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  • 1
    In: Journal of Operational Meteorology, National Weather Association
    Abstract: Several historic rainfall and flooding events associated with Atlantic Basin tropical cyclones have occurred in recent years within the conterminous United States: Hurricane Joaquin (2015) in early October over South Carolina; Hurricane Harvey (2017) in late August over southeastern Texas; Hurricane Florence (2018) in September over North Carolina; and Tropical Storm Imelda (2019) in September, again over southeastern Texas. A common attribute of these events includes a dramatic transition from dry soils to exceptional flooding in a very short time. We use an observations-driven land surface model to measure the response of modeled soil moisture to these tropical cyclone rainfall events and quantify the soil moisture anomalies relative to a daily, county-based model climatology spanning 1981 to 2013. Modeled soil moisture evolution is highlighted, including a comparison of the total column (0-2 m) soil moisture percentiles (derived from analysis values) to the 1981-2013 climatological database. The South Carolina event associated with Hurricane Joaquin resulted in a sudden transition from severe drought to significant flooding in the span of a few days, due to locally 700+ mm of rainfall. The prolonged heavy rainfall associated with Hurricane Harvey resulted in record soil moisture values well in excess of the tail of the climatological distribution. The soil moisture west of the Houston, Texas, metropolitan area was anomalously dry prior to Harvey, but quickly transitioned to near saturation in the top 1 m, while east of the Houston area antecedent soil moisture values were more moist prior to the local 1200+ mm of rainfall and catastrophic flooding in the Beaumont/Port Arthur area. Hurricane Florence led to widespread 500-700+ mm of rainfall in North Carolina, and another dramatic transition from anomalously dry conditions to record wetness. Once again, with Tropical Storm Imelda, portions of southeastern Texas experienced extreme rainfall amounts up to 1000+ mm, resulting in another sharp transition from drought conditions to extreme flooding in 〈 3 days. An experimental forecast soil moisture percentile is presented for the Imelda event, showing the potential to increase situational awareness for upcoming flooding episodes, along with a discussion of how an ensemble-based approach could be explored to address forecast model error and uncertainty.
    Type of Medium: Online Resource
    ISSN: 2325-6184
    Language: English
    Publisher: National Weather Association
    Publication Date: 2021
    Location Call Number Limitation Availability
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  • 2
    In: Journal of Operational Meteorology, National Weather Association
    Abstract: Several historic rainfall and flooding events associated with Atlantic Basin tropical cyclones have occurred in recent years within the conterminous United States: Hurricane Joaquin (2015) in early October over South Carolina; Hurricane Harvey (2017) in late August over southeastern Texas; Hurricane Florence (2018) in September over North Carolina; and Tropical Storm Imelda (2019) in September, again over southeastern Texas. A common attribute of these events includes a dramatic transition from dry soils to exceptional flooding in a very short time. We use an observations-driven land surface model to measure the response of modeled soil moisture to these tropical cyclone rainfall events and quantify the soil moisture anomalies relative to a daily, county-based model climatology spanning 1981 to 2013. Modeled soil moisture evolution is highlighted, including a comparison of the total column (0-2 m) soil moisture percentiles (derived from analysis values) to the 1981-2013 climatological database. The South Carolina event associated with Hurricane Joaquin resulted in a sudden transition from severe drought to significant flooding in the span of a few days, due to locally 700+ mm of rainfall. The prolonged heavy rainfall associated with Hurricane Harvey resulted in record soil moisture values well in excess of the tail of the climatological distribution. The soil moisture west of the Houston, Texas, metropolitan area was anomalously dry prior to Harvey, but quickly transitioned to near saturation in the top 1 m, while east of the Houston area antecedent soil moisture values were more moist prior to the local 1200+ mm of rainfall and catastrophic flooding in the Beaumont/Port Arthur area. Hurricane Florence led to widespread 500-700+ mm of rainfall in North Carolina, and another dramatic transition from anomalously dry conditions to record wetness. Once again, with Tropical Storm Imelda, portions of southeastern Texas experienced extreme rainfall amounts up to 1000+ mm, resulting in another sharp transition from drought conditions to extreme flooding in 〈 3 days. An experimental forecast soil moisture percentile is presented for the Imelda event, showing the potential to increase situational awareness for upcoming flooding episodes, along with a discussion of how an ensemble-based approach could be explored to address forecast model error and uncertainty.
    Type of Medium: Online Resource
    ISSN: 2325-6184
    Language: English
    Publisher: National Weather Association
    Publication Date: 2021
    Location Call Number Limitation Availability
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  • 3
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 13 ( 2022-07-12), p. 5287-5308
    Abstract: Abstract. As a component of the National Aeronautics and Space Administration's (NASA's) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for the PyeongChang 2018 Olympic and Paralympic Winter Games' (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January–March 2018. In this study, the retrieved ocean surface meteorological products – 2 m temperature, 2 m specific humidity, and 10 m wind speed – were assimilated into a regional numerical weather prediction (NWP) framework. This explored the application of these observations for two heavy snowfall events during the ICE-POP 2018, on 27–28 February and 7–8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high-resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, a significantly positive influence of the retrieved surface observation was found for the March case, with improved quantitative precipitation forecasts and reduced errors in temperature forecasts. A slightly smaller yet positive impact was also found in the forecast for the February case.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2456725-5
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  • 4
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 23, No. 16 ( 2023-08-30), p. 9613-9635
    Abstract: Abstract. We evaluate two high-resolution Lake Michigan air quality simulations during the 2017 Lake Michigan Ozone Study campaign. These air quality simulations employ identical chemical configurations but use different input meteorology. The AP-XM configuration follows the U.S. Environmental Protection Agency (EPA)-recommended modeling practices, whereas the YNT_SSNG employs different parameterization schemes and satellite-based inputs of sea surface temperatures, green vegetative fraction, and soil moisture and temperature. Overall, we find a similar performance in the model simulations of hourly and maximum daily average 8 h (MDA8) ozone, with the AP-XM and YNT_SSNG simulations showing biases of −11.42 and −13.54 ppbv (parts per billion by volume), respectively, during periods when the observed MDA8 was greater than 70 ppbv. However, for the two monitoring sites that observed high-ozone events, the AP-XM simulation better matched observations at Chiwaukee Prairie, and the YNT_SSNG simulation better matched observations at the Sheboygan Kohler-Andrae (KA) State Park. We find that the differences between the two simulations are largest for column amounts of ozone precursors, particularly NO2. Across three high-ozone events, the YNT_SSNG simulation has a lower NO2 column bias (0.17×1015 mol cm−2) compared to the AP-XM simulation (0.31×1015 mol cm−2). The YNT_SSNG simulation also has an advantage in that it better captures the structure of the boundary layer and lake breeze during the 2 June high-ozone event, although the timing of the lake breeze is about 3 h too early at Sheboygan. Our results are useful for informing an air quality modeling framework for the Lake Michigan area.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 5
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 23, No. 14 ( 2023-07-18), p. 7935-7954
    Abstract: Abstract. High-resolution simulations were performed to assess the impact of different parameterization schemes, surface datasets, and analysis nudging on lower-tropospheric conditions near Lake Michigan. Simulations were performed where climatological or coarse-resolution surface datasets were replaced by high-resolution, real-time datasets depicting the lake surface temperatures (SSTs), green vegetation fraction (GVF), and soil moisture and temperature (SOIL). Comparison of two baseline simulations employing different parameterization schemes (referred to as AP-XM and YNT, respectively) showed that the AP-XM simulation produced more accurate analyses on the outermost 12 km resolution domain but that the YNT simulation was superior for higher-resolution nests. The diurnal evolution of the surface energy fluxes was similar in both simulations on the 12 km grid but differed greatly on the 1.3 km grid where the AP-XM simulation had a much smaller sensible heat flux during the daytime and a physically unrealistic ground heat flux. Switching to the YNT configuration led to more accurate 2 m temperature and 2 m water vapor mixing ratio analyses on the 1.3 km grid. Additional improvements occurred when satellite-derived surface datasets were incorporated into the modeling platform, with the SOIL dataset having the largest positive impact on temperature and water vapor. The GVF and SST datasets also produced more accurate temperature and water vapor analyses but had degradations in wind speed, especially when using the GVF dataset. The most accurate simulations were obtained when using the high-resolution SST and SOIL datasets and analysis nudging above 2 km a.g.l. (above ground level). These results demonstrate the value of using high-resolution satellite-derived surface datasets in model simulations.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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