A validation study of the Geostationary Lightning Mapper (GLM) on board the Geostationary Operational Environmental Satellite 16 (GOES-16) was done using a ground-based lightning mapping array (LMA) deployed as part of the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign in Argentina. GLM detected lightning with 74.6% efficiency over 61 thunderstorm days in December 2018 through April 2019. However, GLM detection efficiency (DE) was negatively correlated (r = -0.49) with LMA flash rate. GLM DE also was negatively correlated with LMA flash altitude (r = -0.24), reflecting the influence of multiple competing trends. GLM DE was positively correlated (r = 0.27) with number of LMA sources in a flash, indicating improved DE for larger flashes. During periods with anomalously electrified storms, GLM DE was reduced to 50.9%. Statistics were found to be sensitive to analysis criteria, but most of the above trends remained consistent regardless of specific criteria. Because the methodology allowed a GLM flash to match more than one LMA flash, actual GLM flash rate was a factor of 2.9 lower than the LMA flash rate, and this ratio grew larger as LMA flash rate increased. A sensitivity study examined the impact of improved DE for smaller flashes; that is, an improved sensor (or algorithm) that was better able to detect and distinguish between separate small lightning flashes. The results showed improved correlation with LMA flash rates, as well as improved ability to identify lightning jumps associated with intensifying convection.

A new automated method to retrieve charge layer polarity from flashes, named Chargepol, is presented in this paper. Using data from the NASA Lightning Mapping Array (LMA) deployed during the RELAMPAGO field campaign in Cordoba, Argentina, from November 2018 to April 2019, this method estimates the polarity of vertical charge distributions and their altitudes and thicknesses (or vertical depth) using the very-high frequency (VHF) source emissions detected by LMAs. When this method is applied to LMA data for extended periods of time, it is capable of inferring a storm’s bulk electrical charge structure throughout its life cycle. This method reliably predicted the polarity of charge within which lightning flashes propagated and was validated in comparison to methods that require manual assignment of polarities via visual inspection of VHF lightning sources. Examples of normal and anomalous charge structures retrieved using Chargepol for storms in Central Argentina during RELAMPAGO are presented for the first time. Application of Chargepol to five months of LMA data in Central Argentina and several locations in the United States allowed for the characterization of the charge structure in these regions and for a reliable comparison using the same methodology. About 13.3% of Cordoba thunderstorms were defined by an anomalous charge structure, slightly higher than in Oklahoma (12.5%) and West Texas (11.1%), higher than Alabama (7.3%), and considerably lower than in Colorado (82.6%). Some of the Cordoba anomalous thunderstorms presented enhanced low-level positive charge, a feature rarely if ever observed in Colorado thunderstorms.

The Lightning Imaging Sensor (LIS) was launched to the International Space Station (ISS) in February 2017, detecting optical signatures of lightning with storm-scale horizontal resolution during both day and night. ISS LIS data are available beginning 1 March 2017. Millisecond timing allows detailed intercalibration and validation with other spaceborne and ground-based lightning sensors. Initial comparisons with those other sensors suggest flash detection efficiency around 60% (diurnal variability of 51-75%), false alarm rate under 5%, timing accuracy better than 2 ms, and horizontal location accuracy around 3 km. The spatially uniform flash detection capability of ISS LIS from low-Earth orbit allows assessment of spatially varying flash detection efficiency for other sensors and networks, particularly the Geostationary Lightning Mappers. ISS LIS provides research data suitable for investigations of lightning physics, climatology, thunderstorm processes, and atmospheric composition, as well as realtime lightning data for operational forecasting and aviation weather interests. ISS LIS enables enrichment and extension of the long-term global climatology of lightning from space, and is the only recent platform that extends the global record to higher latitudes (± 55). The global spatial distribution of lightning from ISS LIS is broadly similar to previous datasets, with globally averaged seasonal/annual flash rates about 5-10% lower. This difference is likely due to reduced flash detection efficiency that will be mitigated in future ISS LIS data processing, as well as the shorter ISS LIS period of record. The expected land/ocean contrast in the diurnal variability of global lightning is also observed.

In recent years, global kilometer-scale convection-permitting models have shown promising results in producing realistic convection and precipitation. Cold pools, which can be represented by km-scale models, are identified as one of the significant mesoscale processes responsible for modulating the life cycle of mesoscale organized convection. However, there is still a lack of understanding about cold pool properties across the spatio-temporal scales, as well as their representation in models. In this study, a 2.5 km global Icosahedral Nonhydrostatic (ICON) model simulation run for 40 days (06 UTC 01 Aug - 23 UTC 10 Sep 2016) from the Dynamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) initiative is used to identify thermal cold pools (using Tv) over the tropical oceans. The diurnal cycle of simulated thermal cold pools is compared against NASA’s RapidScat-observed gradient feature (GF) frequency and IMERG precipitation. ICON and IMERG exhibit morning peaks in cold pool activity similar to RapidScat GF frequency but miss the afternoon peak. Advanced Scatterometer (ASCAT) and RapidScat GF spatial climatology is also compared to ICON cold pools, where ICON shows more cold pools over the Indo-Pacific and western Atlantic basins. Random forest regression is applied to identify critical environmental properties with column water vapor found to be most important for controlling cold pool properties. Regional differences between cold pool properties are explored, where easterly waves dominate the eastern Pacific and Atlantic cold pool activity. The western Pacific and the Indian Ocean cold pools are controlled by local mesoscale forcing and intraseasonal oscillations.

We will report on the first systematic comparison between global optical lightning measurements and backscatter lidar observations of cloud properties. The results suggest that lidar observations can provide significant insight into the global thunderstorm climatology and also enable new methods for quality control of spaceborne optical lightning observations. The International Space Station Lightning Imaging Sensor (ISS LIS) has been observing thunderstorms between +/-55° latitude since March 2017. During the first ~8 months of the mission the Cloud-Aerosol Transport System (CATS) lidar was co-located with LIS on the ISS. CATS provided vertical profiles of cloud and aerosol properties along a nadir curtain. For thunderstorms, CATS observations enabled retrieval of cloud-top height, the presence of liquid water vs. ice, and other important cloud properties that are relevant to the production of lightning. Through systematic comparison of ISS LIS and CATS granules, over 8000 LIS-detected flashes were matched with nearby coincident CATS profiles between 1 March and 30 October 2017. All of these flashes’ centroids were within 25 km of the CATS laser’s ground track. Two-dimensional histograms of cloud-top height and latitude show consistency with the expected global behavior of thunderstorm height – namely, that storm heights are constrained by the tropopause, which slopes downward toward the poles. The observed CATS/LIS trend was found to be consistent with long-term March-October thunderstorm 20-dBZ echo-top height climatologies derived from the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) mission (the latter combined with Worldwide Lightning Location Network data). However, the radar-based climatologies indicate that 20-dBZ echo tops average ~2 km lower in altitude compared to lidar-inferred cloud tops. The CATS lidar also enabled identification of potential LIS false alarms (FAs). Additional analyses, including lidar-inferred ice-cloud properties in thunderstorms (e.g., ice-water content), will be presented. Overall, this pathfinder study with a limited ~8-month dataset suggests that fruitful scientific insights may be expected from potentially larger combined lidar/lightning datasets.

The Cyclone Global Navigation Satellite System (CYGNSS) is a multi-satellite constellation that utilizes Global Positioning System (GPS) reflectometry to retrieve near-surface wind speeds over the ocean. While CYGNSS is primarily aimed at measuring wind speeds in tropical cyclones, our research has established that the mission may also provide valuable insight into the relationships between wind-driven surface fluxes and general tropical oceanic convection. Currently, we are examining organized tropical convection using a mixture of CYGNSS level 1 through level 3 data, IMERG (Integrated Multi-satellite Retrievals for Global Precipitation Measurement), and other ancillary datasets (including buoys, GPM level 1 and 2 data, as well as ground-based radar). In addition, observing system experiments (OSEs) are being performed using hybrid three-dimensional variational assimilation to ingest CYGNSS observations into a limited-domain, convection-resolving model. Our focus for now is on case studies of convective evolution, but we will also report on progress toward statistical analysis of convection sampled by CYGNSS. Our working hypothesis is that the typical mature phase of organized tropical convection is marked by the development of a sharp gust-front boundary from an originally spatially broader but weaker wind speed change associated with precipitation. This increase in the wind gradient, which we demonstrate is observable by CYGNSS, likely helps to focus enhanced turbulent fluxes of convection-sustaining heat and moisture near the leading edge of the convective system where they are more easily ingested by the updraft. Progress on the testing and refinement of this hypothesis, using a mixture of observations and modeling, will be reported.

Approximately eight months of co-located spaceborne lidar and lightning observations were analyzed in a pathfinder study to understand the advantages and challenges of using these combined observations to understand thunderstorms. Data from the Lightning Imaging Sensor (LIS) and the Cloud-Aerosol Transport System (CATS) lidar were used when they overlapped on the International Space Station during March-October 2017. Using simple matching criteria, 8246 LIS flashes occurred within 25 km of the CATS ground track. CATS cloud-top heights near these flashes showed similar behavior with latitude when compared to a spaceborne radar-based climatology, but the lidar cloud tops were approximately 2-km higher than 20-dBZ radar echo tops. CATS cloud phase near LIS flashes was consistent with ice or mixed-phase more than 90% of the time, showing the value of using lightning observations to validate lidar-based feature masks. In addition, correlations between a proxy for LIS flash rate and CATS ice water path, cloud optical depth, and cloud-top height were low (0.38-0.42) but positive and highly statistically significant (> 99%), suggesting lidar retrievals of cloud properties can be meaningfully compared with lightning observations despite lidar’s known inability to penetrate deeply into optically thick clouds like thunderstorms. Finally, CATS was used to help diagnose LIS false alarms due to surface-based glint. The false alarm rate was approximately 0.1%, which demonstrated the excellent performance of the surface glint filter in the LIS processing code. The results suggest that fruitful scientific insights can be expected from larger combined lidar/lightning datasets.