Optical lightning sensors like the Optical Transient Detector and Lightning Imaging Sensor (LIS) measure total lightning across large swaths of the globe with high detection efficiency. With two upcoming missions that employ these sensors—LIS on the International Space Station and the Geostationary Lightning Mapper on the GOES‐R satellite—there has been increased interest in what these measurements can reveal about lightning and thunderstorms in addition to total flash activity. Optical lightning imagers are capable of observing the characteristics of individual flashes that include their sizes, durations, and radiative energies. However, it is important to exercise caution when interpreting trends in optical flash measurements because they can be affected by the scene. This study uses coincident measurements from the Tropical Rainfall Measuring Mission (TRMM) satellite to examine the properties of LIS flashes and the surrounding cloud regions they illuminate. These combined measurements are used to assess to what extent optical flash characteristics can be used to make inferences about flash structure and energetics. Clouds illuminated by lightning over land and ocean regions that are otherwise similar based on TRMM measurements are identified. Even when LIS flashes occur in similar clouds and background radiances, oceanic flashes are still shown to be larger, brighter, longer lasting, more prone to horizontal propagation, and to contain more groups than their land‐based counterparts. This suggests that the optical trends noted in literature are not entirely the result of radiative transfer effects but rather stem from physical differences in the flashes.

A unique dataset of coincident high-altitude passive microwave and electric field observations taken by the NASA ER-2 aircraft is used to assess the feasibility of estimating electric fields above electrified clouds using ubiquitous global and multidecadal satellite products. Once applied to a global dataset, such a product would provide a unique approach for diagnosing and monitoring the current sources of the global electric circuit (GEC).In this study an algorithm has been developed that employs ice scattering signals from 37-and 85-GHz passive microwave observations to characterize the electric fields above clouds overflown by the ER-2 aircraft at nearly 20-km altitude. Electric field estimates produced by this passive microwave algorithm are then compared to electric field observations also taken by the aircraft to assess its potential future utility with satellite datasets. The algorithm is shown to estimate observed electric field strengths over intense convective clouds at least 71% (58%) of the time over land and 43% (40%) of the time over the ocean to within a factor of 2 from 85-GHz (37 GHz) passive microwave observations. Electric fields over weaker clouds can be estimated 58% (41%) of the time over land and 22% (8%) of the time over the ocean from 85-GHz (37 GHz) passive microwave observations. The accuracy of these estimates is limited by systematic errors in the observations along with other factors. Despite these sources of error, the algorithm can produce reasonable estimates of electric fields over carefully selected individual electrified clouds that differ from observations by less than 20 V m 21 for clouds that produce 200-400 V m 21 electric fields at 20 km.

Electrified clouds are known to play a major role in the Global Electric Circuit. These clouds produce upward currents which maintain the potential difference between Earth's surface and the upper atmosphere. In this study, model output from two simulations of the Community Earth System Model (CESM) are compared with conduction currents and other data derived from the Tropical Rainfall Measuring Mission (TRMM) satellite, including both the Lightning Imaging Sensor and Precipitation Radar. The intention is to determine CESM's skill at representing these microphysical and dynamical properties of clouds. Then, these cloud properties are used to develop a model parameterization to compute conduction currents from electrified clouds. Specifically, we evaluate the ability of global mean convective mass flux, ice water path, and convective precipitation to represent conduction current sources. Parameterizations using these variables yield derived global mean currents that agree well with the geographical patterns of TRMM currents. In addition, comparing the diurnal variations of modeled global mean current to the observed diurnal variations of electric potential gradient, root‐mean‐square (RMS) errors range between 6.5% and 8.1%, but the maximum occurs 4 to 6 h early in all three variables. Output currents derived from the model variables generally match well to the currents derived from TRMM, and the total global current estimates agree well with past studies. This suggests that cloud parameters are well suited for representing the global distribution and strength of currents in a global model framework.

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