Abstract
Since their introduction 22 years ago, lightning mapping arrays (LMA) have played a central role in the investigation of lightning physics. Even in recent years with the proliferation of digital interferometers and the introduction of the LOw Frequency ARray (LOFAR) radio telescope, LMAs still play an important role in lightning science. LMA networks use a simple windowing technique that records the highest pulse in either 80 μs or 10 μs fixed windows in order to apply a time‐of‐arrival location technique. In this work, we develop an LMA‐emulator that uses lightning data recorded by LOFAR to simulate an LMA, and we use it to test three new styles of pulse windowing. We show that they produce very similar results as the more traditional LMA windowing, implying that LMA lightning mapping results are relatively independent of windowing technique. In addition, each LMA station has its GPS‐conditioned clock. While the timing accuracy of GPS receivers has improved significantly over the years, they still significantly limit the timing measurements of the LMA. Recently, new time‐of‐arrival techniques have been introduced that can be used to self‐calibrate systematic offsets between different receiving stations. Applying this calibration technique to a set of data with 32 ns uncertainty, observed by the Colorado LMA, improves the timing uncertainty to 19 ns. This technique is not limited to LMAs and could be used to help calibrate future multi‐station lightning interferometers.
Highlights
Since their introduction 22 years ago, lightning mapping arrays (LMAs) have played a central role in investigating lightning physics and storm electrification processes (Rison et al, 1999)
We developed a system to emulate the operation of an LMA with LOw Frequency ARray (LOFAR)
This LMA-emulator allowed us to test the effect of different windowing techniques
Summary
Since their introduction 22 years ago, lightning mapping arrays (LMAs) have played a central role in investigating lightning physics and storm electrification processes (Rison et al, 1999). LMA networks use a simple windowing technique that records the highest pulse in fixed time windows, either 80 μs or 10 μs in length, in order to apply a time-of-arrival location technique Such a windowing scheme could potentially be improved, as high-amplitude pulses that should be locatable often occur in the same time window, either at all or some of the stations, and/or with different peak amplitudes and being selected, in which case one or more pulses are not detected. We apply new time-of-arrival techniques for self-calibrating systematic offsets in LOFAR observations to develop an algorithm that corrects small remnant systematic timing differences between LMA stations This algorithm can improve the timing accuracy of a set of data collected by the Colorado LMA (COLMA) (which typically has 25 ns uncertainty) from 32 to 19 ns. This technique is very instrument-agnostic, and could be applied to future multi-station interferometers
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