Insights
Seasonal Forecasts: What They Are, How They Work
and How to Interpret Them
Seasonal forecasts do not predict
the weather on a specific day several months ahead.
Instead, they describe, in probabilistic terms,
how temperature and precipitation may
deviate from climatological conditions
over the coming weeks and months.
Understanding concepts such as
anomalies, probability and uncertainty
is essential for correctly interpreting this information
and assessing its value in planning processes.
01
Not the Weather on a Single Day,
but the Outlook for a Period
Seasonal forecasts describe, in probabilistic terms,
how temperature and precipitation may behave
relative to climatological conditions.
They do not predict the weather on an individual day.
Instead, they describe trends over periods of approximately
10 days, extending across a forecast
horizon of around four months.
This distinction is fundamental.
A seasonal forecast does not attempt to determine
what will happen on a specific date.
It describes the expected conditions over a period
compared with a climatological reference.
Weather Forecast
What will happen in the coming days?
Describes how weather conditions are expected to evolve,
with a level of detail suitable for short- and
medium-range forecasting.
Seasonal Forecast
How might conditions evolve over a period?
Describes trends relative to climatology
over the coming weeks and months.
02
Anomalies, Probability and Uncertainty
The starting point is the
anomaly relative to climatology:
the difference between forecast conditions
and a reference climatological value.
A temperature anomaly of +2 °C
indicates that the forecast average temperature
for the period is 2 °C above the climatological reference.
Similarly, a positive precipitation anomaly
indicates precipitation totals above the
climatological reference for that period.
Seasonal forecasts are also based on
multiple possible scenarios.
Therefore, beyond the central tendency,
it is important to consider probability and uncertainty.
Anomaly
The difference between forecast conditions
and a reference climatological value.
Probability
Indicates the extent to which different scenarios
support particular conditions or a specific trend.
Uncertainty
Indicates how widely the different forecast
scenarios are distributed.
Key Takeaway
A seasonal forecast
does not predict the date of an individual
extreme event or a specific thunderstorm.
Instead, it describes the overall tendency
of a period relative to climatology.
03
A Seasonal Forecast That Evolves Over Time
Hypermeteo develops this forecasting approach
through two complementary systems.
Hypermeteo Seasonal System
Combines seasonal ensembles from multiple
international meteorological centres using
a multi-model approach,
establishing the seasonal baseline.
Hypermeteo Sub-Seasonal System
Uses the latest available sub-seasonal information
to assign greater weight to seasonal scenarios
that are more consistent with recent conditions.
The result remains a seasonal forecast,
but one that is
progressively updated over time.
H3S does not replace the seasonal forecast
with a shorter-range prediction.
Instead, it uses sub-seasonal information
to reweight the scenarios already included
in the seasonal forecast.
How Does the Updating Process Work?
04
From Information to Decision-Making
The value of seasonal forecasts does not lie
in knowing with certainty what will happen
several months from now.
Their role is different: to provide
additional meteorological information
when decisions must be made before operational
weather forecasts can offer sufficient detail.
Anomalies, probability, uncertainty and
continuous updates should therefore be
considered together to support planning
activities in sectors particularly sensitive
to weather variability.
The Decision-Making Process
Decision to Be Made
Seasonal Information
Probability and Uncertainty
Updates Over Time
Planning
In Summary
A Probabilistic Outlook for the Coming
Weeks and Months
Seasonal forecasts extend the horizon
of meteorological information into the
coming weeks and months.
Their value does not lie in predicting
individual weather events, but in providing
a probabilistic assessment of possible
future conditions, progressively updated
and applicable to decision-making processes.
Hypermeteo Seasonal Forecasts
Want to Understand How to Use This Information
in Your Decision-Making Processes?
Get in touch with the Hypermeteo team
to explore how seasonal forecasting information
can be integrated into your analysis
and planning activities.
