Lab 7- Dual Polarization: 12/20/12 Milwaukee WI (KMKX) (Tim Calamari and Kassidy Lange)

A major winter storm affected southern Wisconsin and the western Great Lakes region Wednesday

evening through Thursday night, Dec 19th and 20th. This storm rapidly intensified as it moved

northeastward from the Texas/Oklahoma Panhandles toward southern Lake Michigan, eventually

producing widespread heavy snowfall and blizzard conditions across southern Wisconsin. This case

will use radar reflectivity as well as Dual-Pol variables to analyze the event in-depth to determine what

kind of precipitation was experienced during this event and if there are any other meteorological

components that contribute to the overall state of this event. 

Gif 1- Radar Reflectivity values in dBZ valid 12/20/12

Gif 2- Differential Reflectivity (ZDR) values valid 12/20/12

Gif 3- Correlation Coefficient values (CC) valid 12/20/12

Gif 4 - Differential Phase values valid 12/20/12

Use dual-pol variables—Differential  Reflectivity  (ZDR),  Correlation  Coefficient  (CC),  and differential Phase (φDP)—to find the melting layer and to identify particular areas of liquid, melting, and frozen precipitation.  

Upon analyzing the Correlation Coefficient, the Differential Reflectivity, and the Differential Phase of

this event, it can be concluded that a melting layer was absent from this event and the only type of

precipitation observed was frozen. This is to be expected as this event occurred in winter (technically the

day before official winter) which, more often than not, at least in the northern states only frozen

precipitation is observed. Given our initial observations of the event, there is one area that propagates

over the Gurnee IL to Racine/Kenosha area of Wisconsin that has noticeably higher reflectivity values

than the rest of the event. This area also corresponds to slightly lower correlation coefficient values as

well as slightly higher Differential Reflectivity values. Given this, the precipitation in this area is most likely

wet snow aggregates. 

Analyze typical values of ZDR andCC for areas that you identify as a liquid, melting, and frozen.  Do your findings agree with your expectations based on the lecture notes?

This case does not appear to experience any liquid or melting precipitation but seems to only experience frozen precipitation as expected given the time of year this event is occurring. The benefits of this event are that the findings agree with what has been learned about types of precipitation in dual-pol variables.

Choose two locations in the precipitating region and calculate KDPfrom φDPat two different points along the radar beam  (as you outlined in your pre-lab).   Does your calculated value correspond to heavy rainfall or other types of precipitation?

Choosing two locations in the precipitating region, we calculated KDP from φDPat at these locations. In the northeast region of our radar view is where we drew the two locations from. With our first location at a φDPat of 46° and our second location with a φDPat of 13°. Using our equation from lecture 3.4 for KDP, with the range between our two locations of ~5km, we attain a KDP value between our two locations of 3.3°/km. This KDP value indicates a high probability that we have heavy rainfall occurring between our two locations in the northeast portion of our radar view.

What do these dual-pol capabilities allow you to conclude about the drop size distributions for this case?

Having these dual-pol capabilities allows us to gain information from the radar about the shapes and sizes of the targets of interest. With horizontally and vertically polarized radar beams, we are able to deduce an estimate for the drop size distributions for our case. For our case when looking at ZDR, we notice early on in the time loop an area over Chicago over relatively lower ZDR than seen in the surrounding precipitation. This eventually fades away throughout the time loop, and we notice ZDR values in our case near 0 dBz. This dual-pol capability is able to show us that the general precipitation falling while the storm system passes through Wisconsin is rainfall. The area of lower ZDR along with decreased correlation coefficient near Chicago early on in the time loop may very well be mixed precipitation. Once this mixed precipitation is seen to phase out, the majority of our radar view shows rainfall with similar drop size distributions throughout.

What insight into other microphysical details, like orientation and shape, do you gather about your case using the dual-pol variables?

The Dual-Pol capabilities allowed the conclusion to be reached that wet snow aggregates were most likely falling over the Gurnee, Racine, and Kenosha area while possibly drier and smaller snowflakes were falling more or less in the other areas of the observed event. Starting with ZDR, the value of ZDR helps to determine if the objects picked up on the radar have a preferential alignment to the horizontal or vertical. Precipitation that is more spherical in nature will have lower ZDR values as they have no preference for the horizontal or vertical orientation. When viewing the ZDR imagery for this event, higher ZDR values are found over the Kenosha/Racine area while lower values are found in the other areas. This is an indication that the precipitation falling over this area of interest has more preference for the horizontal direction over the vertical direction compared to the other areas. Taking a look at the Correlation Coefficient image, the area of interest over Kenosha/Racine has lower CC values compared to the rest of the radar image. CC is an indication of how well the vertical and horizontal orientations correlate. Higher CC values relate to precipitation that is rounder in nature. With the lower values of CC over the area of interest, it can be concluded that the precipitation over this area strayed from the spherical realm more than the precipitation viewed in other areas where the precipitation was viewed to be more spherical in nature. Given this information, it can be assumed that the majority of this event experienced smaller, close to spherical frozen precipitation while the area over Kenosha/Racine most likely experienced larger wet snow aggregates.

How do dual-pol variables behave in areas of ground clutter?

The dual-pol variable with the best view of ground clutter is shown to be the correlation coefficient.

Near the base of the radar, correlation coefficient values of less than 0.5 are seen in areas of ground

clutter around the radar. The precipitation that is falling in that same location shows up on the correlation

coefficient plot as values near 1. The distinction between ground clutter and precipitation is visualized

best when using the correlation coefficient dual-pol variable.

Is the freezing level constant in time?  (Probably more applicable to cases with 2+ hours of data)

This observed case shows just about exactly 2 hours of data. It is safe to assume that the freezing level remains constant with time and is situated at approximately the surface. 

Figure 1- Atmospheric Sounding taken over Davenport IL, valid 00Z 12/20/12

Figure 2- Atmospheric Sounding taken over Green Bay WI, valid 12/20/12

Is the freezing level constant throughout the radar coverage area?

Looking at soundings from Davenport  IL and Green Bay WI ( the southern and northern tips of the event respectively) the freezing level appears to be at the surface in Green Bay to approximately 950 mb over Davenport. This is a good indication that the precipitation is frozen all the way throughout the layer which is supported by the absence of a brightband in the correlation coefficient image of our event. Although one thing to note about the slight difference in the freezing level is that it is slightly higher to the south of the precipitation event. This knowledge could help to interpret the wet aggregate snow experienced over southeastern Wisconsin/ northeastern Illinois. Since the freezing level over Davenport is experienced at about 950 mb, the precipitation around this region may have had the chance to melt slightly before reaching the surface (as temperatures at the surface are slightly above freezing). This melting due to the higher freezing layer could have aided in the processes of the creation of the large wet aggregates in this area of interest. 

Are the findings consistent with your understanding of the synoptic situation?

Using information gathered from the NWS this event was associated with a low-pressure system that just fell short of “bomb cyclogenesis”. Precipitation events often associated with bomb cyclogenesis bring dramatic amounts (sometimes types depending on the season in which it occurs) of precipitation which holds true with the event observed here. A cross-section taken through the event shows that this event extended fairly deep into the atmosphere signifying that this event was characteristic of convective precipitation. Noted by the CIMSS Satellite Blog, this event experienced “thundersnow” which is a snowfall event characterized by thunder and lightning! This information is not immediately obvious looking at the soundings taken at 6pm on the 20th.

Figure 3- Time series plot of Temperature (Fahrenheit) and Precipitation (inches) over Milwaukee WI, valid 12/20/12

Use the archive http://www.wunderground.com/historyto find surface data if relevant to relate your understanding of the radar observations to things like surface temperature, surface precipitation type, and surface rain intensity.

Taking a look at archived data from Wunderground, the time of interest for this event is approximately

3pm- 5pm. During this time period, the temperature dramatically falls off from about 40℉ to 32℉ at 5pm.

The temperatures observed during this time period are not particularly conducive to frozen precipitation

conditions. This observation supports the hypothesis that some melting of frozen precipitation occurred

over this area causing the precipitation to fall as wet aggregates compared to the dryer snowfall seen

throughout the rest of the observed event. Additionally, during this time period, the precipitation increases

owing to the fact that the precipitation is most likely falling as snow which is less dense and accumulates

faster.

Part II: Hail identification using dual-pol

This section uses various dual-pol variables to identify the regions of hail during a southeastern Wisconsin severe weather event.

Gif 5- Radar Reflectivity (in dbZ) values valid 8/7/12

Gif 6- Differential Reflectivity (ZDR) values valid 8/7/12

Gif 7- Correlation Coefficient (CC) values valid 8/7/12

Load the August 7,  2012, Milwaukee case (KMKX) and focus on the time frame from 20:49Z to21:19Z. Using relevant dual-pol observations, identify which storm cells are likely hailing and which are likely not.  You may want to compare your findings to SPC storm reports, but remember these reports only include hail one inch or greater. 

Hail in the radar has the following characteristics: reflectivity, ZDR, and Correlation Coefficient.

Since Hail is made up of ice, values in the reflectivity will be very high when hail is present. Since Hail

forms spherically due to the tumbling it experiences hail on ZDR maps will appear as very low values

due to the fact that it has no preference in the horizontal nor the vertical orientation. Finally, in Correlation

Coefficient maps, hail will appear as very high values due to the fact that hail correlates significantly in

the vertical and horizontal orientation since it is generally round. Given this information, looking at the

images generated for this case, there is hail present over Washington and Ozaukee county trailing into

Lake Michigan while normal precipitation appears to be occurring everywhere else.