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aerostratospheric
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uogw

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train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
generated_at_utc: timestamp[s]
entry_dates: list<item: timestamp[s]>
  child 0, item: timestamp[s]
archive_by_date: list<item: timestamp[s]>
  child 0, item: timestamp[s]
entry_count: int64
role: string
git_policy: string
external_bundles: list<item: string>
  child 0, item: string
absolute_thresholds: struct<temperature_c: struct<alert_high: int64, watch_high: int64, watch_low: int64, alert_low: int6 (... 934 chars omitted)
  child 0, temperature_c: struct<alert_high: int64, watch_high: int64, watch_low: int64, alert_low: int64, examples: list<item (... 54 chars omitted)
      child 0, alert_high: int64
      child 1, watch_high: int64
      child 2, watch_low: int64
      child 3, alert_low: int64
      child 4, examples: list<item: struct<case: string, value: double, fires: string>>
          child 0, item: struct<case: string, value: double, fires: string>
              child 0, case: string
              child 1, value: double
              child 2, fires: string
  child 1, pressure_msl_hpa: struct<watch_low: int64, info_high: int64, examples: list<item: struct<case: string, value: double,  (... 16 chars omitted)
      child 0, watch_low: int64
      child 1, info_high: int64
      child 2, examples: list<item: struct<case: string, value: double, fires: string>>
          child 0, item: struct<case: string, value: double, fires: string>
              child 0, case: string
              child 1, value: double
              child 2, fires: string
  child 2, wind_speed_ms: 
...
s: struct<population: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary (... 419 chars omitted)
  child 0, population: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary_trigger: bool>
      child 0, id: string
      child 1, formula: string
      child 2, watch_abs: double
      child 3, alert_abs: double
      child 4, primary_trigger: bool
  child 1, sample: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary_trigger: bool>
      child 0, id: string
      child 1, formula: string
      child 2, watch_abs: double
      child 3, alert_abs: double
      child 4, primary_trigger: bool
  child 2, modified_mad: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary_trigger: bool, not (... 11 chars omitted)
      child 0, id: string
      child 1, formula: string
      child 2, watch_abs: double
      child 3, alert_abs: double
      child 4, primary_trigger: bool
      child 5, notes: string
  child 3, range_normalized: struct<id: string, formula: string, primary_trigger: bool, notes: string>
      child 0, id: string
      child 1, formula: string
      child 2, primary_trigger: bool
      child 3, notes: string
  child 4, percentile_rank: struct<id: string, formula: string, primary_trigger: bool>
      child 0, id: string
      child 1, formula: string
      child 2, primary_trigger: bool
disclaimer: string
schema: string
updated: timestamp[s]
curator: string
to
{'schema': Value('string'), 'updated': Value('timestamp[s]'), 'curator': Value('string'), 'disclaimer': Value('string'), 'absolute_thresholds': {'temperature_c': {'alert_high': Value('int64'), 'watch_high': Value('int64'), 'watch_low': Value('int64'), 'alert_low': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'pressure_msl_hpa': {'watch_low': Value('int64'), 'info_high': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'wind_speed_ms': {'watch': Value('int64'), 'alert': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'dry_hot_compound': {'temperature_c_min': Value('int64'), 'relative_humidity_pct_max': Value('int64'), 'severity': Value('string'), 'examples': List({'case': Value('string'), 'temperature_c': Value('int64'), 'relative_humidity_pct': Value('int64'), 'fires': Value('string')})}, 'wave_height_m': {'watch': Value('int64'), 'alert': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'water_temp_c': {'info_high': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'casey_diurnal_range_c': {'watch': Value('int64'), 'examples': List({'case': Value('string'), 'min': Value('int64'), 'max': Value('int64'), 'range': Value('int64'), 'fires': Value('string')})}}, 'zscore_methods': {'population': {'id': Value('string'), 'formula': Value('string'), 'watch_abs': Value('float64'), 'alert_abs': Value('float64'), 'primary_trigger': Value('bool')}, 'sample': {'id': Value('string'), 'formula': Value('string'), 'watch_abs': Value('float64'), 'alert_abs': Value('float64'), 'primary_trigger': Value('bool')}, 'modified_mad': {'id': Value('string'), 'formula': Value('string'), 'watch_abs': Value('float64'), 'alert_abs': Value('float64'), 'primary_trigger': Value('bool'), 'notes': Value('string')}, 'range_normalized': {'id': Value('string'), 'formula': Value('string'), 'primary_trigger': Value('bool'), 'notes': Value('string')}, 'percentile_rank': {'id': Value('string'), 'formula': Value('string'), 'primary_trigger': Value('bool')}}, 'worked_example': {'baseline_temperature_c': List(Value('float64')), 'today_temperature_c': Value('float64'), 'approx': {'mean': Value('float64'), 'z_pop': Value('float64'), 'z_sample': Value('float64'), 'z_mad': Value('float64')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              generated_at_utc: timestamp[s]
              entry_dates: list<item: timestamp[s]>
                child 0, item: timestamp[s]
              archive_by_date: list<item: timestamp[s]>
                child 0, item: timestamp[s]
              entry_count: int64
              role: string
              git_policy: string
              external_bundles: list<item: string>
                child 0, item: string
              absolute_thresholds: struct<temperature_c: struct<alert_high: int64, watch_high: int64, watch_low: int64, alert_low: int6 (... 934 chars omitted)
                child 0, temperature_c: struct<alert_high: int64, watch_high: int64, watch_low: int64, alert_low: int64, examples: list<item (... 54 chars omitted)
                    child 0, alert_high: int64
                    child 1, watch_high: int64
                    child 2, watch_low: int64
                    child 3, alert_low: int64
                    child 4, examples: list<item: struct<case: string, value: double, fires: string>>
                        child 0, item: struct<case: string, value: double, fires: string>
                            child 0, case: string
                            child 1, value: double
                            child 2, fires: string
                child 1, pressure_msl_hpa: struct<watch_low: int64, info_high: int64, examples: list<item: struct<case: string, value: double,  (... 16 chars omitted)
                    child 0, watch_low: int64
                    child 1, info_high: int64
                    child 2, examples: list<item: struct<case: string, value: double, fires: string>>
                        child 0, item: struct<case: string, value: double, fires: string>
                            child 0, case: string
                            child 1, value: double
                            child 2, fires: string
                child 2, wind_speed_ms: 
              ...
              s: struct<population: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary (... 419 chars omitted)
                child 0, population: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary_trigger: bool>
                    child 0, id: string
                    child 1, formula: string
                    child 2, watch_abs: double
                    child 3, alert_abs: double
                    child 4, primary_trigger: bool
                child 1, sample: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary_trigger: bool>
                    child 0, id: string
                    child 1, formula: string
                    child 2, watch_abs: double
                    child 3, alert_abs: double
                    child 4, primary_trigger: bool
                child 2, modified_mad: struct<id: string, formula: string, watch_abs: double, alert_abs: double, primary_trigger: bool, not (... 11 chars omitted)
                    child 0, id: string
                    child 1, formula: string
                    child 2, watch_abs: double
                    child 3, alert_abs: double
                    child 4, primary_trigger: bool
                    child 5, notes: string
                child 3, range_normalized: struct<id: string, formula: string, primary_trigger: bool, notes: string>
                    child 0, id: string
                    child 1, formula: string
                    child 2, primary_trigger: bool
                    child 3, notes: string
                child 4, percentile_rank: struct<id: string, formula: string, primary_trigger: bool>
                    child 0, id: string
                    child 1, formula: string
                    child 2, primary_trigger: bool
              disclaimer: string
              schema: string
              updated: timestamp[s]
              curator: string
              to
              {'schema': Value('string'), 'updated': Value('timestamp[s]'), 'curator': Value('string'), 'disclaimer': Value('string'), 'absolute_thresholds': {'temperature_c': {'alert_high': Value('int64'), 'watch_high': Value('int64'), 'watch_low': Value('int64'), 'alert_low': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'pressure_msl_hpa': {'watch_low': Value('int64'), 'info_high': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'wind_speed_ms': {'watch': Value('int64'), 'alert': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'dry_hot_compound': {'temperature_c_min': Value('int64'), 'relative_humidity_pct_max': Value('int64'), 'severity': Value('string'), 'examples': List({'case': Value('string'), 'temperature_c': Value('int64'), 'relative_humidity_pct': Value('int64'), 'fires': Value('string')})}, 'wave_height_m': {'watch': Value('int64'), 'alert': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'water_temp_c': {'info_high': Value('int64'), 'examples': List({'case': Value('string'), 'value': Value('float64'), 'fires': Value('string')})}, 'casey_diurnal_range_c': {'watch': Value('int64'), 'examples': List({'case': Value('string'), 'min': Value('int64'), 'max': Value('int64'), 'range': Value('int64'), 'fires': Value('string')})}}, 'zscore_methods': {'population': {'id': Value('string'), 'formula': Value('string'), 'watch_abs': Value('float64'), 'alert_abs': Value('float64'), 'primary_trigger': Value('bool')}, 'sample': {'id': Value('string'), 'formula': Value('string'), 'watch_abs': Value('float64'), 'alert_abs': Value('float64'), 'primary_trigger': Value('bool')}, 'modified_mad': {'id': Value('string'), 'formula': Value('string'), 'watch_abs': Value('float64'), 'alert_abs': Value('float64'), 'primary_trigger': Value('bool'), 'notes': Value('string')}, 'range_normalized': {'id': Value('string'), 'formula': Value('string'), 'primary_trigger': Value('bool'), 'notes': Value('string')}, 'percentile_rank': {'id': Value('string'), 'formula': Value('string'), 'primary_trigger': Value('bool')}}, 'worked_example': {'baseline_temperature_c': List(Value('float64')), 'today_temperature_c': Value('float64'), 'approx': {'mean': Value('float64'), 'z_pop': Value('float64'), 'z_sample': Value('float64'), 'z_mad': Value('float64')}}}
              because column names don't match

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Aerostratospheric

Unified Open Global Weather (UOGW)

An open atmospheric data commons for research — curated by Aerostratospheric

Start here: science-package.json · science-analytics.json · hub-endpoints.json · docs/DATA_PACKAGES.md
Data Hub: https://midwestsds.com/msds-data-hub.html
Sibling GIR (hazards / open geospatial): aerostratospheric-defense-gir

What UOGW is

A versioned, multi-layer discovery and sampling layer for open atmospheric observations: ground, marine, upper-air, stratospheric/space, satellite/model, and first-party Aerostratospheric near-space flight products. Independent GitHub Actions keep indexes, science packages, anomaly reports, and °F charts fresh. UOGW does not replace agency systems of record; it organizes public access with attribution.

Daily data packages

Package	Path	Purpose
Science package	`data/latest/science-package.json`	Combined observations + summary
Science analytics	`data/latest/science-analytics.json`	Extremes, coverage, research flags
Anomaly report	`data/latest/anomaly-report.json`	Multi-method research screening
Hub endpoints	`data/latest/hub-endpoints.json`	Stable machine map for the Data Hub
Layer trees	`layers/`	Ground · Marine · Upper-air · …
Weekly status	`reports/weekly/`	Automated weekly roll-up
Charts	`visuals/latest/`	°F PNG gallery + markdown

Full consumer guide: docs/DATA_PACKAGES.md

Built-in graphs and charts (°F)

Global city temperatures

Horizontal bar chart of current surface air temperature for each successful global city sample. Bars are sorted cold→hot; warmer colors mark heat (≥86°F / ≥95°F).

City temperature map

Scatter map of the same city samples by longitude/latitude, colored by temperature (°F).

Casey, IL hourly temperature

24-hour Open-Meteo model temperature trace for the Casey, Illinois grid point. Model data, not station observations. Weather data by Open-Meteo.com, CC BY 4.0.

NDBC marine samples

NOAA NDBC buoy sample panel: wave height (meters) plus water and air temperature (°F).

Global city relative humidity

Relative humidity (%) for the same global city sample network.

Anomaly severity

Count of UOGW research anomaly flags by severity (alert / watch / info). Not an NWS warning product.

Anomaly detection guide

Severity	Meaning
Alert	Strong outlier vs thresholds or baseline (extreme heat/cold, \|z\| ≥ 3, very high waves).
Watch	Elevated interest — heat/cold, wind, low pressure, or \|z\| ≥ 2.5 vs the 7-day baseline.
Info	Lower urgency (hot + very dry, strong high, warm water sample).

Methods: docs/ANOMALY_METHODS.md · visuals/ANOMALY_GUIDE.md · anomaly-report.json

Research cities daily Tmin / Tmax

Daily summary card

Full descriptions: visuals/CHART_DESCRIPTIONS.md · gallery: visuals/latest/CHARTS.md

Feature highlights

Area	What you get
Daily science package	Combined observations + summary
Science analytics	Extremes, coverage, heat-index flags
Anomaly detection	Threshold + multi-method z-scores (research only)
Charts automation	°F PNGs + markdown after data workflows
Hub endpoints map	`data/latest/hub-endpoints.json`
Health / rollback	Self-heal, alert PRs, rollback docs
Weekly status report	`reports/weekly/` via Actions
Six atmospheric layers	Ground → Flight (see `docs/Layers.md`)
25+ cataloged datasets	`catalog/catalog.json`

See docs/FEATURES.md.

Related open ecosystem

Repository	Role
aerostratospheric-defense-gir	Open-tier geospatial hazard / defense-adjacent GIR + daily exec reports
msds-data	Casey Open-Meteo model weather series (Weather data by Open-Meteo.com, CC BY 4.0) + HAB flight packages
International-Ground-Data-Repository	IGRA / international ground indexes
x2griffon	Payload platform

Repository hygiene

Doc	Purpose
CONTRIBUTING.md	How to contribute (open/redistributable only)
SECURITY.md	Vulnerability reporting
docs/DATA_PACKAGES.md	Package map for consumers
docs/FEATURES.md	Feature catalog
docs/Layers.md	Layer definitions

License

UOGW contains both Aerostratospheric data and third-party data, so licensing is per source. Full list with terms links: layers/ATTRIBUTION.md. This applies to layers/, data/ and snapshots/ here and on the Hugging Face mirror.

Aerostratospheric first-party data and documentation: CC BY 4.0 (layers/LICENSE). This covers the GMC-800 radiation station, the X-Sense logger, flight products and docs.
Third-party layers keep their own terms:
- NOAA / NWS U.S. government data (NWS, NCEI GHCN-Daily and IGRA, NDBC, SWPC, NCEP GFS) is public domain: https://www.weather.gov/disclaimer
- Open-Meteo data is CC BY 4.0 (https://open-meteo.com/en/license). This includes the Casey, Illinois daily/hourly series, which is Open-Meteo model data, not observations from our station. "Weather data by Open-Meteo.com, CC BY 4.0."
- Copernicus CAMS air-quality data (via Open-Meteo) is under the Copernicus licence: https://apps.ecmwf.int/datasets/licences/copernicus/
- Iowa Environmental Mesonet data is used per its terms: https://mesonet.agron.iastate.edu/disclaimer.php
- NOAA/NASA satellite catalog metadata follows the provider's data policies.
Excluded: KILCASEY47 data retrieved through the Weather Underground API (layers/ground/casey/wunderground/, casey-wu.json) is not licensed by us while the WU API terms are reviewed.
Code (scripts, workflows) is not licensed under CC BY 4.0.

Citation

Aerostratospheric (2026). Unified Open Global Weather (UOGW). https://github.com/Midwest-Stratospheric/Unified-Open-Global-Weather

Always cite upstream providers (Open-Meteo, NOAA NDBC, NOAA NCEI, NASA, etc.); see layers/ATTRIBUTION.md.

Published by Aerostratospheric, Olney, Illinois. · launchcontrol@midwestsds.com · NASA GLOBE GO-4VW9B · Ham KE9CFY

Aerostratospheric

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Total file size:

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Models trained or fine-tuned on aerostratospheric/uogw

Collection including aerostratospheric/uogw

Aerostratospheric open atmospheric data

Collection

UOGW commons, Casey IL ground data, forecast and hazard models. Live: midwestsds.com/msds-data-hub.html · Collaborate: space@aerostratospheric.com • 11 items • Updated 24 days ago • 1