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Thomas L. Koehler, John C. Derber, Brian D. Schmidt, and Lyle H. Horn

Abstract

Evaluations of operational TIROS-N and NOAA-6 temperature soundings over North America are presented for an early January 1980 period one month after completion of the First GARP Global Experiment. In addition to collocated comparisons, synoptic analyses derived only from satellite data and model forecasts initialized from these analyses are compared with those obtained from conventional data. The collocated results, similar to those presented by Phillips et al. (1979) and Schlatter (1981) from TIROS-N soundings, show maximum sounding errors new the surface and tropopause. The analysis comparisons further illustrate that thermal gradients inferred from satellite soundings are too weak, with NOAA-6 gradients slightly weaker than TIROS-N gradients. Difference fields between satellite and conventional thickness analyses propagate eastward with the synoptic patterns, strongly suggesting a correlation of satellite sounding errors to synoptic patterns. These anomalies are also retained in model forecasts started from satellite analyses. These results stress the importance of properly defining the error characteristics of satellite soundings before incorporating them into analysis-forecast systems.

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John F. Weaver, Dan Lindsey, Dan Bikos, Chris C. Schmidt, and Elaine Prins

Abstract

This paper demonstrates the proper use of geostationary satellite imagery in wildland fire detection. The roles of both the visible and the 3.9-μm channels are emphasized. Case studies from June 2002 are presented to illustrate techniques that can be utilized in both the detection and short-range forecasting processes. The examples demonstrate that, when utilized correctly, the sensitivity of the shortwave infrared channel to subpixel heat sources can often result in detections that match the timelines of human observations. Finally, a derived satellite product that increases the detection rate of wildland fires from space is described.

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Clara Orbe, Luke Van Roekel, Ángel F. Adames, Amin Dezfuli, John Fasullo, Peter J. Gleckler, Jiwoo Lee, Wei Li, Larissa Nazarenko, Gavin A. Schmidt, Kenneth R. Sperber, and Ming Zhao

Abstract

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

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Suzanne Van Cooten, Kevin E. Kelleher, Kenneth Howard, Jian Zhang, Jonathan J. Gourley, John S. Kain, Kodi Nemunaitis-Monroe, Zac Flamig, Heather Moser, Ami Arthur, Carrie Langston, Randall Kolar, Yang Hong, Kendra Dresback, Evan Tromble, Humberto Vergara, Richard A Luettich Jr., Brian Blanton, Howard Lander, Ken Galluppi, Jessica Proud Losego, Cheryl Ann Blain, Jack Thigpen, Katie Mosher, Darin Figurskey, Michael Moneypenny, Jonathan Blaes, Jeff Orrock, Rich Bandy, Carin Goodall, John G. W. Kelley, Jason Greenlaw, Micah Wengren, Dave Eslinger, Jeff Payne, Geno Olmi, John Feldt, John Schmidt, Todd Hamill, Robert Bacon, Robert Stickney, and Lundie Spence

The objective of the Coastal and Inland Flooding Observation and Warning (CI-FLOW) project is to prototype new hydrometeorologic techniques to address a critical NOAA service gap: routine total water level predictions for tidally influenced watersheds. Since February 2000, the project has focused on developing a coupled modeling system to accurately account for water at all locations in a coastal watershed by exchanging data between atmospheric, hydrologic, and hydrodynamic models. These simulations account for the quantity of water associated with waves, tides, storm surge, rivers, and rainfall, including interactions at the tidal/surge interface.

Within this project, CI-FLOW addresses the following goals: i) apply advanced weather and oceanographic monitoring and prediction techniques to the coastal environment; ii) prototype an automated hydrometeorologic data collection and prediction system; iii) facilitate interdisciplinary and multiorganizational collaborations; and iv) enhance techniques and technologies that improve actionable hydrologic/hydrodynamic information to reduce the impacts of coastal flooding. Results are presented for Hurricane Isabel (2003), Hurricane Earl (2010), and Tropical Storm Nicole (2010) for the Tar–Pamlico and Neuse River basins of North Carolina. This area was chosen, in part, because of the tremendous damage inflicted by Hurricanes Dennis and Floyd (1999). The vision is to transition CI-FLOW research findings and technologies to other U.S. coastal watersheds.

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Bruce Albrecht, Virendra Ghate, Johannes Mohrmann, Robert Wood, Paquita Zuidema, Christopher Bretherton, Christian Schwartz, Edwin Eloranta, Susanne Glienke, Shaunna Donaher, Mampi Sarkar, Jeremy McGibbon, Alison D. Nugent, Raymond A. Shaw, Jacob Fugal, Patrick Minnis, Robindra Paliknoda, Louis Lussier, Jorgen Jensen, J. Vivekanandan, Scott Ellis, Peisang Tsai, Robert Rilling, Julie Haggerty, Teresa Campos, Meghan Stell, Michael Reeves, Stuart Beaton, John Allison, Gregory Stossmeister, Samuel Hall, and Sebastian Schmidt

Abstract

The Cloud System Evolution in the Trades (CSET) study was designed to describe and explain the evolution of the boundary layer aerosol, cloud, and thermodynamic structures along trajectories within the North Pacific trade winds. The study centered on seven round trips of the National Science Foundation–National Center for Atmospheric Research (NSF–NCAR) Gulfstream V (GV) between Sacramento, California, and Kona, Hawaii, between 7 July and 9 August 2015. The CSET observing strategy was to sample aerosol, cloud, and boundary layer properties upwind from the transition zone over the North Pacific and to resample these areas two days later. Global Forecast System forecast trajectories were used to plan the outbound flight to Hawaii with updated forecast trajectories setting the return flight plan two days later. Two key elements of the CSET observing system were the newly developed High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Cloud Radar (HCR) and the high-spectral-resolution lidar (HSRL). Together they provided unprecedented characterizations of aerosol, cloud, and precipitation structures that were combined with in situ measurements of aerosol, cloud, precipitation, and turbulence properties. The cloud systems sampled included solid stratocumulus infused with smoke from Canadian wildfires, mesoscale cloud–precipitation complexes, and patches of shallow cumuli in very clean environments. Ultraclean layers observed frequently near the top of the boundary layer were often associated with shallow, optically thin, layered veil clouds. The extensive aerosol, cloud, drizzle, and boundary layer sampling made over open areas of the northeast Pacific along 2-day trajectories during CSET will be an invaluable resource for modeling studies of boundary layer cloud system evolution and its governing physical processes.

Open access
William L. Smith Jr., Christy Hansen, Anthony Bucholtz, Bruce E. Anderson, Matthew Beckley, Joseph G. Corbett, Richard I. Cullather, Keith M. Hines, Michelle Hofton, Seiji Kato, Dan Lubin, Richard H. Moore, Michal Segal Rosenhaimer, Jens Redemann, Sebastian Schmidt, Ryan Scott, Shi Song, John D. Barrick, J. Bryan Blair, David H. Bromwich, Colleen Brooks, Gao Chen, Helen Cornejo, Chelsea A. Corr, Seung-Hee Ham, A. Scott Kittelman, Scott Knappmiller, Samuel LeBlanc, Norman G. Loeb, Colin Miller, Louis Nguyen, Rabindra Palikonda, David Rabine, Elizabeth A. Reid, Jacqueline A. Richter-Menge, Peter Pilewskie, Yohei Shinozuka, Douglas Spangenberg, Paul Stackhouse, Patrick Taylor, K. Lee Thornhill, David van Gilst, and Edward Winstead

Abstract

The National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties during the critical late summer to autumn sea ice minimum and commencement of refreezing. The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014. ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center. These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began. The most critical and unique aspect of ARISE mission planning was to coordinate the flight tracks with NASA Cloud and the Earth’s Radiant Energy System (CERES) satellite sensor observations in such a way that satellite sensor angular dependence models and derived top-of-atmosphere fluxes could be validated against the aircraft data over large gridbox domains of order 100–200 km. This was accomplished over open ocean, over the marginal ice zone (MIZ), and over a region of heavy sea ice concentration, in cloudy and clear skies. ARISE data will be valuable to the community for providing better interpretation of satellite energy budget measurements in the Arctic and for process studies involving ice–cloud–atmosphere energy exchange during the sea ice transition period.

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