SolarStations.org

Ground measured solar irradiance data is critical for benchmarking solar radiation products, modeling climate processes, and understanding the Earth’s radiation budget. However, due to high costs and maintenance requirements, there are only a few hundred high-quality stations globally. Partly due to the scarcity and even more so due to a lack of an overview, it has historically been difficult to determine if and where there is a nearby solar irradiance monitoring station. To address this, this site provides an overview of multi-component solar irradiance monitoring stations worldwide and supporting metadata.

A complete list of stations and metadata can be found in the station catalog.

For more details on the SolarStations.org catalog, the reader is referred to the data article published in Solar Energy, DOI: Jensen et al. (2025). We hope that you will cite the article if you use the catalog in published works.

To find the nearest station to a point of interest, check out the interactive map below. Note that it is possible to click on a station icon to get the station name and country.

import pandas as pd
import folium
from folium import plugins
import folium_legend

# Load stations
solarstations = pd.read_csv('../solarstations.csv', dtype={'Tier': str}).fillna('')
esmap_stations = pd.read_csv('../esmap_stations.csv', dtype={'Tier': str}).fillna('')
# Add esmap stations first so they are underneath
stations = pd.concat([solarstations, esmap_stations], axis='rows', ignore_index=True)
stations = stations[~stations['Instrumentation'].str.contains('G;Ds')]  # remove Tier 3 stations

GHIImagery = "https://d2asdkx1wwwi7q.cloudfront.net/v20210621/ghi_global/{z}/z{z}_{x}x{y}.jpg"
DNIImagery = "https://d2asdkx1wwwi7q.cloudfront.net/v20210621/dni_global/{z}/z{z}_{x}x{y}.jpg"
GlobalSolarAtlasAttribution = "Source: GlobalSolarAtlas 2.0. Data from Solargis."
EsriImagery = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}"
EsriAttribution = "Tiles &copy; Esri &mdash; Source: Esri, i-cubed, USDA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGN, IGP, UPR-EGP, and the GIS User Community"

# Create Folium map
m = folium.Map(
    location=[0, 15],
    zoom_start=1, min_zoom=1, max_bounds=True,
    control_scale=True,  # Adds distance scale in lower left corner
    tiles='Cartodb Positron')

def station_status(time_period):
    if time_period.endswith('-'):
        return 'Active'
        color = '#008000'  # Green for active stations
    elif (time_period == '') | time_period.endswith('?'):
        return 'Unknown'
    else:
        return 'Inactive'

stations['Status'] = stations['Time period'].map(station_status)

status_dict = {
    'Active': '#008000',  # Green for active stations
    'Unknown': '#3186cc',  # Blue for stations with unknown status
    'Inactive': '#ff422b',  # Red for inactive stations
}

stations['Color'] = stations['Status'].map(status_dict)

z_order_dict = {'Active': 2, 'Unknown': 1, 'Inactive': 0}
stations['z_order'] = stations['Status'].map(z_order_dict)

stations['Tier'] = 2
stations.loc[stations['Instrumentation'].str.startswith('G;B;D'), 'Tier'] = 1
stations = stations.sort_values('z_order')

annual_irradiance = pd.read_csv('../data/nasa_power_annual_irradiance_global.csv', index_col=[0, 1])
for index, row in stations.iterrows():
    lat_round = round(row['Latitude']*2-0.5, 0)/2 + 0.25
    lon_round = round(row['Longitude']*2-0.5, 0)/2 + 0.25
    try:
        stations.loc[index, ['GHI', 'DHI', 'DNI']] = \
            annual_irradiance.loc[(lat_round, lon_round), :].values
    except KeyError as e:
        continue

# Add each station to the map
for index, row in stations.iterrows():    
    folium.CircleMarker(
        location=[row['Latitude'], row['Longitude']],
        popup=folium.Popup(
            f"{row['Station name']}, {row['Country']}<br>"
            f"Tier: {row['Tier']}<br>"
            f"Elevation: {row['Elevation']} m<br>"
            f"GHI: {row['GHI']:.0f} kWh/m^2<br>"
            f"DNI: {row['DNI']:.0f} kWh/m^2",
            max_width="100"),
        tooltip=row['Abbreviation'],
        radius=5, color=row['Color'],
        fill_color=row['Color'], fill=True).add_to(m)

folium.raster_layers.TileLayer(EsriImagery, name='World imagery', attr=EsriAttribution, show=False).add_to(m)
folium.raster_layers.TileLayer(GHIImagery, name='GHI', attr=GlobalSolarAtlasAttribution,
                               max_zoom=10, max_native_zoom=10, zoomOffset=1, show=False).add_to(m)
folium.raster_layers.TileLayer(DNIImagery, name='DNI', attr=GlobalSolarAtlasAttribution,
                               max_zoom=10, max_native_zoom=10, zoomOffset=1, show=False).add_to(m)
folium.LayerControl(position='topright').add_to(m)

# Additional options and plugins
# Note it's not possible to change the position of the scale
plugins.Fullscreen(position='bottomright').add_to(m)  # Add full screen button to map
folium.LatLngPopup().add_to(m)  # Show latitude/longitude when clicking on the map
# plugins.MiniMap(toggle_display=True, zoom_level_fixed=1, minimized=True, position='bottomright').add_to(m)  # Add minimap to the map
# plugins.MeasureControl(position='topleft').add_to(m)  # Add distance length measurement tool

# Create legend
legend = folium_legend.make_legend(status_dict.keys(), status_dict.values(), title="Station status")
m.get_root().html.add_child(legend)  # Add Legend to map

# Show the map
m

Acknowledgments¶

Solar irradiance map backgrounds were obtained from the Global Solar Atlas 2.0, a free, web-based application developed and operated by Solargis s.r.o. on behalf of the World Bank Group, utilizing Solargis data, with funding provided by the Energy Sector Management Assistance Program (ESMAP). For additional information see https://globalsolaratlas.info.

References¶

Jensen, A. R., Sifnaios, I., Anderson, K. S., & Gueymard, C. A. (2025). SolarStations.org—A global catalog of solar irradiance monitoring stations. Solar Energy, 295, 113457. 10.1016/j.solener.2025.113457

Introduction

Acknowledgments¶