Curated ECMWF static dataset covering the June 2026 European heatwave. Contains the Extreme Forecast Index (EFI) for 2 m temperature and four Thermofeel human-thermal-comfort parameters, computed from the operational ENS. Cited as [10.5281/zenodo.21224650](https://doi.org/10.5281/zenodo.21224650).

About this dataset

This static dataset provides a curated set of probabilistic extreme-weather indicators and human thermal comfort parameters covering the June 2026 European heatwave (1 June 2026 – 5 July 2026). All fields are computed from the operational ECMWF Ensemble Prediction System (ENS) and the Thermofeel post-processing library.

It is intended to support post-event analysis, verification studies, communication and media work, and downstream research on early-warning signals for heat extremes over Europe.

The dataset contains two families of fields, initialised twice daily (00 and 12 UTC) for every forecast cycle from 2026-06-01 00 UTC to 2026-07-05 12 UTC.

1. Extreme Forecast Index (EFI) — 2 m temperature

- Ensemble-derived probabilistic indicator of how anomalous the forecast 2 m temperature distribution is compared to the model climate (M-climate) for the same location and calendar week.
- Dimensionless, bounded on [−1, +1]; positive values indicate anomalously warm conditions.

2. Thermofeel human-thermal-comfort parameters

Computed from ENS 2 m temperature, 2 m dewpoint, 10 m wind and radiation fields using the ECMWF [Thermofeel](https://github.com/ecmwf/thermofeel) Python library:

| Short name | Parameter | Notes |
|---|---|---|
| `heatx` | Heat Index | Rothfusz / NWS formulation — temperature + humidity. |
| `utci` | Universal Thermal Climate Index | Bröde et al. (2012) — temperature, humidity, wind, mean radiant temperature. |
| `aptmp` | Apparent Temperature | Steadman-style "feels-like". |
| `wbgt` | Wet Bulb Globe Temperature | Occupational heat-stress — temperature, humidity, wind, radiation. |

### Temporal coverage

- **Initialisation cycles:** 2026-06-01 00 UTC → 2026-07-05 12 UTC, 12-hourly (00 and 12 UTC).
- **Forecast steps:** 0–144 h at 3-hourly resolution; 150–360 h at 6-hourly resolution.

### Spatial coverage

Global domain.

### File format

**GRIB2.** We recommend ecCodes ≥ 2.42.0. For Python analysis, `cfgrib` + `xarray` is the most convenient stack.

---

### Where to find the data

The data are hosted openly on the ECMWF public S3 bucket:

```
s3://ecmwf-static-datasets/heatwave/june-2026/
```

No credentials, no registration — pass `--no-sign-request` to the AWS CLI (or the equivalent anonymous flag in any S3-compatible client).

> [PANEL — tip]
> New to the static datasets area? See the parent page: **Static Datasets** for the general access pattern, licence and hosting information.

---

### Examples: accessing the data

#### Browse the archive

```bash
aws s3 ls --no-sign-request s3://ecmwf-static-datasets/heatwave/june-2026/
```

#### Download a single file

```bash
aws s3 cp --no-sign-request \
s3://ecmwf-static-datasets/heatwave/june-2026/<path/to/file>.grib2 .
```

#### Mirror the full dataset

```bash
aws s3 sync --no-sign-request \
s3://ecmwf-static-datasets/heatwave/june-2026/ ./june-2026-heatwave/
```

#### Programmatic access — Python / boto3

```python
import boto3
from botocore import UNSIGNED
from botocore.config import Config

s3 = boto3.client("s3", config=Config(signature_version=UNSIGNED))

# List objects
resp = s3.list_objects_v2(
Bucket="ecmwf-static-datasets",
Prefix="heatwave/june-2026/",
)
for obj in resp.get("Contents", []):
print(obj["Key"], obj["Size"])

# Download one
s3.download_file(
"ecmwf-static-datasets",
"heatwave/june-2026/<path/to/file>.grib2",
"local.grib2",
)
```

#### Reading a GRIB2 file — Python / xarray + cfgrib

```python
import xarray as xr

ds = xr.open_dataset(
"efi_2t_2026062812_step024.grib2",
engine="cfgrib",
)
print(ds)
```

---

### Provenance

- **Forecasts:** ECMWF Integrated Forecasting System (IFS), ENS configuration, operational cycle *[TBC]*, 51 members (control + 50 perturbed).
- **EFI:** computed against the operational M-climate (model re-forecast climate) for the corresponding calendar week and location.
- **Thermofeel outputs:** computed member-by-member from ENS 2 m temperature, 2 m dewpoint, 10 m wind and radiation fields using [Thermofeel](https://github.com/ecmwf/thermofeel). Ensemble mean and selected quantiles are archived.

### Limitations

> [PANEL — note]
> - This dataset captures the **operational forecast view** of the event; it is **not a reanalysis**. Values reflect ECMWF's forecasts at issue time, not observed conditions.
> - EFI is a signal of **unusualness** relative to model climate, not a magnitude. It should be read alongside the underlying ensemble distribution and, where possible, the Shift of Tails (SOT) diagnostic.
> - Thermofeel indicators are diagnostic combinations of forecast variables; their accuracy inherits the underlying forecast skill — particularly for wind and radiation at short lead times.

---

### Citation

Please cite the dataset via its DOI:

> Pidduck, E., *et al.* (2026). *ECMWF EFI and Thermofeel heat-stress indicators for the June 2026 European heatwave* (Version 1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21224650

BibTeX:

```bibtex
@dataset{pidduck_2026_heatwave_efi_thermofeel,
author = {Pidduck, Emma and others},
title = {ECMWF EFI and Thermofeel heat-stress indicators
for the June 2026 European heatwave},
year = 2026,
publisher = {Zenodo},
version = {1.0.0},
doi = {10.5281/zenodo.21224650},
url = {https://doi.org/10.5281/zenodo.21224650}
}
```

---

### Related resources

- [ECMWF Extreme Forecast Index — documentation](https://www.ecmwf.int/en/forecasts/documentation-and-support/extreme-forecast-index)
- [Thermofeel library on GitHub](https://github.com/ecmwf/thermofeel)
- [ECMWF open data: real-time forecasts from IFS and AIFS](https://confluence.ecmwf.int/spaces/DAC/pages/272310539/)
- Lalaurette, F. (2003). *Early detection of abnormal weather conditions using a probabilistic extreme forecast index.* Q. J. R. Meteorol. Soc., **129**, 3037–3057.
- Bröde, P. *et al.* (2012). *Deriving the operational procedure for the Universal Thermal Climate Index (UTCI).* Int. J. Biometeorol., **56**, 481–494.

---

### Contact

Emma Pidduck, ECMWF User Services Section — emma.pidduck@ecmwf.int
Or via the [ECMWF support portal](https://support.ecmwf.int/).

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