Development of Precise Precipitation Data for Assessing the Potential Impacts of Climate Change

  • Akiyo YatagaiEmail author
  • Vinay Kumar
  • Tiruvalam N. Krishnamurti
Part of the The Anthropocene: Politik—Economics—Society—Science book series (APESS, volume 18)


In this chapter we introduce the rain-gauge-based grid precipitation data APHRODITE, and show an experimental result of applying the synthetic super-ensemble (SSE) method to winter precipitation over the Middle East. As the change in precipitation according to climate variation is essential, in this study we used the precise observational precipitation as well as the outputs of numerical simulations. The APHRODITE precipitation data is widely used for understanding monsoon variability, various downscaling for impact assessment studies of global warming and validating precipitation estimates from satellites and models. Since the rain-gauge products are more accurate than those of satellites and used as ‘teacher’ data in various situations, APHRODITE is used for the SSE method developed at Florida State University. It is a unique method to combine several model outputs and precise observation data to make the best forecast. We first show the application of SSE to the Middle East area. We used the simulated precipitation of the five coupled general circulation model (CGCM) outputs, which are part of the CMIP5 project. The five models were chosen due to the availability of the APHRODITE model data up to 2007, along with the 10 years of (1997/1998–2006/2007) monthly precipitation (December, January and February) over the Middle East region (20°E–65°E, 15°N–45°N).

For the seasonal climate forecasts, a SSE technique was used and a cross-validation technique was adopted, in which the year to be forecasted was excluded from the calculations for obtaining the regression coefficients. As a result, seasonal forecasts of the Middle East precipitation were considerably improved by the use of APHRODITE rain-gauge-based data. These forecasts are much superior to those from the best model of our suite and ensemble mean. The use of statistical downscaling and SSE for multi-model forecasts of seasonal climate significantly improved precipitation prediction at higher resolution.

These results demonstrate that high-resolution precipitation data from a dense network of rain gauges is essential for improving seasonal rainfall estimation over the Middle Eastern region. However, unfortunately, SSE does not represent the large-scale decreasing trend pattern, except in the eastern part of Turkey and part of Israel.


APHRODITE CMIP5 Fertile Crescent Synthetic Super Ensemble 


  1. Bentsen M, Bethke I, Debernard JB, Iversen T, Kirkevåg A, Seland Ø, Drange H, Roelandt C, Seierstad IA, Hoose C, Kristjánsson JE (2012) The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation. Geoscientific Model Devevelopment Discussions 5:2843–2931. Scholar
  2. Chakraborty A, Krishnamurti TN (2009) Improving global model precipitation forecasts over India from downscaling and FSU super-ensemble. Part II: Seasonal climate. Monthly Weather Review 137:2736–2757.CrossRefGoogle Scholar
  3. Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology 33:140–158.CrossRefGoogle Scholar
  4. Hamada A, Arakawa O, Yatagai A (2011) An automated quality control method for daily rain gauge data. Global Environmental Research 15:165–172.Google Scholar
  5. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965‒1978.CrossRefGoogle Scholar
  6. IPCC (2013) Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge: Cambridge University Press.Google Scholar
  7. Kamiguchi K, Arakawa O, Kitoh A, Yatagai A, Hamada A, Yasutomi N (2010) Development of APHRO_JP, the first Japanese high-resolution daily precipitation product for more than 100 years. Hydrological Research Letters 4:60–64.CrossRefGoogle Scholar
  8. Kitoh A, Yatagai A, Alpert P (2008) First super-high-resolution model projection that the ancient “Fertile Crescent” will disappear in this century. Hydrological Research Letters 2:1–4.CrossRefGoogle Scholar
  9. Krishnamurti TN, Mishra AK, Simon A, Yatagai A (2009) Use of a Dense Rain-gauge Network over India for Improving Blended TRMM Products and Downscaled Weather Models. Journal of the Meteorological Society of Japan 87A:393–412. Scholar
  10. Krishnamurti TN, Kumar V (2012) Improved seasonal precipitation forecasts for the Asian Monsoon using a large suite of atmosphere ocean coupled models. Journal of Climate 25:65–88.CrossRefGoogle Scholar
  11. Kumar V, Krishnamurti TN (2012) Improved seasonal precipitation forecasts for the Asian Monsoon using a large suite of atmosphere ocean coupled models. Journal of Climate 25:39–64.CrossRefGoogle Scholar
  12. Schmidt GA, Kelley M, Nazarenko L, Ruedy R, Russell GL, Aleinov I, Bauer M, Bauer SE, Bhat MK, Bleck R, Canuto V, Chen YH, Cheng Y, Clune TL, Del Genio A, De Fainchtein R, Faluvegi G, Hansen JE, Healy RJ, Kiang NY, Koch D, Lacis AA, LeGrande AN, Lerner J, Lo KK, Matthews EE, Menon S, Miller RL, Oinas V, Oloso AO, Perlwitz JP, Puma MJ, Putman WM, Rind D, Romanou A, Sato M, Shindell DT, Sun S, Syed RA, Tausnev N, Tsigaridis K, Unger N, Voulgarakis A, Yao MS, Zhang J (2013) Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive. Journal of Advances in Modeling Earth Systems 6(1):141–184.CrossRefGoogle Scholar
  13. Voldoire A, Sanchez-Gomez E, Salas, Mélia D, Decharme B, Cassou C, Sénési S, Valcke S, Beau I, Alias A, Chevallier M, Déqué M, Deshayes J, Douville H, Fernandez E, Madec G, Maisonnave E, Moine MP, Planton S, Saint-Martin D, Szopa S, Tyteca S, Alkama R, Belamari S, Braun A, Coquart L, Chauvin F (2012) The CNRM-CM5.1 global climate model: description and basic evaluation. Climate Dynamics 40(9):2091–2121. Scholar
  14. Xie P, Yatagai A, Chen M, Hayasaka T, Fukushima Y, Liu C, Yang S (2007) A gauge-based analysis of daily precipitation over East Asia. Journal of Hydrometeorology 8:607–627.CrossRefGoogle Scholar
  15. Yatagai A, Xie P, Alpert P (2008) Development of a daily gridded precipitation data set for the Middle East. Advances in Geosciences 12:165–170.CrossRefGoogle Scholar
  16. Yatagai A (2011) Trends in orographic rainfall over the Fertile Crescent, Middle East. Global Environmental Research 15:147–156.Google Scholar
  17. Yatagai A, Kamiguchi K, Arakawa O, Hamada A, Yasutomi N, Kitoh A (2012) APHRODITE: Constructing a Long-term Daily Gridded Precipitation Dataset for Asia based on a Dense Network of Rain Gauges. American Meteorological Society 93:1401–1415. Scholar
  18. Yatagai A, Krishnamurti TN, Kumar V, Mishra AK, Simon A (2014) Use of APHRODITE rain-gauge-based precipitation and TRMM3B43 products for improving Asian monsoon seasonal precipitation forecasts. Journal of Climate 27:1062–1069.CrossRefGoogle Scholar
  19. Yukimoto S, Adachi Y, Hosaka M, Sakami T, Yoshimura H, Hirabara M, Tanaka TY, Shindo E, Tsujino H, Deushi M, Mizuta R, Yabu S, Obata A, Nakano H, Koshiro T, Ose T, Kitoh A (2012) A New Global Climate Model of the Meteorological Research Institute: MRI-CGCM3 – Model Description and Basic Performance. Journal of the Meteorological Society of Japan 90A:23–64.CrossRefGoogle Scholar
  20. Yun WT, Stefanova L, Krishnamurti TN (2003) Improvement of the super-ensemble technique for seasonal forecasts. Journal of Climate 16:3834–3840.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Akiyo Yatagai
    • 1
    Email author
  • Vinay Kumar
    • 2
  • Tiruvalam N. Krishnamurti
    • 2
  1. 1.Hirosaki UniversityHirosaki, AomoriJapan
  2. 2.Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeUS

Personalised recommendations