523 research outputs found

    Extreme Thunderstorms as Seen by Satellite

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    ENSO Related Inter-Annual Lightning Variability from the Full TRMM LIS Lightning Climatology

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    The El Nino/Southern Oscillation (ENSO) contributes to inter-annual variability of lightning production more than any other atmospheric oscillation. This study further investigated how ENSO phase affects lightning production in the tropics and subtropics using the Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS). Lightning data were averaged into mean annual warm, cold, and neutral 'years' for analysis of the different phases and compared to model reanalysis data. An examination of the regional sensitivities and preliminary analysis of three locations was conducted using model reanalysis data to determine the leading convective mechanisms in these areas and how they might respond to the ENSO phase

    The Evolution and Extratropical Transition of Tropical Cyclones from a GPM, ISS LIS and GLM Perspective

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    Not much is known about the evolution of lightning within extra-tropical cyclones traversing the mid-latitudes, especially its oceans. To facilitate such studies we combine a recently constructed precipitation features (PF) database obtained from the Global Precipitation Measurement (GPM) mission constellation of satellites with lightning observations from the Geostationary Lightning Mapper (GLM) onboard GOES-16 and the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS). The goal of this study is to provide a new observationally-based view of the tropical to extra-tropical transition and its impact on lightning production. Such data fusion approaches, as presented here, will also be important in future satellite studies of convective precipitation

    ENSO Related Interannual Lightning Variability from the Full TRMM LIS Lightning Climatology

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    It has been shown that the El Nino/Southern Oscillation (ENSO) contributes to inter-annual variability of lightning production in the tropics and subtropics more than any other atmospheric oscillation. This study further investigated how ENSO phase affects lightning production in the tropics and subtropics. Using the Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) and the Oceanic Nino Index (ONI) for ENSO phase, lightning data were averaged into corresponding mean annual warm, cold, and neutral 'years' for analysis of the different phases. An examination of the regional sensitivities and preliminary analysis of three locations was conducted using model reanalysis data to determine the leading convective mechanisms in these areas and how they might respond to the ENSO phases. These processes were then studied for inter-annual variance and subsequent correlation to ENSO during the study period to best describe the observed lightning deviations from year to year at each location

    Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Validation Using Dropsondes

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    Surface wind speed retrievals have been generated and evaluated using Hurricane Imaging Radiometer (HIRAD) measurements from flights over Hurricane Joaquin, Hurricane Patricia, Hurricane Marty, and the remnants of Tropical Storm Erika, all in 2015. Procedures are described here for producing maps of brightness temperature, which are subsequently used for retrievals of surface wind speed and rain rate across a approx.50 km wide swath for each flight leg. An iterative retrieval approach has been developed to take advantage of HIRAD's measurement characteristics. Validation of the wind speed retrievals has been conducted, using 636 dropsondes released from the same WB-57 high altitude aircraft carrying HIRAD during the Tropical Cyclone Intensity (TCI) experiment. The HIRAD wind speed retrievals exhibit very small bias relative to the dropsondes, for winds tropical storm strength (17.5 m/s) or greater. HIRAD has reduced sensitivity to winds weaker than tropical storm strength, and a small positive bias (approx.2 m/s) there. Two flights with predominantly weak winds according to the dropsondes have abnormally large errors from HIRAD, and large positive biases. From the other flights, root mean square errors are 4.1 m/s (33%) for winds below tropical storm strength, 5.6 m/s (25%) for tropical storm strength winds, and 6.3 m/s (16%) for hurricane strength winds. Mean absolute errors for those categories are 3.2 m/s (25%), 4.3 m/s (19%), and 4.8 m/s (12%), with bias near zero for tropical storm and hurricane strength winds

    Signatures of Hydrometeor Species from Airborne Passive Microwave Data for Frequencies 10-183 GHz

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    There are 2 basic precipitation retrieval methods using passive microwave measurements: (1) Emission-based: Based on the tendency of liquid precipitation to cause an increase in brightness temperature (BT) primarily at frequencies below 22 GHz over a radiometrically cold background, often an ocean background (e.g., Spencer et al. 1989; Adler et al. 1991; McGaughey et al. 1996); and (2) Scattering-based: Based on the tendency of precipitation-sized ice to scatter upwelling radiation, thereby reducing the measured BT over a relatively warmer (usually land) background at frequencies generally 37 GHz (e.g., Spencer et al. 1989; Smith et al. 1992; Ferraro and Marks 1995). Passive microwave measurements have also been used to detect intense convection (e.g., Spencer and Santek 1985) and for the detection of hail (e.g., Cecil 2009; Cecil and Blankenship 2012; Ferraro et al. 2014). The Global Precipitation Measurement (GPM) mission expands upon the successful Tropical Rainfall Measurement Mission program to provide global rainfall and snowfall observations every 3 hours (Hou et al. 2014). One of the instruments on board the GPM Core Observatory is the GPM Microwave Imager (GMI) which is a conically-scanning microwave radiometer with 13 channels ranging from 10-183 GHz. Goal of this study: Determine the signatures of various hydrometeor species in terms of BTs measured at frequencies used by GMI by using data collected on 3 case days (all having intense/severe convection) during the Mid-latitude Continental Convective Clouds Experiment conducted over Oklahoma in 2011

    Harmonizing Conversion and the Means Test in Bankruptcy

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    Determining whether the means test applies in cases converted from Chapter 13 to Chapter 7 has divided courts across the United States and has even caused bankruptcy judges within the same district court to disagree. In the nearly 15 years since the enactment of the Bankruptcy Abuse Prevention and Consumer Protection Act (“BAPCPA”), a majority of courts have held that the means test applies in converted cases. However, a considerable minority view has emerged, which virtually all scholarship on the issue has adopted. Although both the majority and minority views cause interpretive problems, this article argues that the means test should apply in cases converted from Chapter 13 to Chapter 7. This view promotes a better reading of § 707(b) and the Bankruptcy Code in general and prevents debtors from manipulating the bankruptcy system by filing under Chapter 13 and then converting to Chapter 7 to avoid the means test. Additionally, this article also provides language that Congress should adopt in amending the Bankruptcy Code to codify the view that the means test applies in converted cases

    Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

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    Lightning observations are collected using ground-based and satellite-based sensors. The National Lightning Detection Network (NLDN) in the United States uses multiple ground sensors to triangulate the electromagnetic signals created when lightning strikes the Earth's surface. Satellite-based lightning observations have been made from 1998 to present using the Lightning Imaging Sensor (LIS) on the NASA Tropical Rainfall Measuring Mission (TRMM) satellite, and from 1995 to 2000 using the Optical Transient Detector (OTD) on the Microlab-1 satellite. Both LIS and OTD are staring imagers that detect lightning as momentary changes in an optical scene. Passive microwave remote sensing (85 and 37 GHz brightness temperatures) from the TRMM Microwave Imager (TMI) has also been used to quantify characteristics of thunderstorms related to lightning. Each lightning detection system has fundamental limitations. TRMM satellite coverage is limited to the tropics and subtropics between 38 deg N and 38 deg S, so lightning at the higher latitudes of the northern and southern hemispheres is not observed. The detection efficiency of NLDN sensors exceeds 95%, but the sensors are only located in the USA. Even if data from other ground-based lightning sensors (World Wide Lightning Location Network, the European Cooperation for Lightning Detection, and Canadian Lightning Detection Network) were combined with TRMM and NLDN, there would be enormous spatial gaps in present-day coverage of lightning. In addition, a globally-complete time history of observed lightning activity is currently not available either, with network coverage and detection efficiencies varying through the years. Previous research using the TRMM LIS and Microwave Imager (TMI) showed that there is a statistically significant correlation between lightning flash rates and passive microwave brightness temperatures. The physical basis for this correlation emerges because lightning in a thunderstorm occurs where ice is first present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the flash rate) was calculated for storms having 85 GHz PCT greater than 150 K. NLDN data was used to determine if a CG strike occurred for a storm. This probability of CG lightning was plotted as a function of minimum 85 GHz PCT and minimum 37 GHz PCT. These probabilities were used in conjunction with the linear model to estimate the CG flash rate for weaker storms with minimum 85 GHz PCTs greater than 150 K. Results from the investigation of CG lightning and passive microwave radiation signals agree with the previous research investigating total lightning and brightness temperature. Future work will take the established relationships and apply them to the decades of available DMSP data for the USA to derive a map of CG lightning flash rates. Validation of this method and uncertainty analysis will be done by comparing the derived maps of CG lightning flash rates against existing NLDN maps of CG lightning flash rates

    Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Assessment Using Dropsondes

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    The Hurricane Imaging Radiometer (HIRAD) is an experimental C-band passive microwave radiometer designed to map the horizontal structure of surface wind speed fields in hurricanes. New data processing and customized retrieval approaches were developed after the 2015 Tropical Cyclone Intensity (TCI) experiment, which featured flights over Hurricanes Patricia, Joaquin, Marty, and the remnants of Tropical Storm Erika. These new approaches produced maps of surface wind speed that looked more realistic than those from previous campaigns. Dropsondes from the High Definition Sounding System (HDSS) that was flown with HIRAD on a WB-57 high altitude aircraft in TCI were used to assess the quality of the HIRAD wind speed retrievals. The root mean square difference between HIRAD-retrieved surface wind speeds and dropsonde-estimated surface wind speeds was 6.0 meters per second. The largest differences between HIRAD and dropsonde winds were from data points where storm motion during dropsonde descent compromised the validity of the comparisons. Accounting for this and for uncertainty in the dropsonde measurements themselves, we estimate the root mean square error for the HIRAD retrievals as around 4.7 meters per second. Prior to the 2015 TCI experiment, HIRAD had previously flown on the WB-57 for missions across Hurricanes Gonzalo (2014), Earl (2010), and Karl (2010). Configuration of the instrument was not identical to the 2015 flights, but the methods devised after the 2015 flights may be applied to that previous data in an attempt to improve retrievals from those cases
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