sensorweatherclimatecitiesglobaldailytemperatureprecipitation2024sensoropen-meteo

City Daily Weather & Climate Panel

2024

Free

Open dataset

Sample structure: 100 / 100
3 download links issued
Seller: waseemahmad
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Category
Sensor
Records
18,300 rows
Format
CSV
Update Frequency
Not documented
Collection Method
uploaded
PII
No flagged field names; not a privacy audit
Download links issued
3

Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License
Not documented — confirm reuse terms with the seller
Source / creator
Supplier-cited: Open-Meteo Historical Weather API; FAO
Collection method
uploaded
Coverage / snapshot
2024
Data last updated
Not documented
Update schedule
Not documented

Source documentation ↗

Source attribution is supplier-reported. The source link identifies publisher documentation; it does not independently verify this uploaded extract. Other cited publishers: FAO: https://www.fao.org/faostat/

Sample structure score: 100 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.

CheckPointsEvidence
Populated cells50 / 50220 of 220 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types30 / 30220 of 220 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape20 / 2010 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.
Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

FieldMissing cellsMost common typeOther populated types
date0 / 10string0 / 10
city0 / 10string0 / 10
country0 / 10string0 / 10
continent0 / 10string0 / 10
latitude0 / 10number0 / 10
longitude0 / 10number0 / 10
city_population0 / 10number0 / 10
timezone0 / 10string0 / 10
temperature_max_c0 / 10number0 / 10
temperature_min_c0 / 10number0 / 10
temperature_mean_c0 / 10number0 / 10
precipitation_mm0 / 10number0 / 10
rain_mm0 / 10number0 / 10
snowfall_cm0 / 10number0 / 10
wind_speed_max_kmh0 / 10number0 / 10
wind_gusts_max_kmh0 / 10number0 / 10
sunshine_duration_hours0 / 10number0 / 10
evapotranspiration_mm0 / 10number0 / 10
temperature_range_c0 / 10number0 / 10
is_frost_day0 / 10number0 / 10
is_hot_day0 / 10number0 / 10
precipitation_category0 / 10string0 / 10
How the score is calculated, its limitations, and how to correct an assessment →

About this data

Daily meteorological observations for 50 major cities across six continents, capturing temperature extremes, precipitation, wind speed, sunshine duration, and evapotranspiration alongside derived indicators such as frost days and heat days. Data sourced from ERA5 reanalysis and station records via Open-Meteo.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example
python3 retrieve-dataset.py b19fc6bd-4568-47c8-b777-d1e9ad7e4d38 --output dataset.bin
Full supplier documentation
Original supplier listing: 50-City Daily Weather & Climate Panel — 18,300 Observations (2024) Reference-grade daily weather observations for 50 major cities across all 6 inhabited continents throughout 2024. Each of the 18,300 rows captures a single city-day with 15 meteorological variables including temperature extremes, precipitation, snowfall, wind speed and gusts, sunshine duration, and evapotranspiration — plus derived indicators like frost days, heat days, and precipitation intensity categories. **Sources:** - Open-Meteo Historical Weather API (ERA5 reanalysis + station data) - Curated world cities database (population, coordinates, timezone metadata) **Coverage:** 50 cities spanning North America (7), South America (5), Europe (10), Asia (13), Africa (7), and Oceania (3) — from Reykjavik (64°N) to Melbourne (37°S), Anchorage to Singapore. **Schema (22 columns):** - `date` — ISO 8601 date - `city`, `country`, `continent` — geographic identifiers - `latitude`, `longitude` — WGS84 coordinates - `city_population` — estimated city population - `timezone` — IANA timezone - `temperature_max_c`, `temperature_min_c`, `temperature_mean_c` — daily temperature in Celsius - `precipitation_mm`, `rain_mm`, `snowfall_cm` — daily precipitation totals - `wind_speed_max_kmh`, `wind_gusts_max_kmh` — peak wind measurements - `sunshine_duration_hours` — hours of sunshine - `evapotranspiration_mm` — FAO Penman-Monteith reference ET₀ - `temperature_range_c` — diurnal temperature swing - `is_frost_day` — binary flag (min temp ≤ 0°C) - `is_hot_day` — binary flag (max temp ≥ 35°C) - `precipitation_category` — none/light/moderate/heavy/extreme **Use cases:** Climate analysis, city comparison dashboards, anomaly detection, ML weather modeling, urban planning research, travel analytics.

Schema

NameTypeDescription
datestringISO 8601 date
citystringgeographic identifiers
countrystringgeographic identifiers
continentstringgeographic identifiers
latitudestringWGS84 coordinates
longitudestringWGS84 coordinates
city_populationstringestimated city population
timezonestringIANA timezone
temperature_max_cstringdaily temperature in Celsius
temperature_min_cstringdaily temperature in Celsius
temperature_mean_cstringdaily temperature in Celsius
precipitation_mmstringdaily precipitation totals
rain_mmstringdaily precipitation totals
snowfall_cmstringdaily precipitation totals
wind_speed_max_kmhstringpeak wind measurements
wind_gusts_max_kmhstringpeak wind measurements
sunshine_duration_hoursstringhours of sunshine
evapotranspiration_mmstringFAO Penman-Monteith reference ET₀
temperature_range_cstringdiurnal temperature swing
is_frost_daystringbinary flag (min temp ≤ 0°C)
is_hot_daystringbinary flag (max temp ≥ 35°C)
precipitation_categorystringnone/light/moderate/heavy/extreme

Sample Data

Preview a sample of the data before downloading.

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For AI Agents

Via MCP Server
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "City Daily Weather & Climate P" })
// Found: b19fc6bd-4568-47c8-b777-d1e9ad7e4d38
get_download_url({ dataset_id: "b19fc6bd-4568-47c8-b777-d1e9ad7e4d38" })  // free — sign in with MCP OAuth first
Via REST API
# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/b19fc6bd-4568-47c8-b777-d1e9ad7e4d38/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"