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General forecast JSON format

tags: reference

This JSON format is meant for encoding meteorological and oceanographic forecast timeseries data for a specific geographical point on earth.

This documentation has two parts. The first part describes the structure of the JSON format. The second part describes how this format is used in our services to represent forecast data.

Format

The format has three main parts:

Here is an excerpt of a forecast response:

{
  "type": "Feature",
  "geometry": {
    "type": "Point",
    "coordinates": [
      10,
      60.1,
      267
    ]
  },
  "properties": {
    "meta": {
      "updated_at": "2020-06-10T13:04:26Z",
      "units": {
        "air_pressure_at_sea_level": "hPa",
        "air_temperature": "celsius",
        "air_temperature_max": "celsius",
        "air_temperature_min": "celsius",
        "cloud_area_fraction": "%",
        "cloud_area_fraction_high": "%",
        "cloud_area_fraction_low": "%",
        "cloud_area_fraction_medium": "%",
        "dew_point_temperature": "celsius",
        "fog_area_fraction": "%",
        "precipitation_amount": "mm",
        "precipitation_amount_max": "mm",
        "precipitation_amount_min": "mm",
        "probability_of_precipitation": "%",
        "probability_of_thunder": "%",
        "relative_humidity": "%",
        "ultraviolet_index_clear_sky": "1",
        "wind_from_direction": "degrees",
        "wind_speed": "m/s",
        "wind_speed_of_gust": "m/s"
      }
    },
    "timeseries": [
      {
        "time": "2020-06-10T13:00:00Z",
        "data": {
          "instant": {
            "details": {
              "air_pressure_at_sea_level": 1020.5,
              "air_temperature": 20.7,
              "cloud_area_fraction": 58.0,
              "cloud_area_fraction_high": 47.7,
              "cloud_area_fraction_low": 17.7,
              "cloud_area_fraction_medium": 1.7,
              "dew_point_temperature": 9.5,
              "fog_area_fraction": 0.0,
              "relative_humidity": 48.6,
              "ultraviolet_index_clear_sky": 4.7,
              "wind_from_direction": 151.8,
              "wind_speed": 2.5,
              "wind_speed_of_gust": 6.6
            }
          },
          "next_12_hours": {
            "summary": {
              "symbol_code": "partlycloudy_day"
            },
            "details": {
              "probability_of_precipitation": 2.2
            }
          },
          "next_1_hours": {
            "summary": {
              "symbol_code": "partlycloudy_day"
            },
            "details": {
              "precipitation_amount": 0.0,
              "precipitation_amount_max": 0.0,
              "precipitation_amount_min": 0.0,
              "probability_of_precipitation": 0.0,
              "probability_of_thunder": 0.0
            }
          },
          "next_6_hours": {
            "summary": {
              "symbol_code": "partlycloudy_day"
            },
            "details": {
              "air_temperature_max": 20.7,
              "air_temperature_min": 18.4,
              "precipitation_amount": 0.0,
              "precipitation_amount_max": 0.0,
              "precipitation_amount_min": 0.0,
              "probability_of_precipitation": 1.1
            }
          }
        }
      },
    [..]

You can get a complete forecast response using the /complete method, e.g.

https://api.met.no/weatherapi/locationforecast/2.0/complete?lat=60.10&lon=10

Geographical description

"type": "Feature",
"geometry": {
  "type": "Point",
  "coordinates": [
    10,
    60.1,
    267
  ]
},

We use the GeoJSON standard to structure our format, see our documentation for more details.

All forecast data are listed under the GeoJSON attribute called properties.

Forecast metadata

"meta": {
  "updated_at": "2020-06-10T13:04:26Z",
  "units": {
    "air_pressure_at_sea_level": "hPa",
    "air_temperature": "celsius",
     "air_temperature_max": "celsius",
    "air_temperature_min": "celsius",
    "cloud_area_fraction": "%",
    "cloud_area_fraction_high": "%",
    "cloud_area_fraction_low": "%",
    "cloud_area_fraction_medium": "%",
    "dew_point_temperature": "celsius",
    "fog_area_fraction": "%",
    "precipitation_amount": "mm",
    "precipitation_amount_max": "mm",
    "precipitation_amount_min": "mm",
    "probability_of_precipitation": "%",
    "probability_of_thunder": "%",
    "relative_humidity": "%",
    "ultraviolet_index_clear_sky": "1",
    "wind_from_direction": "degrees",
    "wind_speed": "m/s",
    "wind_speed_of_gust": "m/s"
  }
},

Currently we have only two pieces of metadata in our forecast data.

The first bit is updated_at. This specifies the most recent time when we updated the forecast data.

The second piece of metadata is units. The unit of all forecast parameters listed in the forecast data are listed in this block. The units are listed in each forecast document, but the unit for e.g air_temperature will be same for all locations. We will notify you about any change in unit values for a parameter.

Forecast timeseries

The forecast timeseries is structured as an array of forecast objects. The array is always sorted with increasing time.

The time resolution for a timeseries can vary. E.g the first half of a timeseries can have time values with one hour intervals, while the last half of the timeseries can have time values with six hour intervals.

Each forecast object contains a time attribute and a number of forecast parameters for that time. We have two main types of forecast parameters:

Parameters for a time instant

These parameters are found under the instant object. These parameters, e.g air_temperature has a value that describes the state at that exact time instant.

Parameters for a time period

These parameters are found under a number of objects: next_1_hours, next_6_hours, next_12_hours. These parameters, e.g precipitation_amount describe a period of time. E.g precipitation_amount under the object next_1_hours describe the amount of forecasted precipitation for the period time + 1 hour.

The parameters under the object summary describes the weather situation based on many of the other parameters. E.g symbol_code will describe the weather situation for period of time, and includes information about clouds, precipitation and more. It is also used as the basename of the weathericon filename, by appending the desired extension (.png, .svg or similar).

Please note that there will typically be multiple period objects for any given time value, e.g one forecast object can have next_1_hours, next_6_hours and next_12_hours. There will never be a period object with shorter period than the current time resolution in the timeseries. So, if its 6 hours until the next time value, the current forecast object will NOT have a next_1_hours period object.

—Håvard Futseter, 3 May 2020