An impact-type Joss–Waldvogel disdrometer (JWD), a two-dimensional video disdrometer (2DVD), and a laser optical OTT Particle Size and Velocity (PARSIVEL) disdrometer (PD) were used to measure the raindrop size distribution (DSD) over a 6-month period in Huntsville, Alabama. Comparisons indicate event rain totals for all three disdrometers that were in reasonable agreement with a reference rain gauge. In a relative sense, hourly composite DSDs revealed that the JWD was more sensitive to small drops (<1 mm), while the PD appeared to severely underestimate small drops less than 0.76 mm in diameter. The JWD and 2DVD measured comparable number concentrations of midsize drops (1–3 mm) and large drops (3–5 mm), while the PD tended to measure relatively higher drop concentrations at sizes larger than 2.44 mm in diameter. This concentration disparity tended to occur when hourly rain rates and drop counts exceeded 2.5 mm h−1 and 400 min−1, respectively. Based on interactions with the PD manufacturer, the partially inhomogeneous laser beam is considered the cause of the PD drop count overestimation. PD drop fall speeds followed the expected terminal fall speed relationship quite well, while the 2DVD occasionally measured slower drops for diameters larger than 2.4 mm, coinciding with events where wind speeds were greater than 4 m s−1. The underestimation of small drops by the PD had a pronounced effect on the intercept and shape of parameters of gamma-fitted DSDs, while the overestimation of midsize and larger drops resulted in higher mean values for PD integral rain parameters.

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.

An algorithm that provides an early indication of impending severe weather from observed trends in thunderstorm total lightning flash rates has been developed. The algorithm framework has been tested on 20 thunderstorms, including 1 nonsevere storm, which occurred over the course of six separate days during the spring months of 2002 and 2003. The identified surges in lightning rate (or jumps) are compared against 110 documented severe weather events produced by these thunderstorms as they moved across portions of northern Alabama and southern Tennessee. Lightning jumps precede 90% of these severe weather events, with as much as a 27-min advance notification of impending severe weather on the ground. However, 37% of lightning jumps are not followed by severe weather reports. Various configurations of the algorithm are tested, and the highest critical success index attained is 0.49. Results suggest that this lightning jump algorithm may be a useful operational diagnostic tool for severe thunderstorm potential.

Rainfall retrieval algorithms often assume a gamma-shaped raindrop size distribution (DSD) with three mathematical parameters N_w, D_m, and μ. If only two independent measurements are available, as with the dual-frequency precipitation radar on the Global Precipitation Measurement (GPM) mission core satellite, then retrieval algorithms are underconstrained and require assumptions about DSD parameters. To reduce the number of free parameters, algorithms can assume that μ is either a constant or a function of D_m. Previous studies have suggested μ–Λ constraints [where Λ = (4 + μ)/D_m], but controversies exist over whether μ–Λ constraints result from physical processes or mathematical artifacts due to high correlations between gamma DSD parameters. This study avoids mathematical artifacts by developing joint probability distribution functions (joint PDFs) of statistically independent DSD attributes derived from the raindrop mass spectrum. These joint PDFs are then mapped into gamma-shaped DSD parameter joint PDFs that can be used in probabilistic rainfall retrieval algorithms as proposed for the GPM satellite program. Surface disdrometer data show a high correlation coefficient between the mass spectrum mean diameter D_m and mass spectrum standard deviation σ_m. To remove correlations between DSD attributes, a normalized mass spectrum standard deviation is constructed to be statistically independent of D_m, with representing the most likely value and std representing its dispersion. Joint PDFs of D_m and μ are created from D_m and . A simple algorithm shows that rain-rate estimates had smaller biases when assuming the DSD breadth of than when assuming a constant μ.

Measurements from a 2-D video disdrometer (2DVD) have been used for drop size distribution (DSD) comparisons with co-located Parsivel measurements in Huntsville, Alabama. The comparisons were made in terms of the mass-weighted mean diameter, Dm, the standard deviation of the mass-spectrum, σm, and the rainfall rate, R, all based on 1-min DSD from the two instruments. Time series comparisons show close agreement in all three parameters for cases where R was less than 20 mm h−1. In four cases, discrepancies in all three parameters were seen for "heavy" events, with the Parsivel showing higher Dm, σm and R, when R reached high values (particularly above 30 mm h−1). Possible causes for the discrepancies include the presence of a small percentage of non-fully melted hydrometers, with higher than expected fall velocity and with very different axis ratios as compared with rain, indicating small hail or ice pellets or graupel. We also present here Parsivel-to-Parsivel comparisons as well as comparisons between two 2DVD instruments, namely a low-profile unit and the latest generation, "compact unit" which was installed at the same site in November 2009. The comparisons are included to assess the variability between the same types of instrument. Correlation coefficients and the fractional standard errors are compared.