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Steven C. Hardiman, Ian A. Boutle, Andrew C. Bushell, Neal Butchart, Mike J. P. Cullen, Paul R. Field, Kalli Furtado, James C. Manners, Sean F. Milton, Cyril Morcrette, Fiona M. O’Connor, Ben J. Shipway, Chris Smith, David N. Walters, Martin R. Willett, Keith D. Williams, Nigel Wood, N. Luke Abraham, James Keeble, Amanda C. Maycock, John Thuburn, and Matthew T. Woodhouse

Abstract

A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.

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Sid-Ahmed Boukabara, Vladimir Krasnopolsky, Stephen G. Penny, Jebb Q. Stewart, Amy McGovern, David Hall, John E. Ten Hoeve, Jason Hickey, Hung-Lung Allen Huang, John K. Williams, Kayo Ide, Philippe Tissot, Sue Ellen Haupt, Kenneth S. Casey, Nikunj Oza, Alan J. Geer, Eric S. Maddy, and Ross N. Hoffman

Abstract

Promising new opportunities to apply artificial intelligence (AI) to the Earth and environmental sciences are identified, informed by an overview of current efforts in the community. Community input was collected at the first National Oceanic and Atmospheric Administration (NOAA) workshop on “Leveraging AI in the Exploitation of Satellite Earth Observations and Numerical Weather Prediction” held in April 2019. This workshop brought together over 400 scientists, program managers, and leaders from the public, academic, and private sectors in order to enable experts involved in the development and adaptation of AI tools and applications to meet and exchange experiences with NOAA experts. Paths are described to actualize the potential of AI to better exploit the massive volumes of environmental data from satellite and in situ sources that are critical for numerical weather prediction (NWP) and other Earth and environmental science applications. The main lessons communicated from community input via active workshop discussions and polling are reported. Finally, recommendations are presented for both scientists and decision-makers to address some of the challenges facing the adoption of AI across all Earth science.

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David C. Fritts, Ronald B. Smith, Michael J. Taylor, James D. Doyle, Stephen D. Eckermann, Andreas Dörnbrack, Markus Rapp, Bifford P. Williams, P.-Dominique Pautet, Katrina Bossert, Neal R. Criddle, Carolyn A. Reynolds, P. Alex Reinecke, Michael Uddstrom, Michael J. Revell, Richard Turner, Bernd Kaifler, Johannes S. Wagner, Tyler Mixa, Christopher G. Kruse, Alison D. Nugent, Campbell D. Watson, Sonja Gisinger, Steven M. Smith, Ruth S. Lieberman, Brian Laughman, James J. Moore, William O. Brown, Julie A. Haggerty, Alison Rockwell, Gregory J. Stossmeister, Steven F. Williams, Gonzalo Hernandez, Damian J. Murphy, Andrew R. Klekociuk, Iain M. Reid, and Jun Ma

Abstract

The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.

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Kenneth J. Davis, Edward V. Browell, Sha Feng, Thomas Lauvaux, Michael D. Obland, Sandip Pal, Bianca C. Baier, David F. Baker, Ian T. Baker, Zachary R. Barkley, Kevin W. Bowman, Yu Yan Cui, A. Scott Denning, Joshua P. DiGangi, Jeremy T. Dobler, Alan Fried, Tobias Gerken, Klaus Keller, Bing Lin, Amin R. Nehrir, Caroline P. Normile, Christopher W. O’Dell, Lesley E. Ott, Anke Roiger, Andrew E. Schuh, Colm Sweeney, Yaxing Wei, Brad Weir, Ming Xue, and Christopher A. Williams

Abstract

The Atmospheric Carbon and Transport (ACT) – America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five, six-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America data set and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise sub-continental GHG flux estimates.

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M. Susan Lozier, Sheldon Bacon, Amy S. Bower, Stuart A. Cunningham, M. Femke de Jong, Laura de Steur, Brad deYoung, Jürgen Fischer, Stefan F. Gary, Blair J. W. Greenan, Patrick Heimbach, Naomi P. Holliday, Loïc Houpert, Mark E. Inall, William E. Johns, Helen L. Johnson, Johannes Karstensen, Feili Li, Xiaopei Lin, Neill Mackay, David P. Marshall, Herlé Mercier, Paul G. Myers, Robert S. Pickart, Helen R. Pillar, Fiammetta Straneo, Virginie Thierry, Robert A. Weller, Richard G. Williams, Chris Wilson, Jiayan Yang, Jian Zhao, and Jan D. Zika

Abstract

For decades oceanographers have understood the Atlantic meridional overturning circulation (AMOC) to be primarily driven by changes in the production of deep-water formation in the subpolar and subarctic North Atlantic. Indeed, current Intergovernmental Panel on Climate Change (IPCC) projections of an AMOC slowdown in the twenty-first century based on climate models are attributed to the inhibition of deep convection in the North Atlantic. However, observational evidence for this linkage has been elusive: there has been no clear demonstration of AMOC variability in response to changes in deep-water formation. The motivation for understanding this linkage is compelling, since the overturning circulation has been shown to sequester heat and anthropogenic carbon in the deep ocean. Furthermore, AMOC variability is expected to impact this sequestration as well as have consequences for regional and global climates through its effect on the poleward transport of warm water. Motivated by the need for a mechanistic understanding of the AMOC, an international community has assembled an observing system, Overturning in the Subpolar North Atlantic Program (OSNAP), to provide a continuous record of the transbasin fluxes of heat, mass, and freshwater, and to link that record to convective activity and water mass transformation at high latitudes. OSNAP, in conjunction with the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array (RAPID–MOCHA) at 26°N and other observational elements, will provide a comprehensive measure of the three-dimensional AMOC and an understanding of what drives its variability. The OSNAP observing system was fully deployed in the summer of 2014, and the first OSNAP data products are expected in the fall of 2017.

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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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