Report-back:
Can you spot an atmospheric river?

An ever-widening definition is making it more difficult, but ground-based observations can help discern impacts.

Atmospheric rivers are commonly associated with the most impactful winter storms along the west coast of North America. Skillfully forecasting winter storms is crucial for our communities to prepare for potential flooding and other impacts such as power outages, road closures, and landslides. 

But as storms are more frequently “tagged” as atmospheric rivers, we are seeing confusion grow about what exactly the term means for west coast communities, especially those in mountains. Because the precipitation phase in these storms is closely tied to the impacts – such as huge snowfall or major flood problems – correctly predicting whether precipitation will fall as rain or snow brings more clarity to both forecasters and the communities relying on accurate predictions. 

Let’s start with a quiz: Of the four satellite images below showing the total amount of water vapor in the atmosphere, in which do you see an atmospheric river? Storm 1 gives a hint of what to look for! 

Storm 1 shows the signature form of an atmospheric river that the definition was originally based upon. But in fact, all four of these storms could be, and were, identified as atmospheric rivers using the broadest definition of this type of storm. 

Definitions aside, let’s explore the precipitation brought by each storm. Even though each of these storms could be counted as an atmospheric river, they produced widely varying precipitation totals. Storm 1 on October 22-24 was an extreme atmospheric river that brought very heavy rainfall and the tail end brought high elevation snow. On December 13-15, Storm 2 brought heavy snow and low elevation rainfall. Storm 3 on December 26-28 resulted in snowfall that was quite heavy across a large range of elevations. Finally, Storm 4 on January 3-5 did not deliver a great deal of precipitation due to the unfavorable wind orientation with respect to the mountains, despite a strong signal for an atmospheric river along the coast (Storm 4 above). 

By comparing precipitation and snowfall amounts in the figure above, you can see how different the storm patterns actually were! The term “atmospheric river” was applied to both very impactful storms (Storm 1 and 3) and relatively less impactful (Storms 2 and 4). 

We have seen confusion created when all storms become termed atmospheric rivers–especially in the popular media–which can make it difficult for communities to prepare. If the total rain or snowfall of these storms differs greatly, yet we apply the same terminology to all storms, we risk the effects of “crying wolf” when community member’s expectations of a storm’s impact are greater than the storm’s outcome. Take this scenario, for example: A meteorologist gets a call prior to Storm 4: “I heard it is going to be an atmospheric river. Will it be that bad?” But Storm 4 vastly underperformed relative to expectations of what we used to think of as the major flood (or impact) producing storms. As a result, this can erode the trust of community members in the forecast over time. 

Further complicating the matter is that atmospheric rivers are often classified based on the amount of water being transported and not based on the forecast precipitation amount, let alone the phase of precipitation that is forecast. Precipitation falling as rain or snow present very different hazards depending on where and when it falls. For example, one inch water falling as rain on an extensive and ready-to-melt snowpack will have larger consequences than an inch of water falling as snow in a remote mountain region.

Consensus among experts is important for consistency in communication to support preparedness for any storm. But exactly how to define an atmospheric remains a lively discussion among atmospheric science researchers. The height of the gold spikes below can be interpreted as the probability experts will agree that a storm should be classified as an atmospheric river. These probabilities were developed by O’Brien et al. (2020) and were calculated through input from experts in meteorology using historic storms, and then applied to newly identified storms using machine learning. We thank Yang Zhou at Lawrence Berkeley National Laboratory for providing the atmospheric river detection probabilities. 

As you can see, there is not complete consensus as to whether or not these storms should be defined (or detected) as an atmospheric river. Some events have a higher probability, others have much lower probabilities, and these probabilities do not correspond perfectly with precipitation amounts or precipitation phase. 

So what is missing to be able to differentiate and predict an impactful event? Precipitation phase (rain, snow, mixed) is one of the most important characteristics of large storms that needs to be simulated correctly, especially in mountains. Specifically, we need to know what elevation and when the precipitation actually transitioned from rain to snow to understand a storm’s potential impacts, regardless of whether it is termed an atmospheric river.   

This gets to one of the core contributions of the Mountain Rain or Snow project to improve our forecasts. Your observations help us understand the precipitation phase differences within and across storms. We can see with better accuracy the proportion of rain, snow, and mixed precipitation that fell during each storm, and very importantly, where the rain-snow transition took place on the landscape and when it changed. Counts of the observations of precipitation phase are shown in the chart below.

In any storm, the rain-snow boundary may change as the storm progresses. Before Mountain Rain or Snow, insights into the rain-snow transition could be derived from just one daily satellite snapshot.  

Comparing and contrasting the number of rain, snow, and/or mixed observations across the four storms (and other storms during the winter), we can use your observations to understand the nuances of each storm’s progression. For example, we saw that Storm 1 was largely characterized by high elevation rain until snow finally began later in the event (rather than snow up high throughout). Storm 2 had both rain, snow, and mixed observations throughout, indicating a variety of areas receiving different precipitation phases, but it finished very cold with snow into the valleys. Because it was very cold, Storm 3 had very few rain observations. Storm 4 was quite dry and had very few observations of precipitation at all.

Your precipitation phase observations help us understand what differentiates these events after they make landfall. The rain-snow transition remains very difficult to predict, and forecasters need to know what characteristics of big storms matter the most to produce the best forecasts of precipitation totals and where the rain will turn to snow. You are an important part of helping us to pin down these differences and improve our capabilities to communicate the important nuances of storms. Until these prediction tools are perfected, the next time you hear “another atmospheric river is approaching” in the news, wait for a little more information before deciding to start filling sandbags, waxing your skis, or needing to do both!