CAPE Times P Explains Lightning Over Land But Not the Land‐Ocean Contrast

Romps, David M.; Charn, Alexander B.; Holzworth, R. H.; Lawrence, William E.; Molinari, John; Vollaro, David

doi:10.1029/2018gl080267

Cited by 63 publications

(89 citation statements)

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“…CAPE × P was introduced by Romps et al () and has been validated extensively over CONUS (Romps et al, , ; Tippett et al, ). In the cloud‐resolving simulations over CONUS used in section , CAPE is calculated instantaneously, the precipitation rate P is averaged over the ensuing three hours, and CAPE × P is defined as their product.…”

Section: Proxiesmentioning

confidence: 99%

Evaluating the Future of Lightning in Cloud‐Resolving Models

Romps

2019

Geophysical Research Letters

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Two proxies for lightning predict very different responses to global warming: the CAPE times precipitation proxy predicts a large increase in lightning over both the continental United States and the tropical oceans, while the ice flux proxy predicts a small increase over the United States and a decrease over the tropical oceans. To date, however, these proxies have been studied only in global climate models with parameterized convection. Here, cloud-resolving simulations are used to assess their predictions of future lightning rates. Over the United States, all proxies predict a large increase in the lightning rate in the range of 8-16%/K. On the other hand, in the tropics as modeled by radiative convective equilibrium, half of the proxies predict an increase (of 5-12%/K), while the other half predict a decrease (of 1-4%/K). The reasons for the different responses of these proxies is explored, but it remains unclear which proxy is best suited to predicting future lightning rates. SimulationsThe analysis presented here will take advantage of two sets of simulations available from other studies: a pair of 13-year-long cloud-resolving simulations over CONUS (RM. Rasmussen & Liu, 2017) and three 4-year-long cloud-resolving simulations of tropical radiative convective equilibrium (RCE) over a slab ocean. WRF Simulations of CONUSThe pair of cloud-resolving simulations over CONUS were conducted with the Weather Research and Forecasting (WRF) model v3.4.1 using a 4-km horizontal grid spacing (RM. Rasmussen & Liu, 2017). Key Points:• Lightning proxies are studied in cloud-resolving simulations of global warming over the United States and the tropical ocean • All the proxies predict that lightning increases over the United States in the range of 8-16% per kelvin • The proxies disagree over the tropical ocean, predicting either a substantial increase of 5-12%/K or a moderate decrease of 1-4%/K Supporting Information:• Supporting Information S1

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Section: Proxiesmentioning

confidence: 99%

Evaluating the Future of Lightning in Cloud‐Resolving Models

Romps

2019

Geophysical Research Letters

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“…One by Romps et al (2014Romps et al ( , 2018, hereafter called CPCAPE, based on the product of the CP and the convective available potential energy (CAPE), and another one by Finney et al (2014), hereafter called ICEFLUX, based on the upward ice flux-lightning relationship. One by Romps et al (2014Romps et al ( , 2018, hereafter called CPCAPE, based on the product of the CP and the convective available potential energy (CAPE), and another one by Finney et al (2014), hereafter called ICEFLUX, based on the upward ice flux-lightning relationship.…”

Section: Lightning Parameterizationsmentioning

confidence: 99%

“…We have analyzed four of the lightning parameterizations (CTH, CTH-M, CP, and MFLUX) considered by Clark et al (2017) plus the CPCAPE and ICEFLUX lightning schemes recently proposed by Romps et al (2014Romps et al ( , 2018 and Finney et al (2014), respectively. We have analyzed four of the lightning parameterizations (CTH, CTH-M, CP, and MFLUX) considered by Clark et al (2017) plus the CPCAPE and ICEFLUX lightning schemes recently proposed by Romps et al (2014Romps et al ( , 2018 and Finney et al (2014), respectively.…”

Section: Introductionmentioning

confidence: 99%

“…In the present paper we have explored not only the global lightning frequency but also how lightning affect the global atmospheric chemistry depending on the selected lightning parameterization. We have analyzed four of the lightning parameterizations (CTH, CTH-M, CP, and MFLUX) considered by Clark et al (2017) plus the CPCAPE and ICEFLUX lightning schemes recently proposed by Romps et al (2014Romps et al ( , 2018 and Finney et al (2014), respectively.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Six Lightning Parameterizations in CAM5 and the Impact on Global Atmospheric Chemistry

Gordillo‐Vázquez

Pérez‐Invernón

Huntrieser

et al. 2019

Earth and Space Science

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We present simulations performed with six lightning parameterizations implemented in the Community Atmosphere Model (CAM5). The amount of lightning-produced nitrogen oxides (LNO x ) by the various schemes considered is estimated. We provide some insight on how the lightning NO injected in the atmosphere influences the global concentrations of key chemical species such as OH, HO 2 , H 2 O 2 , NO x , O 3 , SO 2 , CO, and HNO 3 . The vertical global averaged densities of HO 2 , H 2 O 2 , CO, and SO 2 are depleted due to lightning while those of NO, NO 2 , O 3 , OH, and HNO 3 increase. Our results indicate that the parameterizations based on the upward ice flux (ICEFLUX) exhibit the largest global and midlatitude spatial correlations (0.73 and 0.632 for ICEFLUX and 0.72 and 0.553 for cloud top height) with respect to satellite global flash rate observations. Five out of the six lightning schemes investigated exhibit larger LNO x per flash in the midlatitudes than in the tropics. In particular, it is found that the ICEFLUX midlatitude LNO x per flash exhibits the largest difference with respect to its predicted tropical LNO x per flash, in agreement with available observations. When using CAM5, the ICEFLUX lightning parameterization could be considered a reliable lightning scheme (within its intrinsic uncertainties) in terms of its geographical distribution. Both ICEFLUX and cloud top height results agree with the enhancements of NO 2 and O 3 produced by lightning over tropical Atlantic and Africa and the weaker lightning background over the tropical Pacific reported by Martin et al. (2007) in the periods and locations (upper troposphere) where lightning is expected to dominate the trace gas observations.

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“…Investigating the diurnal cycle of atmospheric electricity facilitates understanding this relationship between the GEC and weather. Over the past few years, the interest in studying the diurnal variation of atmospheric electrical parameters has been increasing; recent progress in this direction is related to satellite and aircraft cloud observations (Liu et al, 2010;Mach et al, 2011;Peterson et al, 2017), analyzing the data of global lightning locating systems (Hutchins et al, 2014;Mezuman et al, 2014), and using weather and climate models to simulate DC GEC parameters (Jánský et al, 2017;Kalb et al, 2016;Mareev & Volodin, 2014) and distribution of lightning flashes (Romps et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Modeling Contributions of Continents and Oceans to the Diurnal Variation of the Global Electric Circuit

Slyunyaev

Ilin

Mareev

2019

Geophysical Research Letters

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Contributions of different land and ocean regions to the diurnal variation of the global electric circuit are simulated using the Weather Research and Forecasting model by estimating the ionospheric potential produced by thunderstorms and electrified shower clouds in each grid column. The model predicts that contributions from land regions have maxima at about 14:00–18:00 local time (LT), whereas contributions from oceans have maxima at about 2:00–6:00 LT, and different ocean regions show nearly the same relative diurnal variation. It is remarkable that contributions from ocean regions with many islands (Maritime Continent and Middle America) have maxima at both 14:00–18:00 and 2:00–6:00 LT.

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CAPE Times P Explains Lightning Over Land But Not the Land‐Ocean Contrast

Cited by 63 publications

References 23 publications

Evaluating the Future of Lightning in Cloud‐Resolving Models

Evaluating the Future of Lightning in Cloud‐Resolving Models

Comparison of Six Lightning Parameterizations in CAM5 and the Impact on Global Atmospheric Chemistry

Modeling Contributions of Continents and Oceans to the Diurnal Variation of the Global Electric Circuit

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