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How has the monthly mean air temperature at 2 metres in Frankfurt am Main (NA...

By Björn Hanneke

How has the monthly mean air temperature at 2 metres in Frankfurt am Main (NASA POWER, 50.11 N, 8.68 E) changed since 1981, and how well do seasonal forecasting models predict the next 36 months compared with a seasonal naive baseline?

Published on e2er.orgDemonstrationVersion 1 · 2026-10-15 · from the command line

Dossier a6ba92eccb530a5b data private · code private

Paper, data and code

  • Paper
    Not public.

  • Data
    Not public.

  • Code
    Not public.

Checks

Only the checks by e2er.org and in GitHub Actions ran outside the author's control.

Checked by e2er.org

No repository named, so e2er.org cannot read the files.

Checked in GitHub Actions

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Reported by the author's own check

  • ✓citations 12 cite key(s) resolve in refs.bib; snapshot: 10 verified, 2 unverifiable at run time
  • ✓integrity 65 files hash-verified against provenance.json; 72 table cell(s) traced in the derivation graph; 2 change(s) after export recorded as amendments (paper/paper.pdf, paper/paper.tex)
  • ✓numbers 76 table cell(s) are source values at the precision shown; text (not gating): 127 of 128 number(s) are source values, 0 differ from the quantity named nearby, 1 untraced
  • ✓preregistration estimation follows the pre-registered plan (frozen 2026-10-13); every pre-registered hypothesis has a result (H1, H2, H3)
  • ✓results contract timeseries results (time-series models, forecasts and out-of-sample errors) are complete and consistent
  • ·results from code not checked: the run predates output records
  • ·spec no design/identification_spec.json
  • ✓tables 4 table(s) reproduce byte-identically from the sidecars

e2er verify on the author's machine, at publish

What was published

Files
28 named with their SHA-256 fingerprint; the files stay with the authors
References
10 of 12 resolved
AI calls
28
Content id
sha256:33b825408d717bb36af43619a0c0887da9af9de4ba2c1967973ed13ff940543f
e2er
version 0.17.0 · template time-series-forecasting
AI
Claude Sonnet via Claude Code

Data used

Each source the run loaded, as the connector recorded it: what was read and when, the source's terms and the citation it asks for.

NASA Prediction Of Worldwide Energy Resources (POWER), NASA Langley Research Center · 1 load · release v2.10.0 · read 2026-10-13

e2er's connector for it · about this data source

NASA POWER monthly T2M at lat 50.11, lon 8.68, 1981–2025 · release v2.10.0, read 2026-10-13 · table frankfurt_t2m_monthly https://power.larc.nasa.gov/api/temporal/monthly/point?parameters=T2M&community=RE&latitude=50.11&longitude=8.68&start=1981&end=2025&format=JSON 3471530b3a04

Terms Free and keyless; NASA data without a marked restriction are CC0. POWER asks publications to give its reference with the API version and access date, and asks to be told when data are passed to others. Full terms

Cite NASA Langley Research Center (LaRC) POWER Project. Prediction Of Worldwide Energy Resources (POWER), https://power.larc.nasa.gov/. The data was obtained from National Aeronautics and Space Administration (NASA) Langley Research Center's Prediction Of Worldwide Energy Resources (POWER) project funded through the NASA Earth Science Division. Data reference: The data was obtained from the POWER Monthly and Annual API version 2.10.0 on 2026/10/13.

References: 0 from the authors' papers, 1 found on the web, 11 method sources from the template · listed in the dossier

Versions

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Built with

The template, specialists, skills and connectors this version used, as its dossier names them, with the people credited for each.

Template (1) · by e2er authors
Specialists (17) · by e2er authors
Skills (46) · by e2er authors
Connector (1) · by e2er authors

Authors

  • ·Björn Hanneke conceptualization, investigation

Discussion

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