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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+---
+
+# PeakWeather 🌦️🌤️⛈️
+
+PeakWeather is a dataset of surface weather measurements for spatiotemporal deep learning 
+with data collected every 10 minutes over the course of more than 8 years, from January 2017 until March 2025.
+It includes a diverse set of meteorological variables obtained from of SwissMetNet, 
+the network of automatic weather stations operated by
+the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss). The network counts over 300 station locations
+distributed across Switzerland's complex terrain.
+To provide geographical context, it is enriched with topographical features derived from a digital elevation model.
+Additionally, ensemble forecasts from the currently operational high-resolution NWP model ICON-CH1-EPS are included
+as a baseline for evaluating new forecasting approaches.
+
+<div style="display: flex; justify-content: center; gap: 20px;">
+  <img src="https://raw.githubusercontent.com/MeteoSwiss/PeakWeather/main/figures/stations.png" alt="Description" width="450"/>
+</div>
+
+## How to use PeakWeather
+
+To load the data, refer to the dataset implementation and instructions provided [on GitHub](https://github.com/MeteoSwiss/PeakWeather) 📦.
+
+The dataset is distributed as a lightweight, framework-agnostic Python library that exposes the data in a way that can
+easily integrate with modern deep learning frameworks while keeping dependencies to a minimum.
+
+**License**: CC-BY-4.0
+
+**Source**: MeteoSwiss