Regional Environmental Change

, Volume 14, Issue 4, pp 1533–1548 | Cite as

Potential impacts of early twenty-first century changes in temperature and precipitation on rainfed annual crops in the Central Andes of Peru

  • Janeet Sanabria
  • Pierluigi Calanca
  • Constantino Alarcón
  • Glicerio Canchari
Original Article
First Online:
Received:
Accepted:

Abstract

Smallholder agriculture in the Central Andes of Peru is based to large extent on rainfed cropping systems, is exposed to climatic risks and is expected to respond sensitively to increasing temperatures and shifts in the precipitation regime. Here, we examine the potential implications of early twenty-first century climate change scenarios for the cultivation of potato, maize, wheat, barley and broad bean, five annual crops that account for 50 % of the cultivated area in the Department of Cusco and Apurímac and provide the dietary backbone for a large share of the local population. The scenarios disclose a regionally coherent increase in temperature of the order of 1 °C but overall only moderate changes in growing season precipitation by 2030. A simple crop model is used to assess the effects of these changes on crop phenology and development. The results show earlier harvest dates, shorter cropping seasons and, in a few cases, a slightly higher risk of planting failure in the near future. This suggests that a better understanding of changes in the precipitation regime at the onset of the cropping season is required to evaluate short-term needs and possibilities for adaptation. However, as the scenarios are highly uncertain, these conclusions should be verified.

Keywords

Climate change Temperature Precipitation Annual crops Central Andes Rainfed agriculture 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

This study was carried out within the framework of the Adaptation Program to Climate Change in Peru (Programa de Adaptación al Cambio Climático en el Perú), an initiative funded by the Swiss Agency for Development and Cooperation (SDC) and coordinated by Christian Huggel and Nadine Salzmann at the University of Zurich and Helvetas Swiss Intercooperation. Work carried out that the National Weather Services of Peru (SENAMHI) was promoted by Elizabeth Silverstre. We are also indebted to Olimpio Solis Caceres of the Department of Statistics and Information Technology of SENAMHI for extracting and processing all climatic data.

References

  1. Acuña D, Llacza A, Cubas F, Jácome G, Díaz A, Avalos G (2012) Escenarios de cambio climático en las regiones Cusco y Apurímac: Precipitación y Temperatura 2030 y 2050 (Climate change scenarios for the region of Cusco and Apurimac: Precipitation and temperatura, 2030 and 2050). Report, Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI), Lima, Peru, 144 ppGoogle Scholar
  2. AgMIP (Agricultural Model Intercomparison and Improvement Project) (2013) Protocols for crop models improvement teams. http://www.agmip.org/protocols-for-agmip-crop-model-improvement-teams/. Accessed 18 Nov 2013
  3. Alarcón Velazco C (1991) Caracterizaciòn Agrolimàtica del Departamento de Cusco (Agrocliamtic Characterization of the Department of Cusco). PhD Thesis. Universidad Nacional Agraria La Molina, LimaGoogle Scholar
  4. Allen RG, Pereira L, Raes D, Smith M (1998) Crop evapotranspiration. Guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56. Food and Agriculture Organization of the United Nations. Rome, 300 ppGoogle Scholar
  5. Altieri MA, Koohafkan P (2008) Enduring Farms: Climate Change, Smallholders and Traditional Farming Communities. Third World Network, Penang, Malaysia. ISBN: 978-983-2729-55-6Google Scholar
  6. Alvarez M, Repo R (1999) Desarrollo de Productos de Papas Nativas (Development of Native Potatoes). Centro Internacional de la Papa (International Potato Centre), Lima, p 108Google Scholar
  7. Baigorria GM, Villegas EB, Trebejo I, Carlos JF, Quiroz R (2004) Atmospheric transmissivity: distribution and empirical estimation around the Central Andes. Int J Climatol 24:1121–1136. doi: 10.1002/joc.1060 CrossRefGoogle Scholar
  8. Bauer A, Frank AB, Black AL (1993) A crop calendar for spring wheat and for spring barley. N D Farm Res 49(6):21–25. http://library.ndsu.edu/repository/handle/10365/8301. Accessed 11 June 2013
  9. Berdegué JA, Fuentealba R (2011) Latin America: the state of smallholders in agriculture. Paper presented at the IFAD conference on new directions for smallholder agriculture, 24–25 January, 2011, Rome, IFAD Head Quarters. http://www.ifad.org/events/agriculture/doc/papers/berdegue.pdf. Accessed 11 June 2013
  10. Blázquez J, Nuñez MN (2013) Performance of a high resolution global model over southern South America. Int J Climatol 33:904–919. doi: 10.1002/joc.3478 CrossRefGoogle Scholar
  11. Boulanger J-P, Brasseur G, Carril AF et al (2010) A Europe–South America network for climate change assessment and impact studies. Clim Change 98:307–329. doi: 10.1007/s10584-009-9734-8 CrossRefGoogle Scholar
  12. Confalone A, Lizaso JI, Ruiz-Nogueira B, López-Cedrón FX, Sau F (2010) Growth, PAR use efficiency, and yield components of field-grown Vicia faba L. under various temperature and photoperiod regimes. Field Crops Res 115:140–148. doi: 10.1016/j.fcr.2009.10.014 CrossRefGoogle Scholar
  13. Déqué M (2007) Frequency of precipitation and temperatures extremes over France in an anthropogenic scenario. Glob Planet Change 57:16–26. doi: 10.1016/j.gloplacha.2006.11.030 CrossRefGoogle Scholar
  14. Doorenbos J, Kassam A (1979) Yield response to water. FAO Irrigation and Drainage Paper 33. Food and Agriculture Organization of the United Nations. Rome, 193 ppGoogle Scholar
  15. ECLAC (Economic Commission for Latin America and the Caribbean, CL), FAO (Food and Agriculture Organization of the United Nations, IT), IICA (Inter-American Institute for Cooperation on Agriculture, CR) (2010) The outlook for agriculture and rural development in the Americas: A perspective on Latin America and the Caribbean IICA, Santiago, ChileGoogle Scholar
  16. Forbes JC, Watson RD (1992) Plants in Agriculture. Cambridge University Press, Cambridge, p 355Google Scholar
  17. Frère M, Rijks JQ, Rea J (1975) Estudio Agroclimatológico de la Zona Andina (Agroclimatological Investigation of the Andean Region). WMO Technical Note No. 506. World Meteorological Organization (WMO), Geneva, 375 ppGoogle Scholar
  18. Garcia M, Raes D, Jacobsen SE (2003) Evapotranspiration analysis and irrigation requirements of quinoa (Chenopodium quinoa) in the Bolivian highlands. Agric Water Manag 60:119–134. doi: 10.1016/S0378-3774(02)00162-2 CrossRefGoogle Scholar
  19. Garcia M, Raes D, Allen R, Herbas C (2004) Dynamics of reference evapotranspiration in the Bolivian highlands (Altiplano). Agric Forest Meteorol 125:67–82. doi: 10.1016/j.agrformet.2004.03.005 CrossRefGoogle Scholar
  20. Garcia M, Raes D, Jacobsen SE, Michel T (2007) Agroclimatic constraints for rainfed agriculture in the Bolivian Altiplano. J Arid Environ 71:109–121. doi: 10.1016/j.jaridenv.2007.02.005 CrossRefGoogle Scholar
  21. Garreaud RD (2009) The Andes climate and weather. Adv Geosci 22:1–9. doi: 10.5194/adgeo-22-3-2009 CrossRefGoogle Scholar
  22. Garreaud RD, Aceituno P (2001) Interannual rainfall variability over the South American Altiplano. J Clim 14:2779–2789. http://dx.doi.org/10.1175/1520-0442(2001)014<2779:IRVOTS>2.0.CO;2 CrossRefGoogle Scholar
  23. Geerts S, Raes D, Garcia M, Miranda R, Cusicanqui JA, Taboada C, Mendoza J, Huanca R, Mamani A, Condori O, Mamani J, Morales B, Osco V, Steduto P (2009) Simulating yield response of quinoa to water availability with AquaCrop. Agron J 101:499–508. doi: 10.2134/agronj2008.0137s CrossRefGoogle Scholar
  24. Gilford MT, Vojtesak MJ, Myles G, Bonam RC, Martens DL (1992) South America South of the Amazon River-A climatological study. USAF Environmental Technical Applications Center, 803 ppGoogle Scholar
  25. Gómez R, Roca W, Ordinola M, Manrique K, Julca P, Tapia M (2008) Papas nativas del Perú (Native potatoes of Peru). Ministerio de Agricultura (Ministry of Agriculture), LimaGoogle Scholar
  26. Haylock MR, Peterson T, Alves LM, Ambrizzi T, Anunciação YMT, Baez J, Barros VR, Berlato MA et al (2006) Trends in total and extreme South American rainfall 1960–2000 and links with sea surface temperature. J Clim 19:1490–1512. http://dx.doi.org/10.1175/JCLI3695.1 CrossRefGoogle Scholar
  27. Horqque R (1989) Informe sobre la producción de haba en Perú (Report of vean production in Peru). In: Hernández-Bravo G, Ramakrishna B (eds) Investigación para la producción de haba, lenteja, arverja y garbanzo en la subregión andina. Programa Cooperativo de Investigación Agrícola Para la Subregión Andina, PROCIANDINO, Quito, Ecuador, pp 189–222Google Scholar
  28. IGN (Instituto Geográfico Nacional, National Geographic Institute) (1989) Atlas del Perú (Atlas of Peru). Lima, Peru, 399 ppGoogle Scholar
  29. INEI (Instituto Nacional de Estadística e Informática, National Institute of Statistics and Information Technology) (1994) III Censo Nacional Agropecuario (3rd National Census of the Agricultural Sector). Technical Report. Lima, Peru. Available at http://proyectos.inei.gob.pe/CenagroWeb/. Accessed 11 June 2013
  30. INEI (Instituto Nacional de Estadística e Informática, National Institute of Statistics and Information Technology) (2010) Evolución de la Pobreza al 2009 (Evolution of poverty till 2009). Technical Report. Lima, Peru, 91 ppGoogle Scholar
  31. INEI (Instituto Nacional de Estadística e Informática, National Institute of Statistics and Information Technology) (2013a) Evolución de la Pobreza Monetaria 2007–2012 (Evolution of monetary poverty 2007–2012). Technical Report. Lima, Peru, 106 ppGoogle Scholar
  32. INEI (Instituto Nacional de Estadística e Informática, National Institute of Statistics and Information Technology) (2013b) IV Censo Nacional Agropecuario (4th National Census of the Agricultural Sector). Technical Report. Lima, Peru. http://proyectos.inei.gob.pe/CenagroWeb/. Accessed 18 Nov 2013
  33. INIA (Instituto Nacional de Investigación Agraria, National Institute of Agricultural Research) (2005) Cebada. Proyecto nacional de investigación en cultivos andinos (Barley. National Research Project on Andean Crops). Dirección general de Investigación Agraria. http://www.inia.gob.pe/notas/nota050/. Accessed 11 June 2013
  34. IPCC (2001) Climate change 2001: the scientific basis. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Contribution of working group I to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  35. Jarvis A, Ramirez J, Bonilla-Findji O, Zapata E (2011) Impacts of climate change on crop production i Latin America. In: Yadav SS, Redden RJ, Hatfield JL, Lotze-Campen H, Hall AE (eds) Crop adaptation to climate change. Wiley, Chichester, pp 44–56CrossRefGoogle Scholar
  36. Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) DSSAT cropping system model. Eur J Agron 18:235–265. doi: 10.1016/S1161-0301(02)00107-7 CrossRefGoogle Scholar
  37. Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ (2003) An overview of APSIM, a model designed for farming systems simulation. Eur J Agron 18:267–288CrossRefGoogle Scholar
  38. Lagos P, Silva Y, Nickl E, Mosquera K (2008) El Niño—related precipitation variability in Perú. Adv Geosci 14:231–237. doi: 10.5194/adgeo-14-231-2008 CrossRefGoogle Scholar
  39. Larcher W (2003) Physiological plant ecology. Springer, BerlinCrossRefGoogle Scholar
  40. Latif M, Keenlyside NS (2009) El Niño/Southern Oscillation response to global warming. Proc Nat Acad Sci PNAS 106:20578–20583. doi: 10.1073/pnas.0710860105 Google Scholar
  41. Lhomme JP, Katerji N (1991) A simple modelling of crop water balance for agrometeorological applications. Ecol Model 57:11–25. doi: 10.1016/0304-3800(91)90052-3 CrossRefGoogle Scholar
  42. Lhomme JP, Vacher JJ (2002) Modelling nocturnal heat dynamics and frost mitigation in Andean raised field systems. Agric For Meteorol 112:179–193. doi: 10.1016/S0168-1923(02)00081-3 CrossRefGoogle Scholar
  43. Lhomme JP, Mougou R, Mansour M (2009) Potential impact of climate change on durum wheat cropping in Tunisia. Clim Change 96:549–564. doi: 10.1007/s10584-009-9571-9 CrossRefGoogle Scholar
  44. Lobell DB, Schlenker W, Costa-Roberts J (2011) Climate trends and global crop production since 1980. Science 333:616–620. doi: 10.1126/science.1204531 CrossRefGoogle Scholar
  45. Magrin G, Gay García C, Cruz Choque C, Giménez JC, Moreno AR, Nagy GJ, Nobre C, Villamizar A (2007) Latin America. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate Change 2007: impacts, adaptation and vulnerability. contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 581–615Google Scholar
  46. 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, MO. http://www.ipm.montana.edu/Training/PMT../2006/mt200103.pdf. Accessed 11 June 2013
  47. MINAG (Ministerio de Agricultura del Perú - Ministry of Agriculture of Peru) (2013a) Sistema de Acceso de Base de Datos (web access to databases). http://frenteweb.minag.gob.pe/index.html. Accessed 11 June 2013
  48. MINAG (Ministerio de Agricultura del Perú—Ministry of Agriculture of Peru) (2013b) Calendario agricola (agricultural calendar). http://www.minag.gob.pe/agricola/calendario.shtml. Accessed 11 June 2013
  49. MINAG (Ministerio de Agricultura del Perú—Ministry of Agriculture of Peru) (2013c) Inventario y evaluación de los recursos naturales de la zona alto andina del Perú (Inventory and evaluation of the natural resources of the Andean highlands in Peru). http://cid.ana.gob.pe/ana/inventario-y-evaluaci%C3%B3n-de-los-recursos-naturales-de-la-zona-alto-andina-del-per%C3%BA-reconocimiento. Accessed 11 June 2013
  50. Minvielle M, Garreaud RD (2011) Projecting rainfall changes over the South American Altiplano. J Clim 24:4577–4583. doi: 10.1175/JCLI-D-11-00051.1 CrossRefGoogle Scholar
  51. Mizuta R, Oouchi K, Yoshimura H, Noda A, Katayama K, Yukimoto S, Hosaka M, Kusunoki S, Kawai H, Nakagawa M (2006) 20-km-mesh global climate simulations using JMA-GSM model—mean climate states—. J Meteor Soc Jpn 84:165–185. doi: 10.2151/jmsj.84.165 CrossRefGoogle Scholar
  52. Mizuta R, Yoshimura H, Murakami H, Matsueda M, Endo H, Ose T, Kamiguchi K, Hosaka M, Sugi M, Yukimoto S, Kusunoki S, Kitoh A (2012) Climate Simulations Using MRI-AGCM3.2 with 20-km Grid. J Meteor Soc Jpn 90A:233–258. doi: 10.2151/jmsj.2012-A12 CrossRefGoogle Scholar
  53. Monteith JL (1972) Solar radiation and productivity in tropical ecosystems. J Appl Ecol 9:747–766CrossRefGoogle Scholar
  54. Nakicenovic N, Swart R (eds) (2000) Special report on emission scenarios: a special report of working group III of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  55. Nickl EA (2007) Teleconnections and climate in the Peruvian Andes. Master Thesis, University of DelawareGoogle Scholar
  56. Noda A, Kusunoki S, Yoshimura H, Oouchi K, Mizuta R (2008) Global warming projections by an atmospheric general circulation model with a 20-km grid. In: Hamilton K, Ohfuchi W (eds) High resolution numerical modelling of the atmosphere and ocean. Global and regional climate models. Springer, Berlin, pp 113–128CrossRefGoogle Scholar
  57. Perez C, Nicklin C, Dangles O, Vanek S, Sherwood S, Halloy S, Garrett K, Forbes G (2010) Climate change in the high andes: implications and adaptation strategies for small-scale farmers. Int J Environ Cult Econ Soc Sustain 6(5), www.Sustainability-Journal.com. Accessed 11 June 2013
  58. Quevedo K, Reyes C, Zambrano A (2006) Estudio agroclimático de las condiciones hídricas en la sierra central del Perú: aplicación a los cultivos de papa, haba y quinua. Servicio Nacional de Meteorología e Hidrología, Ministerio del Ambiente, 88 ppGoogle Scholar
  59. Rötter RP, Carter TR, Olesen JE, Porter JR (2011) Crop–climate models need an overhaul. Nat Clim Change 1:175–177. doi: 10.1038/nclimate1152 CrossRefGoogle Scholar
  60. Salhuana W (2004) Diversidad y descripción de las razas en el maíz en el Perú (Diversity and description of the varieties of maize in Peru). In: Salhuana W, Valdez A, Scheuch F, Davelouis J (eds) Programa cooperativo de investigaciones en maíz (PCMI) (Cooperative research programme on maize). Universidad Nacional Agraria La Molina, Lima, pp 204–252Google Scholar
  61. Salzmann N, Huggel C, Calanca P, Díaz A, Jonas T, Jurt C, Konzelmann T, Lagos P, Rohrer M, Silverio W, Zappa M (2009) Integrated assessment and adaptation to climate change impacts in the Peruvian Andes. Adv Geosci 22:35–39. doi: 10.5194/adgeo-22-35-2009 CrossRefGoogle Scholar
  62. Sanabria J, Lhomme JP (2013) Climate change and potato cropping in the Peruvian Altiplano. Theor Appl Climatol 112:683–695. doi: 10.1007/s00704-012-0764-1 CrossRefGoogle Scholar
  63. Sanabria J, Marengo J, Valverde M (2009) Escenarios de Cambio Climático con modelos regionales sobre el Altiplano Peruano (Departamento de Puno). Rev Peruana Geo-Atmosférica 1:133–148Google Scholar
  64. Schwarb M, Acuña D, Konzelmann T, Rohrer M, Salzmann N, Serpa Lopez B, Silvestre E (2011) A data portal for regional climatic trend analysis in a Peruvian High Andes region. Adv Sci Res 6:219–226. doi: 10.5194/asr-6-219-2011 CrossRefGoogle Scholar
  65. Sietz D, Mamani Choque SE, Lüdeke MKB (2012) Typical patterns of smallholder vulnerability to weather extremes with regard to food security in the Peruvian Altiplano. Reg Environ Change 12:489–505. doi: 10.1007/s10113-011-0246-5 CrossRefGoogle Scholar
  66. Sivakumar MVK (1988) Predicting rainy season potential from the onset of rains in Southern Sahelian and Sudanian climatic of West Africa. Agric For Meteorol 42:295–305. doi: 10.1016/0168-1923(88)90039-1 CrossRefGoogle Scholar
  67. Sivakumar MVK, Motha RP (eds) (2007) Managing climate risks in agriculture. Springer, BerlinGoogle Scholar
  68. Snyder RL, de Melu-Abreu JP (2005) Frost Protection: fundamentals, practice, and economics. Environment and Natural Resources Series 10. Food and Agriculture Organization of the United Nations, Rome. http://www.fao.org/docrep/008/y7223e/y7223e00.htm. Accessed 23 Nov 2013
  69. Solman SA (2013) Regional climate modeling over South America: A review. Adv Meteorol Volume 2013, Article ID 504357, 13 pp, http://dx.doi.org/10.1155/2013/504357
  70. Solman SA, Sanchez E, Samuelsson P, da Rocha RP, Li L, Marengo J, Pessacg NL, Remedio ARC, Chou SC, Berbery H, Le Treut H, de Castro M, Jacob D (2013) Evaluation of an ensemble of regional climate model simulations over South America driven by the ERA-Interim reanalysis: model performance and uncertainties. Clim Dyn 41:1139–1157. doi: 10.1007/s00382-013-1667-2 CrossRefGoogle Scholar
  71. Steduto P, Hsiao TC, Fereres E, Raes D (2012) Crop yield response to water. FAO Irrigation and drainage paper 66. Food and Agriculture Organization of the United Nations. Rome, 500 ppGoogle Scholar
  72. Stern RD, Denett MD, Dale IC (1982) Methods for analyzing daily rainfall measurements to give useful agronomic results. I. Direct methods. Exp Agric 18:223–236. doi: 10.1017/S001447970001379X CrossRefGoogle Scholar
  73. Stöckle CO, Donatelli M, Nelson R (2003) CropSyst, a cropping systems simulation model. Eur J Agron 18:289–307. doi: 10.1016/S1161-0301(02)00109-0 CrossRefGoogle Scholar
  74. Tapia ME (1997) Zonificación agroecológica basado en el uso de la tierra, el conocimiento local y las alternativas de producción. I Curso Taller: manejo integral de microcuencas (Agroecological zonation based on land use, local knowledge and alternative forms of production. 1st Class: Integral management of watersheds). Centro Internacional de la Papa (International Potato Centre), pp 52–66. http://www.cepes.org.pe/pdf/OCR/Partidos/manejo_integral_microcuencas/manejo_integral_microcuencas4.pdf. Accessed 11 June 2013
  75. Tapia ME, Fries AM (2007) Guía de campo de los cultivos andinos (Field Guide to Andean Crops). Food and Agriculture Organization (FAO) of the United Nations, Rome, and Asociación Nacional de Productores Ecológicos del Perú (National Association of Ecological Producers of Peru; ANPE), Lima, 209 ppGoogle Scholar
  76. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteor Soc 93:485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  77. Thibeault J, Seth A, Wang G (2012) Mechanisms of summertime precipitation variability in the Bolivian Altiplano: present and future. Int J Climatol 39:2033–2041. doi: 10.1002/joc.2424 CrossRefGoogle Scholar
  78. Urrutia R, Vuille M (2009) Climate change projections for the tropical Andes using a regional climate change model: temperature and precipitation simulations for the 21st century. J Geophys Res 114:D02108. doi: 10.1029/2008JD011021 Google Scholar
  79. van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque J-F, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK (2011) The representative concentration pathways: an overview. Clim Change 109:5–31. doi: 10.1007/s10584-011-0148-z CrossRefGoogle Scholar
  80. Vanuytrecht E, Raes D, Willems P, Geerts S (2012) Quantifying field-scale effects of elevated carbon dioxide concentration on crops. Clim Res 54:35–47. doi: 10.3354/cr01096 CrossRefGoogle Scholar
  81. Vergara W, Scholz SM (2010) Assessment of the risk of Amazon dieback: main report. Environmentally and Socially Sustainable Development Department, The World Bank, Washington DC, 86 ppGoogle Scholar
  82. Vergara W, Perez E, Mendez J, Magaña V, Martinez M, Ruiz F, Avalos G, Palacios E (2007) Visualizing future climate in Latin America: results from the application of the Earth Simulator, Latin America and Caribbean Region Sustainable Development Working Paper 30. The Word Bank, Washington DC, 90 ppGoogle Scholar
  83. Wang W, Bruyere C, Duda M, Dudhia J, Gill D, Lin HC, Michalakes J, Rizvi S, Zhang X, Beezley JD, Coen JL, Mandel J (2012) ARW version 3 modeling system user’s guide. Mesoscale and Miscroscale Meteorology Division, National Center for Atmospheric http://www.mmm.ucar.edu/wrf/users/docs/user_guide_V3/ARWUsersGuideV3.pdf. Accessed 11 June 2013
  84. Wilby RL, Troni J, Biot Y, Tedd L, Hewitson BC, Smith DM, Sutton RT (2009) A review of climate risk information for adaptation and development planning. Int J Climatol 29:1193–1215. doi: 10.1002/joc.1839 CrossRefGoogle Scholar
  85. Yin L, Fu R, Shevliakova E, Dickinson RE (2013) How well can CMIP5 simulate precipitation and its controlling processes over tropical South America? Clim Dyn 41:3127–3143. doi: 10.1007/s00382-012-1582-y CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Janeet Sanabria
    • 1
    • 2
  • Pierluigi Calanca
    • 3
  • Constantino Alarcón
    • 1
  • Glicerio Canchari
    • 1
  1. 1.Department of AgrometeorologyNational Meteorological and Hydrological Services (SENAMHI) of PeruLima 11Peru
  2. 2.UMR 5563 GET, Université de Toulouse - CNRS - IRD - OMP - CNESToulouseFrance
  3. 3.Agroscope, Institute for Sustainability Sciences ISSZurichSwitzerland

Personalised recommendations