Journal of Climate (journal-of-climate)

Journal positioning

Journal of Climate is the American Meteorological Society's journal for research on the large-scale climate of the atmosphere, ocean, land, and cryosphere. Its defining expectation is a contribution to climate science: an advance in understanding climate dynamics, variability, change, predictability, or diagnostics at regional-to-global scale, supported by rigorous analysis. A local weather case study, a short-range forecast verification, or an impacts paper that applies climate data without contributing to climate understanding is a poor fit, however careful. This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current author guidance. Before submitting, re-check the live Journal of Climate / AMS author instructions.

When to trigger

• The author names Journal of Climate and wants a fit/framing check for a climate-dynamics or climate-variability paper.
• A regional analysis or model run must be re-framed into a large-scale climate-science contribution rather than a local case study.
• The author is choosing between Journal of Climate, a dynamics-focused AMS sibling, and a broader earth-science venue.
• The author needs the journal's model-evaluation and statistical-significance expectations.

Scope & topic fit

• Large-scale atmospheric and oceanic circulation and their role in climate.
• Climate variability and modes (ENSO, NAO, monsoons, decadal variability) and their mechanisms and teleconnections.
• Climate change detection, attribution, and projection using observations and models.
• Climate modeling and model evaluation: process representation, biases, ensembles, and model intercomparison.
• Climate diagnostics, reanalyses, and the energy/water/carbon budgets of the climate system.
• Land–atmosphere and ocean–atmosphere coupling, cryosphere–climate interactions, and climate predictability on seasonal-to-decadal scales.

Method & evidence bar

• The contribution must advance climate understanding, not merely report that a model or region behaved a certain way.
• Statistical claims require appropriate significance testing that accounts for autocorrelation, finite ensemble size, and multiplicity; effect sizes and confidence intervals should be reported, not just p-values.
• Model-based results must be evaluated against observations or reanalysis, with biases and internal variability explicitly addressed (single realizations are rarely sufficient).
• Mechanistic claims need diagnostic evidence linking the proposed dynamics to the observed signal, not correlation alone.
• Datasets, reanalyses, and model output should be identified by version and source so the analysis is reproducible; AMS expects clear data-availability statements.
• Trend and attribution work must separate forced response from internal variability with a defensible framework.

Structure & house style

• AMS article format; re-check current article types and length expectations on the live guide.
• The introduction must state the climate-science question and gap, not just describe a dataset or region.
• Figures should be quantitative and diagnostic (maps, time series with significance, composite/regression analyses); they must support the mechanistic argument.
• Methods must specify datasets, model configurations, ensemble sizes, and statistical procedures precisely enough to reproduce; AMS requires a data-availability statement.
• Terminology and metrics should follow established climate-science conventions so results are comparable across studies.

Official-submission checklist

• Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the AMS anchors, then cite the current Journal of Climate page you checked.
• Search the live site for "Journal of Climate author guidelines" and follow the current AMS version.
• Re-check article types, abstract/format expectations, and length/figure expectations.
• Confirm the AMS data-availability and code/software policy: identify datasets, model output, and reanalyses with sources and persistent identifiers where possible.
• Re-check competing-interests, funding, author-contribution, AI-use disclosure, and open-access/page-charge terms.
• If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

• The paper advances climate understanding, not a single local weather or impacts case.
• Statistical significance accounts for autocorrelation, ensemble size, and multiplicity.
• Model results are evaluated against observations/reanalysis with biases and internal variability addressed.
• Mechanistic claims are backed by diagnostic evidence, not correlation alone.
• Forced response is separated from internal variability in any trend/attribution claim.
• Datasets, model configurations, and an AMS data-availability statement are specified.

Common desk-reject triggers

• A local weather event or short-range forecast study with no large-scale climate contribution.
• An impacts/applications paper that uses climate data but adds nothing to climate science.
• Trends or significance reported without accounting for autocorrelation or multiple testing.
• Model results presented without observational evaluation or any treatment of internal variability.
• Mechanistic claims resting on correlation with no diagnostic support.
• Missing data/model-version provenance or a non-compliant data-availability statement.

Re-routing decision

• Flagship climate-change significance for a broad audience → nature-climate-change.
• Broad earth/environment open-access framing → communications-earth-and-environment.
• Short, high-immediacy geophysical result → geophysical-research-letters.
• Hydrologic-cycle or water-resources focus dominant → water-resources-research / journal-of-hydrology.
• Carbon/nutrient biogeochemical budgets dominant → global-biogeochemical-cycles.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] Journal of Climate
[Topic tags] <2–3 closest climate-science topics>
[Climate-science contribution] <the advance in dynamics/variability/change/predictability>
[Method/evidence] <does model evaluation + statistical rigor clear the bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / data-availability / statistical conventions / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>