Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

Global Climate Change01:50

Global Climate Change

24.3K
Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
24.3K
What is Climate?01:16

What is Climate?

18.4K
Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
18.4K
Precipitation Processes01:12

Precipitation Processes

442
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
442
What is Weather?01:07

What is Weather?

18.2K
Overview
18.2K
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

1.8K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
1.8K
Variability: Analysis01:11

Variability: Analysis

137
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
137

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Changes in El Niño-Southern Oscillation and global frequency entrainment.

Nature communications·2026
Same author

AMOC slowdown amplifies North Atlantic salinity variability to unprecedented levels.

Nature communications·2026
Same author

Oceanic mesoscale eddies enhance the Pacific Decadal Oscillation and its predictability.

Science advances·2026
Same author

Distinct impacts of tropical North Atlantic warming flavors on cross-basin tropical cyclone activity.

Science advances·2026
Same author

Critical role of low cloud feedback in irreversible sea level rise.

Nature communications·2026
Same author

Projected changes in tropical instability wave activity in the Pacific Ocean under greenhouse warming.

Proceedings of the National Academy of Sciences of the United States of America·2026

Video Experimental Relacionado

Updated: Jun 22, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

5.8K

La previsibilidad explicable de El Niño a partir de las interacciones de los modos climáticos

Sen Zhao1, Fei-Fei Jin2,3, Malte F Stuecker4,5

  • 1Department of Atmospheric Sciences, School of Ocean and Earth Science and Technology (SOEST), University of Hawai'i at Mānoa, Honolulu, HI, USA.

Nature
|June 26, 2024
PubMed
Resumen

Un modelo de oscilador de recarga no lineal extendido mejora las previsiones de El Niño-Oscilación Sur (ENSO) hasta 18 meses. Este modelo vincula la habilidad de pronóstico a las condiciones iniciales de otros modos climáticos, mejorando la previsibilidad más allá de los modelos climáticos actuales.

Más Videos Relacionados

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

938
Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Published on: June 8, 2015

8.7K

Videos de Experimentos Relacionados

Last Updated: Jun 22, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

5.8K
Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

938
Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Published on: June 8, 2015

8.7K

Área de la Ciencia:

  • Ciencias del clima
  • La oceanografía
  • Ciencias atmosféricas

Sus antecedentes:

  • El Niño-Oscilación del Sur (ENSO) es el principal impulsor de la variabilidad climática estacional global.
  • La cuantificación de las fuentes de previsibilidad de ENSO sigue siendo un desafío importante.
  • La inteligencia artificial ofrece pronósticos avanzados pero carece de vínculo con el proceso físico.

Objetivo del estudio:

  • Desarrollar y validar un modelo para el pronóstico de ENSO.
  • Identificar y cuantificar las fuentes de previsibilidad de ENSO.
  • Mejorar la comprensión de la dinámica y las interacciones de ENSO.

Principales métodos:

  • Desarrollo de un modelo de oscilador de recarga no lineal extendido (XRO).
  • Incorporación de las dinámicas centrales del ENSO y de las interacciones con otros modos climáticos.
  • Análisis de las condiciones iniciales y efectos de memoria de los modos climáticos en el ENSO.

Principales resultados:

  • El modelo XRO logró pronósticos ENSO hábiles de hasta 16-18 meses, superando a los modelos climáticos globales.
  • La habilidad de pronóstico estaba vinculada a las condiciones iniciales y a la memoria de otros modos climáticos.
  • La reducción de los sesgos del modelo en la dinámica de ENSO y las interacciones de modo mejoró la habilidad de pronóstico.

Conclusiones:

  • El modelo XRO proporciona un marco parsimonioso pero eficaz para la predicción de ENSO.
  • La comprensión de las interacciones entre ENSO y otros modos climáticos es crucial para mejorar las previsiones.
  • El marco XRO ofrece objetivos para mejorar las simulaciones y predicciones ENSO.