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

Irrotational Flow01:28

Irrotational Flow

1.1K
Irrotational flow is characterized by fluid motion where particles do not rotate around their axes, resulting in zero vorticity. For a flow to be irrotational, the curl of the velocity field must be zero. This imposes specific conditions on velocity gradients. For instance, to maintain zero rotation about the z-axis, the gradient condition:
1.1K
General External Flow Characteristics01:26

General External Flow Characteristics

573
The study of external flow is essential for creating structures and objects that interact efficiently and safely with moving fluids, such as air or water. When a body is immersed in a flowing fluid, it experiences two primary forces: drag, which opposes motion along the flow direction, and lift, which acts perpendicular to the flow. The shape, size, and orientation of the object influence these forces.Streamlined and Blunt Bodies in External FlowObjects in fluid flow are classified as...
573
Plane Potential Flows01:23

Plane Potential Flows

1.0K
Plane potential flows simplify fluid motion by assuming the fluid to be irrotational and incompressible. These characteristics allow these flows to be described by a velocity potential function, ϕ, representing the flow speed in a given direction, and a stream function, ψ, that visualizes the flow path, both governed by Laplace's equation. These parameters help in estimating flow patterns, velocity distributions, and pressure fields around various hydraulic structures.
Uniform...
1.0K
Turbulent Flow01:24

Turbulent Flow

810
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
810
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

682
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
682
Rapidly Varying Flow01:24

Rapidly Varying Flow

561
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
561

You might also read

Related Articles

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

Sort by
Same author

Gap filling between GRACE and GRACE-FO missions: assessment of interpolation techniques.

Journal of geodesy·2024
Same journal

Forecasting secular variation using physics-informed neural networks for IGRF-14.

Earth, planets, and space : EPS·2026
Same journal

Global data-driven predictions of seasonal non-tectonic signals in vertical GNSS displacement time series from non-tidal surface loading data.

Earth, planets, and space : EPS·2026
Same journal

IGRF-14 secular variation prediction from core surface flow acceleration.

Earth, planets, and space : EPS·2026
Same journal

Model calculations for neutron-induced reactions in meteorites and planetary surfaces.

Earth, planets, and space : EPS·2026
Same journal

The spatiotemporal development of the midlatitude troughs and subauroral ion drift during a geomagnetic storm observed by multiple DMSP satellites.

Earth, planets, and space : EPS·2026
Same journal

A database of geomagnetic observatory monthly means: from historic to the satellite era.

Earth, planets, and space : EPS·2026
See all related articles

Related Experiment Video

Updated: Mar 3, 2026

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.5K

How do core surface flow models vary when inverted from IGRF-14 candidate field models?

H F Rogers1, M Mandea2

  • 1School of Earth and Environment, University of Leeds, Woodhouse, Leeds, LS2 9JT UK.

Earth, Planets, and Space : EPS
|March 2, 2026
PubMed
Summary
This summary is machine-generated.

The new International Geomagnetic Reference Field (IGRF-14) model refines Earth's magnetic field predictions. Analysis shows variations in candidate models impact core flow predictions, with higher truncation degrees improving accuracy.

Keywords:
Core surface flow inversionInternational Geomagnetic Reference Field (IGRF)Secular variation

More Related Videos

Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods
09:17

Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods

Published on: April 23, 2018

11.3K
Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

13.1K

Related Experiment Videos

Last Updated: Mar 3, 2026

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.5K
Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods
09:17

Experimental Investigation of the Flow Structure over a Delta Wing Via Flow Visualization Methods

Published on: April 23, 2018

11.3K
Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

13.1K

Area of Science:

  • Geophysics and Earth Sciences
  • Geomagnetism and Earth's Magnetic Field
  • Core Dynamics and Geodynamo Theory

Background:

  • The International Geomagnetic Reference Field (IGRF) models the Earth's large-scale magnetic field, crucial for navigation, space weather, and resource exploration.
  • The 14th generation (IGRF-14) provides definitive models for 2020.0, predictions for 2025.0, and secular variation (SV) for 2025.0-2030.0.
  • Secular variation (SV) is linked to the flow at the Earth's outer core, making IGRF candidate models valuable for studying core dynamics.

Purpose of the Study:

  • To investigate predicted core flow variability using the ensemble of IGRF-14 candidate models.
  • To analyze how differences in IGRF candidate models affect inferred core flow.
  • To assess the impact of spherical harmonic truncation degree on SV predictions and core flow.

Main Methods:

  • Utilized the pygeodyn Python package with the AR-1 'dense' methodology and a 71% geodynamo prior.
  • Kept inversion parameters fixed to isolate the effect of IGRF candidate model variations on core flow.
  • Compared SV candidate models truncated at spherical harmonic degree 13 versus degree 8.

Main Results:

  • While all IGRF candidates produced similar flow spectra, greater deviations from the median model led to larger flow differences, primarily at small spatial scales.
  • Flow speed differences remained below 25% of the mean model's maximum flow speed, with highest uncertainty in the Pacific and polar regions.
  • Increasing SV truncation degree to 13 altered flow spectral energy and increased maximum flow speed by up to 31%, while maintaining high correlation in flow maps.

Conclusions:

  • Deviations in IGRF candidate models significantly influence inferred core flow, highlighting the importance of model consensus.
  • Core flow uncertainty is greatest in regions with weaker magnetic field constraints.
  • The study supports increasing the spherical harmonic truncation degree to 13 for the SV component of future IGRF models to improve accuracy.