Physics Based MODels (PBMOD )

The PBMOD ionospheric model is a system of Physics Based MODels that describes the three-dimensional time-dependent evolution of the low-latitude ionosphere on several different spatial scales: globally it provides the plasma density and composition at altitudes between 90 and 2000 km; at finer scales it describes the development of fluid plasma turbulence within this region and the resulting radio scintillation.

IONOSPHERE/THERMOSPHERE

Contributor(s)

Initial contribute: 2020-07-02

Authorship

:  
Boston College
Is authorship not correct? Feed back

Classification(s)

Application-focused categoriesNatural-perspectiveSpace-earth regions
Method-focused categoriesProcess-perspectivePhysical process calculation

Detailed Description

English {{currentDetailLanguage}} English

Quoted from: https://ccmc.gsfc.nasa.gov/models/modelinfo.php?model=PBMOD

Model Description
The PBMOD ionospheric model is a system of Physics Based MODels that describes the three-dimensional time-dependent evolution of the low-latitude ionosphere on several different spatial scales: globally it provides the plasma density and composition at altitudes between 90 and 2000 km; at finer scales it describes the development of fluid plasma turbulence within this region and the resulting radio scintillation. The numerical model of the ambient (global scale) ionosphere yields density distributions for electrons and several ion species (O+, H+, and NO+, O2+, N2+) as a function of latitude, longitude, and altitude on a prespecified spatial grid at specified times. The system also includes models that evaluate the growth rate for the generalized Rayleigh-Taylor instability, perform evolutionary calculations of the self-consistent nonlinear development of equatorial low-density plasma plumes/bubbles, and perform a phase-screen calculation to estimate the strength of amplitude and phase scintillation of radio signals passing through the turbulent structure.

Numerous physical and chemical processes are contained in the model, including field-aligned diffusion, cross-field electrodynamic drifts, thermospheric winds, ion production due to EUV radiation, chemical and other collisional processes. The model uses the IGRF geomagnetic field model for an accurate depiction of the Earth's magnetic-field geometry. Depending on the inputs, the global ionospheric model can describe different solar cycle, seasonal, and daily variations. It can describe the low-latitude effects of geomagnetic storm dynamics.

Model Input
The main global inputs are the neutral densities, temperatures, and winds; the magnetospheric and equatorial electric field distributions and histories; the plasma temperatures; the plasma production rate; and the seed perturbation for the plume calculation. The empirical or statistical models used for these inputs are parameterized by

For storm simulations, the temporal variation of the magnetospheric and atmospheric inputs must be specified. Simple scalings with the interplanetary electric field (that can provide a rough estimate of the penetration field and thermospheric energy input in storm events) are provided by

  • Solar-wind parameters measured on the ACE satellite

Model Output

  • NmF2
  • hmF2
  • TEC (Total Electron Content)
  • Number densities: O+, H+, sum of minor molecular ions, and electron (m-3)
  • Rayleigh-Taylor Growth Rate
  • Scintillation index (S4) for vertical propagation:
    • UHF S4: for UHF (250 MHz) signal,
    • L-band S4: for L-band (1500 MHz) signal.

Limitations and Caveats
1. To a large extent, the reliability of the calculated ionospheric parameters depends on the accuracy to which the global inputs have been specified. The ambient ionospheric model is particularly sensitive to the equatorial electric field (including both penetration and dynamo fields), but also depends on thermospheric winds, neutral densities, plasma temperatures, and plasma production rates.

2. The plasma plume model depends on the parameters in 1, and is additionally dependent on the choice of 'seed' or initial perturbation for plume development.

3. The structuring of the plasma in the turbulent plumes does not feed back into the ambient model.

References and relevant publications
Retterer, J. M., D. T. Decker, W. S. Borer, R. E. Daniell, and B. G. Fejer, Assimilative Modeling of the Equatorial Ionosphere for Scintillation Forecasting: Modeling with Vertical Drifts, J. Geophys. Res., 110, A11307, 2005. 
Retterer, J. M., Physics-based forecasts of equatorial radio scintillation for C/NOFS, Space Weather Journal, 3, S12C03, 2005. 
Retterer, J. M., Forecasting Low-Latitude Radio Scintillation with 3-D Ionospheric Plume Models: I. Plume Model, J. Geophys. Res., doi:10.1029/2008JA013839, 2010 
Retterer, J. M., Forecasting Low-Latitude Radio Scintillation with 3-D Ionospheric Plume Models: II. Scintillation Calculation, J. Geophys. Res., doi:10.1029/2008JA013840, 2010. 
Retterer, J. M., and M. C. Kelley, Solar wind drivers for low-latitude ionosphere models during geomagnetic storms, J. Atmos. Solar-Terr. Phys., doi:10.1016/j.jastp.2009.07.00,3, 2010.

Relevant links
http://ccmc.gsfc.nasa.gov/RoR_WWW/pbmod-rt/pbmodf_realtime.php

http://ccmc.gsfc.nasa.gov/RoR_WWW/pbmod-rt/PBMOD-Text.html

CCMC Contact(s)
Katherine Garcia-Sage, Jia.yue
301-286-3651, 301-286-1648

Developer Contact(s)
John M. Retterer

模型元数据

{{htmlJSON.HowtoCite}}

John M. Retterer (2020). Physics Based MODels (PBMOD ), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/6d21d002-0892-4e2a-a4bd-320db192c8ca
{{htmlJSON.Copy}}

History

Last modifier
haolingchen
Last modify time
2020-12-29
Modify times
View History

Contributor(s)

Initial contribute : 2020-07-02

{{htmlJSON.CoContributor}}

Authorship

:  
Boston College
Is authorship not correct? Feed back

History

Last modifier
haolingchen
Last modify time
2020-12-29
Modify times
View History

QR Code

×

{{curRelation.overview}}
{{curRelation.author.join('; ')}}
{{curRelation.journal}}









{{htmlJSON.RelatedItems}}

{{htmlJSON.LinkResourceFromRepositoryOrCreate}}{{htmlJSON.create}}.

Drop the file here, orclick to upload.
Select From My Space
+ add

{{htmlJSON.authorshipSubmitted}}

Cancel Submit
{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
{{htmlJSON.Localizations}} + {{htmlJSON.Add}}
{{ item.label }} {{ item.value }}
{{htmlJSON.ModelName}}:
{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
名称 别名 {{tag}} +
系列名 版本号 目的 修改内容 创建/修改日期 作者
摘要 详细描述
{{tag}} + 添加关键字
* 时间参考系
* 空间参考系类型 * 空间参考系名称

起始日期 终止日期 进展 开发者
* 是否开源 * 访问方式 * 使用方式 开源协议 * 传输方式 * 获取地址 * 发布日期 * 发布者



编号 目的 修改内容 创建/修改日期 作者





时间分辨率 时间尺度 时间步长 时间范围 空间维度 格网类型 空间分辨率 空间尺度 空间范围
{{tag}} +
* 类型
图例


* 名称 * 描述
示例描述 * 名称 * 类型 * 值/链接 上传


{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
Title Author Date Journal Volume(Issue) Pages Links Doi Operation
{{htmlJSON.Cancel}} {{htmlJSON.Submit}}
{{htmlJSON.Add}} {{htmlJSON.Cancel}}

{{articleUploading.title}}

Authors:  {{articleUploading.authors[0]}}, {{articleUploading.authors[1]}}, {{articleUploading.authors[2]}}, et al.

Journal:   {{articleUploading.journal}}

Date:   {{articleUploading.date}}

Page range:   {{articleUploading.pageRange}}

Link:   {{articleUploading.link}}

DOI:   {{articleUploading.doi}}

Yes, this is it Cancel

The article {{articleUploading.title}} has been uploaded yet.

OK
{{htmlJSON.Cancel}} {{htmlJSON.Confirm}}
EEdYGheHv1yg