Last week produced the second landfalling tropical storm of the season in the United States, as Tropical Storm Bill came ashore along the central Texas coast. Bill moved slowly north and eventually northeast and weakened to a tropical depression, producing copious amounts of rain from Texas through Oklahoma and into Missouri. The figure below shows PQPE (WDT’s radar-estimated precipitation) for the 72-hour period ending at 7 am CDT on June 19. The black line shows the approximate track of the center of Bill during that time.
Tropical storms and hurricanes are known for producing both tremendous amounts of rain due to both the long duration of rainfall as well as torrential hourly rainfall rates that are commonly under-estimated by conventional radar-based estimation methods. The rain rates calculated using various common relationships for reflectivity between 30 and 50 dBZ are shown below. Note how much higher the tropical rain rate (green line) is for the same reflectivity.
The main reason tropical rainfall is different is that the process that produces the rain drops inside the clouds is different, as illustrated very well in the figure below, from the COMET program. Most non-tropical rain actually starts as snow high up in the cloud where the temperature is below freezing. As the snow flakes fall, they melt into rain drops. This is known as a “cold rain” process because the particles grow mainly as snow. Heavier precipitation rates corresponding to reflectivity above 30 dBZ generally mean larger snow flakes that will melt into relatively large drops.
Tropical rainfall is generally formed by a different process that does not involve ice, and is known as “warm rain”. In this process, some liquid rain drops grow just large enough to start falling (still relatively small for rain drops). As they fall, they collide with other droplets that are smaller and not falling as fast (possibly moving upward with the wind). Often the two drops involved in the collision merge together into a larger drop that falls even faster and collides with more small drops. Collisions between drops can also cause the drops to break up into two or more smaller ones. Though this process can result in some large drops, it also results in very many small drops. These small drops contribute quite a bit to the rain rate but not very much to the reflectivity. The tropical rainfall formula accounts for these small drops, which is why it yields much higher rain rates for the same reflectivity.
The difficulty for meteorologists is often in knowing when to apply the tropical formula and when to apply one of the “normal” ones, because tropical rainfall can occur far from oceans or locations that would normally be considered tropical if there is a warm, humid air mass present (like one would often expect to find in the tropics). The most important characteristics of the air mass that supports tropical rain are high relative humidity through a deep layer, low cloud bases, and a high freezing level. In years past, analysis of these environmental factors was the key to knowing whether to switch to the tropical rain rate formula or not.
However, the recent dual-polarization upgrade allows for better characterization of the drop size distribution by using reflectivity and differential reflectivity (Zdr) together. The differential reflectivity essentially measures the average shape of the particles. Spherical particles have Zdr that is near zero, and particles that are “pancake-shaped” have positive Zdr. A fortunate property of rain drops is that they are spherical when small, but become increasingly “pancake-shaped” as they get bigger, so the Zdr can be used to infer the size of the drops as well. Methods to estimate precipitation that incorporate this information (such as PQPE) can handle both tropical rainfall and “normal” rainfall without having to switch from one formula to another.
Because we know that tropical rainfall has unusually large numbers of small drops, and small drops have low Zdr, we would expect that tropical rainfall would have unusually low Zdr for a given reflectivity. Below are representative reflectivity images from Tropical Depression Bill while it was over Oklahoma (left) and a typical non-tropical convective system over Nebraska (right).
From several times near the times shown for each case, I calculated the mean Zdr for each reflectivity value between 30 and 50 dBZ (the dark green, yellow, and orange colors). These are shown in the figure below. The typical range of Zdr at those reflectivity values is between the thin black lines. As expected, the mean Zdr is considerably lower in the Oklahoma data. Unlike most cases where the Zdr increases as reflectivity increases, in the Oklahoma tropical rain data Zdr is nearly constant between 0.5 and 0.9 dB.
This is another example of how data from dual-polarization radars helps meteorologists identify physical processes occurring in the atmosphere. When this information is used skillfully, it can lead to more flexible algorithms for estimating precipitation.