Climate Risk Navigator for Growing Conditions
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The Climate Risk Navigator for Growing Conditions application helps users monitor growing conditions year round, so that they can better identify risks, ensure supply, and prepare for adverse climate impacts that might impact crop projections. This application, which updates daily, provides 46 different crop layers so users can compare current figures with historical analogs and prior seasons on a district (county) level. 

The app’s crop-weighted, growing conditions indicators include: 

  • Normalized Difference Vegetation Index (NDVI)
  • Daily Soil Moisture
  • Monthly Evapotranspiration Anomaly
  • Daily Potential Evapotranspiration

Customers Use the Tool to

  • Monitor supplies of a variety of agricultural products
  • Track food inflation
  • Project potential price fluctuations for crops based on planted-area weightings
  • Identify major climate and weather risks by crop

Why It Matters

The Climate Risk Navigator can help users prepare for adverse weather and climate conditions, and because the data is crop-weighted, users can compare current conditions with past seasons. Users can also monitor how changing climate variables are impacting the growing conditions for specific crops.


The Climate Risk Navigator for Growing Conditions takes a data series and calculates a weighted average for each day in that data series at a district level using district-level weightings.

For example, using a temperature data series for two districts over five days, as shown here:  District A=[10, 15, 10, 20, 10] and District B= [20, 30, 10, 20, 30]. We then apply a weighting series number for each district. 

Let's say we own 30 ice cream shops in District A and 70 ice cream shops in District B. Our weighting series would look like weights=[30, 70]

Now, to produce our ice cream store-weighted output series, we use our weights to calculate a weighted average for each day in the series: 

On the first day, it was 10 degrees in District A and 20 degrees in District B

Thus our ice cream shop-weighted temperature on the first day is:



We repeat the formula above for each day to obtain weighted series=[17, 25.5, 10, 20, 24]

The above example shows, at a basic level, how we produce all of our weighted averages. To measure the impact of conditions on yield, the Growing Conditions application uses this same method and applies it to 46 different crops globally. 

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