growth trend in China. Environ Res Lett 6(4):044027CrossRefGoogle Scholar
  34. Peng S, Piao S, Ciais P, Myneni RB, Chen A, Chevallier F, Dolman AJ, Janssens IA, Peñuelas J, Zhang G (2013) Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation. Nature 501(7465):88–92CrossRefGoogle Scholar
  35. Pettorelli N, Vik JO, Mysterud A, Gaillard JM, Tucker CJ, Stenseth NC (2005) Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol Evol 20(9):503–510CrossRefGoogle Scholar
  36. Piao S, Mohammat A, Fang J, Cai Q, Feng J (2006) NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China. Glob Environ Chang 16(4):340–348CrossRefGoogle Scholar
  37. Piao S, Yin G, Tan J, Cheng L, Huang M, Li Y, Liu R, Mao J, Myneni RB, Peng S (2015) Detection and attribution of vegetation greening trend in China over the last 30 years. Glob Chang Biol 21(4):1601–1609CrossRefGoogle Scholar
  38. Qian W, Lin X (2004) Regional trends in recent temperature indices in China. Clim Res 27(2):119–134CrossRefGoogle Scholar
  39. Qu S, Wang LC, Lin AW, Zhu HJ, Yuan MX (2018) What drives the vegetation restoration in Yangtze River basin, China: climate change or anthropogenic factors? Ecol Indic 90:438–450CrossRefGoogle Scholar
  40. Sang YF (2012) Spatial and temporal variability of daily temperature in the Yangtze River Delta, China. Atmos Res 112(112):12–24CrossRefGoogle Scholar
  41. Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389CrossRefGoogle Scholar
  42. Sheffield J, Wood EF, Roderick ML (2012) Little change in global drought over the past 60 years. Nature 491(7424):435–438CrossRefGoogle Scholar
  43. Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex B, Midgley BM (2013) IPCC, 2013: climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Comput Geom 18(2):95–123Google Scholar
  44. Su BD, Jiang T, Jin WB (2006) Recent trends in observed temperature and precipitation extremes in the Yangtze River basin, China. Theor Appl Climatol 83(1–4):139–151CrossRefGoogle Scholar
  45. Su B, Gemmer M, Jiang T (2008) Spatial and temporal variation of extreme precipitation over the Yangtze River Basin. Quat Int 186(1):22–31CrossRefGoogle Scholar
  46. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94CrossRefGoogle Scholar
  47. Tian Q, Prange M, Merkel U (2016) Precipitation and temperature changes in the major Chinese river basins during 1957–2013 and links to sea surface temperature. J Hydrol 536:208–221CrossRefGoogle Scholar
  48. Tucker CJ, Pinzon JE, Brown ME, Slayback DA, Pak EW, Mahoney R, Vermote EF, Saleous NE (2005) An extended AVHRR 8km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int J Remote Sens 26(20):4485–4498CrossRefGoogle Scholar
  49. Vicente-Serrano SM, Gouveia C, Camarero JJ, Beguería S, Trigo R, López-Moreno JI, Azorín-Molina C, Pasho E, Lorenzo-Lacruz J, Revuelto J (2013) Response of vegetation to drought time-scales across global land biomes. Proc Natl Acad Sci U S A 110(1):52–57CrossRefGoogle Scholar
  50. Vrieling A, Leeuw JD, Said MY (2013) Length of growing period over Africa: variability and trends from 30 years of NDVI time series. Remote Sens 5(2):982–1000CrossRefGoogle Scholar
  51. Wang Q, Zhang M, Wang S, Ma Q, Sun M (2014) Changes in temperature extremes in the Yangtze River Basin, 1962–2011. J Geogr Sci 24(1):59–75CrossRefGoogle Scholar
  52. Wang H, Chen A, Wang Q, He B (2015) Drought dynamics and impacts on vegetation in China from 1982 to 2011. Ecol Eng 75:303–307CrossRefGoogle Scholar
  53. Xie ZQ, Du Y, Zeng Y, Yan ML, Zhu CY (2010) Accelerated human activities affecting the spatial pattern of temperature in the Yangtze River Delta. Quat Int 226(1):112–121CrossRefGoogle Scholar
  54. Xu Y, Xu C, Gao X, Luo Y (2009) Projected changes in temperature and precipitation extremes over the Yangtze River Basin of China in the 21st century. Quat Int 208(1–2):44–52CrossRefGoogle Scholar
  55. Xu L, Myneni RB, Iii FSC, Callaghan TV, Pinzon JE, Tucker CJ, Zhu Z, Bi J, Ciais P, Tømmervik H (2013) Temperature and vegetation seasonality diminishment over northern lands. Nat Clim Chang 3(6):581–586CrossRefGoogle Scholar
  56. Xu Y, Yang J, Chen Y (2016) NDVI-based vegetation responses to climate change in an arid area of China. Theor Appl Climatol 126(1–2):213–222CrossRefGoogle Scholar
  57. Yang SL, Milliman JD, Xu KH, Deng B, Zhang XY, Luo XX (2014) Downstream sedimentary and geomorphic impacts of the Three Gorges Dam on the Yangtze River. Earth Sci Rev 138:469–486CrossRefGoogle Scholar
  58. Yao R, Wang L, Huang X, Guo X, Niu Z, Liu H (2017) Investigation of urbanization effects on land surface phenology in Northeast China during 2001–2015. Remote Sens 9(1)Google Scholar
  59. You Q, Kang S, Aguilar E, Pepin N, Flügel WA, Yan Y, Xu Y, Zhang Y, Jie H (2011) Changes in daily climate extremes in China and their connection to the large scale atmospheric circulation during 1961–2003. Clim Dyn 36(11–12):2399–2417CrossRefGoogle Scholar
  60. Zhang Q, Jiang T, Gemmer M, Becker S (2005) Precipitation, temperature and runoff analysis from 1950 to 2002 in the Yangtze basin, China. Hydrol Sci J 50(1):65–80CrossRefGoogle Scholar
  61. Zhang Q, Xu CY, Jiang T, Wu Y (2007) Possible influence of ENSO on annual maximum streamflow of the Yangtze River, China. J Hydrol 333(2–4):265–274CrossRefGoogle Scholar
  62. Zhang YL, Song CH, Zhang KR, Cheng XL, Band LE, Zhang QF (2014) Effects of land use/land cover and climate changes on terrestrial net primary productivity in the Yangtze River Basin, China, from 2001 to 2010. J Geophys Res Biogeosci 119(6):1092–1109CrossRefGoogle Scholar
  63. Zhang Q, Xiao M, Singh VP, Wang Y (2016) Spatiotemporal variations of temperature and precipitation extremes in the Poyang Lake basin, China. Theor Appl Climatol 124(3–4):855–864CrossRefGoogle Scholar
  64. Zhang Q, Kong D, Singh VP, Shi P (2017) Response of vegetation to different time-scales drought across China: spatiotemporal patterns, causes and implications. Glob Planet Chang 152:1–11CrossRefGoogle Scholar
  65. Zhao G, Mu X, Hörmann G, Fohrer N, Xiong M, Su B, Li X (2012) Spatial patterns and temporal variability of dryness/wetness in the Yangtze River Basin, China. Quat Int 282(1):5–13CrossRefGoogle Scholar
  66. Zhou A, Zhang A, Liu X, Cao S (2017) Spatiotemporal changes of normalized difference vegetaion index (NDVI) and response to climate extremes and ecoligical restoration in the Loess Plateau, China. Theor Appl Climatol 6:1–13Google Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  • Lifang Cui
    • 1
  • Lunche Wang
    • 1
  • Sai Qu
    • 2
  • Ramesh P. Singh
    • 3
  • Zhongping Lai
    • 1
  • Rui Yao
    • 1
  1. 1.Laboratory of Critical Zone Evolution, School of Earth SciencesChina University of GeosciencesWuhanChina
  2. 2.School of Resource and Environmental ScienceWuhan UniversityWuhanChina
  3. 3.School of Life and Environmental Sciences, Schmid College of Science and TechnologyChapman UniversityOrangeUSA

Personalised recommendations