Latin America & Caribbean

Last modified by S2S_regionact on 2023/10/18 05:21


This page contains relevant information about activities and projects developed in Latin America and the Caribbean dedicated to sub-seasonal to seasonal predictions.  The majority of these activities and projects are associated to the work of National Meteorological Services and Regional Climate Centers, links to the websites of these institutions are below (content in Spanish). At the bottom it can be found important publications related to the sub-seasonal to seasonal predictability and climate variability in the region.

Consider sign-up to the mailing list to receive updates on Regional S2S Activities. Find the link at the bottom of the main page:

Information on regional workshops

  • Webinar: Seasonal Forecasting Fundamentals and Tools: Webinar organized by the Regional Climate Center for the South of South America (CRC-SAS) and dictated by researcher Dr. Marisol Osman from the Center for Research on the Sea and Atmosphere (CIMA / UBA-CONICET). In Spanish.

          Part 1:

          Part 2:

          Part 3:

  • Regional Climate Outlook Forums (RCOF) for Western South America: The Regional Climate Outlook Forum (RCOF), organized by the Regional Climate Center for Western South America (CRC-OSA), started in the city of Lima, Peru, in 1997, and its first objectives were to bring together experts in meteorology, climatology, hydrology, and oceanography, mainly from western South America, but also from other countries, to assess ocean-atmospheric conditions and prospects climatic conditions for the Latin American region. More information (in Spanish): 
  • Regional Climate Outlook Forums (RCOF) for Southern South America: The Regional Climate Outlook Forum (RCOF), organized by the Regional Climate Center for Southern South America (CRC-SAS). More information (in Spanish):
  • Regional Climate Outlook Forums (RCOF) for Central America: The Regional Climate Outlook Forum (RCOF) is organized by the Regional Climate Center for Central America (Comité Regional de Recursos Hidráulicos - CRRH - del Sistema de Integración Centroamericana). The event takes place three times per year (april, july and november). It hosts a group of meteorologists, climatologists and hydrologists from the National Meteorological and Hydrological Services of Central America and provides a space to discuss climate and meteorological forecasts. More information (in Spanish):

  • Advances NextGen S2S Climate Forecasting ToT Workshop for DMC (Chile) and CIAT (Colombia): This Training of Trainers (ToT) workshop focused on providing advanced training on theoretical and practical aspects of the NextGen methodology to experts from two projects and institutions. 

    The International Center for Tropical Agriculture (CIAT)-Bioversity Alliance is the lead institution for the project “AgriLAC Resiliente: Resilient Agri Food Innovation Systems Driving Food Security, Inclusive Growth, and Reduced Out-Migration in Latin America and the Caribbean (LAC)”, which aims to increase the resilience, sustainability and competitiveness of Latin American and Caribbean agrifood systems and actors by better equipping them to meet urgent food security needs, reduce climate threat, stabilize conflict-vulnerable communities and reduce out-migration.

    The Dirección Meteorología de Chile (DMC) is the national meteorological service of Chile. As part of the bilateral agreement between IRI and Chile under the Enhancing Adaptive Capacity of Andean Communities through Climate Services (ENANDES). The ENANDES project (Adaptation Fund & WMO) aims to increase the resilience and adaptive capacity to climate variability and change of highly vulnerable communities living in the Andes. Through the generation of and access to specific climate information and services, governments and communities will together be able to reduce climate-related risks and implement climate adaptation measures for protecting households and increasing food and water security.

    Training wiki page:

Institutions/Projects in the region working on S2S

  • Climate Services Through Knowledge Co-Production (CLIMAX): An inter- and trans-disciplinary framework based on a European-South American research cooperation is implemented to underpin climate services in South America. Climate variability patterns linking the South American Monsoon region, including Amazonia, with south eastern South America, influence climate extremes and impact several societal sectors. More than 200 million people live in the region that is one of the world largest agricultural producing region and where the second world largest hydroelectric power plant is situated. Besides recent progress, further efforts are needed to better understand and predict regional climate variability. The project contributes to the implementation of the "Southern South America Regional Climate Centre (CRC-SAS)", and it includes actors from the national meteorological services, agriculture and energy stakeholders and organizations. Innovative technologies will be codeveloped to produce tools and products for the CRC-SAS, with focus on both agriculture and hydropower sectors. More information:

  • Drought Information System for southern South America (SISSA): SISSA provides tools and information on droughts and their impacts to governments, non-governmental and private institutions, and individuals. SISSA is a virtual institution that operates within the framework of the Regional Climate Center for southern South America (CRC-SAS). More information and forecasts: 

  • The Chilean NextGen: Chile’s National Meteorological Service (DMC, as per its initials in Spanish) had implemented the Next Generation of Seasonal Climate Forecasts (NextGen), developed by the International Research Institute for Climate and Society (IRI). NextGen is a multi-model, statistically calibrated seasonal forecast system that takes advantage of the expertise of forecasters and local scientists. It is a modern forecast methodology that validates global models based on local experiences and climate data to provide more robust and fine-tuned forecasts for specific areas of interest. The predictions are to be used by decision-makers in sectors such as agriculture and food security, energy, water management, disaster prevention, health, and others. More information:

    The seasonal forecast is updated every month and presented in a public discussion and a bulletin. Monthly bulletin (in spanish):

  • The Colombian NextGen: Climate scientists from the International Research Institute for Climate and Society and Colombia’s national meteorological service (called the Institute of Hydrology, Meteorology and Environmental Studies and known by its Spanish acronym, IDEAM develop a more advanced seasonal forecasting system called ‘the Next Generation of Seasonal Climate Forecasts,’ or NextGen. NextGen is a new set of high-quality, flexible, and tailored predictions made by Colombians for Colombians, assisted and funded by the IRI-led Adapting Agriculture to Climate Today, for Tomorrow (ACToday) project, part of Columbia World Projects. More information:

  • The Guatemalan NextGen: The Guatemala's national meteorological service (called Institute of Seismology, Volcanology, Meteorology and Hydrology and known by its Spanish acronym INSIVUMEH) is also collaborating with IRI through the ACToday project to develop seasonal forecasts with the NextGen methodology.  Sub-seasonal forecasts are also being developed.

    The seasonal forecast data can be visualized and downloaded from the INSIVUMEH Data Library - There is a specific maproom with different products available:

  • Seasonal Climate Forecast System for Bolivia: Developed by the International Center for Research on the El Niño Phenomenon (CIIFEN) and the Bolivian Ministry of the Environment and Water (MMAyA), the Bolivian Seasonal Climate Forecasting System (SistPronClim-Bolivia) uses statistical calibration processes of the global model products, based onspatio-temporal patterns, capable of timely identification of risk situations due to deficit and excess precipitation, in the same way, temperature values ​​that are below or above threshold values ​​through indicators adapted to the Bolivian context, in order to feed the systems surveillance, early warning and information to the general public at the local and regional level, supporting preparedness plans and risk management policies.The project is based on the fact that climate prediction is used as an essential tool for takingmedium and long-term decisions, planning, early warning of potential threats such as drought, andadaptation to climate variability and change. More information and forecasts:

    More information about CIIFEN:

  • Subseasonal to Seasonal Forecasts of the Argentine National Meteorological Service:  The SMN (for its acronym in Spanish) periodically conducts climate monitoring and forecasting from the sub-seasonal to the seasonal scale. More information (in Spanish):

    Subseasonal (weekly) forecast:

Key regionally-relevant S2S research questions & activities being pursued in the region


South America

  • Alvarez, M., C. Vera, G. Kiladis, and B. Liebmann, 2014: Intraseasonal Variability in South America during the Cold Season. Climate Dynamics, 42, 3253-3269.

  • Alvarez, M., C. Vera, G. Kiladis, and B. Liebmann, 2016: Influence of the Madden Julian Oscillation on Precipitation and Surface Air Temperature in South America. Climate Dynamics, 46, 245-262.

  • Alvarez, M.S.; C. S. Vera, and G. N. Kiladis, 2017: MJO Modulating the Activity of the Leading Mode of Intraseasonal Variability in South America. Atmosphere, 8 (12), 232.

  • Alvarez, M. S., C. A. S. Coelho, M. Osman, M. Â. F. Firpo, and C. S. Vera, 2020: Assessment of ECMWF Subseasonal Temperature Predictions for an Anomalously Cold Week Followed by an Anomalously Warm Week in Central and Southeastern South America during July 2017. Wea. Forecasting, 35, 1871–1889.

  • Barrett, B. S., Carrasco, J. F., & Testino, A. P. (2012). Madden–Julian oscillation (MJO) modulation of atmospheric circulation and Chilean winter precipitation. Journal of Climate, 25(5), 1678-1688.

  • Barrett, B. S., & Hameed, S. (2017). Seasonal variability in precipitation in central and southern Chile: Modulation by the South Pacific high. Journal of Climate, 30(1), 55-69.

  • Barros, V. R., Grimm, A. M., & Doyle, M. E. (2002). Relationship between temperature and circulation in Southeastern South America and its influence from El Ninño and La Ninña events. Journal of the Meteorological Society of Japan. Ser. II, 80(1), 21-32.

  • Barrucand, M., Rusticucci, M., & Vargas, W. (2008). Temperature extremes in the south of South America in relation to Atlantic Ocean surface temperature and Southern Hemisphere circulation. Journal of Geophysical Research: Atmospheres, 113(D20).

  • Blázquez, J., & Solman, S. A. (2017). Interannual variability of the frontal activity in the Southern Hemisphere: relationship with atmospheric circulation and precipitation over southern South America. Climate Dynamics, 48(7-8), 2569-2579.

  • Campos, D., & Rondanelli, R. ENSO‐related precipitation variability in Central Chile: The role of large scale moisture transport. Journal of Geophysical Research: Atmospheres, e2023JD038671.

  • Cerne, S. B., & Vera, C. S. (2011). Influence of the intraseasonal variability on heat waves in subtropical South America. Climate Dynamics, 36(11), 2265-2277.

  • Coelho, C. A. (2013). Comparative skill assessment of consensus and physically based tercile probability seasonal precipitation forecasts for Brazil. Meteorological Applications, 20(2), 236-245.

  • Collazo, S., Barrucand, M., & Rusticucci, M. (2019). Summer seasonal predictability of warm days in Argentina: statistical model approach. Theoretical and Applied Climatology, 138(3), 1853-1876.

  • Collazo, S., Barrucand, M., & Rusticucci, M. (2019). Variability and predictability of winter cold nights in Argentina. Weather and Climate Extremes, 26, 100236.

  • Delorit, J., Gonzalez Ortuya, E. C., & Block, P. (2017). Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley, Chile. Hydrology and Earth System Sciences, 21(9), 4711-4725.

  • Doss-Gollin, J., Muñoz, Á. G., Mason, S. J., & Pastén, M. (2018). Heavy rainfall in Paraguay during the 2015/16 austral summer: Causes and subseasonal-to-seasonal predictive skill. Journal of Climate, 31(17), 6669-6685.

  • Esquivel, A., Llanos-Herrera, L., Agudelo, D., Prager, S. D., Fernandes, K., Rojas, A., ... & Ramirez-Villegas, J. (2018). Predictability of seasonal precipitation across major crop growing areas in Colombia. Climate Services, 12, 36-47.

  • Fernandes, K., Muñoz, A. G., Ramirez-Villegas, J., Agudelo, D., Llanos-Herrera, L., Esquivel, A., ... & Prager, S. D. (2020). Improving seasonal precipitation forecasts for agriculture in the orinoquía Region of Colombia. Weather and Forecasting, 35(2), 437-449.

  • González, P. M., C. Vera, B. Liebmann, G. Kiladis, 2008: Intraseasonal variability in subtropical South America as depicted by precipitation data. Clim. Dyn., 30, 727–744.

  • González, P., C. Vera, 2014: Summer precipitation variability over South America on long and short intraseasonal timescales. Climate Dynamics, 43, 1993-2007.

  • Gubler, S., Sedlmeier, K., Bhend, J., Avalos, G., Coelho, C. A. S., Escajadillo, Y., Jacques-Coper, M., Martinez, R., Schwierz, C., de Skansi, M., & Spirig, Ch. (2020). Assessment of ECMWF SEAS5 seasonal forecast performance over South America. Weather and Forecasting, 35(2), 561-584.

  • Jacques‐Coper, M., Veloso‐Aguila, D., Segura, C., & Valencia, A. (2021). Intraseasonal teleconnections leading to heat waves in central Chile. International Journal of Climatology.

  • Lowe, R., Stewart-Ibarra, A. M., Petrova, D., García-Díez, M., Borbor-Cordova, M. J., Mejía, R., ... & Rodó, X. (2017). Climate services for health: predicting the evolution of the 2016 dengue season in Machala, Ecuador. The lancet Planetary health, 1(4), e142-e151.

  • Luz Clara, M., Alvarez, M.S., Vera, C., C. Simionato, A. Jaureguizar, 2021: Relationship between sea surface temperature anomalies in the Southwestern Atlantic Continental Shelf and atmospheric variability on intraseasonal timescales. Clim Dyn.

  • Marín, J. C., & Barrett, B. S. (2017). Seasonal and intraseasonal variability of precipitable water vapour in the Chajnantor plateau, Chile. International Journal of Climatology, 37, 958-971.

  • Mayta, V. C., Ambrizzi, T., Espinoza, J. C., & Silva Dias, P. L. (2019). The role of the Madden–Julian oscillation on the Amazon Basin intraseasonal rainfall variability. International Journal of Climatology, 39(1), 343-360.

  • Mayta, V. C., Silva, N. P., Ambrizzi, T., Dias, P. L. S., & Espinoza, J. C. (2020). Assessing the skill of all-season diverse Madden–Julian oscillation indices for the intraseasonal Amazon precipitation. Climate Dynamics, 54, 3729-3749.

  • Meza, F. J., & Wilks, D. S. (2003). Value of operational forecasts of seasonal average sea surface temperature anomalies for selected rain-fed agricultural locations of Chile. Agricultural and Forest Meteorology, 116(3-4), 137-158.

  • Montecinos, A., Díaz, A., & Aceituno, P. (2000). Seasonal diagnostic and predictability of rainfall in subtropical South America based on tropical Pacific SST. Journal of Climate, 13(4), 746-758.

  • Montecinos, A., & Aceituno, P. (2003). Seasonality of the ENSO-related rainfall variability in central Chile and associated circulation anomalies. Journal of climate, 16(2), 281-296.

  • Montecinos, A., Purca, S., & Pizarro, O. (2003). Interannual‐to‐interdecadal sea surface temperature variability along the western coast of South America. Geophysical Research Letters, 30(11).

  • Muñoz, Á. G., Goddard, L., Robertson, A. W., Kushnir, Y., & Baethgen, W. (2015). Cross–time scale interactions and rainfall extreme events in southeastern South America for the austral summer. Part I: Potential predictors. Journal of Climate, 28(19), 7894-7913.

  • Muñoz, Á. G., Goddard, L., Mason, S. J., & Robertson, A. W. (2016). Cross–time scale interactions and rainfall extreme events in southeastern South America for the austral summer. Part II: Predictive skill. Journal of Climate, 29(16), 5915-5934.

  • Muñoz, Á. G., Díaz-Lobatón, J., Chourio, X., & Stock, M. J. (2016). Seasonal prediction of lightning activity in north western Venezuela: Large-scale versus local drivers. Atmospheric Research, 172, 147-162.

  • Osman, M., C. Vera, F. Doblas-Reyes, 2016: Predictability of the tropospheric circulation in the Southern Hemisphere from CHFP models. Climate Dynamics, 46, 7, 2423-2434.

  • Osman, M., & Vera, C. S. (2017). Climate predictability and prediction skill on seasonal time scales over South America from CHFP models. Climate Dynamics, 49(7), 2365-2383.

  • Otero, F., M. S. Alvarez, P. Salio, and, C. Vera, 2019: Intraseasonal modulation of spring‐strong wind events associated with convection in northeastern Argentina. Int. J. Climatol.

  • Petry, I., Fan, F. M., Siqueira, V. A., Collishonn, W., de Paiva, R. C. D., Quedi, E., ... & Paranhos, C. S. A. (2023). Seasonal streamflow forecasting in South America’s largest rivers. Journal of Hydrology: Regional Studies, 49, 101487.

  • Recalde-Coronel, G. C., Barnston, A. G., & Muñoz, Á. G. (2014). Predictability of December–April rainfall in coastal and Andean Ecuador. Journal of Applied Meteorology and Climatology, 53(6), 1471-1493.

  • Rusticucci, M., & Vargas, W. (2002). Cold and warm events over Argentina and their relationship with the ENSO phases: risk evaluation analysis. International Journal of Climatology: A Journal of the Royal Meteorological Society, 22(4), 467-483.

  • Rusticucci, M., Barrucand, M., & Collazo, S. (2017). Temperature extremes in the Argentina central region and their monthly relationship with the mean circulation and ENSO phases. International Journal of Climatology, 37(6), 3003-3017.

  • Rutllant, J., & Fuenzalida, H. (1991). Synoptic aspects of the central Chile rainfall variability associated with the Southern Oscillation. International Journal of Climatology, 11(1), 63-76.

  • Ungerovich, M., Barreiro, M., & Masoller, C. (2021). Influence of Madden–Julian Oscillation on extreme rainfall events in Spring in southern Uruguay. International Journal of Climatology, 41(5), 3339-3351.

  • Vera, C.S., M. S. Alvarez, M.S., P. L. M. Gonzalez, G. N. Kiladis, and B. Liebmann, 2018: Seasonal cycle of precipitation variability in South America on intraseasonal timescales. Climate Dynamics, 51, 5–6, 1991–2001.

  • Verbist, K., Robertson, A. W., Cornelis, W. M., & Gabriels, D. (2010). Seasonal predictability of daily rainfall characteristics in central northern Chile for dry-land management. Journal of Applied Meteorology and Climatology, 49(9), 1938-1955.

  • Xue, J., Luo, J. J., Yuan, C., & Yamagata, T. (2020). Discovery of Chile Niño/Niña. Geophysical Research Letters, 47(5), no-no.

Central America

  • Alfaro, E. (2002). Some characteristics of the annual precipitation cycle in Central America and their relationships with its surrounding tropical oceans.  Tópicos Meteorológicos y Oceanográficos, 9(2), 88-103.
  • Alfaro, E. (2018). Revision of the main drivers and variability of Central America Climate and seasonal forecast systems. Revista de Biología Tropical. 66(Suppl. 1): S153-S175.
  • Alfaro, E., Chourio, X., Muñoz, A., Mason, S. (2017). Improved seasonal prediction skill of rainfall for the Primera season in Central America. International Journal of Climatology, 38, e255-e268. 
  • Pons, D., Muñoz, Á. G., Meléndez, L. M., Chocooj, M., Gómez, R., Chourio, X., & Romero, C. G. (2021). A coffee yield next-generation forecast system for rain-fed plantations: the case of the Samalá watershed in Guatemala. Weather and Forecasting, 36(6), 2021-2038.
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