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General usage

Welcome to the Weather API! You can query our endpoints to be served different Numerical Weather Prediction (NWP) and reanalysis models in the format of your choice.

We have language bindings in Python! You can view code examples in the dark area to the right.

Authentication

To authenticate, use this code:

import requests

url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
response = requests.get(url, headers=headers)

Every request to the API needs to be authenticated with an API key.

The Weather API expects for the API key to be included in all API requests to the server in a header as follows:

Authorization: your_api_key

Parameters

Example basic GET call:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed',
    'output-format': 'json'   
}
response = requests.get(url, headers=headers, params=params)

Example basic POST call:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed',
    'output-format': 'json'
}
response = requests.post(url,
                         headers=headers,
                         data=params,
                         content_type='application/json')

The Weather API expects the following parameters for all endpoints:

Parameter Required Description
model Yes Identifier of the dataset to query
start-date Yes Starting date of requested weather data
end-date Yes Ending date of requested weather data. This date can be in the future when requesting operational forecasts.
reference-time-freq Yes The frequency of the forecasts runs to be returned. E.g. 6H, 12H, 24H
timezone No Timezone used by the request parameters
valid-time-freq No The time frequency of one particular forecast. Usually 1H. Default None.
forecast-horizon No The length of one forecast run. Possible values are: 'latest' - this will return a continuous timeseries with the latest forecast values for a specific valid time; 'full': the entire forecast horizon will be returned for each forecast run; '0, 1, 2, ...': a custom list of lead times (hours) to return
interpolate No Return spatially interpolated values or closest available grid data
output-format No The response output format. Available formats are 'json' and 'netcdf'
output-schema No The schema used to format the output. The values are specific to the output. For 'json' formats, possible values are 'list' or 'xarray'.
latitude Yes A comma separated list of latitudes for the requested locations. E.g. '45.2, 59.2'
longitude Yes A comma separated list of longitudes for the requested locations. E.g. '18.1, 13.4'
variables Yes A comma separated list of the weather variables. When available, specific height levels can be requested for a variable using the notation :. E.g. "Temperature_Height:80.0" refers to the temperature at 80m for the relevant weather model.

Output formats

The API can return JSON data with different schemas or pre-signed URLS to NetCDF4 files. When JSON data is returned, the output schema can be compatible with pandas DataFrames or with xarray Dataset

JSON output, pandas DataFrame schema

Example with pandas DataFrame:

import requests
import pandas as pd

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-02-01',
    'end-date': '2023-02-03',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed',
    'output-format': 'json',
    'output-schema': 'list'
}
response = requests.get(url, headers=headers, params=params)
df = pd.DataFrame(response.json())

# # Optional: Use hierarchical DatetimeIndex
# df['valid_datetime'] = pd.to_datetime(df['valid_datetime'])
# df['ref_datetime'] = pd.to_datetime(df['ref_datetime'])
# df = df.set_index(['ref_datetime', 'valid_datetime'])

Template of returned JSON:

[{
    "ref_datetime": ["2023-02-01T00:00:00Z", "2023-02-01T00:00:00Z", ...],
    "valid_datetime": ["2023-02-01T00:00:00Z", "2023-02-01T01:00:00Z", ...],
    "Temperature": [-3.92, -4.66, -5.22, -5.64, -6.01, ...],
    "WindSpeed": [5.51, 5.55, 5.36, 4.74, 3.7, 2.78, ...],
    ...
},
{
    "ref_datetime": ["2023-02-01T00:00:00Z", "2023-02-01T00:00:00Z", ...],
    "valid_datetime": ["2023-02-01T00:00:00Z", "2023-02-01T01:00:00Z", ...],
    "Temperature": [-1.33, -2.40, 0.50, 0.70, ...],
    "WindSpeed": [6.1, 5.50, 5.20, 4.30, 3.4, ...],
    ...
}
...
]

Before being serialized to JSON, the DataFrame has a structure similar to the following:

pandas DataFrame

xarray Dataset

Example with xarray Dataset:

import requests
import xarray as xr

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed',
    'output-format': 'json',
    'output-schema': 'xarray'
}
response = requests.get(url, headers=headers, params=params)
ds = xr.Dataset.from_dict(response.json())

Template of returned JSON:

{
    "attrs": {},
    "coords": {
        "coord_1": {
            "attrs": {},
            "data": [<coord_1 values>],
            "dims": [<coord_1 dimensions>]
        }, ...
    },
    "data_vars": {
        "variable_name": {
            "attrs": {},
            "data": [
                [ nesting depth depends on the number
                    [ of dimensions of the DataArray,
                        [ here 5 dimensions
                            [
                                <value>
                            ]
                        ],
                        [
                            [
                                <value>
                            ]
                        ], ...
                    ]
                ]
                    ],

            "dims": [                        
                        "point",
                        "reference_time",
                        "valid_time",
                        "height",
                        "latitude",
                        "longitude",
                        ...
                    ]

        }, ...
    },
    "dims": {
        "height": <no_height_slices>,
        "point": <no_point_index>,
        "latitude": <no_latitude_points>,
        "longitude": <no_longitude_points>,
        "reference_time": <no_reference_times>,
        "valid_time": <length_forecast_horizon,
        ...
    }
}

Before being serialized to JSON, the Dataset has a structure similar to the following:

xarray Dataset

For more information about the elements of a xarray Dataset, please refer to xarray's data structures.

The structure of the JSON returned by the API is presented in the json tab of the right column.

URL to NetCDF4 file

Example with NetCDF4 url:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed',
    'output-format': 'netcdf'
}
response = requests.get(url, headers=headers, params=params)
netcdf_url = response.json()['file']

Template of returned JSON:

{
    "create_time": <datetime_link_created>,
    "file": <pre-signed URL>
}

A pre-signed URL to the NetCDF file stored in a S3 bucket, that you can download with the mean of your choice, e.g. your web browser, a cURL command or simply a HTTP GET request. Recommended when the queried data starts to grow in size. Expires after one week.

Endpoints

query

Returns the weather forecast data according to the query parameters for a model.

Example call for query:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed'
}
response = requests.get(url, headers=headers, params=params)

point/operational

Returns the latest weather forecast data according to the query parameters for a model.

Example call for point/operational:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/point/operational"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed:10'
}
response = requests.get(url, headers=headers, params=params)

point/historical

Returns the historical weather forecast data according to the query parameters for a model.

Example call for point/historical:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/point/historical"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed:10'
}
response = requests.get(url, headers=headers, params=params)

area/operational

Returns the latest weather forecast data on a grid specified by the latitude and longitude coordinate list for a model.

Example call for area/operational, xarray output schema:

import requests
import xarray as xr

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/area/operational"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed:10',
    'output-format': 'xarray'
}
response = requests.get(url, headers=headers, params=params)
ds = xr.Dataset.from_dict(response.json())
print(ds)

area/historical

Returns historical weather forecast data on a grid specified by the latitude and longitude coordinate list for a model.

Example call for area/historical, xarray output schema:

import requests
import xarray as xr

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/area/historical"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed:10',
    'output-format': 'xarray'
}
response = requests.get(url, headers=headers, params=params)
ds = xr.Dataset.from_dict(response.json())
print(ds)

Events

New forecast dissemination events are published on a Kafka Server under the datahub_weather topic. The Kafka Server exposes a REST API which can be used to create consumers, subscribe to topics and retrieve latest events.

Authentication is based on the same API keys that are used to query the forecast endpoints.

The servers allows multiple consumers and consumer intances for a single topic.

Create a Kafka consumer and a consumer instance

This request will create a consumer named my_consumer and a consumer instance named my_consumer_instance_1:

curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" \
            -H "Authorization: [API_KEY]" \
            --data '{"name": "my_consumer_instance_1", "format": "json", "auto.offset.reset": "latest"}' \
            https://events.rebase.energy/rest/consumers/my_consumer

Returns:

{
    "instance_id": "my_consumer_instance_1",
    "base_uri": "https://events.rebase.energy/rest/consumers/my_consumer/instances/my_consumer_instance_1"
}

Subscribe the consumer instance my_consumer_instance_1 to the datahub_weather topic

This request will subscribe the consumer instance my_consumer_instance_1 to the datahub_weather topic.

curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" \
            -H "Authorization: [API_KEY]" \
            --data '{"topics":["datahub_weather"]}' \            
            https://events.rebase.energy/rest/consumers/my_consumer/instances/my_consumer_instance_1/subscription 

Returns HTTP Code 204 with no content.

Receive latest events

This request will receive all unread events of the consumer instance my_consumer_instance_1.

curl -X GET -H "Accept: application/vnd.kafka.json.v2+json" \            
            -H "Authorization: [API_KEY]" \
            https://events.rebase.energy/rest/consumers/my_consumer/instances/my_consumer_instance_1/records

Returns an array with the latest unread messages.

[{
    "id": "e837844d-a8a5-445f-a9a6-f569d59d9a60",
    "timestamp: "2022-09-29T18:16:05.273290+00:00",
    "type": 1,
    "model": "MetNo_HIRESMEPS",
    "reference_time": "2022-09-29T17:00Z",
    "message": "New forecast published",
    "info": ""
},
...]

Schema:

Key Description
model the model identifier
timestamp UTC timestamp when the forecast has been published on our platform
type always 1
reference_time the forecast reference time start
message typically information about the forecast
info any additional info about the forecast issued

Reference

Additional help: https://developer.confluent.io/get-started/rest/?_ga=2.91944543.47573013.1664830252-518093079.1664460550#consume-events

Post-processed variables

Different datasets having different naming and unit conventions, we post-process some variables to make it easier for you to query several datasets at once. The post-processing transformations are explained in each datasets' variables section. The available post-process variables are the following:

Name Description DWD-ICON-EU DWD-ICON-D2 NCEP-GFS ECMWF-EPS_CF ECMWF-HiRes ECMWF-HiRes-Operational ECMWF-HiRes-Mix ECMWF-ERA5 ECMWF-ERA5-land MetNo-MEPS MetNo-HiRes MeteoFrance-ARPEGE_EU MetOffice-GlobalHiRes SMHI-MESAN REBASE_AI
Temperature Temperature at 2m (°C)
WindSpeed Wind speed at 10m (m.s-1)
WindDirection Wind direction at 10m (°)
WindSpeed:100 Wind speed at 100m (m.s-1)
WindDirection:100 Wind direction at 100m (°)
CloudCover Cloud cover fraction (0-1)
RelativeHumidity Relative humidity at 2m (%)
PressureReducedMSL Pressure at mean sea level (Pa)
SolarDownwardRadiation Surface solar radiation (W.m-2)
TotalPrecipitation Surface total precipitation (kg.m-2)

Datasets

ICON Europe (DWD), identifier: DWD_ICON-EU

Example call for DWD_ICON-EU:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed, CloudCover'
}
response = requests.get(url, headers=headers, params=params)

Local nest over Europe of the ICOsahedral Nonhydrostatic model (ICON) developed jointly by Deutscher Wetterdienst (DWD) and the Max-Planck Institute for Meteorology in Hamburg (MPI-M) (documentation).

Variables

Name Description
T Temperature in Kelvin (K), at several heights (GRIB variable documentation)
T_2M Temperature in Kelvin (K), at 2m above ground (#dimensions) (GRIB variable documentation)
U Zonal wind in meters per second (m.s-1), at several heights (GRIB variable documentation)
V Meridional wind in meters per second (m.s-1), at several heights (GRIB variable documentation)
U_10m Zonal wind in meters per second (m.s-1), at 10m above ground (#dimensions) (GRIB variable documentation)
V_10m Meridional wind in meters per second (m.s-1), at 10m above ground (#dimensions) (GRIB variable documentation)
CLCT Total cloud cover in percents (%) (GRIB variable documentation)
CLCL Low cloud cover (800hPa-Soil) in percents (%) (GRIB variable documentation)
CLCM Medium cloud cover (400-800 hPa) in percents (%) (GRIB variable documentation)
CLCH High cloud cover (0-400 hPa) in percents (%) (GRIB variable documentation)
ASOB_S Net short wave radiation flux (m) (at the surface) in Watt per square meter (W.m-2). Only available from 2019-08-15 06:00:00 UTC onwards
ASWDIFD_S Surface down solar diffuse radiation (average since model start) in Watt per square meter (W.m-2). Only available from 2019-08-15 06:00:00 UTC onwards
ASWDIR_S Surface down solar direct radiation (average since model start) in Watt per square meter (W.m-2). Only available from 2019-08-15 06:00:00 UTC onwards
RELHUM_2M Relative humidity in percents (%) at 2 meters above the surface (GRIB variable documentation). Only available from 2020-08-05 06:00:00 UTC onwards
PMSL Pressure in Pascals (Pa) reduced to mean sea level(GRIB variable documentation). Only available from 2019-08-06 06:00:00 UTC onwards

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from T_2M
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from U_10m and V_10m
WindDirection Wind direction at 10m in degrees (°) derived from U_10m and V_10m
WindSpeed:100 Wind speed at 100m in meters per second (m.s-1) derived from U and V
WindDirection:100 Wind direction at 100m in degrees (°) derived from U and V
CloudCover Cloud cover fraction (0-1) derived from CLCT
RelativeHumidity Relative humidity at 2m in percents (%) derived from RELHUM_2M
PressureReducedMSL Pressure at mean sea level pressure in Pascals (Pa) derived from PMSL
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from ASOB_S
TotalPrecipitation Surface total precipitation (kg.m-2) derived from TOT_PREC

Dimensions

Name Description
height Height in meters, levels 65 to 74, cf. table
latitude 29.5°N to 70.5°N with a resolution of ~0.0625°
longitude -23.5°E to 45.0°E with a resolution of ~0.0625°

ICON-D2 (DWD), identifier: DWD_ICON-D2

Example call for DWD_ICON-D2:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'DWD_ICON-D2',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '3H',
    'forecast-horizon': 'full',
    'latitude': '52.50, 53.16', 
    'longitude': '13.32, 10.81',
    'variables': 'Temperature, WindSpeed, CloudCover'
}
response = requests.get(url, headers=headers, params=params)

Local nest around Germany of the ICOsahedral Nonhydrostatic model (ICON) developed jointly by Deutscher Wetterdienst (DWD) and the Max-Planck Institute for Meteorology in Hamburg (MPI-M) (documentation).

Variables

Name Description
T Temperature in Kelvins (K) at different heights (GRIB variable documentation)
T_2M Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
U U-component of wind in meters per second (m.s-1) at different heights (GRIB variable documentation)
U_10M U-component of wind in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
V V-component of wind in meters per second (m.s-1) at different heights (GRIB variable documentation)
V_10M V-component of wind in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
CLCT Total cloud cover in percents (%) (GRIB variable documentation)
CLCL Low cloud cover (800hPa-Soil) in percents (%) (GRIB variable documentation)
CLCM Medium cloud cover (400-800 hPa) in percents (%) (GRIB variable documentation)
CLCH High cloud cover (0-400 hPa) in percents (%) (GRIB variable documentation)
CLCT_MOD Modified cloud cover for media (GRIB variable documentation)
CLC Cloud cover in percents (%) at different heights (GRIB variable documentation)
RELHUM_2M Relative humidity in percents (%) at 2 meters above the surface (GRIB variable documentation)
PMSL Pressure in Pascals (Pa) reduced to mean sea level (GRIB variable documentation)
RAIN_GSP Large-scale rain accumulation in kilos per square meter (kg.m-2) (GRIB variable documentation)
TOT_PREC Total precipitation in kilograms per square meter (kg.m-2) (GRIB variable documentation)
RUNOFF_G Soil water runoff (accumulated since model start) in kilos per square meter (kg.m-2) (GRIB variable documentation)
RUNOFF_S Surface water runoff (accumulated since model start) in kilos per square meter (kg.m-2) (GRIB variable documentation)
RHO_SNOW Snow density in kilos per cubic meter (kg.m-3) (GRIB variable documentation)
SNOWLMT Height in meters (m) of snowfall limit above mean sea level (GRIB variable documentation)
SNOW_GSP Large-scale snowfall accumulation
TKE Turbulent kinetic energy in Joules per kilogram (J.kg-1) (GRIB variable documentation)
SOILTYP Soil type (1-9) (GRIB variable documentation)
ROOTDP Root depth in meters (m) of vegetation (GRIB variable documentation)
ASOB_S Net short wave radiation flux (m) (at the surface) in Watt per square meter (W.m-2). Only available from 2023-08-03 12:00:00 UTC onwards
ASWDIFD_S Surface down solar diffuse radiation (average since model start) in Watt per square meter (W.m-2). Only available from 2023-08-03 12:00:00 UTC onwards
ASWDIR_S Surface down solar direct radiation (average since model start) in Watt per square meter (W.m-2). Only available from 2023-08-03 12:00:00 UTC onwards

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from T
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from U_10M and V_10M
WindDirection Wind direction at 10m in degrees (°) derived from U_10M and V_10M
CloudCover Cloud cover fraction (0-1) derived from CLCT
RelativeHumidity Relative humidity at 2m in percents (%) derived from RELHUM_2M
PressureReducedMSL Pressure at mean sea level in Pascals (Pa) derived from PMSL
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from ASOB_S
TotalPrecipitation Surface total precipitation (kg.m-2) derived from TOT_PREC

Dimensions

Name Description
height Height in meters, levels 56 to 65, cf. table
latitude 43.0°N to 58.2°N with a resolution of ~2km
longitude -4.15°E to 20.55°E with a resolution of ~2km

GFS (NCEP), identifier: NCEP_GFS

Example call for NCEP_GFS:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'NCEP_GFS',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature_Height:80.0, CloudCover'
}
response = requests.get(url, headers=headers, params=params)

Global Forecast System (GFS) produced by the National Centers for Environmental Prediction (NCEP) (general documentation, scientific documentation).

Variables

Name Description
WindGust Wind speed (gust) in meters per second (m.s-1) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
WindUMS_Height U-component of wind in meters per second (m.s-1), at several heights (lv_HTGL8) (GRIB variable documentation)
WindVMS_Height V-component of wind in meters per second (m.s-1), at several heights (lv_HTGL8) (GRIB variable documentation)
WindUMS_Isobar U-component of wind in meters per second (m.s-1), at several isobaric heights (lv_ISBL5) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
WindVMS_Isobar V-component of wind in meters per second (m.s-1), at several isobaric heights (lv_ISBL5) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
StormMotionU_Height U-component storm motion, in meters per second (m.s-1) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
StormMotionV_Height V-component storm motion, in meters per second (m.s-1) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
StormRelativeHelicity_Height Storm relative helicity in square meters per square seconds (m2.s-2) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
SurfacePressure Pressure at surface level in Pascal (Pa) (GRIB variable documentation)
PressureReducedMSL Pressure at mean sea level in Pascal (Pa) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
RelativeHumidity_Isobar Relative humidity in percents (%), at several isobaric heights (lv_ISBL5) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
RelativeHumidity_Height Relative humidity in percents (%) (GRIB variable documentation)
PrecipitableWater Precipitable water in kilos per square meters (kg.m-2) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
SurfacePrecipitationRate Precipitation rate at the surface in kilos per square meters per seconds (kg.m-2.s-1) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
SurfacePrecipitationRateAvg Average precipitation rate at the surface in kilos per square meters per seconds (kg.m-2.s-1) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
SurfaceTotalPrecipitation Accumulated total precipitation at the surface in kilos per square meters (kg.m-2) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
SurfaceSnowDepth Snow depth at the surface in meters (m) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
SurfaceWaterEqAccSnowDepth Water equivalent of accumulated snow depth at the surface in kilos per square meters (kg.m-2) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
Temperature_Height Temperature in Kelvin (K), at several heights (lv_HTGL2) (GRIB variable documentation)
PotentialTemperature_Sigma Potential temperature in Kelvin (K) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
SoilMoisture_Depth Volumetric soil moisture content in fraction, at several depths (lv_DBLL14) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
SoilTemperature_Depth Soil temperature in Kelvin (K), at several depths (lv_DBLL14) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
PlanetaryBoundaryLayer_Height Planetary boundary layer height in meters (m) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
CloudCover_Isobar Total cloud cover in percent (%), at several isobaric heights (lv_ISBL7) (GRIB variable documentation)
SurfaceRadiationShortWaveDownAvg Average downward short-wave radiation flux in Watts per square meters (W.m-2) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
SurfaceRadiationShortWaveUpAvg Average upward long-wave radiation flux in Watts per square meters (W.m-2) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
SurfaceRadiationLongWaveDownAvg Average downward long-wave radiation flux in Watts per square meters (W.m-2) (GRIB variable documentation). Only available from 2019-09-02 06:00:00 UTC onwards
SurfaceLatentHeatNetFluxAvg Average latent heat net flux at the surface in Watts per square meters (W.m-2) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards
SurfaceSensibleHeatNetFluxAvg Average sensible heat net flux at the surface in Watts per square meters (W.m-2) (GRIB variable documentation). Only available from 2020-03-04 00:00:00 UTC onwards

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from Temperature_Height
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from WindUMS_Height and WindVMS_Height
WindDirection Wind direction at 10m in degrees (°) derived from WindUMS_Height and WindVMS_Height
CloudCover Cloud cover fraction (0-1) derived from CloudCover_Isobar
RelativeHumidity Relative humidity at 2m in percents (%) derived from RelativeHumidity_Height
PressureReducedMSL Pressure at mean sea level in Pascals (Pa) derived from PressureReducedMSL
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from SurfaceRadiationShortWaveDownAvg
TotalPrecipitation Surface total precipitation (kg.m-2) derived from SurfaceTotalPrecipitation

Dimensions

Name Description
lv_HTGL2 Height in meters in the ensemble {2.0; 80.0; 100.0}
lv_HTGL8 Height in meters in the ensemble {10.0; 20.0; 30.0; 40.0; 50.0; 80.0; 100.0}
lv_ISBL5 Isobaric surfaces in Pascals in the ensemble {90000.0; 92500.0} (explanation of constant pressure surfaces).
lv_ISBL7 Isobaric surfaces in Pascals in the ensemble {5000.0; 10000.0; 15000.0; 20000.0; 25000.0; 30000.0; 35000.0; 40000.0; 45000.0; 50000.0; 55000.0; 60000.0; 65000.0; 70000.0; 75000.0; 80000.0; 85000.0; 90000.0; 92500.0; 95000.0; 97500.0; 100000.0} (explanation of constant pressure surfaces)
lv_DBLL14 Depth layers in the ensemble {0; 1; 2; 3}, respectively corresponding to {[0-0.1]; [0.1-0.4]; [0.4-1]; [1-2]} meters below ground
latitude -90.0°N to 90.0°N with a resolution of ~0.25°
longitude 0.0°E to 359.75°E with a resolution of ~0.25°

MEPS (MetNo), identifier: MetNo_MEPS

Example call for MetNo_MEPS:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'MetNo_MEPS',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'air_temperature_z:80.0, WindSpeed, WindDirection'
}
response = requests.get(url, headers=headers, params=params)

MEPS (The MetCoOp Ensemble Prediction System) is a 10-member short-range convection permitting ensemble prediction system produced by MetCoOp, the Meterological Cooperation on Operational Numeric Weather Prediction (NWP) between Finnish Meteorological Institute (FMI), MET Norway and Swedish Meteorological and Hydrological Institute (SMHI) (documentation). The data available through the Weather API corresponds to the first ensemble, the control run, which is not perturbed.

Variables

Name Description
x_wind_10m U-component of wind in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
y_wind_10m V-component of wind in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
x_wind_z U-component of wind in meters per second (m.s-1), at several heights (height2) (GRIB variable documentation)
y_wind_z V-component of wind in meters per second (m.s-1), at several heights (height2) (GRIB variable documentation)
air_pressure_at_sea_level Mean sea level pressure in Pascal (Pa) (GRIB variable documentation)
air_temperature_0m Surface air temperature in Kelvin (K) (GRIB variable documentation)
air_temperature_2m Air temperature in Kelvin (K) at 2 meters above ground (GRIB variable documentation)
air_temperature_z Air temperature in Kelvin (K), at several heights (height2) (GRIB variable documentation)
relative_humidity_2m Relative humidity in proportion (0-1) at 2 meters above ground
relative_humidity_z Relative humidity in proportion (0-1) at several heights (height2)
cloud_area_fraction Total cloud cover in proportion (0-1) (GRIB variable documentation)
low_type_cloud_area_fraction Low cloud cover in proportion (0-1)
medium_type_cloud_area_fraction Medium cloud cover in proportion (0-1)
high_type_cloud_area_fraction High cloud cover in proportion (0-1)
integral_of_rainfall_amount_wrt_time Accumulated rainfall at surface in kilograms per square meters (kg.m-2)
integral_of_surface_net_downward
_shortwave_flux_wrt_time
Accumulated net downward surface short-wave radiation in Watts second per square meters (W.s.m-2)
symbols String describing the weather conditions (list of possible values)

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from air_temperature_2m
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from x_wind_10m and y_wind_10m
WindDirection Wind direction at 10m in degrees (°) derived from x_wind_10m and y_wind_10m
CloudCover Cloud cover fraction (0-1) derived from cloud_area_fraction
RelativeHumidity Relative humidity at 2m in percents (%) derived from relative_humidity_2m
PressureReducedMSL Pressure at mean sea level in Pascals (Pa) derived from air_pressure_at_sea_level
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from integral_of_surface_net_downward
_shortwave_flux_wrt_time
TotalPrecipitation Surface total precipitation (kg.m-2) derived from integral_of_rainfall_amount_wrt_time

Dimensions

Name Description
height2 Height in meters in the ensemble {80.0; 100.0}
latitude 49.75 to 75.20°N with a resolution of ~0.1°
longitude -18.15 to 54.20°E with a resolution of ~0.4°

MEPS High Resolution (MetNo), identifier: MetNo_HIRESMEPS

Example call for MetNo_HIRESMEPS:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'MetNo_HIRESMEPS',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'air_temperature_2m, relative_humidity_2m'
}
response = requests.get(url, headers=headers, params=params)

MEPS (The MetCoOp Ensemble Prediction System) is a 10-member short-range convection permitting ensemble prediction system produced by MetCoOp, the Meterological Cooperation on Operational Numeric Weather Prediction (NWP) between Finnish Meteorological Institute (FMI), MET Norway and Swedish Meteorological and Hydrological Institute (SMHI) (documentation). The data available through the Weather API corresponds to a subset of the first ensemble, the control run, which is not perturbed.

Variables

Name Description
air_pressure_at_sea_level Mean sea level pressure in Pascal (Pa) (GRIB variable documentation)
air_temperature_2m Air temperature in Kelvin (K) at 2 meters above ground (GRIB variable documentation)
relative_humidity_2m Relative humidity in proportion (0-1) at 2 meters above ground
cloud_area_fraction Total cloud cover in proportion (0-1) (GRIB variable documentation)
altitude Surface altitude in meters (m)
wind_direction_10m Wind direction in degrees (∈[0;360])(°) at 10 meters above ground
wind_speed_10m Wind speed in meters per second (m.s-1) at 10 meters above ground
wind_speed_of_gust Wind speed of gust in meters per second (m.s-1)
integral_of_surface_downwelling
_shortwave_flux_in_air_wrt_time
Integral of surface downwelling short-wave flux in air with respect to time in Watts second per square meter (W.s.m-2)
land_area_fraction Proportion (0-1) of land in the grid box(GRIB variable documentation)
precipitation_amount Precipitation amount in kilograms per square meter (kg.m-2)
symbols String describing the weather conditions (list of possible values)

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from air_temperature_2m
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from wind_speed_10m
WindDirection Wind direction at 10m in degrees (°) derived from wind_direction_10m
CloudCover Cloud cover fraction (0-1) derived from cloud_area_fraction
RelativeHumidity Relative humidity at 2m in percents (%) derived from relative_humidity_2m
PressureReducedMSL Pressure at mean sea level in Pascals (Pa) derived from air_pressure_at_sea_level
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from integral_of_surface_downwelling
_shortwave_flux_in_air_wrt_time
TotalPrecipitation Surface total precipitation (kg.m-2) derived from precipitation_amount

Dimensions

Name Description
latitude 52.3 to 73.8°N with a resolution of ~0.0036°
longitude -11.8 to 41.7°E with a resolution of ~0.0117°

ARPEGE Europe (Meteo France), identifier: MeteoFrance_ARPEGE-EU

Example call for MeteoFrance_ARPEGE-EU:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'MeteoFrance_ARPEGE-EU',
    'start-date': '2023-08-01',
    'end-date': '2023-08-03',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed_height:20, SurfaceTotalCloudCover'
}
response = requests.get(url, headers=headers, params=params)

Local nest over Europe of the global numerical weather prediction model ARPEGE (Action de Recherche Petite Echelle Grande Echelle) provided by Météo France (general documentation, scientific documentation).

Variables

Name Description
DownwardLongWaveRadiationFluxAvg Average downward long wave radiation flux in Watts per square meter (W.m-2) at the surface (GRIB variable documentation)
HighCloudCover High cloud cover in percents (%) at the surface (GRIB variable documentation)
LowCloudCover Low cloud cover in percents (%) at the surface (GRIB variable documentation)
MediumCloudCover Medium cloud cover in percents (%) at the surface (GRIB variable documentation)
PressureMSL Mean sea level pressure in Pascals (Pa) (GRIB variable documentation)
SnowMeltAvg Average snow melt in kilos per square meter (kg.m-2) at the surface (GRIB variable documentation)
SurfaceDewPointTemperature Dew point temperature in Kelvins (K) at 2 meters above ground (GRIB variable documentation)
SurfaceDownwardShortWaveRadiationFluxAvg Average downward short wave radiation flux in Watts per square meter (W.m-2) at the surface (GRIB variable documentation)
SurfaceRelativeHumidity Relative humidity in percents (%) at 2 meters above ground (GRIB variable documentation)
SurfaceSpecificHumidity Specific humidity in kilos per kilo (kg.kg-1) at 2 meters above ground (GRIB variable documentation)
SurfaceTotalCloudCover Total cloud cover in percents (%) at the surface (GRIB variable documentation)
SurfaceWindDirection Direction from which the wind blows in degrees true (°) at 10 meters above ground (GRIB variable documentation)
SurfaceWindSpeed Wind speed in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
SurfaceWindSpeedGust Wind speed (gust) in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
SurfaceWindU U-component of wind in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
SurfaceWindUGust U-component of wind speed (gust) in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
SurfaceWindV V-component of wind in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
SurfaceWindVGust V-component of wind speed (gust) in meters per second (m.s-1) at 10 meters above ground (GRIB variable documentation)
Temperature2m Temperature in Kelvin (K) at 2 meters above ground (GRIB variable documentation)
TotalPrecipitationRateAcc Accumulated (since reference time) total precipitation rate at the surface in kilos per square meter per second (kg.m-2.s-1) (GRIB variable documentation)
WindDirection_Height Direction from which the wind blows in degrees true (°) at different heights (GRIB variable documentation)
WindSpeed_height Wind speed in meters per second (m.s-1) at different heights (GRIB variable documentation)
WindU_Height U-component of wind in meters per second (m.s-1) at different heights (GRIB variable documentation)
WindV_Height V-component of wind in meters per second (m.s-1) at different heights (GRIB variable documentation)

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from Temperature2m
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from SurfaceWindSpeed
WindDirection Wind direction at 10m in degrees (°) derived from SurfaceWindDirection
WindSpeed:100 Wind speed at 100m in meters per second (m.s-1) derived from WindSpeed_height
WindDirection:100 Wind direction at 100m in degrees (°) derived from WindDirection_height
CloudCover Cloud cover fraction (0-1) derived from SurfaceTotalCloudCover
RelativeHumidity Relative humidity at 2m in percents (%) derived from SurfaceRelativeHumidity
PressureReducedMSL Pressure at mean sea level in Pascals (Pa) derived from PressureMSL
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from SurfaceDownwardShortWaveRadiationFluxAvg
TotalPrecipitation Surface total precipitation (kg.m-2) derived from TotalPrecipitationRateAcc

Dimensions

Name Description
lv_HTGL0 Height in meters in the ensemble {20, 35, 50, 75, 100, 150, 200, 250, 375, 500, 625, 750, 875, 1000, 1125, 1250, 1375, 1500, 1750, 2000, 2250, 2500, 2750, 3000}
latitude 20.0°N to 72.0°N with a resolution of ~0.1°
longitude -32.0°E to 42.0°E with a resolution of ~0.1°

ERA5 (ECMWF), identifier: ECMWF_ERA5

Example call for ECMWF_ERA5:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_ERA5',
    'start-date': '2021-02-01',
    'end-date': '2021-02-05',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 't2m, msl'
}
response = requests.get(url, headers=headers, params=params)

ERA5 (ECMWF ReAnalysis 5) is the fifth generation atmospheric reanalysis of the global climate provided by ECMWF (documentation). Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics.

Variables

Name Description
msl Air pressure at mean sea level in Pascals (Pa) (GRIB variable documentation)
t2m Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
mx2t Maximum temperature since previous post-processing in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
mn2t Minimum temperature since previous post-processing in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
d2m Dew point temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
u100 U-component of wind in meters per second (m.s-1) at 100 meters above the surface (GRIB variable documentation)
u10 U-component of wind in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
ssrd Surface solar radiation downwards in Joules per square meter (J.m-2) (GRIB variable documentation)
sd Snow depth at the surface in meters of water equivalent (GRIB variable documentation)
v100 V-component of wind in meters per second (m.s-1) at 100 meters above the surface (GRIB variable documentation)
v10 V-component of wind in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
tp Total precipitation in meters (GRIB variable documentation)
rsn Snow density in kilograms per cubic meter (kg.m-3) (GRIB variable documentation)
sp Air pressure in Pascals (Pa) at the surface (GRIB variable documentation)
tcc Total cloud cover in fraction (0-1) (GRIB variable documentation)
hcc High cloud cover in fraction (0-1) (GRIB variable documentation)
mcc Medium cloud cover in fraction (0-1) (GRIB variable documentation)
lcc Low cloud cover in fraction (0-1) (GRIB variable documentation)
ssr Surface net solar radiation in Joules per square meter (J.m-2) (GRIB variable documentation)
lspf Large-scale precipitation fraction in seconds (s) (GRIB variable documentation)
i10fg Instantaneous 10 metres wind gust in meters per second (m.s-1) (GRIB variable documentation)

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from u10 and v10
WindDirection Wind direction at 10m in degrees (°) derived from u10 and v10
WindSpeed:100 Wind speed at 100m in meters per second (m.s-1) derived from u100 and v100
WindDirection:100 Wind direction at 100m in degrees (°) derived from u100 and v100
CloudCover Cloud cover fraction (0-1) derived from tcc
RelativeHumidity Relative humidity at 2m in percents (%) derived from t2m and d2m
PressureReducedMSL Pressure at mean sea level pressure in Pascals (Pa) derived from msl
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from ssr
TotalPrecipitation Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90.0°N to 90.0°N of ~0.25°
longitude 0.0°E to 359.75°E with a resolution of ~0.25°

ERA5-land (ECMWF), identifier: ECMWF_ERA5-land

Example call for ECMWF_ERA5-land:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_ERA5-land',
    'start-date': '2021-02-01',
    'end-date': '2021-02-05',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'Temperature, SolarDownwardRadiation'
}
response = requests.get(url, headers=headers, params=params)

ERA5-land (ECMWF ReAnalysis 5 land) is the fifth generation atmospheric reanalysis of the global climate provided by ECMWF (documentation). Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics.

Variables

Name Description
t2m Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
d2m Dew point temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation
u10 U-component of wind in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
v10 V-component of wind in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
ssrd Surface solar radiation downwards in Joules per square meter (J.m-2) (GRIB variable documentation)
tp Total precipitation in meters (GRIB variable documentation)
sp Air pressure in Pascals (Pa) at the surface (GRIB variable documentation)
ssr Surface net solar radiation in Joules per square meter (J.m-2) (GRIB variable documentation)
ssrd Surface solar radiation downwards in Joules per square meter (J.m-2) ([GRIB variable documentation](https://apps.ecmwf.int/

codes/grib/param-db/?id=169) sro | Surface runoff (m) (GRIB variable documentation

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from u10 and v10
WindDirection Wind direction at 10m in degrees (°) derived from u10 and v10
RelativeHumidity Relative humidity at 2m in percents (%) derived from t2m and d2m
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from ssr
TotalPrecipitation Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90.0°N to 90.0°N of ~0.125°
longitude 0.0°E to 359.75°E with a resolution of ~0.125°

MESAN (SMHI), identifier: SMHI_MESAN

Example call for SMHI_MESAN:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'SMHI_MESAN',
    'start-date': '2019-02-01',
    'end-date': '2019-02-10',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05',
    'variables': 'Temperature, WindSpeed, asngrd'
}
response = requests.get(url, headers=headers, params=params)

MESAN is a meteorological reanalysis model provided by SMHI that describes the current weather conditions in grid tiles (documentation). The model also serves as a complement to observations as the number of measuring stations is limited.

Variables

Name Description
asngrd Wind gusts in meters per second (m.s-1) at the surface
bldgrd Type of precipitation in codes ({-9.; 1.})
c_sigfr Fraction of significant clouds (0-1)
grd2t 3 hours precipitation in millimeters (mm)
hcc High cloud cover in fraction (0-1)
lcc Low cloud cover in fraction (0-1)
mcc Medium cloud cover in fraction (0-1)
mn2t24grd Relative humidity in percents (%) at the surface
p71.129 Total cloud cover in fraction (0-1)
p78.129 Cloud base of significant clouds in meters (m)
p79.129 Cloud top of significant clouds at the surface in meters (m)
rsngrd U-component of wind in meters per second (m.s-1) at the surface
sfgrd Snowfall (convective and stratiform) gradient in meters (m) of water equivalent
sshfgrd Sort of precipitation in codes ([1,6])
sstkgrd V-component of wind in meters per second (m.s-1) at the surface
strdgrd 1 hour fresh snow cover in centimeters (cm)
strfgrd Pressure reduced to mean sea level in Pascals (Pa)
udvwgrd Temperature in Kelvins (K) at the surface
ugrd10 1 hour precipitation in millimeters (mm)
vdvwgrd Wet bulb temperature in Kelvins (K)
vis Visibility in meters (m) at the surface

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from udvwgrd
WindSpeed Wind speed at 10m in meters per second (m.s-1) derived from rsngrd and sstkgrd
WindDirection Wind direction at 10m in degrees (°) derived from rsngrd and sstkgrd
CloudCover Cloud cover fraction (0-1) derived from p71.129
RelativeHumidity Relative humidity at 2m in percents (%) derived from mn2t24grd
PressureReducedMSL Pressure at mean sea level pressure in Pascals (Pa) derived from strfgrd
TotalPrecipitation Surface total precipitation (kg.m-2) derived from ugrd10

Dimensions

Name Description
latitude -90.0°N to 90.0°N of ~0.25°
longitude 0.0°E to 359.75°E with a resolution of ~0.25°

EPS-CF-HIST (ECMWF), identifier: ECMWF_EPS-CF

Example call for ECMWF_EPS-CF:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_EPS-CF',
    'start-date': '2021-02-01',
    'end-date': '2021-02-05',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'i10fg, t2m, WindSpeed:100'
}
response = requests.get(url, headers=headers, params=params)

Control forecast of the ECMWF's medium-range ensemble atmospheric model (documentation).

Variables

Name Availability Description
u10 Hist U-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
v10 Hist V-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
u100 Hist U-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
v100 Hist V-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
u200 Hist U-component of wind in meters per second (m.s-2) at 200 meters above the surface (GRIB variable documentation)
v200 Hist V-component of wind in meters per second (m.s-2) at 200 meters above the surface (GRIB variable documentation)
i10fg Hist Instantaneous wind gusts in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
t2m Hist Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
d2m Hist Dewpoint temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
tav300 Hist Average potential temperature in degrees Celsius (°C) in the upper 300m (GRIB variable documentation)
msl Hist Mean sea level pressure in Pascals (Pa) (GRIB variable documentation)
tcc Hist Total cloud cover in proportion (0-1) (GRIB variable documentation)
lcc Hist Low cloud cover in proportion (0-1) (GRIB variable documentation)
mcc Hist Medium cloud cover in proportion (0-1) (GRIB variable documentation)
hcc Hist High cloud cover in proportion (0-1) (GRIB variable documentation)
dsrp Hist Direct solar radiation in Joules per square meter (J.m-2) (GRIB variable documentation)
uvb Hist Downward UV radiation in Joules per square meter (J.m-2) at the surface (GRIB variable documentation)
tp Hist Total precipitation in meters (m) (GRIB variable documentation)
ilspf Hist Instantaneous large-scale surface precipitation fraction (GRIB variable documentation)

Post-processed variables

Name Availability Description
Temperature Hist Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Hist Wind speed at 10m in meters per second (m.s-1) derived from u10 and v10
WindDirection Hist Wind direction at 10m in degrees (°) derived from u10 and v10
WindSpeed:100 Hist Wind speed at 100m in meters per second (m.s-1) derived from u100 and v100
WindDirection:100 Hist Wind direction at 100m in degrees (°) derived from u100 and v100
CloudCover Hist Cloud cover fraction (0-1) derived from tcc
RelativeHumidity Hist Relative humidity at 2m in percents (%) derived from t2m and d2m
PressureReducedMSL Hist Pressure at mean sea level pressure in Pascals (Pa) derived from msl
SolarDownwardRadiation Hist Surface solar radiation in Watts per square meter (W.m-2) derived from dsrp
TotalPrecipitation Hist Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90°N to 90°N with a resolution of 0.1°
longitude 0°E to 360°E with a resolution of 0.1°

HRES, historical (ECMWF), identifier: ECMWF_HRES

Example call for ECMWF_HRES, historical forecasts:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/point/historical"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_HRES',
    'forecast-horizon': 'full',
    'reference-time-freq': '12H',
    'start-date': '2023-08-01',
    'end-date': '2023-08-04',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed:10, Temperature'
}
response = requests.get(url, headers=headers, params=params)

ECMWF's high resolution 10-day forecast model (documentation).

Variables

The latest forecast is only accessible if you have an additional agreement with us. All the variables below are available historically, but only those marked as latest are available for the latest forecast.

Name Availability Description
u10 Hist + Oper U-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
v10 Hist + Oper V-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
u100 Hist + Oper U-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
v100 Hist + Oper V-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
u200 Hist U-component of wind in meters per second (m.s-2) at 200 meters above the surface (GRIB variable documentation)
v200 Hist V-component of wind in meters per second (m.s-2) at 200 meters above the surface (GRIB variable documentation)
i10fg Hist + Oper Instantaneous wind gusts in meters per second (m.s-1) at 10 meters above the surface (GRIB variable documentation)
t2m Hist + Oper Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
d2m Hist + Oper Dewpoint temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
tav300 Hist Average potential temperature in degrees Celsius (°C) in the upper 300m (GRIB variable documentation)
msl Hist + Oper Mean sea level pressure in Pascals (Pa) (GRIB variable documentation)
tcc Hist + Oper Total cloud cover in proportion (0-1) (GRIB variable documentation)
lcc Hist Low cloud cover in proportion (0-1) (GRIB variable documentation)
mcc Hist Medium cloud cover in proportion (0-1) (GRIB variable documentation)
hcc Hist High cloud cover in proportion (0-1) (GRIB variable documentation)
dsrp Hist + Oper Direct solar radiation in Joules per square meter (J.m-2) (GRIB variable documentation)
ssrd Hist + Oper Surface solar radiation downwards in Joules per square meter (J.m-2) (GRIB variable documentation)
uvb Hist Downward UV radiation in Joules per square meter (J.m-2) at the surface (GRIB variable documentation)
tp Hist + Oper Total precipitation in meters (m) (GRIB variable documentation)
ilspf Hist Instantaneous large-scale surface precipitation fraction (GRIB variable documentation)

Post-processed variables

Name Availability Description
Temperature Hist + Oper Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Hist + Oper Wind speed at 10m in meters per second (m.s-1) derived from u10 and v10
WindDirection Hist + Oper Wind direction at 10m in degrees (°) derived from u10 and v10
WindSpeed:100 Hist + Oper Wind speed at 100m in meters per second (m.s-1) derived from u100 and v100
WindDirection:100 Hist + Oper Wind direction at 100m in degrees (°) derived from u100 and v100
CloudCover Hist + Oper Cloud cover fraction (0-1) derived from tcc
RelativeHumidity Hist + Oper Relative humidity at 2m in percents (%) derived from t2m and d2m
PressureReducedMSL Hist + Oper Pressure at mean sea level pressure in Pascals (Pa) derived from msl
SolarDownwardRadiation Hist + Oper Surface solar radiation in Watts per square meter (W.m-2) derived from ssrd
TotalPrecipitation Hist + Oper Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90°N to 90°N with a resolution of 0.1°
longitude 0°E to 360°E with a resolution of 0.1°

HRES-Oper (ECMWF), identifier: ECMWF_HRES_OPERATIONAL

Example call for ECMWF_HRES_OPERATIONAL, latest forecasts:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/point/operational"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_HRES_OPERATIONAL',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed:10, Temperature'
}
response = requests.get(url, headers=headers, params=params)

Example call for ECMWF_HRES_OPERATIONAL, historical forecasts:

import requests

url = "https://api.rebase.energy/weather/v2/point/historical"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_HRES_OPERATIONAL',
    'forecast-horizon': 'full',
    'reference-time-freq': '12H',
    'start-date': '2023-08-01',
    'end-date': '2023-08-04',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed:10, Temperature'
}
response = requests.get(url, headers=headers, params=params)

ECMWF's high resolution 10-day forecast model, operational (documentation).

Variables

The latest forecast is only accessible if you have an additional agreement with us.

Name Availability Description
u10 Oper U-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
v10 Oper V-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
u100 Oper U-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
v100 Oper V-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
t2m Oper Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
d2m Oper Dewpoint temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
msl Oper Mean sea level pressure in Pascals (Pa) (GRIB variable documentation)
tcc Oper Total cloud cover in proportion (0-1) (GRIB variable documentation)
dsrp Oper Direct solar radiation in Joules per square meter (J.m-2) (GRIB variable documentation)
ssrd Oper Surface solar radiation downwards in Joules per square meter (J.m-2) (GRIB variable documentation)

Post-processed variables

Name Availability Description
Temperature Hist + Oper Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Hist + Oper Wind speed at 10m in meters per second (m.s-1) derived from u10 and v10
WindDirection Hist + Oper Wind direction at 10m in degrees (°) derived from u10 and v10
WindSpeed:100 Hist + Oper Wind speed at 100m in meters per second (m.s-1) derived from u100 and v100
WindDirection:100 Hist + Oper Wind direction at 100m in degrees (°) derived from u100 and v100
CloudCover Hist + Oper Cloud cover fraction (0-1) derived from tcc
RelativeHumidity Hist + Oper Relative humidity at 2m in percents (%) derived from t2m and d2m
PressureReducedMSL Hist + Oper Pressure at mean sea level pressure in Pascals (Pa) derived from msl
SolarDownwardRadiation Hist + Oper Surface solar radiation in Watts per square meter (W.m-2) derived from ssrd
TotalPrecipitation Hist + Oper Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90°N to 90°N with a resolution of 0.1°
longitude 0°E to 360°E with a resolution of 0.1°

HRES-Mix (ECMWF), identifier: ECMWF_HRES_MIX

The ECMWF_HRES_MIX is a blend between the ECMWF_HRES historical and ECMWF_HRES_OPERATIONAL models and returns all ECMWF high resolution model runs up to date. The points coordinates have to be registered via the dashboard.

Example call for ECMWF_HRES_MIX, latest forecasts:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/point/operational"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_HRES_MIX',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed:10, Temperature'
}
response = requests.get(url, headers=headers, params=params)

Example call for ECMWF_HRES_MIX, historical forecasts:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/point/historical"
headers = {"Authorization": your_api_key}
params = {
    'model': 'ECMWF_HRES_MIX',
    'forecast-horizon': 'full',
    'reference-time-freq': '12H',
    'start-date': '2023-08-01',
    'end-date': '2023-08-04',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed:10, Temperature'
}
response = requests.get(url, headers=headers, params=params)

ECMWF's high resolution 10-day forecast model (documentation).

Variables

The latest forecast is only accessible if you have an additional agreement with us. All the variables below are available historically, but only those marked as latest are available for the latest forecast.

Name Availability Description
u10 Hist + Oper U-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
v10 Hist + Oper V-component of wind in meters per second (m.s-2) at 10 meters above the surface (GRIB variable documentation)
u100 Hist + Oper U-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
v100 Hist + Oper V-component of wind in meters per second (m.s-2) at 100 meters above the surface (GRIB variable documentation)
t2m Hist + Oper Temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
d2m Hist + Oper Dewpoint temperature in Kelvins (K) at 2 meters above the surface (GRIB variable documentation)
msl Hist + Oper Mean sea level pressure in Pascals (Pa) (GRIB variable documentation)
tcc Hist + Oper Total cloud cover in proportion (0-1) (GRIB variable documentation)
dsrp Hist + Oper Direct solar radiation in Joules per square meter (J.m-2) (GRIB variable documentation)
ssrd Hist + Oper Surface solar radiation downwards in Joules per square meter (J.m-2) (GRIB variable documentation)

Post-processed variables

Name Availability Description
Temperature Hist + Oper Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Hist + Oper Wind speed at 10m in meters per second (m.s-1) derived from u10 and v10
WindDirection Hist + Oper Wind direction at 10m in degrees (°) derived from u10 and v10
WindSpeed:100 Hist + Oper Wind speed at 100m in meters per second (m.s-1) derived from u100 and v100
WindDirection:100 Hist + Oper Wind direction at 100m in degrees (°) derived from u100 and v100
CloudCover Hist + Oper Cloud cover fraction (0-1) derived from tcc
RelativeHumidity Hist + Oper Relative humidity at 2m in percents (%) derived from t2m and d2m
PressureReducedMSL Hist + Oper Pressure at mean sea level pressure in Pascals (Pa) derived from msl
SolarDownwardRadiation Hist + Oper Surface solar radiation in Watts per square meter (W.m-2) derived from ssrd
TotalPrecipitation Hist + Oper Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90°N to 90°N with a resolution of 0.1°
longitude 0°E to 360°E with a resolution of 0.1°

GlobalHiRes (MetOffice), identifier: MetOffice_GlobalHiRes

Example call for MetOffice_GlobalHiRes:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'MetOffice_GlobalHiRes',
    'start-date': '2023-08-01',
    'end-date': '2023-08-05',
    'reference-time-freq': '6H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'SolarDownwardRadiation, Temperature'
}
response = requests.get(url, headers=headers, params=params)

Global configuration of UK MetOffice's Unified Model (documentation).

Variables

Name Description
cc Total cloud cover in fraction (0-1) (GRIB variable documentation)
vis Visibility in meters (m) at 1.5 meters above the ground (GRIB variable documentation)
r2 Relative humidity in percents (%) at 2 meters above the ground(GRIB variable documentation)
prmsl Pressure in Pascals (Pa) at mean sea level (GRIB variable documentation)
tprate Total precipitation rate in kilos per square meter per second (kg.m-2.s-1) (GRIB variable documentation)
sd Snow depth water equivalent in kilos per square meter (kg.m-2) (GRIB variable documentation)
difswrf Diffuse shortwave radiation flux in Watts per square meter (W.m-2) (GRIB variable documentation)
dirswrf Direct shortwave radiation flux in Watts per square meter (W.m-2) (GRIB variable documentation)
t2m Temperature in Kelvins (K) at 1.5 meters above the ground (GRIB variable documentation)
ws Wind speed in meters per second (m.s-1) at different heights (GRIB variable documentation)
wdir Direction from which the wind blows in degrees true (°) at different heights (GRIB variable documentation)
gust Wind speed (gust) in meters per second (m.s-1) (GRIB variable documentation).
lcc Low cloud cover in percentage (0-100), available between 2020-10-14 to 2021-09-01 and 2023-08-02 to present (GRIB variable documentation)
hcc High cloud cover in percentage (0-100), available between 2020-10-14 to 2021-09-01 and 2023-08-02 to present (GRIB variable documentation)
mcc Medium cloud cover in percentage (0-100), available between 2020-10-14 to 2021-09-01 and 2023-08-02 to present (GRIB variable documentation)

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C) derived from t2m
WindSpeed Wind speed at 10m in meters per second (m.s-1) same as ws:10
WindDirection Wind direction at 10m in degrees (°) same as wdir:10
WindSpeed:100 Wind speed at 100m in meters per second (m.s-1) same as ws:100
WindDirection:100 Wind direction at 100m in degrees (°) same as wdir:100
CloudCover Cloud cover fraction (0-1) same as tcc
RelativeHumidity Relative humidity at 2m in percents (%) same as r2
PressureReducedMSL Pressure at mean sea level pressure in Pascals (Pa) same as prmsl
SolarDownwardRadiation Surface solar radiation in Watts per square meter (W.m-2) derived from dirswrf and difswrf
TotalPrecipitation Surface total precipitation (kg.m-2) derived from tp

Dimensions

Name Description
latitude -90°N to 90°N with a resolution of ~0.09°
longitude -180°E to 180°E with a resolution of ~0.14°
heightAboveGround Height above the grounds in meters in the ensemble {10; 100}

Rebase_AI (Graphcast based), identifier: Rebase_AI

Example call for Rebase_AI:

import requests

your_api_key = '' # insert your API key here
url = "https://api.rebase.energy/weather/v2/query"
headers = {"Authorization": your_api_key}
params = {
    'model': 'Rebase_AI',
    'start-date': '2023-01-01',
    'end-date': '2023-01-05',
    'reference-time-freq': '24H',
    'forecast-horizon': 'full',
    'latitude': '60.1, 61.2, 59.33', 
    'longitude': '17.2, 13.1, 18.05', 
    'variables': 'WindSpeed, Temperature'
}
response = requests.get(url, headers=headers, params=params)

Rebase AI configuration for Google DeepMind's Graphcast deep neural network learning model (documentation).

Post-processed variables

Name Description
Temperature Temperature at 2m in degrees Celsius (°C)
WindSpeed Wind speed at 10m in meters per second (m.s-1)
WindDirection Wind direction at 10m in degrees (°)
RelativeHumidity Relative humidity at 2m in percents (%)
PressureReducedMSL Pressure at mean sea level pressure in Pascals (Pa)
TotalPrecipitation Surface total precipitation (kg.m-2)

Dimensions

Name Description
latitude -90°N to 90°N with a resolution of 0.25°
longitude -180°E to 180°E with a resolution of 0.25°

Policies

By using the Weather API, you agree to our terms of service. Please take a moment to review the terms.

Rebase Energy reserves the right to suspend or terminate accounts that violate our policies.

Errors

The Weather API uses the following error codes:

Error Code Meaning
400 Bad Request -- Your request is invalid.
401 Unauthorized -- Your API key is invalid.
403 Forbidden -- You do not have sufficient rights to access this data.
404 Not Found -- The specified data could not be found.
405 Method Not Allowed -- You tried to access a dataset with an invalid method.
406 Not Acceptable -- You requested a format that is not json.
410 Gone -- The dataset requested has been removed from our servers.
418 I'm a teapot. 🙃
429 Too Many Requests -- You're exceeding our rate policies
500 Internal Server Error -- We had a problem with our server. Please try again later.
503 Service Unavailable -- The service is not available at the moment. Please try again later.