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Weather forecasters have Detective Archivesa difficult enough time convincing people of the forecast on a typical day. But what happens when an event like Tropical Storm Harvey comes along, bringing hazards well beyond anyone's experience?

Meteorologists expressed a sense of queasiness and helplessness as their worst fears about Harvey were realized. Yes, they accurately communicated the potential for epic amounts of rain and life-threatening flooding. But still, lives were lost.

In the days leading up to then-Hurricane Harvey's first landfall in Texas on Aug. 26, computer models that project future weather conditions were insistent that as much as 40 to 60 inches of rain could fall, as the storm would execute an unusual stalling maneuver that would produce heavy rains for days on end.

SEE ALSO: Dramatic video shows ocean waves on a Texas highway after Harvey

Forecasters in private industry, broadcast television stations, and Internet companies stared at the simulations in disbelief, while warning that the signal for an unprecedented rainfall and flooding event was unusually high.

Harvey provides example of just how far meteorology has come during the past several decades, with high-speed computer models capable of simulating even the most unusual storm scenarios. Yet the forecast also illustrates the limitations of making an accurate prediction. It's not enough to simply get the forecast right and call it a day.

Homes are surrounded by floodwaters from Tropical Storm Harvey, in Humble, Texas on August 29, 2017. Credit: AP/REX/Shutterstock

A successful weather forecast can only be called a success if it induces society, from policy makers to individual families, to take appropriate actions to protect themselves.

Arguably, too few storm shelter orders and evacuations were issued ahead of time for particularly vulnerable areas, and many people did not seem to understand that the flooding would be beyond anything they've ever experienced before -- despite forecasts calling for just that.

First, let's start with the forecast basics. The National Hurricane Center's storm track forecasts for Harvey were uncannily accurate, predicting both the storm's initial landfall north of Corpus Christi and its virtual standstill above southeastern Texas. The storm intensity forecast was another story, as the Hurricane Center initially did not expect it to rapidly intensify into the strongest such storm to hit the U.S. in 12 years.

Forecasters were left in an anxiety-provoking limbo: They knew what was about to happen, were communicating that as much as they could, but were still watching an unprecedented disaster unfold and wreak havoc across a wide area.

No one can say that Hurricane Harvey and its ensuing floods were a surprise. Nor, however, can they say that the forecasts were 100 percent useful, considering how quickly the storm intensified, and how much uncertainty there was about exactly where the heaviest rains would fall.

In the run-up to the storm, weather forecasters warned of a potentially "catastrophic," and even unprecedented, rainfall event from Harvey. But it wasn't until Saturday, after the storm made landfall, that it became clear that the Houston and Galveston area would most likely bear the brunt of the flooding, rather than areas to the south and west of there.

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As radar observations began to match computer model forecasts on Saturday evening, meteorologists on Twitter expressed helplessness watching the storm unfold as a worst-case scenario.

"The event has turned so extreme that even we [meteorologists] are somewhat stunned, hardly able to believe our own dire predictions are actually playing out,” wrote Jason Samenow, the chief meteorologist for the Washington Post's Capital Weather Gang blog.

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Samenow's highly popular site first began warning of Harvey's flood potential on Tuesday. (Mashabledid so starting the next day.)

On August 23, the National Weather Service's Weather Prediction Center in Maryland began issuing forecasts showing that huge amounts of rain would fall in Texas, and ramped up precipitation amounts from that point forward.

"I would give them the credit for "going big" with forecast numbers into record territory," said Ryan Maue, a meteorologist with WeatherBell, a private forecasting company.

"In my opinion, it doesn't really matter that [the] GFS or ECMWF [models] picked up on the event 6 to 8 days prior," Maue said in an email. "That is mostly a function of getting the track and stall-out of Harvey "close enough." 

"The key here was putting the worst rainfall impacts on the largest population center of Houston.  Analysis shows that Harvey's rains fell on the most concentrated population at the most prodigious rates [and] amounts."

Maue said the stalling of the storm was highly unusual, and computer models correctly picked up on this aspect of the storm well ahead of time. One model, which was recently upgraded with more computing power behind it, also accurately forecast the storm's intensification into a major hurricane.

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"The stalling of Harvey was an extreme event in its own right," he said.

Marshall Shepherd, a meteorology professor at the University of Georgia, wrote about the forecast challenges facing his profession, and what the storm has been like from his perspective.

"In the days leading up to this storm, I physically got sick to my stomach because I knew what was coming. Heck, any good meteorologist worth their salt knew," he said.

"There is still work to be done on hurricane intensity forecasts... and pinpointing where the actual rainbands will be established, but overall, this was a solid forecast," he wrote.

Communication challenges remain, though, when it comes to how forecasters inform the public and decision makers of the scale and scope of an event.

As Hurricane Sandy showed in 2012, people have a tendency to compare storms to their past experience. This can get them into dangerous situations when a storm comes along that is outside the scope of their memory, however.

Gina Eosco, who is an expert in how people perceive weather forecasts, said the cacophony of weather forecast information available today via television, radio, online, and social media may be hindering the public's comprehension of a storm's full spectrum of threats.

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"With the rise of social media and a 24/7 media environment, have we created a signal to noise issue?" she said in an email. "Does the lack of chronology on Facebook and Twitter (based on retweets) make it difficult to know at what time a message is relevant versus out of date?"

"Does it cause a perception of inconsistency to an otherwise consistent and coordinated weather communication effort? The medium changes our weather message," she added.

In addition, Eosco says, the description that forecasters use as well as the visuals they show play a big role in determining the public's response. "What does 35 inches of rain look like in reality? Sadly, now we know," she said.

"But prior to the event, how were people processing this information," she said, adding that technology might be available to show inland flood potential in a more realistic way.

As climate change continues to tilt the odds in favor of extreme events, such as heavy rainstorms and heat waves, it's becoming more likely that unprecedented events will occur. Harvey shows that we don't yet excel at picturing how they will unfold, and aren't geared toward preparing for them ahead of time.

Perhaps this is the result of wishful thinking or built-in psychological biases. But we'd better crack the code for making the implications of such forecasts clearer, because at some point, all of our lives may depend on it.

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