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  • 2020-2022  (5)
  • 1
    Publication Date: 2020-03-13
    Description: It has been theorized that thundersnow (TSSN) occurs in conjunction with heavy snowfall rates and in geographical regions where heavy-banded snow occurs more frequently. This study aims to objectively and quantitatively identify characteristics associated with TSSN to improve the situational awareness of heavy snowfall and associated hazards. The Geostationary Lightning Mapper (GLM), National Environmental Satellite Data and Information Services (NESDIS) merged Snowfall Rate (mSFR) product, and surface observations were utilized to characterize snowfall accumulation, snow-to-liquid ratio (SLR) values, and radar characteristics of heavy snowfall events from a GLM perspective. When at least 2 in. of snowfall accumulation occurred, areas with TSSN flashes identified by the thundersnow detection algorithm (TDA) were likely to receive, on average, a total of 24.5 cm (9.6 in.) of snowfall. TSSN was more likely to occur in snowfall rates less than 2.54 cm h−1 (1 in. h−1) and be associated with snow-to-liquid ratio (SLR) values between 8:1 and 10:1. It was determined that TSSN flashes observed by GLM occurred in isothermal reflectivity values less than 30 dBZ and average spatial offsets of 131 km between the lightning flash location and the heaviest snowfall rates were observed. GLM flashes in proximity of National Lightning Detection Network cloud-to-ground flashes and tall structures were found to be statistically different (p 〈 0.05) regarding snowfall rates, SLR values, and various Multi-Radar Multi-Sensor variables compared to other TSSN flashes. It was inferred that tower TSSN flashes, on median, were more likely to initiate within light-to-moderately rimed snowfall. Last, a heavy snowfall event was analyzed to demonstrate the capability of these products in identifying storm characteristics associated with TSSN.
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
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  • 2
    Publication Date: 2020-03-10
    Description: In this paper, we describe how researchers and weather forecasters work together to make satellite sounding data sets more useful in severe weather forecasting applications through participation in National Oceanic and Atmospheric Administration (NOAA)’s Hazardous Weather Testbed (HWT) and JPSS Proving Ground and Risk Reduction (PGRR) program. The HWT provides a forum for collaboration to improve products ahead of widespread operational deployment. We found that the utilization of the NOAA-Unique Combined Atmospheric Processing System (NUCAPS) soundings was improved when the product developer and forecaster directly communicated to overcome misunderstandings and to refine user requirements. Here we share our adaptive strategy for (1) assessing when and where NUCAPS soundings improved operational forecasts by using real, convective case studies and (2) working to increase NUCAPS utilization by improving existing products through direct, face-to-face interaction. Our goal is to discuss the lessons we learned and to share both our successes and challenges working with the weather forecasting community in designing, refining, and promoting novel products. We foresee that our experience in the NUCAPS product development life cycle may be relevant to other communities who can then build on these strategies to transition their products from research to operations (and operations back to research) within the satellite meteorological community.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
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  • 3
    Publication Date: 2020-01-24
    Description: No abstract available
    Keywords: Meteorology and Climatology
    Type: MSFC-E-DAA-TN76613 , American Meteorological Society (AMS) Annual Meeting; Jan 12, 2020 - Jan 16, 2020; Boston, MA; United States
    Format: application/pdf
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  • 4
    Publication Date: 2021-10-18
    Description: Using gridded and interpolated Derived Motion Winds from the Advanced Baseline Imager (ABI), a Lagrangian cloud-feature tracking technique was developed to create, and document trajectories associated with electrified snowfall and changes in cloud characteristics leading up to the initiation of lightning, respectively. This study implemented the thundersnow detection algorithm and defined thundersnow initiation (TSI) as the first group in a flash detected by the Geostationary Lightning Mapper when snow was occurring. Ten ABI channels and four multispectral (e.g., red-green-blue–RGB) composites were analyzed to investigate characteristics that lead up to TSI for 16,644 thundersnow (TSSN) flashes. From the 10.3 μm channel, TSI trajectories were associated with a median decrease of 12.2 K in brightness temperature (TB) one hour prior to TSI. Decreases in the reflectance component of the 3.9 μm channel indicated that TSI trajectories were associated with ice crystal collisions and/or particle settling at cloud top. The Nighttime Microphysics, Day Cloud Phase Distinction, Differential Water Vapor, and Airmass RGBs were examined to evaluate the microphysical and environmental changes prior to TSI. For daytime TSI trajectories, the predominant colors associated with the Day Cloud Phase Distinction RGB transitioned from cyan to yellow/green, physically representing cloud growth and glaciation at cloud top. Gold/orange hues in the Differential Water Vapor RGB indicated that some trajectories were associated with dry upper-level air masses prior to TSI. The analysis of ABI characteristics prior to TSI, and subsequently relating those characteristics to physical processes, inherently increases the fundamental understanding and ability to forecast TSI; thus, providing additional lead-time into changes in surface conditions (i.e., snowfall rates).
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
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  • 5
    Publication Date: 2021-08-25
    Description: Hyperspectral infrared satellite sounding retrievals are used to examine thermodynamic changes in the tropical cyclone (TC) environment associated with the diurnal cycle of radiation. Vertical profiles of temperature and moisture are retrieved from the Suomi National Polar–orbiting Partnership (S–NPP) satellite system, National Oceanic and Atmospheric Administration (NOAA)–20, and the Meteorological Operational (MetOp) A/B satellite system, leveraging both infrared and microwave sounding technologies. Vertical profiles are binned radially based on distance from the storm center and composited at 4–hr intervals to reveal the evolution of the diurnal cycle. For the three cases examined – Hurricane Dorian (2019), Hurricane Florence (2018) and Hurricane Irma (2017) – a marked diurnal signal is evident that extends through a deep layer of the troposphere. Statistically significant differences at the 95% level are observed in temperature, moisture, and lapse rate profiles, indicating a moistening and destabilization of the mid to upper troposphere that is more pronounced near the inner core of the TC at night. Observations support a favorable environment for the formation of deep convection caused by diurnal differences in radiative heating tendencies, which could partially explain why new diurnal pulses tend to form around sunset. These findings demonstrate that the diurnal cycle of radiation affects TC thermodynamics through a deep layer of the troposphere, and suggest that hyperspectral infrared satellite sounding retrievals are valuable assets in detecting thermodynamic variations in TCs.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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