Amazon Forecast is no longer available to new customers. Existing customers of Amazon Forecast can continue to use the service as normal. Learn more"

Weather Index

The Amazon Forecast Weather Index is a built-in featurization that incorporates historical and projected weather information into your model. It is especially useful for retail use cases, where temperature and precipitation can significantly affect product demand.

When the Weather Index is enabled, Forecast applies the weather featurization only to time series where it finds improvements in accuracy during predictor training. If supplementing a time series with weather information does not improve its predictive accuracy during backtesting, Forecast does not apply the Weather Index to that particular time series.

To apply the Weather Index, you must include a geolocation attribute in your target time series dataset and any related time series datasets. You also need to specify time zones for your target time-series timestamps. For more information regarding dataset requirements, see Conditions and Restrictions.

Enabling the Weather Index

The Weather Index is enabled during the predictor training stage. When using the CreateAutoPredictor operation, the Weather Index is included in the AdditionalDataset data type.

Before enabling the Weather Index, you must include a geolocation attribute in your target time series and related timeseries datasets, and define the time zones for your timestamps. For more information, see Adding Geolocation Information and Specifying Time Zones.

You can enable the Weather Index using the Forecast console or the Forecast Software Development Kit (SDK) .

Console

To enable the Weather Index

1. Sign in to the AWS Management Console and open the Amazon Forecast console at https://console.aws.amazon.com/forecast/.

2. From Dataset groups, choose your dataset group.

3. In the navigation pane, choose Predictors.

4. Choose Train new predictor.

5. Choose Enable Weather Index.

SDK

To enable the Weather Index

Using the CreateAutoPredictor operation, enable the Weather Index by adding "Name": "weather" and "Value": "true" in the AdditionalDataset data type.

    "DataConfig": { 
        ...
        "AdditionalDatasets": [
            ...                      
            {             
                "Name": "weather",       
            }      
            ]   
        },

Adding Geolocation Information to Datasets

To use the Weather Index, you must include a geolocation attribute for each item in your target time series and related time series datasets. The attribute is defined with the geolocation attribute type within the dataset schemas.

All geolocation values in a dataset must be exclusively within a single region. The regions are: US (excluding Hawaii and Alaska), Canada, South America, Central America, Asia Pacific, Europe, and Africa & Middle East.

Specify the geolocation attribute in one of two formats:

The Latitude & Longitude format is supported for all regions. The Postal code format is only supported for the US region.

Latitude & Longitude Bounds

The following are the latitudinal and longitudinal bounds for the accepted regions:

US Region

Bounds: latitude (24.6, 50.0), longitude (-126.0, -66.4).

Canada Region

Bounds: latitude (41.0, 75.0), longitude (-142.0, -52.0).

Europe Region

Bounds: latitude (34.8, 71.8), longitude (-12.6, 44.8).

South America Region

Bounds: latitude (-56.6, 14.0), longitude (-82.4, -33.00).

Asia Pacific Region

Bounds: latitude (-47.8, 55.0), longitude (67.0, 180.60).

Central America Region

Bounds: latitude (6.80, 33.20), longitude (-118.80, -58.20).

Africa & Middle East Region

Bounds: latitude (-35.60, 43.40), longitude (-18.80, -58.20).

Including Geolocation in the Dataset Schema

Using the console or CreateDataset operation, define the location attribute type as 'geolocation' within the JSON schema for the target time series and any related time series. The attributes in the schema must be ordered as they appear in the datasets.

 { 
  "Attributes":[
    {
       "AttributeName": "timestamp",
       "AttributeType": "timestamp"
    },
    {
       "AttributeName": "target_value",
       "AttributeType": "float"
    },
    {
       "AttributeName": "item_id",
       "AttributeType": "string"
    },
    {
       "AttributeName": "location",
       "AttributeType": "geolocation"
    }
  ]
}

Setting the Geolocation Format

The format of the geolocation attribute can be in the Postal Code or Latitude & Longitude format. You can set the geolocation format using the Forecast console or the Forecast Software Development Kit (SDK).

Console

To add a geolocation attribute to a time series dataset

1. Sign in to the AWS Management Console and open the Amazon Forecast console at https://console.aws.amazon.com/forecast/.

2. Choose Create dataset group.

3. In the Schema builder, set your geolocation Attribute type to geolocation.

4. In the Geolocation format drop-down, choose your location format.

You can also define your attributes in JSON format and select a location format from the Geolocation format drop-down.

SDK

To add a geolocation attribute to a time series dataset

Using the CreateDatasetImportJob operation, set the value of GeolocationFormat to one of the following:

• Latitude & longitude (All regions): "LAT_LONG"

• Postal code (US Only): "CC_POSTALCODE"

For example, to specify the latitude & longitude format, include the following in CreateDatasetImportJob request:

{
    ...
    "GeolocationFormat": "LAT_LONG"
}

Specifying Time Zones

You can either let Amazon Forecast automatically synchronize your time zone information with your geolocation attribute, or you can manually assign a single time zone to your entire dataset.

Automatically Sync Time Zones with Geolocation

This option is ideal for datasets that contain timestamps in multiple time zones, and those timestamps are expressed in local time. Forecast assigns a time zone for every item in the target time series dataset based on the item’s geolocation attribute.

You can automatically sync your timestamps with your geolocation attribute using the Forecast console or Forecast SDK.

Console

To sync time zones with the geolocation attribute

1. Sign in to the AWS Management Console and open the Amazon Forecast console at https://console.aws.amazon.com/forecast/.

2. In the navigation pane, choose Create dataset group.

3. In Dataset import details, choose Sync time zone with location.

SDK

To sync time zones with the geolocation attribute

Using the CreateDatasetImportJob operation, set "UseGeolocationForTimeZone" to "true".

{
    ...
    "UseGeolocationForTimeZone": "true"
}

Manually Select a Single Time Zone

This option is ideal for datasets with all timestamps within a single time zone, or if all timestamps are normalized to a single time zone. Using this option applies the same time zone to every item in the dataset.

The Weather Index accepts the following time zones:

US region

Canada region

Europe region

South America region

Asia Pacific region

Central America

Africa & Middle East

Other

Select a time zone from the Other list if items in your dataset are located within one of the accepted region, but your timestamps are standardized to a time zone outside of that region.

For a complete list of valid time zone names, see Joda-Time library.

You can manually set a time zone for your datasets using the Forecast console or Forecast SDK.

Console

To select a single time zone for your dataset

1. Sign in to the AWS Management Console and open the Amazon Forecast console at https://console.aws.amazon.com/forecast/.

2. In the navigation pane, choose Create dataset group.

3. In Dataset import details, choose Select time zone.

For example, use the following to apply Los Angeles time (Pacific Standard Time) to your datasets.

SDK

To select a single time zone for your dataset

Using the CreateDatasetImportJob operation, set "TimeZone" to a valid time zone.

For example, use the following to apply Los Angeles time (Pacific Standard Time) to your datasets.

{
    ...
    "TimeZone": "America/Los_Angeles"
}

Conditions and Restrictions

The following conditions and restrictions apply when using the Weather Index: