Assessing Climatological Impacts of Precipitation and Temperature at the NCAR Marshall Field Site from 1994-2018

The Marshall Field Site, located about ten miles southeast of Boulder, Colorado, is home to various precipitation and wind testing instruments to create data for the National Center for Atmospheric Research (NCAR). Precipitation data has been recorded for nearly 30 years using three main types of instruments, the Ott Pluvio II rain gauge, the Geonor 16” Single Alter gauge, and the Geonor double fence intercomparison reference (DFIR) gauge located in the southern region of the Marshall Site. The Ott Pluvio II gauge has data ranging back to 2012, the 16” Geonor dates back to 1994, and the DFIR Geonor dates back to 1999. The 16 inch Geonor is cheaper to install and takes up less space but the DFIR Geonor is more accurate at detecting snowfall due to its dual layer of fencing to keep the wind out. To further understand what trends the precipitation has caused over the years, data will be compared for each month of each year side by side to show the decline that has occurred over the last three decades. The data from the devices is sent to the Marshall site database, where the precipitation amounts are recorded in a Microsoft Excel spreadsheet and organized into charts or other means of visualization. The maximum and minimum amount of precipitation recorded each month is used to determine the average precipitation for the entire month. Results from the study have shown that the maximum precipitation in each month has decreased steadily over the years. Precipitation was much more spread out and normalized during the earlier years than the more recent ones. Data shows the precipitation trends for the Denver-Boulder region of Colorado, but it is likely that similar climates in the United States have followed the same patterns. Further data could show the trend the precipitation follows over the next 10 to 20 years

Spatial variation of snowfall accumulation on Antarctica’s Ross Ice Shelf

Antarctica is a relatively understudied area, where we primarily use the Antarctic Mesoscale Precipitation System (AMPS) weather model to estimate and predict snowfall amounts. Understanding snow accumulation in Antarctica may help us calculate the snowmass budget of its ice sheets and adjust estimates of sea level rise due to melting. In this study, automated weather instruments were installed in November 2017 to measure liquid water equivalent (LWE) amounts of snowfall across four field sites on the Ross Ice Shelf during an 8-month period and used to determine variation of snow accumulation. The raw Pluvio2 data for all sites were plotted and compared, while snow events for each site were identified and sorted based on LWE and date. Our study found that the two sites more inland of the Ross Ice Shelf accumulated less snowfall, likely due to terrain effects of local, snowfall-enhancing upslope effects, suggesting that ice sheet growth may be greater near Antarctica’s coastlines. Snow events were often followed by sublimation events, appearing greatest in summer and minimal in winter. This research provides novel insights on accumulation trends and serves as a model for the potential of future automated weather systems in Antarctica

A First Look at Sublimation Rates in Toss Island Region, Antarctica

70% of Earth’s fresh water is held in Antarctica ice sheet. If the sheet melts, it has the potential to raise global sea levels by 190 feet (Klekociuk and Wiennecke, 2016). As the climate changes, it is imperative that to understand precipitation systems of Antarctica in order to measure and predict weather around the world. One aspect of precipitation events that we do not understand fully in Antarctica is sublimation. Data was collected from four Ott Pluvio Precipitation Gauges with Belfort Double Alter Shields placed in and around the Ross Ice Shelf from November of 2017 to present. An R program was created to analyze and visualize periods of sublimation. A sublimation event was defined as a period at least 6 hours long that had statistically significant monotonic decreasing trend based on the Mann-Kendall Test. The rate of sublimation was then estimated using a Sen’s Slope calculation. Sublimation was detected in 60 to 70 percent of summer months and 30 to 40 percent in winter months, with median summer sublimation rates from .006 to .014 mm/hr and median winter sublimation rates from .003 to .006 mm/hr. Monthly sublimation spiked in the months of December, January, and February. These initial findings on Sublimation in Antarctica can be used to analyze the relationship between sublimation and wind, humidity, and temperature. Additionally, these sublimation estimates can be used in combination with precipitation time series to find the percentage of snowfall returning to the atmosphere via sublimation

Snowfall Simulator Quick-Release Retrofit

In the early 1990s, UCAR fabricated a snowfall simulator that they have used to test deicing fluids for aircraft, among other applications. Ice cores are actuated by a stepper motor and travel along a linear guide rail feeding it into an auger bit. This bit shaves the ice core, creating conditions that simulate snowfall. Currently, the simulator is in satisfactory operating condition, however upgrades have been proposed to make the simulator more user friendly. When one ice core has been exhausted, the motor controlling the carriage must be actuated in reverse to move the mount along a lead screw back to reloading position, which can take upwards of three minutes. The purpose of this project is to retrofit the simulator with a quick release system that allows for the user to manually unlock the carriage and quickly pull it back into the reloading position, decreasing turn around time in the testing process. The final design is a symmetric 2-clamp system that is installed directly onto the ice core mount. The two clamps engage the lead screw from the left and the right. To reload the ice cores, the user must simply lift the Destaco clamps on each side and pull the entire carriage back to the original position at the front of the simulator

Process of Developing the Artificial Snow Machine System

In order to test different types of anti-icing fluids that are used on aircraft surfaces prior to take off, it is necessary to develop a machine that artificially generates snow. Deicing aircraft is a two-step process that consists of applying both deicing and anti-icing fluids. Deicing fluids are applied to eliminate accumulated ice on aircraft surfaces that could obstruct proper airflow. Anti-icing fluids are then applied to prevent the additional accumulation of frost, ice, and/or snow for a period of time known as the endurance time. The endurance time is the duration the anti-icing fluid remains effective on the aircraft surface. Results from the snow machine tests have shown that it accurately replicates natural snowfall, and allows for repeated, controlled-environment testing throughout the year. Variables controlled include wind speed, air temperature, and liquid-water equivalent snowfall (LWE) rates. The machine is also affordable and more efficient than outdoor testing. In order to continue studying the factors that influence endurance time and accumulation rates, the design of the existing snow machine has been modified to increase effectiveness and efficiency. Aluminum struts make up the framework of the snow machine which measures 2.75m tall with a base of 0.91m by 0.66m and are bolted at the midpoints for structural integrity. The sides are made of clear Plexiglass which slide into the frame rather than being attached from the outside with hinges. This eliminates excessive construction material and provides a better appearance. The top of the machine is cut into 45° angles to evenly fit and level the pieces of struts, whereas, the previous model had overlapping struts that formed gaps between overlaid pieces of the frame. Finally, wheels were added for easy transport. These modifications, along with software improvements are targeted for additional testing in the near future

A 12 Year Temperature and Wind Speed Climatology for the Marshall Field Site near Boulder Colorado 2006-2018

The Denver-Boulder region in Colorado is located on the border of two distinct weather regimes, the Rocky Mountains to the west and the Great Plains to the east. This region experiences inclement and sometimes unpredictable weather events, which can be accompanied by changes in temperatures and wind speed. To better understand the climate for the region, nearly 12 years of temperature and wind speed data from the Marshall Field Site were analyzed to assess changes in these parameters over time. Methods: Temperature recordings were primarily taken from a CS-500L probe, with data gaps filled in from a Lufft WS600 and a Hotplate sensor. Wind speed was primarily recorded from a R.M. Young Wind monitor with data gaps filled in from a Lufft WS600 and a Hotplate sensor. All measurements occurred at the Marshall Field Site near Boulder, CO. Raw temperature and wind speed data values were recorded by the various instruments once per minute. A script was developed in the Perl scripting language to filter bad data, and to find and calculate the monthly minimum, maximum, and average values for both temperature in °C and wind speed in m/s. Available data spans from January 01, 2006 to June 31, 2018 Findings: Yearly average temperature has been mostly steady. 2012 had the highest average maximum temperature. Monthly average temperatures are generally increasing each year in the spring and fall. Average wind speeds are generally decreasing for all months. Not much overall change since 2006 in average low temperature extremes. Autumn low temperatures are getting less extreme. Wind speed extremes have decreased slightly for all months on average. 138 months is not enough time show clear patterns in climatic cycles. At least 20-30 years of data might begin to show more clear patterns and/or stronger trends even with some missing monthly data points

Testing and Comparing Precipitation Algorithms

An algorithm (Alg. 2) was created to calculate precipitation rates and to predict weather events using raw data from a weather event simulator for the duration of two months. The Alg. 2’s results from the simulation were compared to the results of the algorithm that currently produces the data for the Marshall Field Site Webplots (Alg. 1) using a Pierce Skill Score(PSS) as a performance comparison. The two algorithms were also compared using the precipitation accumulation data, acquired from the Tall Double Fence Intercomparison Reference(DFIR) shielded GEONOR gauge in the Marshall field site, 1 April – 30 April 2017. The precipitation rate results from the two algorithms were then compared visually for this data set. The data acquired from these two comparisons showed that the adjusted algorithm had a Pierce Skill Score for predicting weather events that was 8.99% higher than the Alg. 1, it was quicker at identifying weather events, and had a reliable and accurate precipitation rate detection, but had a higher false alarm rate

Assessing the Origin of Noise in the Precipitation Gauge Geonor T-200B

The Geonor T-200B is an all-weather precipitation gauge utilized by the Research Applications Laboratory (RAL) under the University Corporation for Atmospheric Research (UCAR) and the National Center for Atmospheric Research (NCAR). RAL has been dealing with a persistent issue of noise within the Geonor Devices during non-precipitation events. When there is not precipitation occurring, the data reading off the Geonor would be expected to be a constant value, as no precipitation is being collected. However, the device is producing unaccounted variation (noise) causing tremor like lines to appear in the data. The noise in the data is an issue for RAL because it makes it complicated to pinpoint the exact beginning and end of a precipitation event. Many airports use the Geonor sensors to predict unsafe flying conditions. Being able to pinpoint the beginning and ending weather patterns during storms would lead to more accurate and efficient airport scheduling. To isolate the source of the undesired noise two correlation experiments were run on the Geonor gauges. The experiments were conducted at the NCAR Marshal Field test site. The first test was to understand the effect of temperature change on the noise. The second test provided assess the effect of electrical interference on the noise in the device. The change in temperature correlated 63% to a change in frequency from the Geonor. The electrical interference test provided a reduction of variation in the frequency by two hertz. From the result of the study it can be stated that a change in temperature has a great effect on the noise from the Geonor and causes diurnal variation in the data. The electrical interference test showed promising results as a possible origin of the noise. Further experiments should be conducted to prove that adding an electrical shield reduces the noise within the device. Another source of noise to asses in further experiments would be the effect of temperature on the electrical panel that collects the data

Analyzing the Atmospheric Conditions that Caused Two Unexpected Tornado Events

On May 25, 2016 and July 7, 2016, two individual tornadic storms occurred near Chapman, Kansas and Eureka, Kansas. Neither of these tornadic storms was forecast to occur by the National Oceanic and Atmospheric Administration’s (NOAA) Storm Prediction Center (SPC). In this research project, data from several online sources were analyzed to identify the atmospheric conditions around the times and near the concerned areas where the tornadoes spawned. Identifying and understanding the causes of these tornadoes will help future meteorologists better predict possible tornadoes in the future. Data was obtained from meteorological maps of surface pressure, temperature, dew-point temperature, wind speed and direction at the surface and aloft, and atmospheric soundings from nearby weather balloon locations. Areas of low pressure, cold fronts, warm fronts, dry-lines were identified by the process of analyzing the meteorological maps. Other atmospheric conditions that lead to the organization of the thunderstorms related to the tornadoes were also analyzed; namely, instability, vertical wind shear, moisture, and causes for lifting of air. Afterwards the focus was to determine the severity of the thunderstorms and how the tornadoes formed; doing so allows for the tornadic environments to be analyzed. For the Chapman tornado, the interactions of a new storm that initiated on the western flank of the primary storm likely played a role in the intensity of the tornado at various points along its path. For the Eureka tornado, interactions with the surface warm front likely provided the storm with necessary boundary-layer vorticity to support the tornado