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  • 1
    Online Resource
    Online Resource
    American Meteorological Society ; 2015
    In:  Bulletin of the American Meteorological Society Vol. 96, No. 8 ( 2015-08-01), p. 1369-1379
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 96, No. 8 ( 2015-08-01), p. 1369-1379
    Abstract: Cloud computing offers new opportunities to the scientific community through cloud-deployed software, data-sharing and collaboration tools, and the use of cloud-based computing infrastructure to support data processing and model simulations. This article provides a review of cloud terminology of possible interest to the meteorological community, and focuses specifically on the use of infrastructure as a service (IaaS) concepts to provide a platform for regional numerical weather prediction. Special emphasis is given to developing countries that may have limited access to traditional supercomputing facilities. Amazon Elastic Compute Cloud (EC2) resources were used in an IaaS capacity to provide regional weather simulations with costs ranging from $40 to $75 per 48-h forecast, depending upon the configuration. Simulations provided a reasonable depiction of sensible weather elements and precipitation when compared against typical validation data available over Central America and the Caribbean.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 2
    In: Remote Sensing, MDPI AG, Vol. 13, No. 24 ( 2021-12-15), p. 5098-
    Abstract: In response to Hurricane Florence of 2018, NASA JPL collected quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument, observing record-setting river stages across North and South Carolina. Fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging, stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study used random forest classification to generate maps of inundation from L-band UAVSAR imagery processed using the Freeman–Durden decomposition method. An average overall classification accuracy of 87% is achieved with this methodology, with areas of both under- and overprediction for the focus classes of open water and inundated forest. Fuzzy logic operations using hydrologic variables are used to reduce the number of small noise-like features and false detections in areas unlikely to retain water. Following postclassification refinement, estimated flood extents were combined to an event maximum for societal impact assessments. Results from the Hurricane Florence case study are discussed in addition to the limitations of available validation data for accuracy assessments.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2022
    In:  JAWRA Journal of the American Water Resources Association Vol. 58, No. 1 ( 2022-02), p. 104-118
    In: JAWRA Journal of the American Water Resources Association, Wiley, Vol. 58, No. 1 ( 2022-02), p. 104-118
    Abstract: Vegetation is parameterized in the operational National Oceanic and Atmospheric Administration National Water Model (NWM) using climatologies of leaf area index and green vegetation fraction (GVF) which do not capture interannual variability or seasonal anomalies. This study investigates the impact of assimilating real‐time Visible Infrared Imaging Radiometer Suite (VIIRS) GVF on NWM streamflow and land surface energy and moisture fluxes. Using a subset of the NWM over three humid watersheds in Alabama, VIIRS GVF was assimilated into an experimental NWM configuration to replace the default GVF climatology to provide a more accurate representation of the land surface vegetation greenness. Although the use of real‐time VIIRS GVF in place of the climatological GVF slightly improved NWM stream‐flow prediction, results were not statistically significant. GVF assimilation also improved the interannual representation of land surface fluxes with increases in GVF resulting in increased evapotranspiration and latent heat.
    Type of Medium: Online Resource
    ISSN: 1093-474X , 1752-1688
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2090051-X
    SSG: 14
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  • 4
    In: Remote Sensing, MDPI AG, Vol. 12, No. 21 ( 2020-11-01), p. 3588-
    Abstract: The Greater Houston metropolitan area has experienced recurring flooding events in the past two decades related to tropical cyclones and heavy inland rainfall. With the projected recurrence of severe weather events, an approach that outlines the susceptibility of different localities within the study area to potential floods based on analyses of the impacts from earlier events would be beneficial. We applied a novel C-band Sentinel-1 Synthetic Aperture Radar (SAR)-based flood detection method to map floodwater distribution following three recent severe weather events with the goal of identifying areas that are prone to future flood hazards. Attempts were made to calibrate and validate the C-band-based results and analyses to compensate for possible sources of error. These included qualitative and quantitative assessments on L-band aerial SAR data, as well as aerial imagery acquired after one of the events. The findings included the following: (1) most urban centers of Harris county, with few exceptions, are not believed to be prone to flooding hazards in contrast to the densely populated areas on the outskirts of Harris county; (2) nearly 44% of the mapped flood-prone areas lie within a 1 km distance of major drainage networks; (3) areas experiencing high subsidence rates have persistently experienced flooding, possibly exacerbated by morphological changes to the land surface induced by subsidence.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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  • 5
    Online Resource
    Online Resource
    American Meteorological Society ; 2016
    In:  Monthly Weather Review Vol. 144, No. 11 ( 2016-11), p. 4327-4347
    In: Monthly Weather Review, American Meteorological Society, Vol. 144, No. 11 ( 2016-11), p. 4327-4347
    Abstract: Derived radar reflectivities and fall speeds for four Weather Research and Forecasting (WRF) Model bulk microphysical parameterizations (BMPs) run at 1.33-km grid spacing are compared with ground-based, vertically pointing Ku-band radar, scanning S-band radar, and in situ measurements at Stony Brook, New York. Simulations were partitioned into periods of observed riming degree as determined manually using a stereo microscope and camera during nine winter storms. Simulations were examined to determine whether the selected BMPs captured the effects of varying riming intensities, provided a reasonable match to the vertical structure of radar reflectivity or fall speed, and whether they produced reasonable surface fall speed distributions. Schemes assuming nonspherical mass–diameter relationships yielded reflectivity distributions closer to observed values. All four schemes examined in this study provided a better match to the observed, vertical structure of reflectivity during moderate riming than light riming periods. The comparison of observed and simulated snowfall speeds had mixed results. One BMP produced episodes of excessive cloud water at times, resulting in fall speeds that were too large. However, most schemes had frequent periods of little or no cloud water during moderate riming periods and thus underpredicted the snowfall speeds at lower levels. Short, 1–4-h periods with relatively steady snow conditions were used to compare BMP and observed size and fall speed distributions. These limited data suggest the examined BMPs underpredict fall speeds of cold-type snow habits and underrepresent aggregates larger than 4-mm diameter.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2016
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 6
    In: Weather and Forecasting, American Meteorological Society, Vol. 38, No. 9 ( 2023-09), p. 1575-1588
    Abstract: Hail and damaging winds are two threats associated with intense and severe thunderstorms that traverse the Midwest and Great Plains during the primary growing season. In certain severe thunderstorm events, large swaths of agricultural crops are impacted, allowing the damage to be viewed from multiple satellite remote sensing platforms. Previous studies have focused on analyzing individual hail and wind damage swaths (HWDSs) using satellite remote sensing, but these swaths have never been officially archived or documented. This lack of documentation has made it difficult to analyze the spatial extent and temporal frequency of HWDSs from year to year. This study utilizes daily true color imagery from MODIS aboard NASA’s Terra and Aqua satellites and daily local storm reports from the Storm Prediction Center to build a database of HWDSs occurring in the months of May–August, for years 2000–20. This database identified 1646 HWDSs in 12 states throughout the Midwest and Great Plains, confirmed through a combination of archived severe weather warnings, radar information, and official storm reports. For each entry in the HWDS database, a geospatial outline is provided along with the most likely date of first visible damage from MODIS imagery as well as the physical characteristics and time of occurrence estimated from available warnings. This study also provides a summary of the radar characteristics for a portion of the database. This database will further the understanding of severe weather damage by hail and wind to agriculture to help understand the frequency of these events and assist in mapping the impacted areas. Significance Statement Hail and wind damage swaths (HWDSs) frequently occur during the primary growing season throughout the Midwest and Great Plains but are not yet officially documented or tracked like other severe weather impacts (e.g., tornadoes and derechos). This study describes the creation of a 21-yr HWDS event database using archived daily storm reports and daily true color satellite imagery. Once the database was completed and underwent quality checks, the research team identified spatial and temporal trends from the confirmed swaths.
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2023
    detail.hit.zdb_id: 2025194-4
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  • 7
    Online Resource
    Online Resource
    American Meteorological Society ; 2010
    In:  Monthly Weather Review Vol. 138, No. 11 ( 2010-11-01), p. 4254-4267
    In: Monthly Weather Review, American Meteorological Society, Vol. 138, No. 11 ( 2010-11-01), p. 4254-4267
    Abstract: The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was a field campaign designed to obtain aircraft, surface, and radar observations of clouds and precipitation in support of improving the simulation of snowfall and cold season precipitation, their microphysical processes represented within forecast models, and radiative properties relevant to remotely sensed retrievals. During the campaign, a midlatitude cyclone tracked along the U.S.–Canadian border on 22 January 2007, producing an extensive area of snowfall. Observations of ice crystals from this event are used to evaluate the assumptions and physical relationships for the snow category within the Goddard six-class, single-moment microphysics scheme, as implemented within the Weather Research and Forecasting (WRF) model. The WRF model forecast generally reproduced the precipitation and cloud structures sampled by radars and aircraft, permitting a comparison between C3VP observations and model snowfall characteristics. Key snowfall assumptions in the Goddard scheme are an exponential size distribution with fixed intercept and effective bulk density, and the relationship between crystal diameter and terminal velocity. Fixed values for the size distribution intercept and density did not represent the vertical variability of naturally occurring populations of aggregates, and the current diameter and fall speed relationship underestimated terminal velocities for all sizes of crystals.
    Type of Medium: Online Resource
    ISSN: 1520-0493 , 0027-0644
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2010
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 8
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 103, No. 4 ( 2022-04), p. E1172-E1196
    Abstract: The catastrophic derecho that occurred on 10 August 2020 across the midwestern United States caused billions of dollars of damage to both urban and rural infrastructure as well as agricultural crops, most notably across the state of Iowa. This paper documents the complex evolution of the derecho through the use of low-Earth-orbit passive-microwave imager and GOES-16 satellite-derived products complemented by products derived from NEXRAD weather radar observations. Additional satellite sensors including optical imagers and synthetic aperture radar (SAR) were used to observe impacts to the power grid and agriculture in Iowa. SAR improved the identification and quantification of damaged corn and soybeans, as compared to true-color composites and normalized difference vegetation index (NDVI). A statistical approach to identify damaged corn and soybean crops from SAR was created with estimates of 1.97 million acres of damaged corn and 1.40 million acres of damaged soybeans in the state of Iowa. The damage estimates generated by this study were comparable to estimates produced by others after the derecho, including two commercial agricultural companies.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 9
    Online Resource
    Online Resource
    American Meteorological Society ; 2020
    In:  Bulletin of the American Meteorological Society Vol. 101, No. 3 ( 2020-03), p. E323-E340
    In: Bulletin of the American Meteorological Society, American Meteorological Society, Vol. 101, No. 3 ( 2020-03), p. E323-E340
    Abstract: Severe weather events including tornadoes, damaging winds, hail, and their combination produce changes in land surface vegetation and urban settings that are frequently observed through remote sensing. Capabilities continue to improve through a growing constellation of governmental and commercial assets, increasing the spatial resolution of visible, near to shortwave infrared, and thermal infrared remote sensing. Here, we highlight cases where visual interpretation of imagery benefitted severe weather damage assessments made within the NOAA/NWS Damage Assessment Toolkit. Examples demonstrate utility of imagery in assessing tracks and changes in remote areas where staffing limitations or access prevent a ground-based assessment.
    Type of Medium: Online Resource
    ISSN: 0003-0007 , 1520-0477
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2029396-3
    detail.hit.zdb_id: 419957-1
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  • 10
    Online Resource
    Online Resource
    American Meteorological Society ; 2012
    In:  Monthly Weather Review Vol. 140, No. 9 ( 2012-09-01), p. 2982-3002
    In: Monthly Weather Review, American Meteorological Society, Vol. 140, No. 9 ( 2012-09-01), p. 2982-3002
    Abstract: The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) provided aircraft, surface, and remotely sensed observations of cloud and precipitation characteristics to support improved simulation of cold-season precipitation within weather forecast models and new developments in satellite and radar precipitation retrievals. On 22 January 2007, the C3VP campaign executed an intensive observation period to sample widespread snowfall that occurred as a midlatitude cyclone tracked along the U.S.–Canadian border. Surface air temperature and precipitation measurements, combined with aircraft measurement of hydrometeor content and size distribution, are used to examine various assumptions and parameterizations included within four bulk water microphysics schemes available within the Weather Research and Forecasting Model (WRF). In a simulation of the 22 January 2007 event, WRF forecasts reproduced the overall precipitation pattern observed during aircraft sampling, allowing for a comparison between C3VP measurements and microphysics scheme assumptions. Single-moment schemes that provide flexibility in size distribution parameters as functions of temperature can represent much of the vertical variability observed in aircraft data, but variability is reduced in an environment where the simulated temperature profile is nearly isothermal. Double-moment prediction of total number concentration may improve the representation of ice crystal aggregation. Inclusion of both temperature dependence on distribution parameters and variability in mass–diameter or diameter–fall speed relationships suggest a means of improving upon single-moment predictions.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2012
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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