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Mark Weadon, Pamela Heinselman, Douglas Forsyth, James Kimpel, William E. Benner, and Garth S. Torok

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Mark E. Weber, John Y. N. Cho, Jeffrey S. Herd, James M. Flavin, William E. Benner, and Garth S. Torok

The U.S. Government operates seven distinct radar networks, providing weather and aircraft surveillance for public weather services, air traffic control, and homeland defense. In this paper, we describe a next-generation multimission phased-array radar (MPAR) concept that could provide enhanced weather and aircraft surveillance services with potentially lower life cycle costs than multiple single-function radar networks. We describe current U.S. national weather and aircraft surveillance radar networks and show that by reducing overlapping airspace coverage, MPAR could reduce the total number of radars required by approximately one-third. A key finding is that weather surveillance requirements dictate the core parameters of a multimission radar—airspace coverage, aperture size, radiated power, and angular resolution. Aircraft surveillance capability can be added to a phased array weather radar at low incremental cost because the agile, electronically steered beam would allow the radar to achieve the much more rapid scan update rates needed for aircraft volume search missions, and additionally to support track modes for individual aircraft targets. We describe an MPAR system design that includes multiple transmit-receive channels and a highly digitized active phased array to generate independently steered beam clusters for weather, aircraft volume search, and aircraft track modes. For each of these modes, we discuss surveillance capability improvements that would be realized relative to today's radars. The Federal Aviation Administration (FAA) has initiated the development of an MPAR “preprototype” that will demonstrate critical subsystem technologies and multimission operational capabilities. Initial subsystem designs have provided a solid basis for estimating MPAR costs for comparison with existing, mechanically scanned operational surveillance radars.

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David C. Fritts, Carmen Nappo, Dennis M. Riggin, Ben B. Balsley, William E. Eichinger, and Rob K. Newsom

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Data obtained with multiple instruments at the main site of the 1999 Cooperative Atmosphere–Surface Exchange Study (CASES-99) are employed to examine the character and variability of wave motions occurring in the stable nocturnal boundary layer during the night of 14 October 1999. The predominant motions are surprisingly similar in character throughout the night, exhibiting largely westward propagation, horizontal wavelengths of ∼1 to 10 km, phase speeds slightly greater than the mean wind in the direction of propagation, and highly coherent vertical motions with no apparent phase progression with altitude. Additionally, vertical and horizontal velocities are in approximate quadrature and the largest amplitudes occur at elevated altitudes of maximum stratification. These motions are interpreted as ducted gravity waves that propagate along maxima of stratification and mean wind and that are evanescent above, and occasionally below, the altitudes at which they are ducted. Modal structures for ducted waves are computed for mean wind and stratification profiles for three specific cases and are seen to provide a plausible explanation of the observed motions.

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William L. Smith, Wayne F. Feltz, Robert O. Knuteson, Henry E. Revercomb, Harold M. Woolf, and H. Ben Howell

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The surface-based Atmospheric Emitted Radiance Interferometer (AERI) is an important measurement component of the Department of Energy Atmospheric Radiation Measurement Program. The method used to retrieve temperature and moisture profiles of the plantetary boundary layer from the AERI’s downwelling spectral radiance observations is described.

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Wayne F. Feltz, William L. Smith, Robert O. Knuteson, Henry E. Revercomb, Harold M. Woolf, and H. Ben Howell

Abstract

The Atmospheric Emitted Radiance Interferometer (AERI) is a well-calibrated ground-based instrument that measures high-resolution atmospheric emitted radiances from the atmosphere. The spectral resolution of the instrument is better than one wavenumber between 3 and 18 μm within the infrared spectrum. The AERI instrument detects vertical and temporal changes of temperature and water vapor in the planetary boundary layer. Excellent agreement between radiosonde and AERI retrievals for a 6-month sample of coincident profiles is presented in this paper. In addition, a statistical seasonal analysis of retrieval and radiosonde differences is discussed. High temporal and moderate vertical resolution in the lowest 3 km of the atmosphere allows meteorologically important mesoscale features to be detected. AERI participation in the Department of Energy Atmospheric Radiation Measurement program at the Southern Great Plains Cloud and Radiation Testbed (SGP CART) has allowed development of a robust operational atmospheric temperature and water vapor retrieval algorithm in a dynamic meteorological environment near Lamont, Oklahoma. Operating in a continuous mode, AERI temperature and water vapor retrievals obtained through inversion of the infrared radiative transfer equation provide profiles of atmospheric state every 10 min to 3 km in clear sky or below cloud base. Boundary layer evolution, cold or warm frontal passages, drylines, and thunderstorm outflow boundaries are all recorded, offering important meteorological information. With important vertical thermodynamic information between radiosonde locations and launch times, AERI retrievals provide data for planetary boundary layer research, mesoscale model initialization, verification, and nowcasting. This paper discusses retrieval performance at the SGP CART site, as well as interesting meteorological case studies captured by AERI profiles. The AERI system represents an important new capability for operational weather- and airport-monitoring applications.

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Harry L. Bryden, William E. Johns, Brian A. King, Gerard McCarthy, Elaine L. McDonagh, Ben I. Moat, and David A. Smeed

Abstract

Northward ocean heat transport at 26°N in the Atlantic Ocean has been measured since 2004. The ocean heat transport is large—approximately 1.25 PW, and on interannual time scales it exhibits surprisingly large temporal variability. There has been a long-term reduction in ocean heat transport of 0.17 PW from 1.32 PW before 2009 to 1.15 PW after 2009 (2009–16) on an annual average basis associated with a 2.5-Sv (1 Sv ≡ 106 m3 s−1) drop in the Atlantic meridional overturning circulation (AMOC). The reduction in the AMOC has cooled and freshened the upper ocean north of 26°N over an area following the offshore edge of the Gulf Stream/North Atlantic Current from the Bahamas to Iceland. Cooling peaks south of Iceland where surface temperatures are as much as 2°C cooler in 2016 than they were in 2008. Heat uptake by the atmosphere appears to have been affected particularly along the path of the North Atlantic Current. For the reduction in ocean heat transport, changes in ocean heat content account for about one-quarter of the long-term reduction in ocean heat transport while reduced heat uptake by the atmosphere appears to account for the remainder of the change in ocean heat transport.

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Ben P. Kirtman, Dughong Min, Johnna M. Infanti, James L. Kinter III, Daniel A. Paolino, Qin Zhang, Huug van den Dool, Suranjana Saha, Malaquias Pena Mendez, Emily Becker, Peitao Peng, Patrick Tripp, Jin Huang, David G. DeWitt, Michael K. Tippett, Anthony G. Barnston, Shuhua Li, Anthony Rosati, Siegfried D. Schubert, Michele Rienecker, Max Suarez, Zhao E. Li, Jelena Marshak, Young-Kwon Lim, Joseph Tribbia, Kathleen Pegion, William J. Merryfield, Bertrand Denis, and Eric F. Wood

The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users.

The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model.

Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2011), a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data are readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (www.cpc.ncep.noaa.gov/products/NMME/). Moreover, the NMME forecast is already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, and presents an overview of the multimodel forecast quality and the complementary skill associated with individual models.

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Molly Baringer, Mariana B. Bif, Tim Boyer, Seth M. Bushinsky, Brendan R. Carter, Ivona Cetinić, Don P. Chambers, Lijing Cheng, Sanai Chiba, Minhan Dai, Catia M. Domingues, Shenfu Dong, Andrea J. Fassbender, Richard A. Feely, Eleanor Frajka-Williams, Bryan A. Franz, John Gilson, Gustavo Goni, Benjamin D. Hamlington, Zeng-Zhen Hu, Boyin Huang, Masayoshi Ishii, Svetlana Jevrejeva, William E. Johns, Gregory C. Johnson, Kenneth S. Johnson, John Kennedy, Marion Kersalé, Rachel E. Killick, Peter Landschützer, Matthias Lankhorst, Tong Lee, Eric Leuliette, Feili Li, Eric Lindstrom, Ricardo Locarnini, Susan Lozier, John M. Lyman, John J. Marra, Christopher S. Meinen, Mark A. Merrifield, Gary T. Mitchum, Ben Moat, Didier Monselesan, R. Steven Nerem, Renellys C. Perez, Sarah G. Purkey, Darren Rayner, James Reagan, Nicholas Rome, Alejandra Sanchez-Franks, Claudia Schmid, Joel P. Scott, Uwe Send, David A. Siegel, David A. Smeed, Sabrina Speich, Paul W. Stackhouse Jr., William Sweet, Yuichiro Takeshita, Philip R. Thompson, Joaquin A. Triñanes, Martin Visbeck, Denis L. Volkov, Rik Wanninkhof, Robert A. Weller, Toby K. Westberry, Matthew J. Widlansky, Susan E. Wijffels, Anne C. Wilber, Lisan Yu, Weidong Yu, and Huai-Min Zhang
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William J. Merryfield, Johanna Baehr, Lauriane Batté, Emily J. Becker, Amy H. Butler, Caio A. S. Coelho, Gokhan Danabasoglu, Paul A. Dirmeyer, Francisco J. Doblas-Reyes, Daniela I. V. Domeisen, Laura Ferranti, Tatiana Ilynia, Arun Kumar, Wolfgang A. Müller, Michel Rixen, Andrew W. Robertson, Doug M. Smith, Yuhei Takaya, Matthias Tuma, Frederic Vitart, Christopher J. White, Mariano S. Alvarez, Constantin Ardilouze, Hannah Attard, Cory Baggett, Magdalena A. Balmaseda, Asmerom F. Beraki, Partha S. Bhattacharjee, Roberto Bilbao, Felipe M. de Andrade, Michael J. DeFlorio, Leandro B. Díaz, Muhammad Azhar Ehsan, Georgios Fragkoulidis, Sam Grainger, Benjamin W. Green, Momme C. Hell, Johnna M. Infanti, Katharina Isensee, Takahito Kataoka, Ben P. Kirtman, Nicholas P. Klingaman, June-Yi Lee, Kirsten Mayer, Roseanna McKay, Jennifer V. Mecking, Douglas E. Miller, Nele Neddermann, Ching Ho Justin Ng, Albert Ossó, Klaus Pankatz, Simon Peatman, Kathy Pegion, Judith Perlwitz, G. Cristina Recalde-Coronel, Annika Reintges, Christoph Renkl, Balakrishnan Solaraju-Murali, Aaron Spring, Cristiana Stan, Y. Qiang Sun, Carly R. Tozer, Nicolas Vigaud, Steven Woolnough, and Stephen Yeager

Abstract

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

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