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Joseph B. Olson, Jaymes S. Kenyon, Irina Djalalova, Laura Bianco, David D. Turner, Yelena Pichugina, Aditya Choukulkar, Michael D. Toy, John M. Brown, Wayne M. Angevine, Elena Akish, Jian-Wen Bao, Pedro Jimenez, Branko Kosovic, Katherine A. Lundquist, Caroline Draxl, Julie K. Lundquist, Jim McCaa, Katherine McCaffrey, Kathy Lantz, Chuck Long, Jim Wilczak, Robert Banta, Melinda Marquis, Stephanie Redfern, Larry K. Berg, Will Shaw, and Joel Cline

Abstract

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.

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Taneil Uttal, Sandra Starkweather, James R. Drummond, Timo Vihma, Alexander P. Makshtas, Lisa S. Darby, John F. Burkhart, Christopher J. Cox, Lauren N. Schmeisser, Thomas Haiden, Marion Maturilli, Matthew D. Shupe, Gijs De Boer, Auromeet Saha, Andrey A. Grachev, Sara M. Crepinsek, Lori Bruhwiler, Barry Goodison, Bruce McArthur, Von P. Walden, Edward J. Dlugokencky, P. Ola G. Persson, Glen Lesins, Tuomas Laurila, John A. Ogren, Robert Stone, Charles N. Long, Sangeeta Sharma, Andreas Massling, David D. Turner, Diane M. Stanitski, Eija Asmi, Mika Aurela, Henrik Skov, Konstantinos Eleftheriadis, Aki Virkkula, Andrew Platt, Eirik J. Førland, Yoshihiro Iijima, Ingeborg E. Nielsen, Michael H. Bergin, Lauren Candlish, Nikita S. Zimov, Sergey A. Zimov, Norman T. O’Neill, Pierre F. Fogal, Rigel Kivi, Elena A. Konopleva-Akish, Johannes Verlinde, Vasily Y. Kustov, Brian Vasel, Viktor M. Ivakhov, Yrjö Viisanen, and Janet M. Intrieri

Abstract

International Arctic Systems for Observing the Atmosphere (IASOA) activities and partnerships were initiated as a part of the 2007–09 International Polar Year (IPY) and are expected to continue for many decades as a legacy program. The IASOA focus is on coordinating intensive measurements of the Arctic atmosphere collected in the United States, Canada, Russia, Norway, Finland, and Greenland to create synthesis science that leads to an understanding of why and not just how the Arctic atmosphere is evolving. The IASOA premise is that there are limitations with Arctic modeling and satellite observations that can only be addressed with boots-on-the-ground, in situ observations and that the potential of combining individual station and network measurements into an integrated observing system is tremendous. The IASOA vision is that by further integrating with other network observing programs focusing on hydrology, glaciology, oceanography, terrestrial, and biological systems it will be possible to understand the mechanisms of the entire Arctic system, perhaps well enough for humans to mitigate undesirable variations and adapt to inevitable change.

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Randall M. Dole, J. Ryan Spackman, Matthew Newman, Gilbert P. Compo, Catherine A. Smith, Leslie M. Hartten, Joseph J. Barsugli, Robert S. Webb, Martin P. Hoerling, Robert Cifelli, Klaus Wolter, Christopher D. Barnet, Maria Gehne, Ronald Gelaro, George N. Kiladis, Scott Abbott, Elena Akish, John Albers, John M. Brown, Christopher J. Cox, Lisa Darby, Gijs de Boer, Barbara DeLuisi, Juliana Dias, Jason Dunion, Jon Eischeid, Christopher Fairall, Antonia Gambacorta, Brian K. Gorton, Andrew Hoell, Janet Intrieri, Darren Jackson, Paul E. Johnston, Richard Lataitis, Kelly M. Mahoney, Katherine McCaffrey, H. Alex McColl, Michael J. Mueller, Donald Murray, Paul J. Neiman, William Otto, Ola Persson, Xiao-Wei Quan, Imtiaz Rangwala, Andrea J. Ray, David Reynolds, Emily Riley Dellaripa, Karen Rosenlof, Naoko Sakaeda, Prashant D. Sardeshmukh, Laura C. Slivinski, Lesley Smith, Amy Solomon, Dustin Swales, Stefan Tulich, Allen White, Gary Wick, Matthew G. Winterkorn, Daniel E. Wolfe, and Robert Zamora

Abstract

Forecasts by mid-2015 for a strong El Niño during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climate event and its impacts while the event was ongoing. Seizing this opportunity, the National Oceanic and Atmospheric Administration (NOAA) initiated an El Niño Rapid Response (ENRR), conducting the first field campaign to obtain intensive atmospheric observations over the tropical Pacific during El Niño.

The overarching ENRR goal was to determine the atmospheric response to El Niño and the implications for predicting extratropical storms and U.S. West Coast rainfall. The field campaign observations extended from the central tropical Pacific to the West Coast, with a primary focus on the initial tropical atmospheric response that links El Niño to its global impacts. NOAA deployed its Gulfstream-IV (G-IV) aircraft to obtain observations around organized tropical convection and poleward convective outflow near the heart of El Niño. Additional tropical Pacific observations were obtained by radiosondes launched from Kiritimati , Kiribati, and the NOAA ship Ronald H. Brown, and in the eastern North Pacific by the National Aeronautics and Space Administration (NASA) Global Hawk unmanned aerial system. These observations were all transmitted in real time for use in operational prediction models. An X-band radar installed in Santa Clara, California, helped characterize precipitation distributions. This suite supported an end-to-end capability extending from tropical Pacific processes to West Coast impacts. The ENRR observations were used during the event in operational predictions. They now provide an unprecedented dataset for further research to improve understanding and predictions of El Niño and its impacts.

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