For years, weather was the hardest variable for Richard Atkins to manage.

As a cherry and walnut grower with orchards in multiple locations, he relied—like many do—on TV forecasts. Neighboring orchards often got the same forecast, even though conditions could differ drastically.

“We have a place in Ripon and a place in Linden,” Richard explained. “Sometimes it’s raining in Linden and dry in Ripon. Or the winds are strong in one and much weaker in another.”

Yet the forecast treated both locations the same. Decisions were made, crews scheduled, sprays planned—and too often, the forecast didn’t hold.

“It was frustrating,” Richard said. “You’d make a call based on the forecast, and then reality would do something different.”

The cost of getting it wrong

Those mismatches weren’t just inconvenient. They were costly.

Just before cherry harvest one year, forecasts called for little to no rain. Based on that outlook, Richard chose not to apply a protective spray that helps prevent cherries from cracking in rain.

Then the storm hit.

A sudden downpour cracked the cherries. The crop couldn’t be picked.

“Could we have saved a lot more if we sprayed?” he asked rhetorically. “Yeah, we could have.”

That experience changed how he approached risk. From then on, even when forecasts said rain was unlikely, he often sprayed anyway, putting out chemicals he might not have needed, because the cost of being wrong was too high. 

Weather wasn’t something he could plan around. It was something he reacted to.

Site-specific forecasts

That changed when Richard began using Weather Tools.

Instead of a single, generalized forecast, he now receives forecasts tailored to each of his orchards. Linden gets its own forecast. Ripon gets its own forecast. Decisions are no longer based on the assumption that nearby orchards will experience the same conditions.

Weather Tools’ machine learning model studies local tendencies at each site and adjusts accordingly. The result is a forecast Richard can trust.

With location-specific forecasts, Richard plans differently. He times sprays around actual wind conditions, identifies safe windows for applications, and assigns crews based on where conditions are best.

“Farmers have to be very efficient for what we’re doing,” Richard explained. “We cannot control the weather, but Weather Tools has made it so we can see what’s going to happen and that benefits us in the future. I have faith in Weather Tools.”

Seasonal Planning at Stockton East

Richard’s perspective extends beyond his own orchards. As a board member for Stockton East Water District, he’s seen firsthand how Weather Tools’ seasonal forecasts support water management.

The California Annual Precipitation (CAP) forecast predicts water year precipitation months in advance. When a tool like this is introduced—especially one that hasn’t existed before—skepticism is natural. Water managers are used to relying on historical patterns and incremental updates, not long-range guidance. Trust in something new isn’t immediate; it’s earned over time through consistent performance.

As the CAP forecasts verify year after year, confidence steadily grows. At Stockton East, that growing trust is now guiding decisions and continues to strengthen with each reliable season.

With precipitation and reservoir inflow forecasts, Stockton East gains early insight into how much water is likely to enter the system, well ahead of traditional updates. That early knowledge helps guide reservoir operations, treatment plant capacity, and agricultural allocations.

Together, these forecasts are shifting weather from an unpredictable variable to a strategic planning input, both in the short and long term.

For Richard, that means relying on location-specific forecasts for day-to-day orchard operations and seasonal precipitation and inflow forecasts for water management. These tools transform uncertainty into strategy, allowing customers like Richard to plan with confidence.

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