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By Ria Persad, CEO of StatWeather

What is Possible?

Is it actually possible to predict the weather 3 or 6 months in advance for a particular state or region? Is it also possible to predict the weather 12 hours in advance to within one square mile? The answer to both the long-range scenario and the short-term, hyper-local scenario is, “Yes, within certain boundaries of precision.”


Suppose you are driving by car to meet your friend at the park, which is 5 miles away.  You forecast your arrival time and tell your friend you’ll be there in 10 minutes, give or take a couple of minutes.  This seems reasonable.

Now suppose you are driving by car from Texas to Florida to meet your friend, who is 1,000 miles away.  You forecast your arrival time and tell your friend you’ll be there the following day around 5pm, give or take a few hours.  This also seems reasonable.

The further out you go, the less precision one would expect.  It doesn’t mean that you cannot “predict” your arrival—it means that the error range might vary.  There is inherent chaos and error with everything----whether it is on the order of microns or miles!  The question is, how much risk can you tolerate within your given application? These bounds must be defined, both spatially and temporally.

Tactical vs. Strategic Weather Intelligence

A “tactical” solution is one that is focused on more short-term operational intelligence that might also involve highly localized solutions.  A “strategic” solution is one that is focused on a longer range of foresight and preparation with a larger overall view.  Both are equally important, critical, and necessary for safety, efficiency, and profitability.


A company is performing a geophysical oil and gas survey in the North Sea and needs ocean wave heights of 12 feet or less in order to ensure smooth sailing for survey vessels and less movement, noise, and interference with onboard surveying equipment.  Higher seas present operational difficulty.

Strategic solution:

The company needs to plan their mission at least 6 months in advance in order to secure resources (lease a ship, hire a contracting crew, procure survey instrumentation).  A strategic weather forecast indicates those weeks of the year which have the highest likelihood of calm winds and waves.  The mission is scheduled for a certain month within certain weeks with an 80% likelihood of wave heights being favorable.

Tactical solution:

About 10 days ahead of time, government models are consulted to figure out the optimal days to conduct the most data-intensive rounds of the geophysical survey.  As the actual days are nearing, then hourly weather intelligence is needed for fine-tuning the steering of the ship in and out of potentially sub-optimal conditions.

A strong strategic solution was needed to guide business and financial decisions on the planning side; then strong tactical intelligence is needed for the day-to-day near-time execution and fine-tuning.

Here is a summary of some key attributes of strategic and tactical weather intelligence.




Lead Time

1 minute to 15 days in advance (short-range to medium-range)

16 days to years in advance (long-range weather and climate modeling)

Spatial Resolution

Hyper-local (e.g., acreage or square mile) up to city-level

City-level up to country/global regions

Temporal Resolution

Updates can be minute-by-minute, hourly, or daily.

Daily, weekly, monthly, seasonal, and yearly updates.

Temporal Error Precision

Errors in timing weather patterns can range from being 30 minutes off to a couple of days off.

Errors in timing weather/climate patterns can range from being a couple of days off to being a couple of weeks off.


Temperature errors can range on average from 1 to 5 degrees off (Fahrenheit).

Temperature errors can range on average from 4 to 8 degrees off (Fahrenheit).

Chaos (Predictability)

Micro-chaos in smaller areas at smaller timescales.

Macro-chaos among larger regions at longer timescales.

Periodicity of Patterns

Weather patterns repeating with higher periodicity or short frequency, even daily (e.g., tropical rains in Tampa, Florida, repeating every day in Summer between 3:00 and 4:00PM).

Weather patterns repeating with longer periodicity or low frequency, with quasi-seasonal and even multi-year/decadal patterns.

Output Frequency

Model or forecast output can be administered by the minute (as in satellite data), hourly, or daily.

Model or forecast output is available daily, weekly, monthly, seasonally, and yearly, with weekly and monthly being most common for lead times under 1 year.

Base Dataset

High frequency satellite data and government model output (for example, GFS, ECMWF, and Canadian models).

Historical “actuals” data of weather and climate conditions; data for predictors that may influence future climate.

Standard Output

Deterministic forecast is conventional, with specific numerical forecast

Probabilistic forecast:  forecast coupled with confidence interval/probability.


Dynamical, physics-based, observation-based.

Statistical, mathematical, causal-, and pattern-driven.

Types of Weather

Focus can include severe conditions:  tornadoes, hurricanes, storms, etc. because of its operational nature.

Focus can include extreme conditions:  heat/cold episodes, droughts, monthly and seasonal volatility, and climate changes.

Error Analysis Methods

RMS (root-mean-square analysis) and anomaly correlation are common for daily skill.

Categorical data often used (“above normal”, “normal”, or “below normal”); analytical methods to determine forecast accuracy in (1) timing, (2) magnitude, and (3) duration of weather patterns.

Common Applications

Some applications include: aviation, short- to medium-term trading, transportation and shipping, public safety, defense, business continuity and operations, farming, construction, and many others.

Some applications include:  retail and supply chain, commodity risk, insurance, trading, real estate investing, long-term utilities forecasting, agribusiness, climate change mitigation, and many others.

Economic Impact

Companies save millions of dollars per year; industries save billions; national economies save trillions!

Companies save millions of dollars per year; industries save billions; national economies save trillions!

For weather sensitive businesses, one thing is for certain:  both tactical and strategic weather intelligence is needed to minimize risks, promote safety, increase productivity, and drive profits.  Generally speaking, tactical and strategic weather solutions are pennies on the dollar when compared to the upside of what can be benefitted with this information...and when compared to the downside of what can be lost without it.

To learn more about tactical and strategic weather intelligence solutions, please contact service@statweather.com, or go to www.statweather.com.

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