[1] The Optical Transient Detector (OTD) is a space-based instrument specifically designed to detect and locate lightning discharges as it orbits the Earth. This instrument is a scientific payload on the MicroLab-1 satellite that was launched into a 70°inclination low Earth orbit in April 1995. Given the orbital trajectory of the satellite, most regions of the Earth are observed by the OTD instrument more than 400 times during a 1 year period, and the average duration of each observation is 2 min. The OTD instrument optically detects lightning flashes that occur within its 1300 Â 1300 km 2 field of view during both day and night conditions. A statistical examination of OTD lightning data reveals that nearly 1.4 billion flashes occur annually over the entire Earth. This annual flash count translates to an average of 44 ± 5 lightning flashes (intracloud and cloud-to-ground combined) occurring around the globe every second, which is well below the traditional estimate of 100 fl s À1 that was derived in 1925 from world thunder day records. The range of uncertainty for the OTD global totals represents primarily the uncertainty (and variability) in the flash detection efficiency of the instrument. The OTD measurements have been used to construct lightning climatology maps that demonstrate the geographical and seasonal distribution of lightning activity for the globe. An analysis of this annual lightning distribution confirms that lightning occurs mainly over land areas, with an average land/ocean ratio of $10:1. The Congo basin, which stands out year-round, shows a peak mean annual flash density of 80 fl km À2 yr À1 in Rwanda, and includes an area of over 3 million km 2 exhibiting flash densities greater than 30 fl km À2 yr À1 (the flash density of central Florida). Lightning is predominant in the northern Atlantic and western Pacific Ocean basins year-round where instability is produced from cold air passing over warm ocean water. Lightning is less frequent in the eastern tropical Pacific and Indian Ocean basins where the air mass is warmer. A dominant Northern Hemisphere summer peak occurs in the annual cycle, and evidence is found for a tropically driven semiannual cycle.

Two approaches are used to characterize how accurately the north Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., anomalous VHF noise sources) are neglected. The detailed spatial distributions of retrieval errors are provided. Even though the two methods are independent of one another, they nevertheless provide remarkably similar results. However, altitude error estimates derived from the two methods differ (the Monte Carlo result being taken as more accurate). Additionally, this study clarifies the mathematical retrieval process. In particular, the mathematical difference between the first-guess linear solution and the Marquardt-iterated solution is rigorously established thereby explaining why Marquardt iterations improve upon the linear solution.

[1] Arrays that detect and locate the four-dimensional spacetime positions of radiation sources from lightning have largely utilized sensors sensitive to the very high frequency (VHF) regime with 15 km baselines or very low frequency/low frequency (VLF/LF) regime with 100 km baselines. This paper details initial results from the newly developed Huntsville Alabama Marx Meter Array (HAMMA), consisting of Marx meters (electric field change meters) sensitive to a frequency band 1 Hz to 400 kHz. The arrival time of HAMMA waveforms due to radiation sources from lightning are used to determine the spacetime position of these sources. The locations are compared with two well-documented and operational arrays, the National Lightning Detection Network (NLDN) and the North Alabama Lightning Mapping Array (NALMA). The standard deviation of the difference between HAMMA and NLDN locations of return strokes is 305 and 266 m in x and y, respectively, while the standard deviation of the difference between HAMMA and NALMA sources is 237, 226, and 688 m in x, y and z, respectively. We further show that NLDN intracloud locations differ in horizontal distance from the corresponding HAMMA locations by a median value of 479 m. In addition, we use HAMMA source locations to map several lightning flashes in the VLF/LF and show HAMMA sources largely map out the same electrical extent as VHF sources and provide unique insights to the properties of the discharges occurring. Finally, we show that VLF/LF sources can determine the leader polarity in several example flashes but not necessarily whether a flash comes to ground.

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 real‐time 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 data sets, 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.

Bioaerosol transport in the atmosphere disperses microbial species between continents, affects human and plant health, and may influence hydrologic cycling. However, there have been few quantitative observations of bioaerosols at altitudes more than a few kilometers above the surface. Lack of data on bioaerosol distributions in the atmosphere has impeded efforts to assess the aerial dissemination of microbes and their vertical extent in the biosphere. In this study, a helium balloon payload system was used to sample microbial cells and dust particles in air masses as high as 38 km above sea level over three locations in the southwestern United States. The cell concentrations at altitudes between 3 and 29 km were highly similar (2-5 × 10 5 cells m −3 ) and approximately threefold lower than those observed in the convective boundary layer (CBL; 1 × 10 6 cells m −3 ), decreasing to 8 × 10 4 cells m −3 at 35-38 km. The detection of adenosine triphosphate (ATP) and recovery of bacteria possessing extreme tolerance to desiccation and shortwave ultraviolet radiation confirmed that certain microorganisms have the capacity to persist at lower altitudes of the stratosphere. Our data and related calculations provide constraints on the upper altitudinal boundary for microbial habitability in the biosphere.