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dc.contributor.authorManzanas, R.
dc.contributor.authorOria, Clara
dc.contributor.authorDe la Cruz, Gustavo
dc.description.abstractThis report briefly describes how SENAMHI ( obtained local projections of precipitation/ maximum/minimum temperature (daily data up to 2065) for 265/105/102 selected stations over Peru, needed for the completion of tasks within the Component I of the AMICAF project. In particular, an analog‐ (regression‐) based technique was applied to generate an ensemble of six ‘plausible’ projections of precipitation (temperatures), considering three different Earth System Models and two Representative Concentration Pathways. The tool used to this aim was the Statistical Downscaling Portal ( developed and maintained by Predictia Intelligent Data Solutions ( and the Meteorology Group of the University of Cantabria ( The Component I of AMICAF Peru provides projections of precipitation/ maximum/mínimum temperature for 256/105/102 stations over Peru up to 2065, by means of statistical downscaling. An ensemble of six ‘plausible’ projections (3 ESMs × 2 RCPs) is considered for each target variable, which allows for a proper assessment of the uncertainties involved in this type of study. For the period 2036‐2065, results show a mean (for the entire country) increment (with respect to 1971‐ 2000) between C and C (C and C) for maximum (minimum) temperature. For precipitation, it is between 10% and 20%.es_PE
dc.description.sponsorshipIs implemented by FAO through a trust fund of the Government of Japan
dc.publisherAnalysis and Mapping of Impacts under Climate Change for Adaptation and Food Security ‐ AMICAFes_PE
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.sourceRepositorio Institucional - SENAMHIes_PE
dc.sourceServicio Nacional de Meteorología e Hidrología del Perúes_PE
dc.subjectCambio Climáticoes_PE
dc.subjectTemperatura del Airees_PE
dc.subjectStatistical Downscalinges_PE
dc.subjectInseguridad Alimentaria
dc.titleGeneration of statistically downscaled climate change scenarios in Perues_PE
dc.title.alternativeRegionalización estadística de escenarios climáticos en el Perú

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