Example of Weather and Forecasting format
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Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format Example of Weather and Forecasting format
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open access Open Access ISSN: 8828156 e-ISSN: 15200434

Weather and Forecasting — Template for authors

Categories Rank Trend in last 3 yrs
Atmospheric Science #42 of 124 down down by 1 rank
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 458 Published Papers | 2212 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 13/07/2020
Insights & related journals
General info
Top papers
Popular templates
Get started guide
Why choose from SciSpace
FAQ

Journal Performance & Insights

  • Impact Factor
  • CiteRatio
  • SJR
  • SNIP

Impact factor determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

2.95

29% from 2018

Impact factor for Weather and Forecasting from 2016 - 2019
Year Value
2019 2.95
2018 2.288
2017 2.276
2016 1.718
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 29% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

CiteRatio is a measure of average citations received per peer-reviewed paper published in the journal.

4.8

9% from 2019

CiteRatio for Weather and Forecasting from 2016 - 2020
Year Value
2020 4.8
2019 4.4
2018 4.1
2017 3.6
2016 3.7
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 9% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR) measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

1.393

20% from 2019

SJR for Weather and Forecasting from 2016 - 2020
Year Value
2020 1.393
2019 1.734
2018 1.744
2017 1.684
2016 1.588
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 20% in last years.
  • This journal’s SJR is in the top 10 percentile category.

Source Normalized Impact per Paper (SNIP) measures actual citations received relative to citations expected for the journal's category.

1.301

2% from 2019

SNIP for Weather and Forecasting from 2016 - 2020
Year Value
2020 1.301
2019 1.322
2018 1.065
2017 1.041
2016 1.146
graph view Graph view
table view Table view

insights Insights

  • SNIP of this journal has decreased by 2% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Related Journals

open access Open Access ISSN: 19391404 e-ISSN: 21511535

IEEE

CiteRatio: 7.2 | SJR: 1.246 | SNIP: 1.579
open access Open Access ISSN: 30007 e-ISSN: 15200477
recommended Recommended

American Meteorological Society

CiteRatio: 13.5 | SJR: 3.367 | SNIP: 2.93
open access Open Access ISSN: 7390572 e-ISSN: 15200426

American Meteorological Society

CiteRatio: 4.1 | SJR: 0.774 | SNIP: 1.154
open access Open Access ISSN: 8948755 e-ISSN: 15200442
recommended Recommended

American Meteorological Society

CiteRatio: 9.8 | SJR: 3.315 | SNIP: 1.909

Weather and Forecasting

Guideline source: View

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American Meteorological Society

Weather and Forecasting

Research on forecasting and analysis techniques, forecast verification studies, and case studies useful to forecasters. This includes submissions that report on changes to the suite of operational numerical models and statistical postprocessing techniques, demonstrate the tran...... Read More

Atmospheric Science

Earth and Planetary Sciences

i
Last updated on
13 Jul 2020
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ISSN
0882-8156
i
Impact Factor
High - 1.066
i
Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
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Bibliography Name
numbered
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Citation Type
Author Year
(Blonder et al. 1982)
i
Bibliography Example
Blonder, G. E., M. Tinkham, and T. M. Klapwijk, 1982: Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B, 25 (7), 4515–4532, URL 10.1103/PhysRevB.25.4515.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2
Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems
Hans Hersbach1
01 Oct 2000 - Weather and Forecasting

Abstract:

Some time ago, the continuous ranked probability score (CRPS) was proposed as a new verification tool for (probabilistic) forecast systems. Its focus is on the entire permissible range of a certain (weather) parameter. The CRPS can be seen as a ranked probability score with an infinite number of classes, each of zero width. A... Some time ago, the continuous ranked probability score (CRPS) was proposed as a new verification tool for (probabilistic) forecast systems. Its focus is on the entire permissible range of a certain (weather) parameter. The CRPS can be seen as a ranked probability score with an infinite number of classes, each of zero width. Alternatively, it can be interpreted as the integral of the Brier score over all possible threshold values for the parameter under consideration. For a deterministic forecast system the CRPS reduces to the mean absolute error. In this paper it is shown that for an ensemble prediction system the CRPS can be decomposed into a reliability part and a resolution/uncertainty part, in a way that is similar to the decomposition of the Brier score. The reliability part of the CRPS is closely connected to the rank histogram of the ensemble, while the resolution/ uncertainty part can be related to the average spread within the ensemble and the behavior of its outliers. The usefulness of such a decomposition is illustrated for the ensemble prediction system running at the European Centre for Medium-Range Weather Forecasts. The evaluation of the CRPS and its decomposition proposed in this paper can be extended to systems issuing continuous probability forecasts, by realizing that these can be interpreted as the limit of ensemble forecasts with an infinite number of members. read more read less

Topics:

Ensemble forecasting (61%)61% related to the paper, Brier score (60%)60% related to the paper
View PDF
966 Citations
open accessOpen access Journal Article DOI: 10.1175/1520-0434(1998)013<0377:TWRA>2.0.CO;2
The WSR-88D Rainfall Algorithm
Richard Fulton1, Jay P. Breidenbach1, Dong Jun Seo1, Dennis Miller1, Timothy O'Bannon
01 Jun 1998 - Weather and Forecasting

Abstract:

A detailed description of the operational WSR-88D rainfall estimation algorithm is presented. This algorithm, called the Precipitation Processing System, produces radar-derived rainfall products in real time for forecasters in support of the National Weather Service’s warning and forecast missions. It transforms reflectivity ... A detailed description of the operational WSR-88D rainfall estimation algorithm is presented. This algorithm, called the Precipitation Processing System, produces radar-derived rainfall products in real time for forecasters in support of the National Weather Service’s warning and forecast missions. It transforms reflectivity factor measurements into rainfall accumulations and incorporates rain gauge data to improve the radar estimates. The products are used as guidance to issue flood watches and warnings to the public and as input into numerical hydrologic and atmospheric models. The processing steps to quality control and compute the rainfall estimates are described, and the current deficiencies and future plans for improvement are discussed. read more read less

Topics:

Quantitative precipitation estimation (56%)56% related to the paper, Weather forecasting (53%)53% related to the paper, Rain gauge (53%)53% related to the paper, NEXRAD (53%)53% related to the paper
880 Citations
open accessOpen access Journal Article DOI: 10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2
Flash Flood Forecasting: An Ingredients-Based Methodology
Charles A. Doswell1, Harold E. Brooks1, Robert A. Maddox1
01 Dec 1996 - Weather and Forecasting

Abstract:

An approach to forecasting the potential for flash flood-producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ascent of air containing substantial water vapor and also depend on the precipitation... An approach to forecasting the potential for flash flood-producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ascent of air containing substantial water vapor and also depend on the precipitation efficiency. The duration of an event is associated with its speed of movement and the size of the system causing the event along the direction of system movement. This leads naturally to a consideration of the meteorological processes by which these basic ingredients are brought together. A description of those processes and of the types of heavy precipitation-producing storms suggests some of the variety of ways in which heavy precipitation occurs. Since the right mixture of these ingredients can be found in a wide variety of synoptic and mesoscale situations, it is necessary to know which of the ingredients is critical in any given case. By knowing which of the ingredients... read more read less
View PDF
845 Citations
The new NMC mesoscale Eta Model: description and forecast examples
Thomas L. Black1
01 Jun 1994 - Weather and Forecasting

Abstract:

In mid-1994 a new version of the Eta Model will begin producing operational forecast guidance down to mesoscale ranges. This version will have a horizontal resolution of approximately 30 km and about 50 layers in the vertical. A summary of the primary aspects of the model is presented that includes a description of the eta co... In mid-1994 a new version of the Eta Model will begin producing operational forecast guidance down to mesoscale ranges. This version will have a horizontal resolution of approximately 30 km and about 50 layers in the vertical. A summary of the primary aspects of the model is presented that includes a description of the eta coordinate and of the dynamical and physical components. Advantages of the mesoscale model are indicated in precipitation skill scores for November 1993. Specific examples are discussed that describe the mesoscale model's ability to capture small-scale circulations under fundamentally different circumstances: (i) the propagation of a strong cold front where the forcing was primarily internal and not orographic; and (ii) a rainfall event where the forcing arose from the interaction of topography with the synoptic-scale flow. read more read less

Topics:

North American Mesoscale Model (64%)64% related to the paper, Mesoscale meteorology (61%)61% related to the paper
671 Citations
open accessOpen access Journal Article DOI: 10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2
A Baseline Climatology of Sounding-Derived Supercell and Tornado Forecast Parameters
Erik N. Rasmussen1, David O. Blanchard1
01 Dec 1998 - Weather and Forecasting

Abstract:

All of the 0000 UTC soundings from the United States made during the year 1992 that have nonzero convective available potential energy (CAPE) are examined. Soundings are classified as being associated with nonsupercell thunderstorms, supercells without significant tornadoes, and supercells with significant tornadoes. This cla... All of the 0000 UTC soundings from the United States made during the year 1992 that have nonzero convective available potential energy (CAPE) are examined. Soundings are classified as being associated with nonsupercell thunderstorms, supercells without significant tornadoes, and supercells with significant tornadoes. This classification is made by attempting to pair, based on the low-level sounding winds, an upstream sounding with each occurrence of a significant tornado, large hail, and/or 10 or more cloud-to-ground lightning flashes. Severe weather wind parameters (mean shear, 0–6-km shear, storm-relative helicity, and storm-relative anvil-level flow) and CAPE parameters (total CAPE and CAPE in the lowest 3000 m with buoyancy) are shown to discriminate weakly between the environments of the three classified types of storms. Combined parameters (energy–helicity index and vorticity generation parameter) discriminate strongly between the environments. The height of the lifting condensation level a... read more read less

Topics:

Supercell (63%)63% related to the paper, Thunderstorm (61%)61% related to the paper, Convective available potential energy (59%)59% related to the paper, Satellite tornado (59%)59% related to the paper, Severe weather (58%)58% related to the paper
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668 Citations
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Weather and Forecasting format uses numbered citation style.

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SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

Absolutely not! With our tool, you can freely write without having to focus on LaTeX. You can write your entire paper as per the Weather and Forecasting guidelines and autoformat it.

Yes. The template is fully compliant as per the guidelines of this journal. Our experts at SciSpace ensure that. Also, if there's any update in the journal format guidelines, we take care of it and include that in our algorithm.

Sure. We support all the top citation styles like APA style, MLA style, Vancouver style, Harvard style, Chicago style, etc. For example, in case of this journal, when you write your paper and hit autoformat, it will automatically update your article as per the Weather and Forecasting citation style.

You can avail our Free Trial for 7 days. I'm sure you'll find our features very helpful. Plus, it's quite inexpensive.

Yup. You can choose the right template, copy-paste the contents from the word doc and click on auto-format. You'll have a publish-ready paper that you can download at the end.

A matter of seconds. Besides that, our intuitive editor saves a load of your time in writing and formating your manuscript.

One little Google search can get you the Word template for any journal. However, why do you need a Word template when you can write your entire manuscript on SciSpace, autoformat it as per Weather and Forecasting's guidelines and download the same in Word, PDF and LaTeX formats? Try us out!.

Absolutely! You can do it using our intuitive editor. It's very easy. If you need help, you can always contact our support team.

SciSpace is an online tool for now. We'll soon release a desktop version. You can also request (or upvote) any feature that you think might be helpful for you and the research community in the feature request section once you sign-up with us.

Sure. You can request any template and we'll have it up and running within a matter of 3 working days. You can find the request box in the Journal Gallery on the right sidebar under the heading, "Couldn't find the format you were looking for?".

After you have written and autoformatted your paper, you can download it in multiple formats, viz., PDF, Docx and LaTeX.

To be honest, the answer is NO. The impact factor is one of the many elements that determine the quality of a journal. Few of those factors the review board, rejection rates, frequency of inclusion in indexes, Eigenfactor, etc. You must assess all the factors and then take the final call.

SHERPA/RoMEO Database

We have extracted this data from Sherpa Romeo to help our researchers understand the access level of this journal. The following table indicates the level of access a journal has as per Sherpa Romeo Archiving Policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

The 5 most common citation types in order of usage are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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After uploading your paper on SciSpace, you would see a button to request a journal submission service for Weather and Forecasting.

Each submission service is completed within 4 - 5 working days.

Yes. SciSpace provides this functionality.

After signing up, you would need to import your existing references from Word or .bib file.

SciSpace would allow download of your references in Weather and Forecasting Endnote style, according to american-meteorological-society guidelines.

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