Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Predicting Molecular Geometry02:27

Predicting Molecular Geometry

46.0K
VSEPR Theory for Determination of Electron Pair Geometries
46.0K
Prediction Intervals01:03

Prediction Intervals

3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.4K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

1.2K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.2K
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

1.4K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
1.4K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

10.9K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
10.9K
Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

14.8K
When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
14.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

ENSO phase transition enables prediction of winter North Atlantic Oscillation one year ahead.

Nature communications·2026
Same author

Tibetan-Plateau heating subseasonally bursts marine heatwaves in Kuroshio Extension.

Science bulletin·2026
Same author

Puerto Rico Coral Reef Monitoring Program Water Quality Data from 2023-2025.

Scientific data·2025
Same author

Recent European marine heatwaves are unprecedented but not unexpected.

Communications earth & environment·2025
Same author

CO<sub>2</sub>-induced climate change assessment for the extreme 2022 Pakistan rainfall using seasonal forecasts.

NPJ climate and atmospheric science·2025
Same author

Towards developing an operational Indian ocean dipole warning system for Southeast Asia.

Scientific reports·2025

Related Experiment Video

Updated: Feb 7, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

920

Predicting El Niño in 2014 and 2015.

Sarah Ineson1, Magdalena A Balmaseda2, Michael K Davey3

  • 1Met Office Hadley Centre, Exeter, UK. sarah.ineson@metoffice.gov.uk.

Scientific Reports
|July 18, 2018
PubMed
Summary

Forecast systems predicted a strong El Niño in 2014/15 but a weak one occurred. Stronger westerly wind bursts in 2015, compared to 2014, were key to the record 2015/16 El Niño event.

More Related Videos

Bioindication Testing of Stream Environment Suitability for Young Freshwater Pearl Mussels Using In Situ Exposure Methods
07:53

Bioindication Testing of Stream Environment Suitability for Young Freshwater Pearl Mussels Using In Situ Exposure Methods

Published on: September 5, 2018

7.8K
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.8K

Related Experiment Videos

Last Updated: Feb 7, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

920
Bioindication Testing of Stream Environment Suitability for Young Freshwater Pearl Mussels Using In Situ Exposure Methods
07:53

Bioindication Testing of Stream Environment Suitability for Young Freshwater Pearl Mussels Using In Situ Exposure Methods

Published on: September 5, 2018

7.8K
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.8K

Area of Science:

  • Climate Science
  • Oceanography
  • Meteorology

Background:

  • Seasonal forecast systems predicted a strong El Niño event for winter 2014/15, but a modest warming occurred.
  • Winter 2015/16 experienced one of the strongest El Niño events on record, contrasting with the previous year.

Purpose of the Study:

  • To assess the forecasting ability of two operational seasonal prediction systems for the 2014/15 and 2015/16 El Niño events.
  • To understand the reasons behind the differing development and outcomes of these two El Niño events using forecast ensembles.

Main Methods:

  • Testing three hypotheses regarding ENSO (El Niño-Southern Oscillation) conditions, sea surface temperature anomalies, and wind burst activity.
  • Analyzing forecast ensembles from ECMWF System 4 and Met Office GloSea5.

Main Results:

  • Neutral ENSO conditions in 2014 were linked to a persistent cold southeast Pacific sea surface temperature anomaly.
  • Warm west equatorial Pacific sea surface temperature anomalies did not impede El Niño development in the forecasts.
  • Stronger westerly wind burst activity in 2015 was identified as a key differentiator from 2014, and this variability was predictable.

Conclusions:

  • The continuation of neutral ENSO conditions and cold southeast Pacific anomalies contributed to the weaker 2014/15 event.
  • Increased westerly wind burst activity was a critical factor in the development of the strong 2015/16 El Niño.
  • ECMWF System 4's tendency to predict more westerly wind bursts than GloSea5 may explain its prediction of larger SST anomalies.