Description and Status of the DC Lightning Mapping Array

The DC Lightning Mapping Array (DC LMA) centered on the Washington, DC metro region has been in operation since 2006. During that time the DC LMA has provided real time data to regional National Weather Service (NSF) Sterling, VA forecast office for operations support and the NOAA Meteorological Development Laboratory (MDL) for new product development and assessment. Data from this network (as well as other from other LMA systems) are now being used to create proxy Geostationary Lightning Mapper (GLM) data sets for GOES-R risk reduction and algorithm development activities. In addition, since spring 2009 data are provided to the Storm Prediction Center in support of Hazardous Weather Testbed and GOES-R Proving Ground activities during the Spring Program. Description, status and plans will be discussed

Characterizing the GOES-R (GOES-16) Geostationary Lightning Mapper (GLM) On-Orbit Performance

Two overlapping efforts help to characterize the GLM performance, the Post Launch Test (PLT) phase to validate the predicted pre-launch instrument performance and the Post Launch Product Test (PLPT) phase to validate the lightning detection product used in forecast and warning decision-making. This paper documents the calibration and validation plans and activities for the first 6 months of GLM on-orbit testing and validation commencing with first light on 4 January 2017. The PLT phase addresses image quality, on-orbit calibration, RTEP threshold tuning, image navigation, noise filtering, and solar intrusion assessment, resulting in a GLM calibration parameter file. The PLPT includes four main activities, the Reference Data Comparisons (RDC), Algorithm Testing (AT), Instrument Navigation and Registration Testing (INRT), and Long Term Baseline Testing (LTBT). Field campaigns are also designed to contribute valuable insights into the GLM performance capabilities. The PLPT tests each contribute to the beta, provisional, and fully validated GLM data

Inter-Comparison of Lightning Trends from Ground-Based Networks During Severe Weather: Applications Toward GLM

The planned GOES-R Geostationary Lightning Mapper (GLM) will provide total lightning data on the location and intensity of thunderstorms over a hemispheric spatial domain. Ongoing GOES-R research activities are demonstrating the utility of total flash rate trends for enhancing forecasting skill of severe storms. To date, GLM total lightning proxy trends have been well served by ground-based VHF systems such as the Northern Alabama Lightning Mapping Array (NALMA). The NALMA (and other similar networks in Washington DC and Oklahoma) provide high detection efficiency (> 90%) and location accuracy (< 1 km) observations of total lightning within about 150 km from network center. To expand GLM proxy applications for high impact convective weather (e.g., severe, aviation hazards), it is desirable to investigate the utility of additional sources of continuous lightning that can serve as suitable GLM proxy over large spatial scales (order 100 s to 1000 km or more), including typically data denied regions such as the oceans. Potential sources of GLM proxy include ground-based long-range (regional or global) VLF/LF lightning networks such as the relatively new Vaisala Global Lightning Dataset (GLD360) and Weatherbug Total Lightning Network (WTLN). Before using these data in GLM research applications, it is necessary to compare them with LMAs and well-quantified cloud-to-ground (CG) lightning networks, such as Vaisala s National Lightning Detection Network (NLDN), for assessment of total and CG lightning location accuracy, detection efficiency and flash rate trends. Preliminary inter-comparisons from these lightning networks during selected severe weather events will be presented and their implications discussed

Relationships Between Long-Range Lightning Networks and TRMM/LIS Observations

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. The present study intercompares long-range lightning data with observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study examines network detection efficiency and location accuracy relative to LIS observations, describes spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by the long-range networks. Improved knowledge of relationships between these datasets will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM)

Evaluation of Long-Range Lightning Detection Networks Using TRMM/LIS Observations

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. Toward this end, the present study evaluates data from the World Wide Lightning Location Network (WWLLN) using observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study documents the WWLLN detection efficiency and location accuracy relative to LIS observations, describes the spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by WWLLN. Improved knowledge of the WWLLN detection capabilities will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM)

The CHUVA Lightning Mapping Campaign

The primary science objective for the CHUVA lightning mapping campaign is to combine measurements of total lightning activity, lightning channel mapping, and detailed information on the locations of cloud charge regions of thunderstorms with the planned observations of the CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement) field campaign. The lightning campaign takes place during the CHUVA intensive observation period October-December 2011 in the vicinity of S o Luiz do Paraitinga with Brazilian, US, and European government, university and industry participants. Total lightning measurements that can be provided by ground-based regional 2-D and 3-D total lightning mapping networks coincident with overpasses of the Tropical Rainfall Measuring Mission Lightning Imaging Sensor (LIS) and the SEVIRI (Spinning Enhanced Visible and Infrared Imager) on the Meteosat Second Generation satellite in geostationary earth orbit will be used to generate proxy data sets for the next generation US and European geostationary satellites. Proxy data, which play an important role in the pre-launch mission development and in user readiness preparation, are used to develop and validate algorithms so that they will be ready for operational use quickly following the planned launch of the GOES-R Geostationary Lightning Mapper (GLM) in 2015 and the Meteosat Third Generation Lightning Imager (LI) in 2017. To date there is no well-characterized total lightning data set coincident with the imagers. Therefore, to take the greatest advantage of this opportunity to collect detailed and comprehensive total lightning data sets, test and validate multi-sensor nowcasting applications for the monitoring, tracking, warning, and prediction of severe and high impact weather, and to advance our knowledge of thunderstorm physics, extensive measurements from lightning mapping networks will be collected in conjunction with electric field mills, field change sensors, high speed cameras and other lightning sensors, dual-polarimetric radars, and aircraft in-situ microphysics which will allow for excellent cross-network inter-comparisons, assessments, and physical understanding

The Intracloud Lightning Fraction in the Contiguous United States

This work addresses the long-term relative occurrence of cloud-to-ground (CG) and intracloud (IC; no attachment to ground) flashes for the contiguous United States (CONUS). It expands upon an earlier analysis by Boccippio et al. who employed 4-yr datasets provided by the U.S. National Lightning Detection Network (NLDN) and the Optical Transient Detector (OTD). Today, the duration of the NLDN historical dataset has more than tripled, and OTD data can be supplemented with data from the Lightning Imaging Sensor (LIS). This work is timely, given the launch of GOES-16, which includes the world's first geostationary lightning mapper that will observe total lightning (IC and CG) over the Americas and adjacent ocean regions. Findings support earlier results indicating factor-of-10 variations in the IC:CG ratio throughout CONUS, with climatological IC fraction varying between 0.3 and greater than 0.9. The largest values are seen in the Pacific Northwest, central California, and where Colorado borders Kansas and Nebraska. An uncertainty analysis indicates that the large values in the northwest and central California are likely not due to measurement uncertainty. The high IC:CG ratio (. 4) throughout much of Texas reported by Boccippio et al. is not supported by this longer-term climatology. There is no clear evidence of differences in IC fraction between land and coastal ocean. Lightning characteristics in six selected large regions show a consistent positive relationship between IC fraction and the percent of positive CG flashes, irrespective of lightning incidence (flash density), dominant season, or diurnal maximum period.NOAA GOES-R Program; TRMM/LIS Science Team; NASA [NNM12AA43C]; [NNH14ZDA001N-INCA]6 month embargo; published online: 1 November 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Intracloud Lightning Fraction in the Contiguous United States

This work addresses the long-term relative occurrence of cloud-to-ground (CG) and intracloud (IC; no attachment to ground) flashes for the contiguous United States (CONUS). It expands upon an earlier analysis by Boccippio et al. who employed 4-yr datasets provided by the U.S. National Lightning Detection Network (NLDN) and the Optical Transient Detector (OTD). Today, the duration of the NLDN historical dataset has more than tripled, and OTD data can be supplemented with data from the Lightning Imaging Sensor (LIS). This work is timely, given the launch of GOES-16, which includes the world's first geostationary lightning mapper that will observe total lightning (IC and CG) over the Americas and adjacent ocean regions. Findings support earlier results indicating factor-of-10 variations in the IC:CG ratio throughout CONUS, with climatological IC fraction varying between 0.3 and greater than 0.9. The largest values are seen in the Pacific Northwest, central California, and where Colorado borders Kansas and Nebraska. An uncertainty analysis indicates that the large values in the northwest and central California are likely not due to measurement uncertainty. The high IC:CG ratio (. 4) throughout much of Texas reported by Boccippio et al. is not supported by this longer-term climatology. There is no clear evidence of differences in IC fraction between land and coastal ocean. Lightning characteristics in six selected large regions show a consistent positive relationship between IC fraction and the percent of positive CG flashes, irrespective of lightning incidence (flash density), dominant season, or diurnal maximum period.NOAA GOES-R Program; TRMM/LIS Science Team; NASA [NNM12AA43C]; [NNH14ZDA001N-INCA]6 month embargo; published online: 1 November 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Raindrop Signature from Microwave Radiometer Over Deserts

International audienceRainfall estimates from spaceborne microwave radiometers form the foundation of global precipitation data sets. Since the beginning of the satellite microwave rainfall estimation era in the 1980s, the primary signature leveraged over land for these estimates has been the brightness temperature (TB) depression due to ice particle scattering. Contrary to this practice, time series analyses based on observations from two spaceborne radars and two spaceborne radiometers reveal a TB increase at H19 due to raindrop emission as the primary cloud particle signature over desert terrain. Low surface emissivity supports the use of liquid raindrop emission as the primary signature over desert surfaces. In these regions, the surface rain rate better correlates with the liquid raindrop emission signal than with the scattering induced by ice further aloft, suggesting a new potential for improving rainfall estimation over deserts by exploiting the liquid raindrop emission signature