Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011in the vicinity of So Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. The SP-LMA data also will be intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment and analyses for intercomparison studies and GOES-R proxy activitie

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

for the existing GOES system currently operating over the Western Hemisphere. New and improved instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved temporal, spatial, and spectral resolution for the next generation Advanced Baseline Imager (ABI). The GLM will map total lightning continuously day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. The GLM will help address the National Weather Service requirement for total lightning observations globally to support warning decision-making and forecast services. Science and application development along with pre-operational product demonstrations and evaluations at NWS national centers, forecast offices, and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and check-out of GOES-R in 2016. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings

Performance Evaluation of the Lightning Imaging Sensor on the International Space Station

Optical lightning observations from low-Earth orbit play an important role in our understanding of long-term global lightning trends. Lightning Imaging Sensors (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite (1997–2015) and International Space Station (2017–present) capture optical emissions produced by lightning. This study uses the well-documented TRMM LIS performance to determine if the ISS LIS performs well enough to bridge the gap between TRMM LIS and the new generation of Geostationary Lightning Mappers (GLMs). The average events per group and groups per flash for ISS LIS are 3.6 and 9.9, which are 18% and 10% lower than TRMM LIS, respectively. ISS LIS has 30% lower mean group energy density and 30%–50% lower mean flash energy density than TRMM LIS in their common (6388) latitude range. These differences are likely the result of larger pixel areas for ISS LIS over most of the field of view due to off-nadir pointing, combined with viewing obstructions and possible engineering differences. For both in-struments, radiometric sensitivity decreases radially from the center of the array to the edges. ISS LIS sensitivity falls off faster and more variably, contributed to by the off-nadir pointing. Event energy density analysis indicate some anomalous hotspot pixels in the ISS LIS pixel array that were not present with the TRMM LIS. Despite these differences, ISS LIS provides similar parameter values to TRMM LIS with the expectation of somewhat lower lightning detection capability. In addition, recalculation of the event, group, and flash areas for both LIS datasets are strongly recommended since the archived values in the current release versions have significant errors. © 2023 American Meteorological Society.6 month embargo; first published 25 September 2023This 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

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

Comparison of Lightning Detection Between the FY‐4A Lightning Mapping Imager and the ISS Lightning Imaging Sensor

Abstract The Lightning Mapping Imager (LMI) onboard Fengyun‐4A (FY‐4A) is the first Chinese lightning detection sensor in geostationary orbit. This study presents the lightning characteristics observed by the FY‐4A LMI in its first year, and then observations from the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS) are used to validate the performance of the LMI sensor. LMI lightning events are defined by the pixel's luminosity exceeding the threshold radiance. During the first year of operation, LMI events revealed a reasonable geographical distribution. The diurnal cycles of LMI event/background/threshold radiance are in general agreement with the later afternoon peaks in previous findings. However, the LMI events that occurred around the LIS flash time and in the LMI observation field‐of‐view show a slightly delayed peak at around 1900 LST. This peak can be shifted closer to LIS's results after removing LMI events with event radiance lower than 300 μJsr−1m−2μm−1, suggesting that a larger threshold radiance value is needed to qualify some of these LMI events. Finally, LIS lightning groups were matched with LMI lightning events using different temporal and spatial collocation criteria. The detection efficiency is defined by the fraction of LIS groups detected by LMI to assess LMI's performance. The LMI detection efficiency relative to LIS was found to be regionally dependent and lower in the daytime than at nighttime. These results contribute to applications of LMI lightning observations in storm research and provide suggestions for further algorithm improvement