Update README.md

README.md

@@ -12,9 +12,9 @@ SolarBench is an initiative focused on reducing barriers for researchers and pra
 This repo contains multiple data modalities and is structured as follow:
 
 - `ground_full`: Ground-based sensor data include **sky images**, a variety of **meteorological measurements**, and labels for solar forecasting tasks, namely different **solar irradiance** components (i.e., GHI, DHI, and DNI) or **power generation** from solar panels.
-- `ground_no_skycam`: A lite version of `ground_full` by excluding **sky images**. Useful for fast analysis and training non-vision models or performing ablation studies.
-- `satellite`: Geostationary satellite imagery including GOES, Himawari, MSG.
-- `weather_forecasts`: Numerical weather predictions (e.g., GFS).
-- `climate_reanalysis`: Retrospective climate reanalysis datasets (e.g., ERA5).
+- `ground_no_skycam`: A lite version of `ground_full` by excluding sky images. Useful for fast analysis and training non-vision models or performing ablation studies.
+- `satellite`: **Geostationary satellite imagery** including GOES, Himawari, MSG.
+- `weather_forecasts`: **Numerical weather predictions** (e.g., GFS).
+- `climate_reanalysis`: Retrospective **climate reanalysis** datasets (e.g., ERA5).
 
 These data can be easily accessed and made into use through the machine learning toolbox we developed. For more details, check it out here: