E-proceedings of the 38 th IAHR World Congress September 1-6, 2019, Panama City, Panama doi:10.3850/38WC092019-1536 292 CLIMATE ANALOGUES OF CAPITAL CITIES IN THE WEST SOUTH AMERICA REINHARDT PINZÓN (1,2) , TOSIYUKI NAKAEGAWA (3) , KENSHI HIBINO (4) , & IZURU TAKAYABU (5) (1) Centro de Investigaciones Hidráulicas e Hidrotécnicas, Universidad Tecnológica de Panamá (UTP), Panamá reinhardt.pinzon@utp.ac.pa (2) Sistema Nacional de Investigación (SNI), Panama (3) Meteorological Research Institute, Japan tnakaega@mri-jma.go.jp (4) Institute of Industrial Science, the University of Tokyo, Japan hibino@iis.u-tokyo.ac.jp (5) Meteorological Research Institute, Japan takayabu@mri-jma.go.jp ABSTRACT By means of a recently customary nonparametric method future climate analogues were predictable for West South American capital cities. The nonparametric scheme showed in this research for identifying climate analogues can be applied for impact assessments under a changing climate. MRI-AGCM3.2H with a horizontal resolution of 60 km, three convection schemes, four sea surface temperature distributions, and two initial conditions and under scenario A1B of the Special Report on Emissions Scenarios were used. The total ensemble scope was 24, with a simulation period of 25 years. Utmost of the future analogues are at lower latitudes than their target cities. Estimated seasonal variations in surface air temperature and rainfall in Santiago de Chile City look similar to the present-day climate of Cape Town, located in South Africa and for La Paz City a climate analogue is found at Oruro in Bolivia. Keywords: Climate analogue, climate change, surface air temperature; rainfall; nonparametric method; West South America. 1 INTRODUCTION Climate analogues method gets how to connect climate at an objective point to regular community, politicians, sponsors, and to experts who study biosciences and environmental resources. For example, recognizing spatial and temporal analogues places or areas making available understandings how biota and crops are vulnerability to climate change, is providing for the climate analogues technique (Leibing et al., 2016). Furthermore, analogues scheme based on climatic features gives visions on regions with present climate environments look like future or past surroundings in a different location (e.g., Williams et al., 2007; Ramírez-Villegas et al., 2011). Numerous regions have been studied using it such as Central America (Pinzon et al., 2017), Japan (Ishizaki et al., 2012), Australia (Webb et al., 2013; Nakaegawa et al., 2017), worldwide (Arnbjerg-Nielsen et al., 2015; Soteriades et al., 2017), nonetheless not for West South America. On the other hand, Hibino et al. (2015) demonstrated probabilistic terrestrial scatterings of climate analogues by integrating uncertainties from greenhouse gases emission scenarios, climate model itself, and internal variability in order to overcome the deterministic-ill issue. Local forcing disturbs the climatological behavior in South America which includes tropical subtropical and extratropical landscapes. Andes chain is a significant western coast feature described by a thin barrier routing the stream in the central part of the mainland. The seasonal precipitation at west of the Andes is defined by the sea surface temperature (SST) over Pacific Ocean (Solman, 2013). Moreover, in this zone, hydroclimatic conditions are determinate by the temperature relations among mainland and the oceans (Nakaegawa et al., 2014c). The agrarian area and food security were affected and producing an economic and social impact on Latin America because both at the same time, El Niño (ENSO), the Pacific Decadal Oscillation and the hottest temperature time on Earth appear on the last 3 years (Martinez et al., 2017). In addition, the Atlantic and the Pacific oceans cause the foremost climate variabilities over the South America (Ramos da Silva Hass, 2016). Precipitation is seems the most leading hydroclimatological component (e.g., Taylor and Alfaro, 2005; Nakaegawa et al., 2014b). Likewise, heterogeneous demographic group migration is most conditioned by exposure