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Andy Paterson • January 20th, 2026.
Predictable rain patterns are critical for agriculture. But, under climate change, we’re seeing longer dry spells, more erratic bouts of extreme precipitation, and irregularities that don’t match historical patterns. This period of more unpredictable rainfall is significantly impacting crop yields and quality, as well as inputs and labor.
Managing new precipitation-related risks and unpredictable rainfall will require an accurate, dynamic understanding of when the rainy season begins, how long dry spells are likely to last, and the distribution and duration of rainfall. This is especially true at the start of the season, when early decisions on planting, inputs, and labor are hardest to reverse.
In this post, we will show how ClimateAi’s platform addresses emerging challenges in predicting when rainfall will occur, how long it will last, and how much it will fall.
Predictable rain patterns are critical in agriculture. A false start, or a delayed onset, can be the difference between a profitable yield and a wasted season.
Every season, producers face decisions about whether to plant based on calendar dates or regional forecasts. However, historical onset dates are increasingly unreliable due to climate variability, and regional forecasts fail to pick up the nuances of microclimates.
Daily uncertainty about when the rain will come and whether it will stay can lead to a shorter growing season, higher irrigation costs, and mistimed planting, applications, or labor deployment.
How ClimateAi Determines If The Rainy Season Has Started
Standard forecasts don’t help with today’s unpredictable rainfall. They might predict whether rain will fall on a given day with a couple day’s lead time.
But what growers need is a seasonal outlook and the expected consistency of rainfall and how much is likely to fall, with a longer lead time, not a single-day forecast.
ClimatAi’s models are designed with those factors in mind:
Unpredictable rainfalls don’t just impact rain-fed crops; irrigation-fed crops are just as impacted.
Across large parts of North America, Africa, and India, producers are entirely dependent on rainfall timing and persistence. Planting decisions hinge on whether early rains will be followed by sustained moisture. If rain starts and then stops for weeks, crops can emerge and fail, fertilizer is wasted, and costly replanting is required.
A common theme we hear from producers in rain-fed systems is that rain starts, so farmers plant, then it doesn’t rain for three weeks, and the plants shrivel.
States in the US Southwest, like California, face a different, but equally risky problem. Rainfall does not directly determine planting, but it governs water availability later in the season.
Winter precipitation and snowpack determine reservoir levels and irrigation security. When early-season rain signals are misread, producers may overcommit acreage or inputs, assuming water will be available, only to encounter mid-season constraints when it’s too late to adjust.
A warmer climate is pushing rainy periods outside their historical norms. For every 1°C of warming, the atmosphere holds an additional 7% of water vapor, leading to more intense rainfall and, in some areas, more drought.
There is also the growing phenomenon of hydrological whiplash, where large or frequent periods of very wet and very dry conditions occur back-to-back. Studies show that these sub-seasonal whiplashes have increased by 66% in recent years, making false starts more common and the onset of rainy seasons harder to predict.
Three High-Cost Failures Caused by Poor Predictions of Rainfall
When rainfall timing and persistence are misread, losses compound quickly, not just in yield, but in labor, inputs, logistics, and irrigation costs.
Three main issues make inaccurate forecasts expensive:
The big question for producers in many regions today is “Will we get enough rain this season?” For many, drought risks creep up slowly, requiring longer periods of expensive irrigation.
Early detection could allow producers to select a more drought-resistant seed variety, lock in irrigation prices early, and for sourcers to find a backup if the drought threshold indicates lower yields.
Some crops require a 3–7-day dry spell for planting or harvesting. Early knowledge of this enables better logistical and labor planning.
Even when rainfall is agronomically beneficial, excess rain can leave fields inaccessible for days or weeks. Muddy conditions and flooding prevent equipment from entering fields, delaying planting, spraying, and harvesting regardless of crop readiness.
One ClimateAi customer used our platform to reschedule a costly site visit, as the originally planned date would have coincided with a period of extreme precipitation.
Knowing when rain will come is one challenge, how much is another. 20mm over 5 days vs 100mm in 24 hours, the result is a totally different outcome. Extreme precipitation events can lead to erosion, flooding, increased runoff, and increased pest risks.
Fertilizer timing is one of the most sensitive early-season decisions tied to rainfall reliability. Applied too early, fertilizer can run off or leach before crops establish, resulting in reapplication that can run into the millions.
Applied too late, it misses peak uptake windows and will lock in yield losses. Unpredictable rain turns fertilizer application into a high-risk gamble rather than a planned data-driven decision.
Leading producers and the procurement teams that rely on them are taking a more proactive rather than a reactive approach.
Instead of relying on historical calendars or single-day forecasts, they use probabilistic, seasonal weather intelligence to make early decisions with confidence and adjust as conditions evolve.
The most critical early-season decisions are based on knowing when the rainy season has actually begun. Leading teams use seasonal onset forecasts with probability bands, often 1–6 months ahead, to understand whether the season is likely to start earlier, later, or within its historical window.
As the season approaches more accurate 7–14 day onset likelihood alerts help teams move from strategic planning to operational execution locking in labor and planting timing.
Crucially, these teams don’t treat the first rain as the start of the season. They monitor rainfall persistence signals that indicate whether early precipitation is likely to be followed by sustained moisture or a dry spell.
This distinction helps them avoid costly false starts that lead to replanting, wasted fertilizer, and misdeployed labor.
Rather than asking “are we in a drought yet?”, high-performing teams assess drought probability early in the season. They rely on seasonal precipitation outlooks with confidence bands to assess the likelihood of below-normal rainfall during the upcoming growing season.
These outlooks are paired with crop-specific drought thresholds to determine how much irrigation is required and for how long, and whether another drought-resistant variety of that crop should be considered.
Leading organizations are seeking decade-scale insights into droughts to decide where to allocate capex to irrigation infrastructure, which regions to scale back, and where future production will be most resilient.
Leaders in adapting to unpredictable rainfall distinguish between steady, beneficial rain and short-duration, high-intensity events that can cause runoff, erosion, disease pressure, and operational delays.
Multi-day accumulation and intensity threshold alerts help them anticipate when rainfall will support crop growth, and when it will disrupt harvest, planting, or input application.
High-resolution 7–14-day forecasts are used to identify narrow operational windows, such as the 3–7-day dry stretches required for planting or harvesting. For organizations managing production across multiple regions, comparative seasonal outlooks enable portfolio-level planning, allowing teams to shift acreage, labor, or sourcing toward areas with more favorable conditions at specific timings.
Changes in rainfall are becoming increasingly difficult to predict and manage. These shifts are leading to costly replanting, yield reductions, and the reapplication of pesticides or fertilizers for those who fail to accurately predict them.
ClimateAi’s models are helping leading producers and procurement teams answer questions, like “is this the first rain of the rainy season, or a false start?” And “will we have enough rain this season?” with the clarity to make cost and yield saving decisions.
👉 If you need support answering these questions and others, we can help!
Because climate variability is increasing. Rainfall is arriving earlier or later than historical norms, with longer dry gaps and more intense events, making annual averages unreliable for planning decisions.
It refers to whether early rain is followed by consistent moisture over the following weeks. Persistence determines whether planting succeeds, or if plants wither when a dry spell is followed by a rainy day.
Most early-season decisions require weeks to months of lead time, not days. Planting, fertilizer procurement, labor scheduling, and irrigation planning all depend on seasonal outlooks combined with short-term confirmation.
Rainfall uncertainty increases the risk of runoff or leaching when fertilizer is applied too early, or yield loss when applied too late. Timing fertilizer around rainfall persistence is critical to protecting both yield and input costs.
No. In irrigated systems, rainfall determines reservoir replenishment and water availability later in the season. Misreading early signals can lead to overcommitted acreage and mid-season water constraints.
A false start occurs when early rains trigger planting but aren’t followed by sustained rainfall, leading to potential crop failure and replanting costs.
They increase the risk of planting too early (false start) or too late (compressed season), and they make it harder to find safe 3–7 day workable field windows.
By forecasting onset timing with probability bands, identifying workable field windows, quantifying drought risk with crop-specific thresholds, and distinguishing helpful rain from disruptive events.
Andy Paterson is a content creator and strategist at ClimateAi. Before joining the team, he was a content leader at various climate and sustainability start-ups and enterprises.
Andy has held writing, content strategy, and editing roles at BCG, Persefoni, and Good.Lab. He has helped build one of the industry’s most popular newsletters and regularly publishes environmental science articles with Research Publishing.