Retrieve NOAA heating/cooling degree day data for load forecasting

Steps

1. Access NOAA's Climate Data Online (CDO) API at ncei.noaa.gov/cdo-web/api/v2/ using a free token requested at ncei.noaa.gov/cdo-web/token; the CDO API provides access to NOAA's full archive of historical station-level climate data including daily HDD and CDD.
2. Query the GHCND (Global Historical Climatology Network - Daily) dataset for the target weather station using GET /data?datasetid=GHCND&stationid={stationid}&startdate={YYYY-MM-DD}&enddate={YYYY-MM-DD}&datatypeid=HDD,CDD&limit=1000; note that HDD and CDD in GHCND are computed relative to a 65°F (18.3°C) base temperature.
3. Identify the nearest suitable weather station using the /stations endpoint filtered by location (latitude/longitude bounding box or FIPS code) and datasetid=GHCND; select a station with long record completeness and minimal missing data for the load forecasting period.
4. For weekly and monthly aggregate degree day summaries and forecasts, supplement CDO data with NOAA's Climate Prediction Center (CPC) degree day products at cpc.ncep.noaa.gov/products/analysis_monitoring/cdus/degree_days/; these provide regional summaries and seasonal forecasts but without a JSON API.
5. For custom base temperatures (e.g., 60°F for a particular building type), derive HDD and CDD from hourly dry-bulb temperature data using the NOAA ISD (Integrated Surface Data) dataset, available from ncei.noaa.gov/products/land-based-station/integrated-surface-database.
6. Join degree day data to your load time series by date and station proximity; validate the degree day–load correlation before using in a forecasting model, as correlation degrades for highly insulated or process-dominated facilities.