# European harvests and weather, 2000–2024

**Explore how European crop yields vary with early-season weather and FAO price context.** This fixed snapshot covers five crops across 69 regions from 2000 to 2024, with one row per region, crop, and harvest year. Use it for regional yield models with a June 1 predictor cutoff. Weather is a single grid point per region, not a cropland-weighted average. ## Coverage - Geography: 69 regions in Czec…

European harvests and weather, 2000–2024 is an open, machine-readable dataset published on Mostly Right as immutable Parquet versions, with a documented column schema, a JSON query API and a direct download. Its first rows are free to read and it is open to AI agents.

## Facts

- Slug: `european-harvests-and-weather-20002024`
- Canonical page: https://mostlyright.md/datasets/european-harvests-and-weather-20002024
- Publisher: mostlyrightmd (https://mostlyright.md/publishers/mostlyrightmd)
- Published: 2026-09-12T09:15:59.330Z
- Tables: 1
- Formats: Apache Parquet (download), JSON (query and sample)
- Cost: the first 500 rows of each table are free to everyone; querying and downloading need a free account and count against a monthly free allowance unless the workspace is subscribed
- Metadata API: `GET https://mostlyright.md/api/v2/public/datasets/european-harvests-and-weather-20002024`
- Topics: agriculture, europe, crop yields, eurostat, nasa power, fao, harvest risk

## How to use it

1. Read a table's schema — no account needed.
2. Fetch its published sample rows — no account needed.
   The first 500 rows of every table, in stored order, are free to everyone, with or without an account. Without an account you get that sample and nothing else: no filter, sort, search, download or page past row 500.
3. Sign in at https://mostlyright.md/login, connect this dataset to a workspace on its page, and create an `mr_use_` key.
4. Query bounded JSON, or download the complete Parquet snapshot and read it locally.
   A free workspace may read 100,000 rows and run 1,000 queries a UTC month past the sample. The allowance is shared by everyone in the workspace, and a free workspace may have any number of members. Reads count against the workspace whose data or key they use. A subscribed workspace is never counted, for anyone working in it.

Agents can do all of this over MCP at `https://mostlyright.md/api/mcp` — searching, reading schemas and sampling rows work with no credential at all.

## Table: regional_harvest_weather

- Table id: `994c0256-368f-4067-a953-2d9d5f194d28`
- Slug: `regional-harvest-weather`
- Immutable version: `308eb3c9-eb59-505b-8495-b56e53a9d2e9`
- Licence: CC-BY-4.0
- Schema: `GET https://mostlyright.md/api/v2/public/tables/994c0256-368f-4067-a953-2d9d5f194d28/schema`
- Sample rows, no key: `GET https://mostlyright.md/api/v2/public/tables/994c0256-368f-4067-a953-2d9d5f194d28/preview`
- Bounded JSON query: `POST https://mostlyright.md/api/v2/public/tables/994c0256-368f-4067-a953-2d9d5f194d28/query` with `x-api-key: mr_use_…`
- Full Parquet snapshot: `GET https://mostlyright.md/api/v2/public/tables/994c0256-368f-4067-a953-2d9d5f194d28/current` with `x-api-key: mr_use_…` (application/vnd.apache.parquet)

### Columns (47)

| Column | Type | Description |
| --- | --- | --- |
| `country` | string | Country code: AT, CZ, DE, FR or PL. |
| `region` | string | Current NUTS 2024 code; observed source histories are retained, not spatially reconstructed. |
| `region_name` | string | Eurostat GISCO region name. |
| `nuts_level` | integer | Geographic level: Germany uses NUTS 1; other countries use NUTS 2. |
| `crop_code` | string | Eurostat crop code. |
| `crop_name` | string | Common wheat and spelt, barley, grain maize, rapeseed or potatoes. |
| `harvest_year` | integer | Year of harvested production. |
| `predictor_cutoff` | date | June 1 of harvest year; weather strictly precedes this day and FAO reference months end in April. Not an as-published vintage claim. |
| `weather_latitude` | decimal | NASA request latitude rounded to five decimals from the GISCO label point. |
| `weather_longitude` | decimal | NASA request longitude rounded to five decimals from the GISCO label point. |
| `outcome_area_ha` | decimal | Reported crop area in hectares, a contemporaneous harvest outcome; exclude from June predictors. |
| `outcome_production_t` | decimal | Reported harvested production in tonnes at EU standard humidity; exclude from predictors. |
| `outcome_yield_t_ha` | decimal | Harvested production divided by positive reported area; continuous observed outcome for downstream modelling. |
| `crop_observation_flags` | string | Combined Eurostat crop flags; empty means none. Preserve provisional, estimate and break information. |
| `weather_days` | integer | Number of daily observations from January 1 through May 31. |
| `complete_weather_days` | integer | Days with all six weather variables present. |
| `jan_may_mean_temp_c` | decimal | January–May daily mean temperature average at the regional label-point grid. |
| `jan_may_max_temp_c` | decimal | Highest daily maximum temperature observed January–May. |
| `jan_may_min_temp_c` | decimal | Lowest daily minimum temperature observed January–May. |
| `jan_may_rainfall_mm` | decimal | Total corrected precipitation January–May. |
| `jan_may_humidity_pct` | decimal | Average daily relative humidity January–May. |
| `jan_may_solar_mj_m2` | decimal | Total daily shortwave irradiance January–May. |
| `jan_may_frost_days` | integer | January–May days with daily minimum temperature below 0 C. |
| `jan_may_hot_days` | integer | January–May days with daily maximum temperature at least 30 C. |
| `jan_may_dry_days` | integer | January–May days with precipitation below 1 mm. |
| `jan_temp_c` | decimal | Jan mean daily temperature at the regional label-point grid. |
| `jan_rainfall_mm` | decimal | Jan total precipitation at the regional label-point grid. |
| `jan_solar_mj_m2` | decimal | Jan total shortwave irradiance at the regional label-point grid. |
| `feb_temp_c` | decimal | Feb mean daily temperature at the regional label-point grid. |
| `feb_rainfall_mm` | decimal | Feb total precipitation at the regional label-point grid. |
| `feb_solar_mj_m2` | decimal | Feb total shortwave irradiance at the regional label-point grid. |
| `mar_temp_c` | decimal | Mar mean daily temperature at the regional label-point grid. |
| `mar_rainfall_mm` | decimal | Mar total precipitation at the regional label-point grid. |
| `mar_solar_mj_m2` | decimal | Mar total shortwave irradiance at the regional label-point grid. |
| `apr_temp_c` | decimal | Apr mean daily temperature at the regional label-point grid. |
| `apr_rainfall_mm` | decimal | Apr total precipitation at the regional label-point grid. |
| `apr_solar_mj_m2` | decimal | Apr total shortwave irradiance at the regional label-point grid. |
| `may_temp_c` | decimal | May mean daily temperature at the regional label-point grid. |
| `may_rainfall_mm` | decimal | May total precipitation at the regional label-point grid. |
| `may_solar_mj_m2` | decimal | May total shortwave irradiance at the regional label-point grid. |
| `fao_food_jan_apr_index` | decimal | January–April mean global food price index, 2014–2016=100. |
| `fao_food_apr_index` | decimal | April global food price index, 2014–2016=100. |
| `fao_cereals_jan_apr_index` | decimal | January–April mean global cereals price index, 2014–2016=100. |
| `fao_cereals_apr_index` | decimal | April global cereals price index, 2014–2016=100. |
| `fao_oils_jan_apr_index` | decimal | January–April mean global oils price index, 2014–2016=100. |
| `fao_oils_apr_index` | decimal | April global oils price index, 2014–2016=100. |
| `fao_months` | integer | Number of January–April FAO observations used. |

## Citing this dataset

Cite the dataset by name and canonical URL (https://mostlyright.md/datasets/european-harvests-and-weather-20002024), the table, and the immutable `version_id` the rows came from. A query response carries `table.version_id` and `table.content_digest`; a download carries a strong ETag and a `Content-Digest` header.