Weather Forecasting: How Does It Work, and How Reliable Is It?

Do you ever wonder exactly how the weather forecast is made? And how good are they, really? In last month’s article, I discussed the accuracy and usefulness of seasonal weather outlooks. This month, I want to hone in on near-term weather forecasts, defined for our purposes as forecasts of specific day-by-day or even hourly conditions for periods less than two weeks into the future. These are the forecasts by which we plan our weather-sensitive operations and personal activities. This is my career passion because it is in these time frames that confidence is high enough to make significant decisions that directly affect agricultural operations and output. Yet, my observation is that weather forecasts are still under-utilized in agricultural decision-making processes, with an over-emphasis on using recent and past data for determining future actions, perhaps due to the historical perception that forecasts are no better than the flip of a coin. Hopefully, this article can help build confidence in modern weather forecasting capabilities.

The weather forecasting process starts with the collection, quality control, and fusion of large amounts of diverse raw observational data from space, airborne, and ground-based assets to produce a coherent, three-dimensional view of the atmosphere at any point in time, from which we project the future conditions, adjust, and repeat. Those are all large topics for another time. For now, let’s just focus on the actual methods used in projecting the weather forward in time from the current conditions.

It turns out there are multiple techniques that are used, each of which has specific time frames for which they are most relevant. These methods are shown in the figure below, which depicts their comparative usefulness as a function of forecast lead time (meaning, how far into the future are you trying to predict, e.g., a forecast for tomorrow would have a lead time of one day).

Automated-Forecast-Method-Comparison-Graph

The two simplest methods are persistence and climatology. A persistence forecast means that conditions are assumed to remain unchanged. We all do this inherently when we look out the window to see if an umbrella or sunglasses are needed for an immediate, short-lived outside activity because in most cases we can assume things remain constant for a few minutes or longer.  A climatology-based forecast assumes conditions for a particular day or time period will fall within statistical normals derived over many years for that same day or period. Interestingly, these two “easy” methods are applicable at opposite ends of the time spectrum, with persistence often working very well for forecasting very near term conditions, and climatology being the best predictor for long-range forecasts. For a forecast to be considered to have any skill, it must be able to at least beat both of these two methods.

Extrapolation is slightly more complicated, and assumes an existing weather feature, such as a cold front or a line of storms, will continue generally moving in the same speed and direction without significant change. But it cannot account for new development or dissipation. We will save teleconnections for another time, as it is primarily for long-range forecasting, using large scale indicators such as the El Niño Southern Oscillation to infer what might be expected for the longer-range patterns.

That leaves numerical weather prediction, which is by far the most important method used in modern meteorology for forecasting lead times beyond a couple of hours. The advent of affordable, high-performance computing has revolutionized our ability to create computer models that simulate the motion and physics of the three-dimensional atmosphere, accounting for its interaction with topography, land surface, and the oceans with amazing realism, without any need for historical data or statistical relationships.

You often hear the TV meteorologist refer to “the models” when talking about the forecast, often accompanied with realistic animations of future clouds and precipitation.  In the last few decades, the advancement of these models have dramatically improved forecast accuracy and changed the role of the human weather forecaster. Yet, they still are subject to errors due to our incomplete understanding of all process interactions, our inability to explicitly simulate down to chaotic, molecular levels, and insufficient sampling of the initial state of the atmosphere, particularly in the mid and upper levels of the atmosphere over the oceans and other unpopulated areas. Thus, in most cases, the best weather forecast is an optimum blend of some or all of these methods, most often performed by a combination of automation and human oversight.

So, how good are the near-term forecasts now? ForecastWatch.com is an independent weather forecast verification service. Each day they collect and archive daily forecasts from a large number of public and private weather forecast providers. They compare these forecasts to weather observations from high-quality, government-operated weather stations and generate statistics on a variety of weather parameters of interest to the general public, including daily high and low temperature, wind speed, and occurrence of precipitation. This provides an excellent “apples-to-apples” comparison across providers because the same methods and truth data are applied to all sources, and the consistency allows for the assessment of long-term changes in accuracy. They recently published their study of daily high-temperature forecast accuracy, based on a 12-year period spanning 2005 through 2016, aggregating almost 200 million individual data sample for over 750 U.S. locations. If you like numbers and graphs, it’s worth a read. But, some key takeaways are summarized here:

  • One-day forecasts have an error of less than 3° Fahrenheit.
  • The five-day forecast is now almost as accurate as a one day forecast was in 2005, and overall error of the daily high-temperature forecast decreased by 33% over that period.
  • We have now reached a point where the nine-day temperature forecast is slightly better than climatology.

The graph below shows statistics from ForecastWatch for this year, spanning January through September. It shows the forecast error in degrees by forecast lead time for a climatology-based forecast (black), persistence forecast (red), and the average error of all providers analyzed by their service (blue). As mentioned, a forecast is really only useful if it performs better than persistence and climatology, and you can see that is the case all the way through day nine. This is consistent with the conclusions drawn from the 12-year study. The error tends to increase roughly 0.5° per day, so you can also infer that by around 10 days out, the forecasts are no longer more accurate than climatology, corroborating my assertion in last month’s article that forecasts of specific conditions at a particular location beyond a couple of weeks are beyond the state of the science.

As models continue to improve, we can expect to see a continuation of improving forecast accuracy, at least to a point. There is much debate about what the realistic limits are for weather forecasting, and it may not ever reach a point where we can project exact weather for a location beyond a few weeks in our lifetimes. But, in terms of things we attempt to predict in this world, the forecasting of near term weather is a major success story. Hopefully, as confidence grows in our ability to forecast weather and soil conditions, much value will be extracted for more efficient operations, higher yields, and better environmental stewardship.

Leave a Reply to Lior Doron Cancel reply

2 comments on “Weather Forecasting: How Does It Work, and How Reliable Is It?

  1. Very interesting and important. We, in Netafim, use short term weather forecast as part of our crop irrigation models and this is an essential part of it.
    Temperature, I guess, is a relatively an easy parameter for forecasting. We mainly straggle with precipitation which is mostly a local event and thus very hard to forecast

    1. Hello Lior,

      Nice to hear from you! Indeed, forecasting temperature, in terms of actual values, is “easier” than forecasting timing and amounts of precipitation, especially in warm season situations where showery convective activity is occurring and can produce very localized differences, with high variability even within farm scale. However, even those situations are now much better forecast than in the past even down to the mesoscale level. That is, we can pretty accurately say, even multiple days out, that a particular area will be susceptible to scattered showery activity vs. wide scale steady precipitation, and even do a reasonable job of bounding the amount of precipitation. The best way of using this information in irrigation decision support, in my opinion, is to use a source of forecast information that provided well-calibrated probability of precipitation along with the forecast amount. Then, you can select the probability value that best balances your decisions in cost vs. loss framework. Doing that will give better overall performance over the season than using no forecast information at all, which seems to be a more common practice in the irrigation world.

      Thanks for reading and contributing!

      – Brent

Data Management Stories
Google-Earth-Map-featured-image
Data ManagementRainfall Revisited: Accurate Observations and Beyond
September 18, 2018
As a provider of weather analysis and forecast services to the agricultural industry, one of the most common questions I Read More
Soil-Hand
Data ManagementAre You Using Your Soil to Its Full Potential?
September 14, 2018
Harvest is progressing across most parts of the U.S. and those growers who aren’t already harvesting are gearing up to Read More
Tablet Grower
Data ManagementThe Power of Predictive Analytics in Agriculture
September 5, 2018
Years ago if we would have been told computers, data, and technology would be scattered around every farm there may Read More
AmericasOn The Scene: 2018 Farm Progress Show Wrap Up
September 5, 2018
Former Monsanto President (now Bayer CropScience Chief Operating Office) Brett Begemann’s opening salvo during his first appearance at a Farm Read More
Trending Articles
Soil-Hand
Data ManagementAre You Using Your Soil to Its Full Potential?
September 14, 2018
Harvest is progressing across most parts of the U.S. and those growers who aren’t already harvesting are gearing up to Read More
Grower-Retailer
Imagery/SensingAgtech: 10 Things I Hate About You!
September 4, 2018
Before you get bent out of shape from the title, remember if you’ve read my articles before you know I Read More
Kansas State University
Industry NewsKansas State University, Topcon Form Precision Ag Research Partnership
August 30, 2018
Kansas State University and Topcon Agriculture are collaborating to develop tools and systems to advance precision agriculture and support farmers. Read More
Blockchain building block graphic
Specialty CropsIs Blockchain the Future of Food Safety?
August 24, 2018
When the Internet Protocol Suite (TCP/IP) was standardized in 1982, permitting the worldwide proliferation of interconnected networks and eventually the Read More
WinField’s Joel Wipperfurth On Empowering Data-Driven Decisions
InfoAg ConferenceOne on One with Joel Wipperfurth, Winfield United
August 15, 2018
Winfield United's Joel Wipperfurth discusses ag technology trends and topics during last month’s InfoAg Conference. Read More
Geosys
Industry NewsUrtheCast to Acquire Geosys from Land O’Lakes in $20 Million Deal
August 15, 2018
UrtheCast Corp. and Land O’Lakes, Inc. today announced they have entered a binding term sheet for the purchase of Geosys Read More
Latest News
Business ManagementIvy Tech, Farmers Partner to Help Precision Ag Educatio…
September 20, 2018
Harvest time has taken on a new meaning for some Wabash Valley farmers, and Bobbi Hunt-Kincaid hopes her family’s first Read More
Sensors
Sensors/IoTThe Answer to Agriculture’s Daunting Challenges – Soil …
September 20, 2018
According to the United Nations, 9.6 billion people will live on planet Earth by 2050. Feeding these mouths will require Read More
Google-Earth-Map-featured-image
Data ManagementRainfall Revisited: Accurate Observations and Beyond
September 18, 2018
As a provider of weather analysis and forecast services to the agricultural industry, one of the most common questions I Read More
PenelopeNagel
Business ManagementWhy Is Funding a Challenge for Women-Led Agtech Compani…
September 17, 2018
When it comes to women-led agtech companies the funding discussion never seems to cease. In June after the The New Read More
Mobile Phone in field
Decision Support SoftwareWhy Are 570 Million Farmers Not Yet Using Agricultural …
September 17, 2018
Until recently, using agricultural apps and software was a rare practice among growers. This is now changing. The mass adoption Read More
Soil-Hand
Data ManagementAre You Using Your Soil to Its Full Potential?
September 14, 2018
Harvest is progressing across most parts of the U.S. and those growers who aren’t already harvesting are gearing up to Read More
Grower Services & SolutionsDeere-Granular Collaboration Produces New Profit Maps T…
September 14, 2018
The newest development from the ongoing John Deere-Granular product development and marketing collaboration is Profit Maps, now available to farmers Read More
Wingtra
DronesOpinion: Combining Two Pluses with the WingtraOne UAV
September 13, 2018
For the every-day consumer interested in UAVs, there is an ocean of products from which to choose. This includes the Read More
Farmer-tablet
AsiaShould Agri-Input Manufacturers Outsource E-Commerce to…
September 12, 2018
Editor’s note: Venky Ramachandran is a contributing writer for PrecisionAg.com’s sister site, AgriBusinessGlobal.com. This article was originally published on LinkedIn. Now, Read More
ICON-Link-Licensing_featured-image
Industry NewsValley Irrigation Adds Remote Irrigation Management Opt…
September 11, 2018
Valley Irrigation, an industry leader in smart irrigation solutions, has announced enhancements to its remote management technologies. Multi-Year Licensing In Read More
Reflex-Connect-Agri-Inject-featured-image
Variable Rate ApplicationVariable Rate Fertigation System Expands with Mobile Co…
September 10, 2018
Building on the success of its Reflex Variable Rate Fertigation system, Agri-Inject has taken fluid injection to the next level Read More
Industry NewsTeralytic Earns Ag Data Transparent Certification
September 10, 2018
Soil analytics company Teralytic has completed the Ag Data Transparent certification, affirming that their data use is private, secure, and Read More
Business ManagementTop 20 Two-Year Colleges for Precision Agriculture
September 10, 2018
Earlier this year, I compiled a list of the 25 best colleges for precision agriculture. It was quite the process. Read More
Industry NewsRaven, Topcon Announce Slingshot API Agreement
September 6, 2018
Raven Industries and Topcon Agriculture announced today a licensing agreement for Topcon Agriculture’s use of the Slingshot Application Programming Interface Read More
Tablet Grower
Data ManagementThe Power of Predictive Analytics in Agriculture
September 5, 2018
Years ago if we would have been told computers, data, and technology would be scattered around every farm there may Read More
DronessenseFly Launches eBee X Drone, Breaks Through 1,000 ac…
September 5, 2018
senseFly today reportedly sets a new standard in mapping tools with the launch of the eBee X. Launched with the Read More
AmericasOn The Scene: 2018 Farm Progress Show Wrap Up
September 5, 2018
Former Monsanto President (now Bayer CropScience Chief Operating Office) Brett Begemann’s opening salvo during his first appearance at a Farm Read More
EventsAg Experts Discuss Big Data Challenges in Agriculture
September 5, 2018
Agricultural experts at a Houston conference praised the advancements in unmanned aerial vehicles, sensors, and data-collecting technology used in precision Read More