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Chainlink Google weather Composite Adapter

An adapter used to query weather data from Google BigQuery. The adapter allows you to fetch the AVG, SUM, MIN or MAX of selected column in the noaa_gsod weather database in Google BigQuery within a given date range.

Configuration

This adapter takes the configuration variables from the Google BigQuery adapter.

In addition, it takes the following environment variables:

Required? Name Description Options Defaults to
DATASET Which BigQuery dataset to query bigquery-public-data.noaa_gsod

Running

See the Composite Adapter README for more information on how to get started.

Example run

To run the adapter locally, assuming you have set up default credentials with the gcloud CLI tool:

cd packages/composites/google-weather
yarn && yarn build
env PROJECT_ID=gcp-pdp-weather-dev yarn start

Input Params

Required? Name Description Options Defaults to
✅ geoJson A GeoJSON object containing the geographies to query
✅ dateFrom The date to query data from (inclusive) in ISO 8601 format
✅ dateTo The date to query data to (inclusive) in ISO 8601 format
✅ method Which method to use to aggregate data in AVG, SUM, MIN, MAX
✅ column Which column to fetch data from Data available
units What unit system to return the result in (conversions) imperial, metric imperial

GeoJSON data

This adapter uses GeoJSON to determine the station location in the query. An entire, valid, GeoJSON object must be included in the request, however the adapter will only support feature types Polygon and Point. A request must include at least one feature, but can support multiple features, even of different types. Generating a GeoJSON object can easily be done without prior knowledge using https://geojson.io/.

Polygon

Providing a Polygon will include observations from all stations located within the Polygon coordinates. If there are no stations with data within the coordinates, no data will be returned.

The query will fetch all stations within the Polygon, regardless if the stations are active or not. This means it could fetch observations from stations which are not active for the entire duration of the time range.

Point

Providing a Point will include observations from the station located geographically closest to the Point coordinates that was active during the entire duration of the time range.

Data available

Mean

Mean columns report the mean of that type on the specified day.

  • temp - Mean temperature for the day in degrees Fahrenheit to tenths
  • dewp - Mean dew point for the day in degrees Fahrenheit to tenths
  • slp - Mean sea level pressure for the day in millibars to tenths
  • stp - Mean station pressure for the day in millibars to tenths
  • visib - Mean visibility for the day in miles to tenths
  • wdsp - Mean wind speed for the day in knots to tenths

Count

  • count_temp - Number of observations used in calculating mean temperature
  • count_dewp - Number of observations used in calculating mean dew point
  • count_slp - Number of observations used in calculating mean sea level pressure
  • count_stp - Number of observations used in calculating mean station pressure
  • count_visib - Number of observations used in calculating mean visibility
  • count_wdsp - Number of observations used in calculating mean wind speed

Extremes

  • max - Maximum temperature reported during the day in Fahrenheit to tenths--time of max temp report varies by country and region, so this will sometimes not be the max for the calendar day.
  • min - Minimum temperature reported during the day in Fahrenheit to tenths--time of min temp report varies by country and region, so this will sometimes not be the min for the calendar day.

Binary

Binary columns report if there was an occurrence of that type on the specified day.

  • fog
  • rain_drizzle
  • snow_ice_pellets
  • hail
  • thunder
  • tornado_funnel_cloud

Total

  • prcp - Total precipitation (rain and/or melted snow) reported during the day in inches and hundredths; will usually not end with the midnight observation--i.e., may include latter part of previous day.
  • sndp - Snow depth in inches to tenths--last report for the day if reported more than once.

Unit conversion

The adapter supports converting units from imperial to metric.

Imperial Metric
F C
bar hPa
inches mm
miles m
knots m/s

Examples

Average of daily average temperature in Bergen, Norway

To get the average daily mean temperature per day, we can get use all stations within a geographical area. For this reason we provide a Polygon in the GeoJSON object.

Input

{
  "id": "1",
  "data": {
    "geoJson": {
      "type": "FeatureCollection",
      "features": [
        {
          "type": "Feature",
          "properties": {},
          "geometry": {
            "type": "Polygon",
            "coordinates": [
              [
                [5.2796173095703125, 60.40673218057448],
                [5.164947509765625, 60.383665698324926],
                [5.17730712890625, 60.211509994185604],
                [5.401153564453124, 60.27694067255946],
                [5.6188201904296875, 60.436558668419984],
                [5.526123046875, 60.42842688461354],
                [5.3002166748046875, 60.5387098888639],
                [5.238418579101562, 60.4951151199491],
                [5.2796173095703125, 60.40673218057448]
              ]
            ]
          }
        }
      ]
    },
    "dateFrom": "2021-04-01",
    "dateTo": "2021-05-01",
    "method": "AVG",
    "column": "temp"
  }
}

Output

{
  "jobRunID": "1",
  "result": 41.52741935483871,
  "statusCode": 200,
  "data": {
    "result": 41.52741935483871
  }
}

This means that the average of daily mean temperature in our area and time range was 41.5 degrees fahrenheit.

Total rainfall in Bergen, Norway

To get the total rainfall, we must use a single station in order to not get duplicate data. For this reason we use a Point in the GeoJSON object.

Input

{
  "id": "1",
  "data": {
    "geoJson": {
      "type": "FeatureCollection",
      "features": [
        {
          "type": "Feature",
          "properties": {},
          "geometry": { "type": "Point", "coordinates": [5.325622558593749, 60.3887552979679] }
        }
      ]
    },
    "dateFrom": "2021-04-01",
    "dateTo": "2021-05-01",
    "method": "SUM",
    "column": "prcp"
  }
}

Output

{
  "jobRunID": "1",
  "result": 3.4300000000000006,
  "statusCode": 200,
  "data": {
    "result": 3.4300000000000006
  }
}

This means there was 3.43 inches of rain- or snowfall in the time range we had defined.

Occurrence of hail in Bergen, Norway

We are looking to know if there was hail in Bergen within a date range. We don't care about the exact number of days with hail, but we'd rather know if there was hail or not. What we're looking for is if the result is 0 or not 0. Because of this we can sum up the number of hail occurrences per day for a Polygon.

Input

{
  "id": "1",
  "data": {
    "geoJson": {
      "type": "FeatureCollection",
      "features": [
        {
          "type": "Feature",
          "properties": {},
          "geometry": {
            "type": "Polygon",
            "coordinates": [
              [
                [5.2796173095703125, 60.40673218057448],
                [5.164947509765625, 60.383665698324926],
                [5.17730712890625, 60.211509994185604],
                [5.401153564453124, 60.27694067255946],
                [5.6188201904296875, 60.436558668419984],
                [5.526123046875, 60.42842688461354],
                [5.3002166748046875, 60.5387098888639],
                [5.238418579101562, 60.4951151199491],
                [5.2796173095703125, 60.40673218057448]
              ]
            ]
          }
        }
      ]
    },
    "dateFrom": "2021-04-01",
    "dateTo": "2021-05-01",
    "method": "SUM",
    "column": "hail"
  }
}

Output

{
  "jobRunID": "1",
  "result": 2,
  "statusCode": 200,
  "data": {
    "result": 2
  }
}

Since the result is >0, it means there was at least one day with hail in our area.