Search Results

You are looking at 1 - 8 of 8 items for

  • Author or Editor: Martin J. Murphy x
  • All content x
Clear All Modify Search
Martin J. Murphy and Ronald L. Holle

Abstract

A local maximum in cloud-to-ground (CG) lightning flash density over northwestern Mexico as measured by the U.S. National Lightning Detection Network is examined in detail. Corrections are derived for the relative detection efficiency of the network in this region that is outside the perimeter of the sensors. The need to adjust the parameters of the signal normalization model used for the network is also documented. New propagation model parameters are employed to derive relative detection efficiency corrections for northwestern Mexico and these are then used to show that the actual CG flash density over the region significantly exceeds that observed in Florida, the area with the highest flash density within the perimeter of the network.

Full access
Martin J. Murphy and Ronald L. Holle
Full access
Ronald L. Holle and Martin J. Murphy

Abstract

Temporal and spatial distributions of the North American monsoon have been studied previously with rainfall and satellite data. In the current study, the monsoon is examined with lightning data from Vaisala’s Global Lightning Dataset (GLD360). GLD360 has been operating for over three years and provides sufficient data to develop an exploratory climatology with minimal spatial variation in detection efficiency and location accuracy across the North American monsoon region. About 80% of strokes detected by GLD360 are cloud to ground. This paper focuses on seasonal, monthly, and diurnal features of lightning occurrence during the monsoon season from Mazatlán north-northwest to northern Arizona and New Mexico. The goal is to describe thunderstorm frequency with a dataset that provides uniform spatial coverage at a resolution of 2–5 km and uniform temporal coverage with individual lightning events resolved to the millisecond, compared with prior studies that used hourly point rainfall or satellite data with a resolution of several kilometers. The monthly lightning stroke density over northwestern Mexico increases between May and June, as thunderstorms begin over the high terrain east of the Gulf of California. The monthly lightning stroke density over the entire region increases dramatically to a maximum in July and August. The highest stroke densities observed in Mexico approach those observed by GLD360 in subtropical and tropical regions in Africa, Central and South America, and Southeast Asia. The diurnal cycle of lightning exhibits a maximum over the highest terrain near noon, associated with daytime solar heating, a maximum near midnight along the southern coast of the Gulf, and a gradual decay toward sunrise.

Full access
Ronald L. Holle and Martin J. Murphy

Abstract

Lightning stroke density measured by the Global Lightning Dataset (GLD360) has shown several strong maxima around the globe. Several of these extremes are located over large tropical water bodies surrounded by terrain features. Four prominent maxima are examined and compared in this study: Lake Maracaibo in South America, the Strait of Malacca in equatorial Asia, Lake Victoria in East Africa, and Lake Titicaca in South America. Specifically, the authors observe that all four water bodies exhibit sustained maxima in lightning occurrence all night, the peak lightning frequency occurs very late at night or the following morning at three of the four sites, and the nocturnal maxima are out of phase at the four locations even though the afternoon maxima over the surrounding terrain all occur between 1500 and 1700 local solar time. The meteorological factors affecting the diurnal cycle of lightning occurrence over these four water bodies, which are all adjacent to mountains, are explored in this study.

Full access
Martin J. Murphy, John A. Cramer, and Ryan K. Said

Abstract

The U.S. National Lightning Detection Network (NLDN) underwent a complete sensor upgrade in 2013 followed by a central processor upgrade in 2015. These upgrades produced about a factor-of-five improvement in the detection efficiency of cloud lightning flashes and about one additional cloud pulse geo-located per flash. However, they also re-aggravated a historical problem with the tendency to misclassify a population of low-current positive discharges as cloud-to-ground strokes when, in fact, most are probably cloud pulses. Furthermore, less than 0.1% of events were poorly geo-located because the contributing sensor data were either improperly associated or simply under-utilized by the geo-location algorithm. To address these issues, Vaisala developed additional improvements to the central processing system, which became operational on November 7, 2018. This paper describes updates to the NLDN between 2013-2018 and then focuses on the effects of classification algorithm changes and a simple means to normalize classification across upgrades.

Restricted access
Donald R. MacGorman, Ivy R. Apostolakopoulos, Nicole R. Lund, Nicholas W. S. Demetriades, Martin J. Murphy, and Paul R. Krehbiel

Abstract

The first flash produced by a storm usually does not strike ground, but little has been published concerning the time after the first flash before a cloud-to-ground flash occurs, particularly for a variety of climatological regions. To begin addressing this issue, this study analyzed data from very-high-frequency (VHF) lightning mapping systems, which detect flashes of all types, and from the U.S. National Lightning Detection Network (NLDN), which identifies flash type and detects roughly 90% of cloud-to-ground flashes overall. VHF mapping data were analyzed from three regions: north Texas, Oklahoma, and the high plains of Colorado, Kansas, and Nebraska. The percentage of storms in which a cloud-to-ground flash was detected in the first minute of lightning activity varied from 0% in the high plains to 10%–20% in Oklahoma and north Texas. The distribution of delays to the first cloud-to-ground flash varied similarly. In Oklahoma and north Texas, 50% of storms produced a cloud-to-ground flash within 5–10 min, and roughly 10% failed to produce a cloud-to-ground flash within 1 h. In the high plains, however, it required 30 min for 50% of storms to have produced a cloud-to-ground flash, and 20% produced no ground flash within 1 h. The authors suggest that the reason high plains storms take longer to produce cloud-to-ground lightning is because the formation of the lower charge needed to produce most cloud-to-ground flashes is inhibited either by delaying the formation of precipitation in the mid- and lower levels of storms or by many of the storms having an inverted-polarity electrical structure.

Full access
Elizabeth J. Kendon, Nigel M. Roberts, Giorgia Fosser, Gill M. Martin, Adrian P. Lock, James M. Murphy, Catherine A. Senior, and Simon O. Tucker

Abstract

For the first time, a model at a resolution on par with operational weather forecast models has been used for national climate scenarios. An ensemble of 12 climate change projections at convection-permitting (2.2 km) scale has been run for the United Kingdom, as part of the UK Climate Projections (UKCP) project. Contrary to previous studies, these show greater future increases in winter mean precipitation in the convection-permitting model compared with the coarser (12 km) driving model. A large part (60%) of the future increase in winter precipitation occurrence over land comes from an increase in convective showers in the 2.2 km model, which are most likely triggered over the sea and advected inland with potentially further development. In the 12 km model, increases in precipitation occurrence over the sea, largely due to an increase in convective showers, do not extend over the land. This is partly due to known limitations of the convection parameterization scheme, used in conventional coarse-resolution climate models, which acts locally without direct memory and so has no ability to advect diagnosed convection over the land or trigger new showers along convective outflow boundaries. This study shows that the importance of accurately representing convection extends beyond short-duration precipitation extremes and the summer season to projecting future changes in mean precipitation in winter.

Restricted access
Ralph A. Kahn, Tim A. Berkoff, Charles Brock, Gao Chen, Richard A. Ferrare, Steven Ghan, Thomas F. Hansico, Dean A. Hegg, J. Vanderlei Martins, Cameron S. McNaughton, Daniel M. Murphy, John A. Ogren, Joyce E. Penner, Peter Pilewskie, John H. Seinfeld, and Douglas R. Worsnop

Abstract

A modest operational program of systematic aircraft measurements can resolve key satellite aerosol data record limitations. Satellite observations provide frequent global aerosol amount maps but offer only loose aerosol property constraints needed for climate and air quality applications. We define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ. The flight program could characterize major aerosol airmass types statistically, at a level of detail unobtainable from space. It would 1) enhance satellite aerosol retrieval products with better climatology assumptions and 2) improve translation between satellite-retrieved optical properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space; improve aerosol constraints on climate modeling; help interrelate remote sensing, in situ, and modeling aerosol-type definitions; and contribute to future satellite aerosol missions. Fifteen required variables are identified and four payload options of increasing ambition are defined to constrain these quantities. “Option C” could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable, even if aerosol loading varies.

Open access