Research

ASCII 2012

My graduate research work with Katja Friedrich through my Research Assistantship includes analyzing observational data from a large array of in-situ and remote sensing instruments, including a microwave radiometer, rain gauges, mobile rawinsondes (MGAUS), a dual-polarization Doppler On Wheels (DOW) X-band radar, a PARSIVEL disdrometer, the airborne W-band Wyoming Cloud Radar (WCR), and a vertically-pointing Ka-band Micro Rain Radar (MRR). The data was collected during the AgI Seeding Cloud Impact Investigation (ASCII) 2012 field project. This project aims to "study the effect of ground-based glaciogenic cloud seeding on snowfall and snow particle characteristics using three different radar systems and snow rate and snow imaging probes deployed at a remote mountain research station" in Wyoming (University of Wyoming). The field study was performed over the winter of 2012, from January through March. My research aims at investigating the natural progression of these winter orographic snow storms, specifically the small-scale dynamical and microphysical mechanisms at play. Two of these small-scale mechanisms include turbulence and wintertime convection. Convection is not well resolved in computer models, let alone in unobserved mountainous environments during winter. It is also well known that baroclinic storms do not follow traditional synoptic evolutions in the mountainous terrain of the Western US. Furthermore, weather forecast models do not resolve terrain well enough to accurately forecast small-scale dynamical mechanisms that generate precipitation in the Rocky Mountains. I am interested in determining the effects of small-scale mechanisms in this unique orographic mountain environment on the three-dimensional precipitation structure and surface snowfall characteristics. My research will add to our current understanding of what dynamical and microphysical mechanisms are important for increasing the fallout of precipitation within these inland mountainous winter environments.

Figures 1 and 2 below show the layout of the ASCII 2012 field study. A breakdown of some of the analysis I have performed is detailed below along with some graphics of the results.

Figure 1: A general diagram showing the location of the ASCII 2012 field campaign. Key locations for my current research include the Battle Pass site on the peak of the Sierra Madre mountain range in Wyoming and the Dixon airport where atmospheric soundings were deployed. The Doppler on Wheels (DOW) dual-pol X-band radar was located at Battle Pass, right next to the Battle Town site that housed a suite of instruments that I have used in my research (see Figure 2 below). Image from Bart Geerts, University of Wyoming.

Figure 2: A close up view of the Battle Pass and Battle Town instrument site. Notice the DOW radar was positioned right on the Continental Divide. Image from Bart Geerts, University of Wyoming.

SURFACE ANALYSIS

I used data from a surface weather station at Dixon, Wyoming as well as surface data from the Doppler on Wheels (DOW) mesonet at the top of the mountain (Battle Pass) to create plots of temperature, wind speed, wind direction, and relative humidity. I also used data from the microwave radiometer stationed at Battle Pass to plot Integrated Liquid Water (ILW) and Integrated Water Vapor (IWV). Cross-barrier wind speeds, the component of the wind perpendicular to the axis of the mountain range, were also calculated and plotted. The surface analysis gives us an overview of the meteorological conditions over the course of each IOP. These plots are shown below for one intensive observational period (IOP).

Figure 3: Plots of ambient temperature, wind speed, wind direction, Integrated Liquid Water, relative humidity, and Integrated Water Vapor over the IOP 2 event from 1200 to 2245 UTC on January 16, 2012. Data incorporated into this graphic come from the DOW 7 mesonet, the Vaisala WXT520 Weather Transmitter (hotplate data), and the passive microwave radiometer located at the Battle Pass site as well as surface weather data from the nearby town of Dixon (Dixon surface data). Can you spot the passage of a front in the plot?

STABILITY ANALYSIS

Typical atmospheric stability variables including Bulk Richardson Number (Ri), Brunt Vaisala Frequency (BVF), and Froude Number (Fr) were calculated for each IOP. BVF is a good variable to determine whether the atmosphere is stable (BVF > 0) or unstable (BVF < 0). Froude Number is used to determine whether atmospheric flow goes over the mountain unperturbed (Fr > 1), is blocked by the mountain (Fr < 1), or may induce gravity waves (Fr ~ 1). Both a dry and moist value were computed assuming dry air motions and saturated air motions, respectively. These stability variables were calculated using two different data sources. I used the surface data from Dixon, Wyoming and the DOW mesonet data to calculate continuous Ri, BVF, and Fr over the entire time of the IOP, and I used the soundings deployed at Dixon, Wyoming to calculate Ri, BVF, and Fr over the same elevation range but at a much larger sampling interval. I used the elevation at Dixon and the elevation of the DOW radar at the Battle Pass site as the two heights for calculating these stability variables. The results of this analysis for BVF and Fr are shown for one IOP in the plot below.

Figure 4: Sounding-based and surface-based stability plots of Brunt Vaisala Frequency and Froude Number over the IOP 2 event from 12:00 to 22:45 UTC on January 16, 2012. The sounding-based results are marked with a black X and the surface weather based results are denoted by the solid lines. Stability based on dry air motions are shown by the red lines, whereas stability based on moist air motions are in blue. Surface data from both the DOW 7 mesonet and the Radiometer were used due to a problem with the DOW 7 mesonet's pressure measurements.

DOW X-BAND RADAR ANALYSIS

I adapted a fuzzy logic algorithm from Gourley (2007) to remove clear air returns and ground clutter from our DOW dual-pol X-band radar dataset from ASCII 2012. Below are a set of radar reflectivity plots for one scan showing the raw reflectivity (on the left) and the clutter-filtered reflectivity (on the right). Notice two main areas of ground clutter are removed, near the radar to the WNW several mountain ridges are present and far from the radar to the east and northeast the next mountain range (Medicine Bows) can be seen.

Figure 5: The plot on the left shows a 0 degree elevation scan prior to ground clutter and clear air removal. The plot on the right shows the same scan after ground clutter and clear air removal using a dual-polarization fuzzy logic scheme adapted from Gourley (2007). Note most of the data to the North and South is missing due to beam blockage, a common issue when trying to collect radar data in mountainous regions.

After ground-clutter removal and interpolating the polar radar data to Cartesian grids using NCAR's Radx programs, I created Hovmoller plots of the DOW reflectivity over each IOP. These plots show the progression of cells of heavy snowfall over the mountain range. The reflectivity values plotted are maximum reflectivity above 3 km MSL and within +/- 20 km of the cross-barrier transect (232 degrees from North). The plot below shows an example Hovmoller diagram for one of the IOPs (IOP02).

Figure 6: A Hovmoller diagram for IOP 2 on January 16, 2012 showing maximum reflectivity along the cross-barrier transect of the target mountain range above 3 km MSL and within 20 km North/South of the transect through the DOW radar location at Battle Pass. The plot on the right shows the maximum reflectivity value within this same domain, but as a function of altitude. The plot on the left shows precipitation accumulation from a Geonor precipitation gauge located at Battle Pass. The plot on the bottom shows the cross-barrier terrain profile, which transects the radar location at X = 0 km.

I also plotted the maximum reflectivity seen over each (x,y) horizontal grid domain and over the entire IOP time period. These plots give an idea of where the heaviest precipitation fell, at least within the well-observed regions to the West and East of the radar that were not blocked by mountain peaks. Typically with orographic snowfall we would expect heavier precipitation at the mountain top and lighter precipitation in the upwind and downwind valleys. This orographic enhancement signature is not always present, though. Convective cells that form upwind of the mountain range and the passage of fronts sometimes complicate the overall orographic enhancement signature. This is the case in IOP2 plotted below.

Figure 7: Maximum DOW reflectivity between 1139 - 2249 UTC on 16 January 2012, during IOP2. The plot on the right shows maximum reflectivity with height within +/- 20 km East and West of the DOW longitude, and the plot on the bottom shows maximum reflectivity with height within +/- 20 km North and South of the DOW latitude. A passing cold front with heavy snowfall caused the high reflectivity values (> 30 dBZ) during this period, and convection early in the IOP caused the towering regions of high reflectivity. Elevation contours (2.1 - 3.6 km MSL) are overplotted every 300 m with grey shades, low elevation (2.1 km MSL) dark grey to high elevation (3.6 km MSL) light grey.

MRR KA-BAND RADAR ANALYSIS

I plotted time-series images of Micro Rain Radar (MRR) reflectivity, Doppler velocity, and spectrum width. The MRR is a vertically-pointing Ka-band radar, and it was located at Battle Pass with the DOW X-band radar at 3,024 meters elevation. The plot below shows an MRR time-series from one of the IOPs with microwave radiometer-derived temperature profiles overplot.

Figure 8: Micro Rain Radar (MRR) reflectivity, Doppler velocity, and spectrum width observations during IOP2 on 16 January 2012 above Battle Pass. Microwave radiometer-derived temperature profiles are overlaid on the MRR data. Issues with the instrument prevented reliable data before 1800 UTC.

WYOMING CLOUD RADAR (WCR) ANALYSIS

Figure 9 below shows an analyzed cross-barrier flight leg over the Sierra Madre mountain range during IOP2 on 16 January 2012. Reflectivity and Doppler velocity profiles observed by the WCR are in the top two panels. The bottom two panels show temperature, liquid water content (LWC), vertical wind velocity, and water vapor mixing ratio observed from instruments on the University of Wyoming King Air (UWKA) aircraft during the cross-barrier flight. The wind during this flight was roughly aligned with the flight direction (left to right). Notice how updrafts are observed upwind of the mountain and downdrafts observed downwind. This indicates the air flowed up and over the mountain range during this time. Also note that the highest reflectivity is above the ground on the downwind side. This is a convective signature, and the lifted air upwind likely released the convection and allowed snow particles to form quickly.

Figure 9: WCR reflectivity is plotted in the top panel, WCR Doppler velocity is plotted in the second panel from the top, in-situ temperature and liquid water content (LWC) are plotted on the third panel from the top, and in-situ vertical air velocity and water vapor mixing ratio are plotted on the bottom panel. Note that the WCR data is from vertically-pointing antennas facing upward and downward on the UWKA aircraft. The underlying terrain is indicated by the white boundary in the top two panels. The flight path is indicated by the data void (black region) 200 m thick around 4 km MSL. The flight time was between 1601 - 1609 UTC on 16 January 2012 during IOP2.

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