In a previous post, we discussed the basic mechanics of a historic lake-effect snow event. I wanted to delve into the basic thermodynamics and ice microphysics of that event. I will first discuss snow-to-liquid ratios, a concept of ice microphysics that applies all snow events, not just lake-effect.
Contrary to popular belief, snow does not form from rain. If rain freezes as it falls, then the ice formed is called “sleet” or “ice pellets”. If rain freezes upon contact with exposed surfaces, then the ice formed is called freezing rain. Snow, on the other hand, forms through more complex microphysical processes within the cloud. The three mechanisms for snowflake formation and growth are: deposition, accretion, and aggregation. Aggregation is the easiest to conceptualize. Aggregation doesn’t play a role in snowflake formation; however, it does contribute to the growth of snowflakes — more specifically, snowflake conglomerates. Snowflake conglomerates are the collection of many snowflakes into a “clump” or conglomerate as they fall toward the ground. Under certain conditions, falling snowflakes will collect others, forming a clump of snow that we often see as very large “snowflakes” when they reach the ground (technically speaking, this type of “snowflake” isn’t a snowflake at all — it is the collection of many snowflakes gathered through the process of aggregation).
The other two microphysical processes mentioned above pertain to both the formation and growth of snowflakes. The most important process is deposition. Deposition, also known as the Bergeron-Findeisen process, occurs when ice crystals form and grow at the expense of nearby liquid droplets in an environment supersaturated with respect to ice, but subsaturated with respect to water. Since the saturation vapor pressure over ice is less than that of water, this configuration within the cloud’s precipitation formation zone creates a vapor pressure gradient that allows for the vaporization of water from the liquid drops to vapor, and then from vapor to nearby ice crystals. Remember, vapor is the gaseous state; therefore, the transfer of vapor (evaporation) from liquid droplets to pure vapor ultimately depletes the cloud of liquid droplets over time; this is what was meant by “…at the expense of liquid droplets” above. At the same time, gaseous vapor can diffuse directly to nearby ice crystals due an opposite gradient
Snow-to-Liquid Ratios: Basic Ice Microphysics
The snow-to-liquid ratio (snow:liquid) is a ratio computed using the observed snowfall and its melted counterpart (liquid equivalent). There are two ways to determine the snow:liquid ratio: 1) measuring the liquid equivalent by melting the snow slowly in a controlled setting, and 2) estimating the ratio based on the atmospheric conditions in the snow-production layer at the time of the event. When using method number 2, it’s important to note that atmospheric conditions often change during the evolution of a winter storm as the thermodynamic profile within the snow-production layer changes; therefore, the snow:liquid ratio may not always be accurate and the process for determining the snow:liquid ratio must be integrated over the duration of the event (recalculated at numerous time intervals).
The snow-production layer is known as the dendritic growth zone (DGZ). The DGZ is a is a layer of air aloft characterized by temperatures between -12°C and -18°C and a relative humidity of at least 80%. Within this temperature range, the atmospheric particulates that serve as ice nuclei are numerous in concentration and are easily activated (ice nucleation). Forecasters assess the thermodynamics of the precipitation-formation layer(s) aloft ahead of all possible winter storms to determine the existence of a DGZ.
Accurate assessment of the DGZ (if one exists) is crucial to determining precipitation type. Furthermore, if a DGZ is present, the characteristics of the DGZ determine the snow:liquid ratio. Generally, dendrites (common snowflakes) form most efficiently at temperatures between -12º and -18ºC; snow-to-liquid ratios are also maximized within this temperature range as shown in figure below. If temperatures in the precipitation-production layer are below freezing, but warmer than -12ºC, dendritic growth becomes less likely. At temperatures between -4ºC and -10ºC, we tend to see elongated ice crystals, rather than dendrites; and, at temperatures between 0ºC and -4ºC, we typically see no ice crystals at all (because of the nature of ice nucleation, which we will elucidate in a future post). So you can see how the thermodynamics of the precipitation-production layer are crucial for determining precipitation type and snow:liquid ratios.
Forcing Mechanisms for Heavy Lake-Effect
Within the DGZ, we also assess the vertical ascent. Vertical ascent is a term for the upward atmospheric motions that result from the forcing provided by various atmospheric disturbances and other lifting mechanisms; both the temperature (discussed above) and the vertical ascent within dendritic growth zone determine the snow-to-liquid ratio. Examples of forcing mechanisms are: upper-level disturbances, isentropic lift (“overrunning precipitation”), frictional convergence, upslope flow, and convection.
When we hear the word “convection”, we often think of thunderstorms. Convection is merely the term for the vertical transport of heat due to buoyancy. Convection can create conditions ranging from clear-air turbulence or fair-weather cumulus to supercells. Convection results from atmospheric instability, and enhances any pre-existing vertical motions from large-scale forcing. For heavy snow, especially lake-effect snow, most of these forcing mechanisms are present.
Let’s Consider Lake-Effect Snow
Lake-effect snow gives us a great opportunity to examine multiple forcing functions working together to create heavy snowfall. Large-scale forcing (vorticity advection aloft) can destabilize the atmosphere by cooling the upper levels and raising the level of the capping inversion. Also, as indicated in the image below, frictional convergence (onshore flow interacting with the landmass is forced upward) and upslope flow (the fetch moves over the topography toward higher elevations) both enhance vertical motions. When all of these forcing functions are considered together, you start to build a conceptual model of how lake-effect snow works.
As discussed in the previous post, there was a significant temperature lapse rate (the rate that the temperature decreases with height). In this case, there was significant instability present, and this aided in convection over the relatively warm lake waters. In the lake-land diagram above, we note the moisture flux from the warm lake waters into the extremely cold air above it. We see often see this on very cold days, when a cold steam or low fog forms over relatively warm, open bodies of water (such as swimming pools, ponds, and lakes). As a very long fetch of extremely cold air flows lengthwise over a large and relatively warm lake, the fetch consumes an enormous amount of warm moisture, which further destabilizes the atmosphere, and generates convection. As those convective plumes develop within the fetch move over the lake, the upward forcing is further enhanced through frictional convergence and upslope over the land. All of these contributed to the enormous snowfall rates of 3 to 5 inches per hour during this recent event. In fact, lightning and thunder were also reported, and were caused by the convective component. So how do we estimate the snow-liquid ratio? Most of the rain/snow gauges in the area are covered in snow and cannot assist us in our endeavor to determine the ratio. So, we must go back to the DGZ and look at the temperature profile.
Upper-Air Data During the Historic Lake-Effect Snow Event
Let’s take a look at the sounding on Tuesday evening (November 18, 2014) when the lake-effect snow event was at its peak (below). At this time, the DGZ was from approximately 850 mb to 700 mb, with a minimum temperature in that layer of approximately -15ºC at 725 mb. The average temperature in this layer appears to be around -10ºC. Using -10ºC as the reference temperature for this event (again, this is only a snapshot at one point in time/space). Referring to the chart above, we can conclude that snow-to-liquid ratios were on the order of 10-to-1 (10 inches of snow per 1 inch of liquid equivalent). This ratio is important because it gives us a rough idea of how much liquid is in the snow. In this case, a 10:1 ratio signifies that for every 10 inches of snow, there is one inch of water. In the areas that received 70 inches or more of snow, this equates to 7+ inches of liquid equivalent. Because of this, there is some concern of flooding once the snow begins to melt. I stress again that this is a computation made from a single snapshot (sounding). For us to really know the liquid equivalent we’d either have to melt a volume of snow in a controlled setting or perform a complete analysis by integrating the thermodynamic profile over the duration of the event (to account for changes in temperature/moisture, etc. as the event evolved).
