Present and future assessment of growing degree days over selected Greek areas with different climate conditions

Abstract

The determination of heat requirements in the first developing phases of plants has been expressed as Growing Degree Days (GDD). The current study focuses on three selected study areas in Greece that are characterised by different climatic conditions due to their location and aims to assess the future variation and spatial distribution of Growing Degree Days (GDD) and how these can affect the main cultivations in the study areas. Future temperature data were obtained and analysed by the ENSEMBLES project. The analysis was performed for the future periods 2021–2050 and 2071–2100 with the A1B and B1 scenarios. Spatial distribution was performed using a combination of dynamical and statistical downscaling technique through ArcGIS 10.2.1. The results indicated that for all the future periods and scenarios, the GDD are expected to increase. Furthermore, the increase in the Sperchios River basin will be the highest, followed by the Ardas and the Geropotamos River basins. Moreover, the cultivation period will be shifted from April–October to April–September which will have social, economical and environmental benefits. Additionally, the spatial distribution indicated that in the upcoming years the existing cultivations can find favourable conditions and can be expanded in mountainous areas as well. On the other hand, due to the rough topography that exists in the study areas, the wide expansion of the existing cultivations into higher altitudes is unaffordable. Nevertheless, new more profitable cultivations can be introduced which can find propitious conditions in terms of GDD.

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    http://www.ogimet.com.

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    http://www.statistics.gr.

References

  1. Allan C, Ferguson L (2014) Physiology of fruit growth as a function of heat in commercial Pistacia vera species. In Proceedings of American Society for Horticultural Science, July 28–31, 2014, Orlando FL

  2. Baker JT, Pinter PJ Jr, Reginato RJ, Kanemasu ET (1986) Effects of temperature on leaf appearance in spring and winter wheat cultivars. Agron J 78:605–613

    Article  Google Scholar 

  3. Bauer A, Garcia R, Kanemasu ET, Blad BL, Hatfield JL, Major DJ, Reginato RJ, Hubbard KG (1988) Effect of latitude on phenology of Colt winter wheat. Agric For Meteorol 44(13):1–140

    Google Scholar 

  4. Black C, Ong C (2000) Utilisation of light and water in tropical agriculture. Agric For Meteorol 104:25–47

    Article  Google Scholar 

  5. Bleta A, Nastos P, Matzarakis A (2014) Assessment of bioclimatic conditions on Crete Island, Greece. Reg Env Chang 14:1967–1981

    Article  Google Scholar 

  6. Bourque CP, Meng F, Gullison JJ, Bridgland J (2000) Biophysical and potential vegetation growth surfaces for a small watershed in northern Cape Breton Island, Nova Scotia, Canada. Can J For Res 30:1179–1195

    Article  Google Scholar 

  7. Butler TJ, Gerald WE, Mark AH, Ringer JR (2002) Flowering in crimson clover as affected by planting date. Crop Sci 42:242–247

    Article  Google Scholar 

  8. Caliskan S, Caliskan ME, Arslan M, Arioglu H (2008a) Effects of sowing date and growth duration on growth and yield of groundnut in a Mediterranean-type environment in Turkey. Field Crops Res 105:131–140

    Article  Google Scholar 

  9. Caliskan S, Caliskan ME, Erturk E, Arioglu H (2008b) Growth and development of Virginia type groundnut cultivars under Mediterranean conditions. Acta Agric Scan B Plant Soil Sci 58:105–113

    Google Scholar 

  10. Canavar Ö, Ali Kaynak M (2010) Growing degree day and sunshine radiation effects on peanut pod yield and growth. Afr J Biotech 9(15):2234–2241

    Google Scholar 

  11. Christensen JH, Christensen OB, Lopez P, van Meijgaard E, Botzet M (1996) The HIRHAM4: Regional atmospheric climate model. Danish Meteorological Institute, Scientific Report 96-4

  12. Christensen J, Carter T, Rummukainen M, Amanatidis G (2007) Evaluating the performance and utility of regional climate models: the prudence project. Clim Chang 81:1–6

    Article  Google Scholar 

  13. Cross HZ, Zuber MS (1972) Prediction of flowering dates in maize based on different methods of estimating thermal units. Agron J 64:351–355

    Article  Google Scholar 

  14. Cutforth HW, Shaykewich CF (1989) Relationship of development rates of corn from planting to silking to air and soil temperature and to accumulated thermal units in a prairie environment. Can J Plant Sci 69:121–132

    Article  Google Scholar 

  15. Davidson HR, Campbell CA (1983) The effect of temperature, moisture and nitrogen on the rate of development of spring wheat as measured by degree days. Can J Plant Sci 63:833–846

    Article  Google Scholar 

  16. Default RJ (1997) Determining heat unit requirements for broccoli in coastal South Carolina. J Am Soc Hortic Sci 122:169–174

    Google Scholar 

  17. Dingman SL (2002) Physical Hydrology, 2nd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  18. Edwardson SE, Watt DL (1987) GROWTH STAGE: using growing degree days to predict the Haun scale of spring wheat. Appl Agric Res 2:224–229

    Google Scholar 

  19. Feidas H, Karagiannidis A, Keppas S, Vaitis M, Kontos T, Zanis P, Melas D, Anadranistakis E (2014) Modeling and mapping temperature and precipitation climate data in Greece using topographical and geographical parameters. Theor Appl Climatol 118:133–146

    Article  Google Scholar 

  20. Gallagher JN (1979) Field studies of cereal leaf growth: I. Initiation and expansion in relation to temperature and ontogeny. J Exp Bot 30:625–636

    Article  Google Scholar 

  21. Gibelin AL, Deque M (2003) Anthropogenic climate change over the Mediterranean region simulated by a global variable resolution model. Clim Dyn 20(4):327–339

    Article  Google Scholar 

  22. Gilmore EC, Rogers JS (1958) Heat units as a method of measuring maturity in corn. Agron J 50:611–615

    Article  Google Scholar 

  23. Giorgi F, Lionello P (2008) Climate change projections for the Mediterranean region. Glob Planet Chang 63(2–3):90–104

    Article  Google Scholar 

  24. Giorgi F, Mearns LO (1999) Introduction to special section: regional climate modeling revisited. J Geophys Res 104:6335–6352

    Article  Google Scholar 

  25. Goodess C, Palutikof J (1998) Development of daily rainfall scenarios for southeast Spain using a circulation-type approach downscaling. Int J Climatol 10:1051–1083

    Article  Google Scholar 

  26. Goyne PJ, Woodruff DR, Churchett JD (1977) Prediction of flowering in sunflowers. Aust J Exp Agric Anim Husb 17(475–48):1

    Google Scholar 

  27. Haan CT (2002) Statistical methods in Hydrology, 2nd edn. Iowa State University Press, Ames, p 378

    Google Scholar 

  28. Hagemann S, Machenhauer B, Jones R, Christensen OB, Deque M, Jacob D, Vidale PL (2004) Evaluation of water and energy budgets in regional climate models applied over Europe. Clim Dyn 23:547–567

    Article  Google Scholar 

  29. Hasan Q, Bourque C, Meng F-R, Richards W (2007) Spatial mapping of growing degree days: an application of MODIS-based surface temperatures and enhanced vegetation index. J Appl Rem Sens 1:013511

    Article  Google Scholar 

  30. Hellenic Army Geographical Service (1988) 1:50,000 Map Sheets

  31. Henriksen HJ, Troldborg L, Nyegaard P, Sonnenborg TO, Refsgaard JC, Madsen B (2003) Methodology for Construction, Calibration and Validation of a National Hydrological Model for Denmark. J Hydr 280:52–71

    Article  Google Scholar 

  32. IPCC (2007) Contribution of Working Group 1 to the Fourth IPCC Assessment Report. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (ed), Climate Change 2007: The Physical Science Basis. Cambridge, UK: Cambridge University Press, p 996

  33. IPCC (2014) Climate Change 2014: Synthesis Report. An Assessment of Intergovernmental Panel on Climate Change. Geneva Switzerland, http://ipcc.ch/index/html

  34. Jaeger EB, Anders I, Lüthi D, Rockel B, Schär C, Seneviratne S (2008) Analysis of ERA40-driven CLM simulations for Europe. Meteorol Zeitschrift 17:349–367

    Article  Google Scholar 

  35. Jefferies RA, Mackerron DKL (1987) Thermal time as a non-destructive method of estimating tuber initiation in potatoes. J Agric Sci Camb 108:249–252

    Article  Google Scholar 

  36. Johns TC (2009a) ENSEMBLES STREAM2 METO-HCHADCM3C 20C3 M run1, daily values. CERA database. World Data Center for Climate, Hamburg. http://cera-www.dkrz.de/WDCC/ui/Entry.jsp? acronym = ENSEMBLES2_HADCM3C_20C3M_1_D

  37. Johns TC (2009b) ENSEMBLES STREAM2 METO-HCHADGEM2AO 20C3M run1, daily values. CERA database. World Data Center for Climate, Hamburg. http://cera-www.dkrz.de/WDCC/ui/ Compact.jsp? acronym = ENSEMBLES2_HADGEM2_20C3M_1_D

  38. Jungclaus JH, Keenlyside N, Botzet M, Haak H, Luo JJ, Latif M, Marotzke J, Mikolajewicz U, Roeckner E (2006) Ocean circulation and tropical variability in the coupled model ECHAM5/MPI-OM. J Clim 19:3952–3972

    Article  Google Scholar 

  39. Ketring DL, Wheless TG (1989) Thermal time requirements for phenological development of peanut. Agron J 81:910–917

    Article  Google Scholar 

  40. Kirby EJM (1995) Factors affecting rate of leaf emergence in barley and wheat. Crop Sci 35:11–19

    Article  Google Scholar 

  41. Klepper B, Belford RK, Rickman RW (1984) Root and shoot development in winter wheat. Agron J 76:117–122

    Article  Google Scholar 

  42. Köse B (2014) Phenology and ripening of Vitis vinifera L. and Vitis labrusca L. varieties in the maritime climate of Samsun in Turkey’s Black Sea Region. S J Enol Vitic 35(1):90–102

  43. Lam N (1983) Spatial interpolation methods: a review. Americ Cart 10(2):129–149

    Article  Google Scholar 

  44. Lautenschlager M, Keuler K, Wunram C, Keup-Thiel E et al (2009) Climate simulation with CLM, scenario A1B run no. 2, data stream 3: European region MPI-M/MaD. World Data Center for Climate, Hamburg. doi:10.1594/WDCC/CLM_A1B_2_D3

  45. Leong SK, Ong CK (1983) The influence of temperature and soil water deficit on the development and morphology of peanuts (Arachis hypogaea L.). J Exp Bot 34:1551–1561

    Article  Google Scholar 

  46. Lu MK, Saylan L (2001) Trends of growing degree-days in Turkey. Water, air & soil poll 126(1–2):83–96

    Google Scholar 

  47. Maris F, Kitikidou K, Angelidis P, Potouridis S (2013) Kriging Interpolation Method for Estimation of Continuous Spatial Distribution of Precipitation in Cyprus. British J of Appl Sci Tech 3(4):1286–1300

    Article  Google Scholar 

  48. Masle J, Doussinalut G, Farquhar GD, Sun B (1989) Foliar stage in wheat correlates better to photothermal time than to thermal time. Plant Cell Environ 12:235–247

    Article  Google Scholar 

  49. Masoni A, Ercoli L, Massantini F (1990) Relationship between number of days, growing degree days and photothermal units and growth in wheat (Triticum aestivum L.) according to seeding time. Agric Med 120:41–51

    Google Scholar 

  50. Mathan KK (1989) Influence of accumulated heat units and sunshine hours on the growth and yield of sorghum (var. Co 25). J Agron and Crop Sci 163:196–200

    Article  Google Scholar 

  51. MATLAB and Statistics Toolbox (2000) Release 2014a. The Mathworks Inc, Natick

    Google Scholar 

  52. Matzarakis A, Balafoutis VB (2004) Heating degree days as an index of energy consumption. Int J Climatol 24:1817–1828

    Article  Google Scholar 

  53. Matzarakis A, Nastos P (2011) Analysis of tourism potential for Crete Island. Greece. Glob NEST J 13(2):141–149

    Google Scholar 

  54. Matzarakis A, Ivanova D, Balafoutis C, Makrogiannis T (2007) Climatology of growing degree days in Greece. Clim Res 34:233–240

    Article  Google Scholar 

  55. Matzarakis A, Endler C, Nastos P (2014) Quantification of climate-tourism potential for Athens, Greece - Recent and future climate simulations. Glob NEST J 16(1):43–51

    Google Scholar 

  56. McMaster GS (1993) Another wheat (Triticum sp.) model? Progress and applications in crop modeling. Rivista di Agron 27:264–272

    Google Scholar 

  57. McMaster GS, Smika DE (1988) Estimation and evaluation of winter wheat phenology in the central Great plains. Agric For Meteorol 43:1–18

    Article  Google Scholar 

  58. McMaster GS, Wilhelm WW (1997) Growing degree-days: one equation, two interpretations. Agr For Meteorol 87:291–300

    Article  Google Scholar 

  59. McMaster GS, Wilhelm WW, Morgan JA (1992) Simulating winter wheat shoot apex phenology. J Agric Sci Camb 119:1–12

    Article  Google Scholar 

  60. Miley WN, Oosterhuis DM (1990) Nitrogen Nutrition of Cotton: Practical Issues. In: Proceedings of 1st Annual Workshop for Practicing Agronomists, February 7, 1990. American Society of Agronomy, Inc., AR

  61. Miller P, Lanier W, Brandt S (2001) Using growing degree days to predict plant stages. Ag/Extension Communications Coordinator. Communications Services. Montana State University-Bozeman, Bozeman

    Google Scholar 

  62. Morrison W, Andresen J, Szendrei Z (2014) The development of the asparagus miner (Ophiomyia simplex Loew; Diptera: Agromyzidae) in temperate zones: a degree-day model. Pest Manag Sci 70(7):1105–1113

    Article  Google Scholar 

  63. Narwal SS, Poonia S, Singh G, Malik DS (1986) Influence of sowing dates on the growing degree days and phenology of winter maize (Zea mays L.). Agric For Meteorol 38:47–57

    Article  Google Scholar 

  64. Nastos P, Kapsomenakis J, Douvis K (2013a) Analysis of precipitation extremes based on satellite and high-resolution gridded data set over Mediterranean basin. Atm Res 131:46–59

    Article  Google Scholar 

  65. Nastos P, Politi N, Kapsomenakis J (2013b) Spatial and temporal variability of the Aridity Index in Greece. Atm Res 119:140–152

    Article  Google Scholar 

  66. Neumann P, Matzarakis A (2014) Potential climate change impacts on wine grape must density and titratable acidity in southwest Germany. Clim Res 59:161–172

    Article  Google Scholar 

  67. Oliver MA, Webster R (1990) Kriging: a method of interpolation for geographical information systems. Int J Geo Inf Syst 4(3):313–332

    Article  Google Scholar 

  68. Orlandi F, Vazquez LM, Ruga L, Bonofiglio T, Fornaciari M, Garcia-Mozo H, Dominguez E, Romano B, Galan C (2005) Bioclimatic requirements for olive flowering in two Mediterranean regions located at the same latitude (Andalucía, Spain, and Sicily, Italy). Ann Agri Environ Med 12:47–52

    Google Scholar 

  69. Orlandi F, Garcia-Mozo H, Dhiab B, Galan C, Msallem M, Fornaciari M (2014) Olive tree phenology and climate variations in the Mediterranean area over the last two decades. Theor Appl Climatol 115:207–218

    Article  Google Scholar 

  70. Paparrizos S, Maris F, Matzarakis A (2014) Estimation and Comparison of Potential Evapotranspiration based on daily and monthly data from Sperchios River valley in Central Greece. Glob NEST J 16(2):204–217

    Google Scholar 

  71. Paparrizos S, Maris F, Matzarakis A (2016a) Integrated analysis of present and future response of precipitation over selected areas with different climate conditions. Atm Res 169:199–208

    Article  Google Scholar 

  72. Paparrizos S, Maris F, Matzarakis A (2016b) Mapping of drought for Sperchios River basin in Greece. Hydrol Sci J. 61(5): 881-891 doi:10.1080/02626667.2014.965175

    Google Scholar 

  73. Paparrizos S, Maris F, Matzarakis A (2016c) Sensitivity analysis and comparison of various Potential Evapotranspiration formulae for selected Greek areas with different climate conditions. Theor Appl Clim. doi:10.1007/s00704-015-1728-z

    Google Scholar 

  74. Paparrizos S, Maris F, Matzarakis A (2016d) Integrated analysis and mapping of aridity over Greek areas with different climate conditions. Glob NEST J 18(1):131–145

    Google Scholar 

  75. Pearson K (1900) Mathematical contributions to the theory of evolution, VII: On the correlation of characters not quantitatively measurable. Philos Trans R Soc A 195:1-147

    Article  Google Scholar 

  76. Peel M, Finlayson B, McMahon T (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci 11:1633–1644

    Article  Google Scholar 

  77. Perry KB, Wehner TC, Johnson GL (1986) Comparison of 14 methods to determine heat unit requirements for cucumber harvest. Hort Sci 21:419–423

    Google Scholar 

  78. Petkeviciene B (2009) The effects of climate factors on sugar beet early sowing timing. Agr Res (Sp. Issue I):436–443

  79. Raes D, Steduto P, Hsiao TC, Fereres E (2010) ANNEXES Reference Manual. AquaCrop, p 50

  80. Roeckner E, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kornblueh L, Manzini E, Schlese U, Schulzweida U (2006) Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 Atmosphere Model. J Clim 19:3771–3791

    Article  Google Scholar 

  81. Ruml M, Vukovic A, Milatovic D (2010) Evaluation of different methods for determining growing degree-day thresholds in apricot cultivars. Int J Biometeorol 54:411–422

    Article  Google Scholar 

  82. Russelle MP, Wilhelm WW, Olson RA, Power JF (1984) Growth analysis based on degree days. Crop Sci 24:28–32

    Article  Google Scholar 

  83. Schubert S, Henderson-Sellers A (1997) A statistical model to downscale local daily temperature extremes from synoptic-scale atmospheric circulation patterns in the Australian region. Clim Dyn 13:223–234

    Article  Google Scholar 

  84. Snedecor G, Cochran G (1989) Statistical methods, 8th edn. Iowa State University, Ames 803 pp

    Google Scholar 

  85. Swanson SP, Wilhelm WW (1996) Planting date and residue rate effects on growth, partitioning, and yield of corn. Agron J 88:205–210

    Article  Google Scholar 

  86. Timbal B, Dufour A, McAvaney B (2003) An estimate of future climate change for western France using a statistical downscaling technique. Clim Dyn 20:807–823

    Article  Google Scholar 

  87. Tolika K, Anagnostopoulou C, Maheras P, Vafiadis M (2008) Simulation of future changes in extreme rainfall and temperature conditions over the Greek area: a comparison of two statistical downscaling approaches. Glob Planet Chang 63:132–151

    Article  Google Scholar 

  88. Tollenaar M, Daynard TB, Hunter RB (1979) Effect of temperature on rate of leaf appearance and flowering date in maize. Crop Sci 19:363–366

    Article  Google Scholar 

  89. Wang JY (1960) A critique of the heat unit approach to plant response studies. Ecology 41:785–790

    Article  Google Scholar 

  90. Wilhelm WW, McMaster GS (1995) The importance of the phyllochron in studying the development of grasses. Crop Sci 35:1–3

    Article  Google Scholar 

  91. Wilhelm WW, Schepers LN, Mielke JS, Doran JW, Ellis JR, Stroup WW (1987) Dryland maize development and yield resulting from tillage and nitrogen fertilization practices. Soil Tillage Res 10:167–179

    Article  Google Scholar 

  92. Wilhelm WW, Bouzerzour H, Power JF (1989) Soil disturbance- residue management effect on winter wheat growth and yield. Agron J 81:581–588

    Article  Google Scholar 

  93. Yang S, Logan J, Coffey DL (1995) Mathematical formulae for calculating the base temperature for growing degree days. Agr For Meteorol 74:61–74

    Article  Google Scholar 

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Acknowledgments

The input meteorological data were obtained from the Hellenic National Meteorological Service (HNMS). For the stations of Edirne (Turkish territory) and Kurdjali (Bulgarian territory) the data were obtained from http://www.ogimet.com.

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Correspondence to Spyridon Paparrizos.

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Responsible Editor: L. Gimeno.

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Paparrizos, S., Matzarakis, A. Present and future assessment of growing degree days over selected Greek areas with different climate conditions. Meteorol Atmos Phys 129, 453–467 (2017). https://doi.org/10.1007/s00703-016-0475-8

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Keywords

  • River Basin
  • Ordinary Kriging
  • Spatial Interpolation
  • Statistical Downscaling
  • Main Cultivation