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      Las soluciones chinas de alerta temprana meteorológica ayudan a más países a afrontar los desafíos climáticos


      News provided by

      Xinhua Silk Road

      Sep 22, 2026, 05:42 ET

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      Xinhua Silk Road: Las soluciones chinas de alerta temprana meteorológica ayudan a más países a afrontar los desafíos climáticos

      PEKÍN, 22 de septiembre de 2026 /PRNewswire/ -- Según sus fieles, la tradicional diosa china del mar, Mazu, ha bendecido los viajes seguros durante milenios. En la actualidad, sistemas chinos de alerta temprana meteorológica que llevan su nombre están ayudando a más países a prevenir desastres meteorológicos.

      Continue Reading
      Photo handout via Xinhua shows the "MAZU" system at the Pakistan Meteorological Department on August 17, 2026.
      Photo handout via Xinhua shows the "MAZU" system at the Pakistan Meteorological Department on August 17, 2026.

      "MAZU", presentado por la Administración Meteorológica de China en la Conferencia Mundial de Inteligencia Artificial (WAIC) de 2025, es un conjunto de soluciones meteorológicas de desarrollo propio impulsadas por IA que ofrece alertas tempranas universales ante múltiples peligros, sistemas de aviso y una cobertura sin brechas.

      Con el respaldo a ensayos basados en la nube en más de 40 países, "MAZU" se ha implementado en naciones como Pakistán, Etiopía, las Islas Salomón, Jordania, Sri Lanka, Mongolia y Yibuti, expandiendo rápidamente su presencia global.

      Como primer conjunto de soluciones en el marco de la iniciativa de la ONU "Alertas Tempranas para Todos", "MAZU" integra modelos de alerta temprana meteorológica basados en inteligencia artificial, datos de los satélites meteorológicos Fengyun, productos de monitoreo de fuentes múltiples y capacidad de computación en la nube.

      En mayo de este año, "MAZU" fue recomendado por la Organización Meteorológica Mundial en el 11º foro de múltiples partes interesadas sobre ciencia, tecnología e innovación para los Objetivos de Desarrollo Sostenible, celebrado en la sede de las Naciones Unidas en Nueva York.

      Como era de esperar, "MAZU" satisface la demanda tanto de soluciones basadas en menús de opciones como de soluciones personalizadas de gran flexibilidad, con el fin de ayudar a los países afectados a prevenir desastres meteorológicos provocados por el cambio climático.

      En Pakistán, donde los monzones y las tormentas suelen provocar inundaciones torrenciales, se integró formalmente en las plataformas pertinentes de la autoridad meteorológica paquistaní un sistema de alerta temprana desarrollado conjuntamente por China y Pakistán.

      En Etiopía, expertos chinos aprovecharon la integración de datos procedentes de los satélites meteorológicos chinos Fengyun y de estaciones meteorológicas locales para ayudar a los meteorólogos de la zona a generar pronósticos a muy corto plazo de alta precisión mediante los modelos de inteligencia artificial Fenglei y Fengqing.

      En Sri Lanka, la oficina meteorológica de la provincia de Fujian, en el sureste de China, está ayudando al país a lograr pronósticos de precipitación y temperatura con alta resolución espacio-temporal.

      Además de los casos de aplicación de "MAZU", cerca de 1.000 personas procedentes de más de 100 países y regiones en desarrollo han viajado a China para recibir formación tecnológica centrada en la alerta temprana.

      Dado que China es un socio fundamental de la iniciativa "Alertas Tempranas para Todos", sus plataformas, satélites y modelos de inteligencia artificial han ayudado a decenas de países a mejorar sus capacidades de alerta temprana, señaló el Secretario General de la ONU, António Guterres, en la WAIC de 2026.

      Esta modalidad de cooperación, que conlleva la transferencia de tecnología, la investigación y el desarrollo conjuntos y el fortalecimiento de las capacidades locales para ayudar a los países en desarrollo a proteger mejor a sus poblaciones, es exactamente lo que el mundo necesita ahora, añadió Guterres.

      Enlace original: https://en.imsilkroad.com/p/352292.html

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