Search Results

You are looking at 21 - 25 of 25 items for

  • Author or Editor: James Marquis x
  • All content x
Clear All Modify Search
James R. Campbell, David A. Peterson, Jared W. Marquis, Gilberto J. Fochesatto, Mark A. Vaughan, Sebastian A. Stewart, Jason L. Tackett, Simone Lolli, Jasper R. Lewis, Mayra I. Oyola, and Ellsworth J. Welton
Open access
Theodore M. McHardy, James R. Campbell, David A. Peterson, Simone Lolli, Richard L. Bankert, Anne Garnier, Arunas P. Kuciauskas, Melinda L. Surratt, Jared W. Marquis, Steven D. Miller, Erica K. Dolinar, and Xiquan Dong

Abstract

We describe a quantitative evaluation of maritime transparent cirrus cloud detection, which is based on Geostationary Operational Environmental Satellite – 16 (GOES-16) and developed with collocated Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) profiling. The detection algorithm is developed using one month of collocated GOES-16 Advanced Baseline Imager (ABI) Channel 4 (1.378 μm) radiance and CALIOP 0.532 μm column-integrated cloud optical depth (COD). First, the relationships between the clear-sky 1.378 μm radiance, viewing/solar geometry, and precipitable water vapor (PWV) are characterized. Using machine learning techniques, it is shown that the total atmospheric pathlength, proxied by airmass factor (AMF), is a suitable replacement for viewing zenith and solar zenith angles alone, and that PWV is not a significant problem over ocean. Detection thresholds are computed using the Ch. 4 radiance as a function of AMF. The algorithm detects nearly 50% of sub-visual cirrus (COD < 0.03), 80% of transparent cirrus (0.03 < COD < 0.3), and 90% of opaque cirrus (COD > 0.3). Using a conservative radiance threshold results in 84% of cloudy pixels being correctly identified and 4% of clear-sky pixels being misidentified as cirrus. A semi-quantitative COD retrieval is developed for GOES ABI based on the observed relationship between CALIOP COD and 1.378 μm radiance. This study lays the groundwork for a more complex, operational GOES transparent cirrus detection algorithm. Future expansion includes an over-land algorithm, a more robust COD retrieval that is suitable for assimilation purposes, and downstream GOES products such as cirrus cloud microphysical property retrieval based on ABI infrared channels.

Restricted access
Adam C. Varble, Stephen W. Nesbitt, Paola Salio, Joseph C. Hardin, Nitin Bharadwaj, Paloma Borque, Paul J. DeMott, Zhe Feng, Thomas C. J. Hill, James N. Marquis, Alyssa Matthews, Fan Mei, Rusen Öktem, Vagner Castro, Lexie Goldberger, Alexis Hunzinger, Kevin R. Barry, Sonia M. Kreidenweis, Greg M. McFarquhar, Lynn A. McMurdie, Mikhail Pekour, Heath Powers, David M. Romps, Celeste Saulo, Beat Schmid, Jason M. Tomlinson, Susan C. van den Heever, Alla Zelenyuk, Zhixiao Zhang, and Edward J. Zipser

Abstract

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft.

A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including: numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

Full access
Stephen W. Nesbitt, Paola V. Salio, Eldo Ávila, Phillip Bitzer, Lawrence Carey, V. Chandrasekar, Wiebke Deierling, Francina Dominguez, Maria Eugenia Dillon, C. Marcelo Garcia, David Gochis, Steven Goodman, Deanna A. Hence, Karen A. Kosiba, Matthew R. Kumjian, Timothy Lang, Lorena Medina Luna, James Marquis, Robert Marshall, Lynn A. McMurdie, Ernani Lima Nascimento, Kristen L. Rasmussen, Rita Roberts, Angela K. Rowe, Juan José Ruiz, Eliah F.M.T. São Sabbas, A. Celeste Saulo, Russ S. Schumacher, Yanina Garcia Skabar, Luiz Augusto Toledo Machado, Robert J. Trapp, Adam Varble, James Wilson, Joshua Wurman, Edward J. Zipser, Ivan Arias, Hernán Bechis, and Maxwell A. Grover

Abstract

This article provides an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in Córdoba and Mendoza provinces in Argentina, and western Rio Grande do Sul State in Brazil in 2018-2019 that involved more than 200 scientists and students from the US, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates and other unusual lightning phenomena, but few tornadoes. The 5 distinct scientific foci of RELAMPAGO: convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multi-national education, public outreach, and social media data-gathering associated with the campaign, is summarized.

Full access
James M. Wilczak, Mark Stoelinga, Larry K. Berg, Justin Sharp, Caroline Draxl, Katherine McCaffrey, Robert M. Banta, Laura Bianco, Irina Djalalova, Julie K. Lundquist, Paytsar Muradyan, Aditya Choukulkar, Laura Leo, Timothy Bonin, Yelena Pichugina, Richard Eckman, Charles N. Long, Kathleen Lantz, Rochelle P. Worsnop, Jim Bickford, Nicola Bodini, Duli Chand, Andrew Clifton, Joel Cline, David R. Cook, Harindra J. S. Fernando, Katja Friedrich, Raghavendra Krishnamurthy, Melinda Marquis, Jim McCaa, Joseph B. Olson, Sebastian Otarola-Bustos, George Scott, William J. Shaw, Sonia Wharton, and Allen B. White

Abstract

The Second Wind Forecast Improvement Project (WFIP2) is a U.S. Department of Energy (DOE)- and National Oceanic and Atmospheric Administration (NOAA)-funded program, with private-sector and university partners, which aims to improve the accuracy of numerical weather prediction (NWP) model forecasts of wind speed in complex terrain for wind energy applications. A core component of WFIP2 was an 18-month field campaign that took place in the U.S. Pacific Northwest between October 2015 and March 2017. A large suite of instrumentation was deployed in a series of telescoping arrays, ranging from 500 km across to a densely instrumented 2 km × 2 km area similar in size to a high-resolution NWP model grid cell. Observations from these instruments are being used to improve our understanding of the meteorological phenomena that affect wind energy production in complex terrain and to evaluate and improve model physical parameterization schemes. We present several brief case studies using these observations to describe phenomena that are routinely difficult to forecast, including wintertime cold pools, diurnally driven gap flows, and mountain waves/wakes. Observing system and data product improvements developed during WFIP2 are also described.

Open access