Effects of diurnal temperature range and drought on wheat yield in Spain

Theoretical and Applied Climatology

Volumn 129, Issue 1-2, 2017, Pages 503-519

  Hernandez Barrera, S ^a   Rodriguez Puebla, C ^a   Challinor, A J ^b  

^a UNIVERSITY OF SALAMANCA   (Spain)

^b UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

Climate change impact; Climate variability; Empirical wheat yield model; Partial least square regression

Indexed keywords

CLIMATE CHANGE; CLIMATE EFFECT; CLIMATE VARIATION; CROP YIELD; DIURNAL VARIATION; DROUGHT; LEAST SQUARES METHOD; NUMERICAL MODEL; REGRESSION ANALYSIS; TEMPERATURE EFFECT; WHEAT;

IBERIAN PENINSULA; SPAIN;

TRITICUM AESTIVUM;

EID: 84962898198     PISSN: 0177798X     EISSN: 14344483     Source Type: Journal    
DOI: 10.1007/s00704-016-1779-9     Document Type: Article

References (106)

1. Abdi H (2010) Partial least squares regression and projection on latent structure regression (pls regression). WIREs Comput Stat:1–10. doi:10.1002/wics.051
2. Angulo C, Rotter R, Lock R, Enders A, Fronzek S, Ewert F (2013) Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe. Agric For Meteorol 170:32–46. doi:10.1016/j.agrformet.2012.11.017
3. Asseng S, Ewert F, Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Thorburn PJ, Rotter RP, Cammarano D, Brisson N, Basso B, Martre P, Aggarwal PK, Angulo C, Bertuzzi P, Biernath C, Challinor AJ, Doltra J, Gayler S, Goldberg R, Grant R, Heng L, Hooker J, Hunt LA, Ingwersen J, Izaurralde RC, Kersebaum KC, Muller C, Kumar SN, Nendel C, O’Leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripoche D, Semenov MA, Shcherbak I, Steduto P, Stockle C, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, Wallach D, White JW, Williams JR, Wolf J (2013) Uncertainty in simulating wheat yields under climate change. Nat Clim Chang 3(9):827–832. doi:10.1038/nclimate1916
4. Atkinson MD, Kettlewell PS, Hollins PD, Stephenson DB, Hardwick NV (2005) Summer climate mediates UK wheat quality response to winter north atlantic oscillation. Agric For Meteorol 130(1-2):27–37. doi:10.1016/j.agrformet.2005.02.002
5. Bannayan M, Lotfabadi SS, Sanjani S, Mohamadian A, Aghaalikhani M (2011) Effects of precipitation and temperature on crop production variability in northeast Iran. Int J Biometeorol 55(3):387–401. doi:10.1007/s00484-010-0348-7
6. Barlow KM, Christy BP, O’Leary GJ, Riffkin PA, Nuttall JG (2015) Simulating the impact of extreme heat and frost events on wheat crop production: A review. Field Crop Res 171:109–119. doi:10.1016/j.fcr.2014.11.010
7. Begueria S, Vicente-Serrano SM, Reig F, Latorre B (2014) Standardized precipitation evapotranspiration index (spei) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int J Climatol 34(10):3001–3023. doi:10.1002/joc.3887
8. Bristow KL, Campbell GS (1984) On the relationship between incoming solar-radiation and daily maximum and minimum temperature. Agric For Meteorol 31(2):159–166. doi:10.1016/0168-1923(84)90017-0
9. Brown I (2013) Influence of seasonal weather and climate variability on crop yields in Scotland. Int J Biometeorol 57(4):605–614. doi:10.1007/s00484-012-0588-9
10. Capa-Morocho M, Rodriguez-Fonseca B, Ruiz-Ramos M (2014) Crop yield as a bioclimatic index of el nino impact in Europe: Crop forecast implications. Agric For Meteorol 198:42–52. doi:10.1016/j.agrformet.2014.07.012
11. Capparelli V, Franzke C, Vecchio A, Freeman M P, Watkins N W, Carbone V (2013) A spatiotemporal analysis of US station temperature trends over the last century. J Geophys Res - Atmos 118 (14):7427–7434. doi:10.1002/jgrd.50551
12. Carter TR (2013) Agricultural impacts multi-model yield projections. Nat Clim Chang 3(9):784–786
13. Centre JR (2014) Mars bulletin vol.21. no6, 2013 and vol.20 n06, 2012. crop monitoring in Europe., http://mars.jrc.ec.europa.eu/mars/Bulletins-Publications
14. Challinor AJ, Wheeler TR, Craufurd PQ, Slingo JM (2005) Simulation of the impact of high temperature stress on annual crop yields. Agric For Meteorol 135(1-4):180–189
15. Challinor AJ, Watson J, Lobell DB, Howden SM, Smith DR, Chhetri N (2014) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Chang 4(4):287–291. doi:10.1038/nclimate215310.1038/nclimate2153
16. Chen C, Zhou GS, Pang YM (2015) Impacts of climate change on maize and winter wheat yields in China from 1961 to 2010 based on provincial data. J Agric Sci 153(5):825–836. doi:10.1017/s0021859614001154
17. Chen X, Wang M, Zhang Y, Feng Y, Wu Z, Huang N E (2013) Detecting signals from data with noise: theory and applications. J Atmos Sci 70(5):1489–1504. doi:10.1175/jas-d-12-0213.1
18. Ciscar J, Soria A, Lavalle C, Raes F, Perry M, Nemry F, Demirel H, Rozsai M, Dosio A, Donatelli M, Srivastava A, Fumagalli D, Niemeyer S, Shrestha S, Ciaian P, Himics M, VanDoorslaer B, Barrios S, Ibanez N, Bianchi A, Dowling P, Camia A, Liberta G, San Miguel J, de Rigo D, Caudullo G, Barredo J, Paci D, Pycroft J, Saveyn B, VanRegemorter D, Revesz T, Vandyck T, Vrontisi Z, Baranzelli C, Vandecasteele I, BatistaSilva F, Ibarreta D (2014) Climate impacts in Europe. The jrc peseta ii project. Report, http://www.jrc.ec.europa.eu
19. Colominas MA, Schlotthauer G, Torres ME (2014) Improved complete ensemble EEMD: A suitable tool for biomedical signal processing. Biomedical Signal Processing and Control 14:19–29. doi:10.1016/j.bspc.2014.06.009
20. Coumou D, Rahmstorf S (2012) A decade of weather extremes. Nat Clim Chang 2(7):491–496. doi:10.1038/nclimate1452
21. Dai A (2011) Drought under global warming: a review. Wiley Interdiscip Rev Clim Chang 2(1):45–65. doi:10.1002/wcc.81
22. Dalla Marta A, Grifoni D, Mancini M, Zipoli G, Orlandini S (2011) The influence of climate on durum wheat quality in Tuscany, central Italy. Int J Biometeorol 55(1):87–96. doi:10.1007/s00484-010-0310-8
23. Deryng D, Conway D, Ramankutty N, Price J, Warren R (2014) Global crop yield response to extreme heat stress under multiple climate change futures. Environ Res Lett 9(3). doi:10.1088/1748-9326/9/3/034011
24. Eitzinger J, Thaler S, Schmid E, Strauss F, Ferrise R, Moriondo M, Bindi M, Palosuo T, Rotter R, Kersebaum KC, Olesen JE, Patil RH, Saylan L, Caldag B, Caylak O (2013) Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria. J Agric Sci 151(6):813–835. doi:10.1017/s0021859612000779
25. FAO (2014) Food agriculture organization of the united nations (FAO)., http://faostat3.fao.org/compare/E
26. Feng J, Wu Z, Liu G (2014) Fast multidimensional ensemble empirical mode decomposition using a data compression technique. J Clim 27(10):3492–3504. doi:10.1175/jcli-d-13-00746.1
27. Flandrin P, Rilling G, Goncalves P (2004) Empirical mode decomposition as a filter bank. IEEE Signal Process Lett 11(2):112–114. doi:10.1109/lsp.2003.821662
28. Franzke C (2010) Long-range dependence and climate noise characteristics of Antarctic temperature data. J Clim 23(22):6074–6081. doi:10.1175/2010jcli3654.1
29. Franzke C (2015) Local trend disparities of european minimum and maximum temperature extremes. Geophys Res Lett (in press). doi:10.1002/2015GL065011
30. Gimeno L, Ribera P, Iglesias R, de la Torre L, Garcia R, Hernandez E (2002) Identification of empirical relationships between indices of ENSO and NAO and agricultural yields in Spain. Clim Res 21(2):165–172. doi:10.3354/cr021165
31. Gonsamo A, Chen JM (2015) Winter teleconnections can predict the ensuing summer European crop productivity. Proc Natl Acad Sci USA 112(18):E2265–E2266. doi:10.1073/pnas.1503450112
32. Gonzalez-Reviriego N, Rodriguez-Puebla C, Rodriguez-Fonseca B (2015) Evaluation of observed and simulated teleconnections over the Euro-Atlantic region on the basis of partial least squares regression. Clim Dyn 44 (11–12):2989–3014. doi:10.1007/s00382-014-2367-2
33. Gouache D, Bouchon AS, Jouanneau E, Le Bris X (2015) Agrometeorological analysis and prediction of wheat yield at the departmental level in France. Agric For Meteorol 209:1–10. doi:10.1016/j.agrformet.2015.04.027
34. Guan BT (2014) Ensemble empirical mode decomposition for analyzing phenological responses to warming. Agric For Meteorol 194:1–7. doi:10.1016/j.agrformet.2014.03.010
35. Hansen JW, Jones JW, Irmak A, Royce F (2001) El Nino-Southern Oscillation impacts on crop production in the southeast United States, pp 55–76. Asa Special Publication
36. Haylock MR, Hofstra N, Tank A, Klok EJ, Jones PD, New M (2008) A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. J Geophys Res - Atmos 113 (D20):55–76. doi:10.1029/2008jd010201.D20119
37. Herrera S, Gutierrez JM, Ancell R, Pons MR, Frias MD, Fernandez J (2012) Development and analysis of a 50-year high-resolution daily gridded precipitation dataset over Spain (spain02). Int J Climatol 32 (1):74–85. doi:10.1002/joc.2256
38. Huang NE, Shen Z, Long SR, Wu MLC, Shih HH, Zheng QN, Yen NC, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond Series A Math Phys Eng Sci 454(1971):903–995
39. Iglesias A, Quiroga S (2007) Measuring the risk of climate variability to cereal production at five sites in Spain. Clim Res 34(1):47–57
40. Iizumi T, Luo JJ, Challinor AJ, Sakurai G, Yokozawa M, Sakuma H, Brown ME, Yamagata T (2014) Impacts of El Nino Southern oscillation on the global yields of major crops. Nat Commun:5. doi:10.1038/ncomms4712
41. IPCC (2012) IPCC, 2012: Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups i and ii of the intergovernmental panel on climate change. In: Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL, Mastrandrea MD, Mach KJ, Plattner G-K, Allen SK, Tignor M, Midgley PM (eds). Report, IPCC
42. IPCC (2013) Climate Change 2013: the physical science basis. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
43. IPCC (2014) Climate Change 2014: impacts, adaptation, and vulnerability. part a: global and sectoral aspects. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
44. Jarlan L, Abaoui J, Duchemin B, Ouldbba A, Tourre YM, Khabba S, Le Page M, Balaghi R, Mokssit A, Chehbouni G (2014) Linkages between common wheat yields and climate in Morocco (1982–2008). Int J Biometeorol 58(7):1489–1502. doi:10.1007/s00484-013-0753-9
45. Ji F, Wu Z, Huang J, Chassignet EP (2014) Evolution of land surface air temperature trend. Nat Clim Chang 4(6):462–466. doi:10.1038/nclimate2223
46. Knutti R, Sedlacek J (2013) Robustness and uncertainties in the new CMIP5 climate model projections. Nat Clim Chang 3(4):369–373. doi:10.1038/nclimate1716
47. Li K, Yang X, Tian H, Pan S, Liu Z, Lu S (2015) Effects of changing climate and cultivar on the phenology and yield of winter wheat in the north China plain. Int J Biometeorol (in press). doi:10.1007/s00484-015-1002-1
48. Lobell DB (2007) Changes in diurnal temperature range and national cereal yields. Agric For Meteorol 145 (3–4):229–238. doi:10.1016/j.agrformet.2007.05.002
49. Lobell DB (2013) Errors in climate datasets and their effects on statistical crop models. Agric For Meteorol 170:58–66. doi:10.1016/j.agrformet.2012.05.013
50. Lobell DB, Burke MB (2010) On the use of statistical models to predict crop yield responses to climate change. Agric For Meteorol 150(11):1443–1452. doi:10.1016/j.agrformet.2010.07.008
51. Lobell DB, Gourdji SM (2012) The influence of climate change on global crop productivity. Plant Physiol 160(4):1686–1697. doi:10.1104/pp.112.208298
52. Lobell DB, Schlenker W, Costa-Roberts J (2011a) Climate trends and global crop production since 1980. Science 333(6042):616–620. doi:10.1126/science.1204531
53. Lobell DB, Torney A, Field CB (2011b) Climate extremes in California agriculture. Clim Chang 109:355–363. doi:10.1007/s10584-011-0304-5
54. Lorenzo-Lacruz J, Vicente-Serrano SM, Gonzalez-Hidalgo JC, Lopez-Moreno JI, Cortesi N (2013) Hydrological drought response to meteorological drought in the Iberian peninsula. Clim Chang 58(2):117–131. doi:10.3354/cr01177
55. Luo Q, Wen L (2015) The role of climatic variables in winter cereal yields: a retrospective analysis. Int J Biometeorol 59(2):181–192. doi:10.1007/s00484-014-0834-4
56. MAGRAMA (2015) Spanish agriculture, food and environment department., http://www.magrama.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/avances-superficies-producciones-agricolas/
57. Moghtaderi A, Flandrin P, Borgnat P (2013) Trend filtering via empirical mode decompositions. Comput Stat Data Anal 58:114–126. doi:10.1016/j.csda.2011.05.015
58. Moore FC, Lobell DB (2014) Adaptation potential of European agriculture in response to climate change. Nat Clim Chang 4(7):610–614. doi:10.1038/nclimate2228
59. Moore FC, Lobell DB (2015) The fingerprint of climate trends on European crop yields. Proc Natl Acad Sci USA 112(9):2670–2675. doi:10.1073/pnas.1409606112
60. Nicholls N (1997) Increased Australian wheat yield due to recent climate trends. Nature 387(6632):484–485
61. Olesen JE, Trnka M, Kersebaum KC, Skjelvag AO, Seguin B, Peltonen-Sainio P, Rossi F, Kozyra J, Micale F (2011) Impacts and adaptation of European crop production systems to climate change. Eur J Agron 34(2):96–112. doi:10.1016/j.eja.2010.11.003
62. Oteros J, Garcia-Mozo H, Botey R, Mestre A, Galan C (2015) Variations in cereal crop phenology in Spain over the last twenty-six years (1986–2012). Clim Chang 130(4):545–558. doi:10.1007/s10584-015-1363-9
63. Otkin J, Mark Shafer M, Svoboda M, Wardlow B, Anderson M, Hain C, Basara J (2015) Facilitating the use of drought early warning information through interactions with agricultural stakeholders. Bull Am Meteorol Soc 7:1073–1078. doi:10.1175/BAMS-D-14-00219.110.1175/BAMS-D-14-00219.1
64. Palosuo T, Kersebaum KC, Angulo C, Hlavinka P, Moriondo M, Olesen JE, Patil RH, Ruget F, Rumbaur C, Takac J, Trnka M, Bindi M, Caldag B, Ewert F, Ferrise R, Mirschel W, Saylan L, Siska B, Rotter R (2011) Simulation of winter wheat yield and its variability in different climates of Europe: a comparison of eight crop growth models. Eur J Agron 35(3):103–114. doi:10.1016/j.eja.2011.05.001
65. Pirttioja N, Carter TR, Fronzek S, Bindi M, Hoffmann H, Palosuo T, Ruiz-Ramos MR, Tao F, Trnka M, Acutis M, Asseng S, Baranowski P, Basso B, Bodin P, Buis S, Cammarano D, Deligios P, Destain M, Dumont B, Ewert F, Ferrise R, Franois L, Gaiser T, Hlavinka P, Jacquemin I, Kersebaum KC, Kollas C, Krzyszczak J, Lorite IJ, Minet J, Minguez MI, Montesino M, Moriondo M, Mller CC, Nendel IO, Perego A, Rodrguez A, Ruane AC, Ruget F, Sanna M, Semenov MA, Slawinski C, Stratonovitch P, Supit I, Waha K, Wang E, Wu L, Zhao Z, Rötter RP (2011) Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces. Clim Res 65:87105. doi:10.3354/cr01322
66. Podesta G, Letson D, Messina C, Royce F, Ferreyra RA, Jones J, Hansen J, Liovet I, Grondona M, O’Brien JJ (2002) Use of ENSO-related climate information in agricultural decision making in Argentina: a pilot experience. Agric Syst 74(3):371–392. doi:10.1016/s0308-521x(02)00046-x
67. Riahi K, Rao S, Krey V, Cho C, Chirkov V, Fischer G, Kindermann G, Nakicenovic N, Rafaj P (2011) Rcp 8.5-a scenario of comparatively high greenhouse gas emissions. Clim Chang 109(1–2):33–57. doi:10.1007/s10584-011-0149-y
68. Rodriguez-Puebla C, Ayuso SM, Frias MD, Garcia-Casado LA (2007) Effects of climate variation on winter cereal production in Spain. Clim Res 34(3):223–232
69. Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Thorburne P, Antle JM, Nelson GC, Porter C, Janssen S, Asseng S, Basso B, Ewert F, Wallach D, Baigorria G, Winter JM (2013) The agricultural model intercomparison and improvement project (agmip): Protocols and pilot studies. Agric For Meteorol 170:166–182. doi:10.1016/j.agrformet.2012.09.011
70. Rotter R, Hohn J (2015) Chapter 4: an overview of climate change impact on crop production and its variability in Europe, related uncertainties and research challenges, Food Agriculture Organization of the United Nations (FAO), Rome, 201, Rome
71. Rotter R, Ewert F, Palosuo T, Bindi M, Kersebaum K, Olesen J, Trnka M, van Ittersum M, Janssen S, Rivington M, Semenov M, Wallach D, Porter J, Stewart D, Verhagen J, Angulo C, Gaiser T, Nendel C, Martre P, de Wit A (2013) Challenges for agro-ecosystem modelling in climate change risk assessment for major European crops and farming systems. In: Impacts World 2013 Conference Proceedings, pp 555–564, DOI 10.2312/pik.2013.001, (to appear in print)
72. Rotter RP (2014) Agricultural impacts robust uncertainty. Nat Clim Chang 4(4):251–252
73. Rotter RP, Carter TR, Olesen JE, Porter JR (2011) Crop-climate models need an overhaul. Nat Clim Chang 1(4):175–177
74. Royce FS, Fraisse CW, Baigorria GA (2011) ENSO classification indices and summer crop yields in the southeastern USA. Agric For Meteorol 151(7):817–826. doi:10.1016/j.agrformet.2011.01.017
75. Ruiz-Ramos M, Sanchez E, Gallardo C, Minguez MI (2011) Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian peninsula. Nat Hazards Earth Syst Sci 11(12):3275–3291. doi:10.5194/nhess-11-3275-2011
76. Schulzweida U (2015) CDO climate data operators, users guide., https://code.zmaw.de/projects/cdo
77. Sen PK (1968) Estimates of regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63(324):1379–1389
78. Smoliak BV, Wallace JM, Stoelinga MT, Mitchell TP (2010) Application of partial least squares regression to the diagnosis of year-to-year variations in Pacific Northwest snowpack and atlantic hurricanes. Geophys Res Lett:37. doi:10.1029/2009gl041478.L03801
79. Smoliak BV, Wallace JM, Lin P, Fu Q (2015) Dynamical adjustment of the Northern Hemisphere surface air temperature field: methodology and application to observations. J Clim 28(4):1613–1629. doi:10.1175/jcli-d-14-00111.1
80. Supit I, van Diepen C A, de Wit AJW, Wolf J, Kabat P, Baruth B, Ludwig F (2012) Assessing climate change effects on European crop yields using the crop growth monitoring system and a weather generator. Agric For Meteorol 164:96–111. doi:10.1016/j.agrformet.2012.05.005
81. Tao F, Zhang S, Zhang Z (2012) Spatiotemporal changes of wheat phenology in China under the effects of temperature, day length and cultivar thermal characteristics. Europ J Agronomy 43:201–212
82. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res - Atmos 106(D7):7183–7192
83. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498. doi:10.1175/bams-d-11-00094.1
84. Tian D, Asseng S, Martinez CJ, Misra V, Cammarano D, Ortiz BV (2015) Does decadal climate variation influence wheat and maize production in the Southeast USA? Agric For Meteorol 204:1–9. doi:10.1016/j.agrformet.2015.01.013
85. Trenberth KE (2012) Framing the way to relate climate extremes to climate change. Clim Chang 115 (2):283–290. doi:10.1007/s10584-012-0441-5
86. Trenberth KE, Dai AG, van der Schrier G, Jones PD, Barichivich J, Briffa KR, Sheffield J (2014) Global warming and changes in drought. Nat Clim Chang 4(1):17–22. doi:10.1038/nclimate2067
87. Trnka M, Eitzinger J, Semeradova D, Hlavinka P, Balek J, Dubrovsky M, Kubu G, Stepanek P, Thaler S, Mozny M, Zalud Z (2011a) Expected changes in agroclimatic conditions in central Europe. Clim Chang 108(1–2):261–289. doi:10.1007/s10584-011-0025-9
88. Trnka M, Olesen JE, Kersebaum KC, Skjelvag AO, Eitzinger J, Seguin B, Peltonen-Sainio P, Rotter R, Iglesias A, Orlandini S, Dubrovsky M, Hlavinka P, Balek J, Eckersten H, Cloppet E, Calanca P, Gobin A, Vucetic V, Nejedlik P, Kumar S, Lalic B, Mestre A, Rossi F, Kozyra J, Alexandrov V, Semeradova D, Zalud Z (2011b) Agroclimatic conditions in Europe under climate change. Glob Chang Biol 17(7):2298–2318. doi:10.1111/j.1365-2486.2011.02396.x
89. Trnka M, Roetter RP, Ruiz-Ramos M, Kersebaum KC, Olesen JE, Zalud Z, Semenov MA (2014) Adverse weather conditions for European wheat production will become more frequent with climate change. Nat Clim Chang 4(7):637–643. doi:10.1038/nclimate224210.1038/nclimate2242
90. UCAR/NCAR (2015) The NCAR command language (software,version 6.3.0). doi:10.5065/D6WD3XH5
91. Vicente-Serrano SM, Cuadrat-Prats JM, Romo A (2006) Early prediction of crop production using drought indices at different time-scales and remote sensing data: application in the Ebro valley (north-east spain). Int J Remote Sens 27(3):511–518
92. Vicente-Serrano SM, Begueria S, Lopez-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23(7):1696–1718. doi:10.1175/2009jcli2909.1
93. Vicente-Serrano SM, Lopez-Moreno JI, Begueria S, Lorenzo-Lacruz J, Sanchez-Lorenzo A, Garcia-Ruiz JM, Azorin-Molina C, Moran-Tejeda E, Revuelto J, Trigo R, Coelho F, Espejo F (2014) Evidence of increasing drought severity caused by temperature rise in Southern Europe. Environ Res Lett 9(4):9. doi:10.1088/1748-9326/9/4/044001
94. Wallace JM, Fu Q, Smoliak BV, Lin P, Johanson CM (2012) Simulated versus observed patterns of warming over the extratropical Northern Hemisphere continents during the cold season. Proc Natl Acad Sci USA 109(36):14:337–14:342. doi:10.1073/pnas.1204875109
95. Watson J, Challinor AJ, Fricker TE, Ferro CAT (2015) Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model. Clim Chang 132(1):93–109. doi:10.1007/s10584-014-1264-3
96. White JW, Hoogenboom G, Kimball BA, Wall GW (2011) Methodologies for simulating impacts of climate change on crop production. Field Crop Res 124(3):357–368. doi:10.1016/j.fcr.2011.07.001
97. WMO (2012) Standardized precipitation index. User Guide. Weather Climate Water, CH 1211 Geneva 2, Switzerland
98. WMO (2013) The global climate 2001-2010. A decade of climatic extremes. summary report. Report
99. Wold S, Sjostrom M, Eriksson L (2001) PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst 58(2):109–130. doi:10.1016/s0169-7439(01)00155-1
100. Wu J, Liu M, Lu A, He B (2014) The variation of the water deficit during the winter wheat growing season and its impact on crop yield in the north China plain. Int J Biometeorol 58(9):1951–1960. doi:10.1007/s00484-014-0798-4
101. Wu Z, Huang NE, Long SR, Peng CK (2007) On the trend, detrending, and variability of nonlinear and nonstationary time series. Proc Natl Acad Sci USA 104(38):14:889–14:894. doi:10.1073/pnas.0701020104
102. Wu ZH, Huang NE, Wallace JM, Smoliak BV, Chen XY (2011) On the time-varying trend in global-mean surface temperature. Clim Dyn 37(3–4):759–773. doi:10.1007/s00382-011-1128-8
103. Xiao D, Tao F, Liu Y, Shi W, Wang M, Liu F, Zhang S, Zhu Z (2013) Observed changes in winter wheat phenology in the north China plain for 1981-2009. Int J Biometeorol 57(2):275–285. doi:10.1007/s00484-012-0552-8
104. Xiao DP, Tao FL (2014) Contributions of cultivars, management and climate change to winter wheat yield in the north China plain in the past three decades. Eur J Agron 52:112–122. doi:10.1016/j.eja.2013.09.020
105. Yu Q, Li L, Luo Q, Eamus D, Xu S, Chen C, Wang E, Liu J, Nielsen D C (2014) Year patterns of climate impact on wheat yields. Int J Climatol 34(2):518–528
106. Yue S, Wang CY (2004) The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manag 18(3):201–218. doi:10.1023/b:warm.0000043140.61082.60