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Dive into the research topics where Steven J. Goodman is active.

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Featured researches published by Steven J. Goodman.


Journal of Geophysical Research | 2012

Aerosol indirect effect on tropospheric ozone via lightning

Tianle Yuan; Lorraine A. Remer; Huisheng Bian; Jerald R. Ziemke; Rachel I. Albrecht; Kenneth E. Pickering; Lazaros Oreopoulos; Steven J. Goodman; Hongbin Yu; Dale J. Allen

[1]xa0Tropospheric ozone (O3) is a pollutant and major greenhouse gas and its radiative forcing is still uncertain. Inadequate understanding of processes related to O3 production, in particular those natural ones such as lightning, contributes to this uncertainty. Here we demonstrate a new effect of aerosol particles on O3production by affecting lightning activity and lightning-generated NOx (LNOx). We find that lightning flash rate increases at a remarkable rate of 30 times or more per unit of aerosol optical depth. We provide observational evidence that indicates the observed increase in lightning activity is caused by the influx of aerosols from a volcano. Satellite data analyses show O3is increased as a result of aerosol-induced increase in lightning and LNOx, which is supported by modle simulations with prescribed lightning change. O3production increase from this aerosol-lightning-ozone link is concentrated in the upper troposphere, where O3 is most efficient as a greenhouse gas. In the face of anthropogenic aerosol increase our findings suggest that lightning activity, LNOx and O3, especially in the upper troposphere, have all increased substantially since preindustrial time due to the proposed aerosol-lightning-ozone link, which implies a stronger O3 historical radiative forcing. Aerosol forcing therefore has a warming component via its effect on O3 production and this component has mostly been ignored in previous studies of climate forcing related to O3and aerosols. Sensitivity simulations suggest that 4–8% increase of column tropospheric ozone, mainly in the tropics, is expected if aerosol-lighting-ozone link is parameterized, depending on the background emission scenario. We note, however, substantial uncertainties remain on the exact magnitude of aerosol effect on tropospheric O3 via lightning. The challenges for obtaining a quantitative global estimate of this effect are also discussed. Our results have significant implications for understanding past and projecting future tropospheric O3forcing as well as wildfire changes and call for integrated investigations of the coupled aerosol-cloud-chemistry system.


Journal of Applied Remote Sensing | 2013

Geostationary Operational Environmental Satellite (GOES)-14 super rapid scan operations to prepare for GOES-R

Timothy J. Schmit; Steven J. Goodman; Daniel T. Lindsey; Robert M. Rabin; Kristopher M. Bedka; Mathew M. Gunshor; John L. Cintineo; Christopher S. Velden; A. Scott Bachmeier; Scott Lindstrom; Christopher C. Schmidt

Abstract Geostationary Operational Environmental Satellite (GOES)-14 imager was operated by National Oceanic and Atmospheric Administration (NOAA) in an experimental rapid scan 1-min mode that emulates the high-temporal resolution sampling of the Advanced Baseline Imager (ABI) on the next generation GOES-R series. Imagery with a refresh rate of 1 min of many phenomena were acquired, including clouds, convection, fires, smoke, and hurricanes, including 6 days of Hurricane Sandy through landfall. NOAA had never before operated a GOES in a nearly continuous 1-min mode for such an extended period of time, thereby making these unique datasets to explore the future capabilities possible with GOES-R. The next generation GOES-R imager will be able to routinely take mesoscale ( 1000 u2009 u2009 km × 1000 u2009 u2009 km ) images every 30 s (or two separate locations every minute). These images can be acquired even while scanning continental United States and full disk images. These high time-resolution images from the GOES-14 imager are being used to prepare for the GOES-R era and its advanced imager. This includes both the imagery and quantitative derived products such as cloud-top cooling. Several animations are included to showcase the rapid change of the many phenomena observed during super rapid scan operations for GOES-R (SRSOR).


93rd American Meteorological Society Annual Meeting | 2014

Integration of the Total Lightning Jump Algorithm into Current Operational Warning Environment Conceptual Models

Christopher J. Schultz; Lawrence D. Carey; Elise V. Schultz; Geoffrey T. Stano; Rich Blakeslee; Steven J. Goodman


Archive | 2010

The Geostationary Lighting Mapper (GLM) for GOES-R: A New Operational Capability to Improve Storm Forecasts and Warnings

Steven J. Goodman; Rich Blakeslee; William J. Koshak; Walt Petersen; Lisa A. Carey; D. Mah


Archive | 2010

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

Steven J. Goodman; Richard J. Blakeslee; William J. Koshak; Douglas M. Mach


Archive | 2010

Total lightning flash characteristics observed from TRMM Lightning Imaging Sensor (LIS) and their relationship with regional convection and precipitation type

Rachel I. Albrecht; Kartik Gopalan; Nancy Wang; Eric C. Bruning; Steven J. Goodman; Ralph Ferraro


Meteoritics & Planetary Science | 2018

Detection of meteoroid impacts by the Geostationary Lightning Mapper on the GOES-16 satellite

Peter Jenniskens; Jim Albers; Clemens E. Tillier; Samantha F. Edgington; Randolph S. Longenbaugh; Steven J. Goodman; Scott D. Rudlosky; Alan R. Hildebrand; Lincoln Hanton; Fabio Ciceri; Richard Nowell; Esko Lyytinen; Donald Hladiuk; Dwayne Free; Nicholas A. Moskovitz; Len Bright; Christopher O. Johnston; Eric Stern


Archive | 2016

A.52: The WRF Lightning Forecast Algorithm: Characterization of Lightning Jumps in Simulated Storms

Eugene W. McCaul; Jonathan L. Case; Themis G. Chronis; Steven J. Goodman


Archive | 2013

Investigating the Use of Deep Convective Clouds (DCCT) to Monitor On-orbit Performance of the Geostationary Lightning Mapper (GLM) using Lightning Imaging Sensor (LIS) Measurements

Dennis E. Buechler; Hugh J. Christian; William J. Koshak; Steven J. Goodman


Archive | 2012

The Geostationary Lightning Mapper (GLM) for the GOES-R Series of Geostationary Satellites

Steven J. Goodman; Richard J. Blakeslee; Douglas M. Mach; William J. Koshak

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William J. Koshak

Marshall Space Flight Center

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Douglas M. Mach

University of Alabama in Huntsville

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Dennis E. Buechler

University of Alabama in Huntsville

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Lawrence D. Carey

North Carolina State University

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Scott D. Rudlosky

National Oceanic and Atmospheric Administration

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Eugene W. McCaul

Universities Space Research Association

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