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Robert Wood, Matthew Wyant, Christopher S. Bretherton, Jasmine Rémillard, Pavlos Kollias, Jennifer Fletcher, Jayson Stemmler, Simone de Szoeke, Sandra Yuter, Matthew Miller, David Mechem, George Tselioudis, J. Christine Chiu, Julian A. L. Mann, Ewan J. O’Connor, Robin J. Hogan, Xiquan Dong, Mark Miller, Virendra Ghate, Anne Jefferson, Qilong Min, Patrick Minnis, Rabindra Palikonda, Bruce Albrecht, Ed Luke, Cecile Hannay, and Yanluan Lin

Abstract

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer.

Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging.

The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

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James D. Doyle, Jonathan R. Moskaitis, Joel W. Feldmeier, Ronald J. Ferek, Mark Beaubien, Michael M. Bell, Daniel L. Cecil, Robert L. Creasey, Patrick Duran, Russell L. Elsberry, William A. Komaromi, John Molinari, David R. Ryglicki, Daniel P. Stern, Christopher S. Velden, Xuguang Wang, Todd Allen, Bradford S. Barrett, Peter G. Black, Jason P. Dunion, Kerry A. Emanuel, Patrick A. Harr, Lee Harrison, Eric A. Hendricks, Derrick Herndon, William Q. Jeffries, Sharanya J. Majumdar, James A. Moore, Zhaoxia Pu, Robert F. Rogers, Elizabeth R. Sanabia, Gregory J. Tripoli, and Da-Lin Zhang

Abstract

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes.

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Gabriele C. Hegerl, Emily Black, Richard P. Allan, William J. Ingram, Debbie Polson, Kevin E. Trenberth, Robin S. Chadwick, Phillip A. Arkin, Beena Balan Sarojini, Andreas Becker, Aiguo Dai, Paul J. Durack, David Easterling, Hayley J. Fowler, Elizabeth J. Kendon, George J. Huffman, Chunlei Liu, Robert Marsh, Mark New, Timothy J. Osborn, Nikolaos Skliris, Peter A. Stott, Pier-Luigi Vidale, Susan E. Wijffels, Laura J. Wilcox, Kate M. Willett, and Xuebin Zhang

Abstract

Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols and because of the large climate variability presently limits confidence in attribution of observed changes.

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Eric J. Jensen, Leonhard Pfister, David E. Jordan, Thaopaul V. Bui, Rei Ueyama, Hanwant B. Singh, Troy D. Thornberry, Andrew W. Rollins, Ru-Shan Gao, David W. Fahey, Karen H. Rosenlof, James W. Elkins, Glenn S. Diskin, Joshua P. DiGangi, R. Paul Lawson, Sarah Woods, Elliot L. Atlas, Maria A. Navarro Rodriguez, Steven C. Wofsy, Jasna Pittman, Charles G. Bardeen, Owen B. Toon, Bruce C. Kindel, Paul A. Newman, Matthew J. McGill, Dennis L. Hlavka, Leslie R. Lait, Mark R. Schoeberl, John W. Bergman, Henry B. Selkirk, M. Joan Alexander, Ji-Eun Kim, Boon H. Lim, Jochen Stutz, and Klaus Pfeilsticker

Abstract

The February–March 2014 deployment of the National Aeronautics and Space Administration (NASA) Airborne Tropical Tropopause Experiment (ATTREX) provided unique in situ measurements in the western Pacific tropical tropopause layer (TTL). Six flights were conducted from Guam with the long-range, high-altitude, unmanned Global Hawk aircraft. The ATTREX Global Hawk payload provided measurements of water vapor, meteorological conditions, cloud properties, tracer and chemical radical concentrations, and radiative fluxes. The campaign was partially coincident with the Convective Transport of Active Species in the Tropics (CONTRAST) and the Coordinated Airborne Studies in the Tropics (CAST) airborne campaigns based in Guam using lower-altitude aircraft (see companion articles in this issue). The ATTREX dataset is being used for investigations of TTL cloud, transport, dynamical, and chemical processes, as well as for evaluation and improvement of global-model representations of TTL processes. The ATTREX data are publicly available online (at https://espoarchive.nasa.gov/).

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Keith A. Browning, Alan M. Blyth, Peter A. Clark, Ulrich Corsmeier, Cyril J. Morcrette, Judith L. Agnew, Sue P. Ballard, Dave Bamber, Christian Barthlott, Lindsay J. Bennett, Karl M. Beswick, Mark Bitter, Karen E. Bozier, Barbara J. Brooks, Chris G. Collier, Fay Davies, Bernhard Deny, Mark A. Dixon, Thomas Feuerle, Richard M. Forbes, Catherine Gaffard, Malcolm D. Gray, Rolf Hankers, Tim J. Hewison, Norbert Kalthoff, Samiro Khodayar, Martin Kohler, Christoph Kottmeier, Stephan Kraut, Michael Kunz, Darcy N. Ladd, Humphrey W. Lean, Jürgen Lenfant, Zhihong Li, John Marsham, James McGregor, Stephan D. Mobbs, John Nicol, Emily Norton, Douglas J. Parker, Felicity Perry, Markus Ramatschi, Hugo M. A. Ricketts, Nigel M. Roberts, Andrew Russell, Helmut Schulz, Elizabeth C. Slack, Geraint Vaughan, Joe Waight, David P. Wareing, Robert J. Watson, Ann R. Webb, and Andreas Wieser

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model.

A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP.

This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

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Russell S. Vose, Scott Applequist, Mark A. Bourassa, Sara C. Pryor, Rebecca J. Barthelmie, Brian Blanton, Peter D. Bromirski, Harold E. Brooks, Arthur T. DeGaetano, Randall M. Dole, David R. Easterling, Robert E. Jensen, Thomas R. Karl, Richard W. Katz, Katherine Klink, Michael C. Kruk, Kenneth E. Kunkel, Michael C. MacCracken, Thomas C. Peterson, Karsten Shein, Bridget R. Thomas, John E. Walsh, Xiaolan L. Wang, Michael F. Wehner, Donald J. Wuebbles, and Robert S. Young

This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.

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Brian J. Butterworth, Ankur R. Desai, Stefan Metzger, Philip A. Townsend, Mark D. Schwartz, Grant W. Petty, Matthias Mauder, Hannes Vogelmann, Christian G. Andresen, Travis J. Augustine, Timothy H. Bertram, William O. J. Brown, Michael Buban, Patricia Cleary, David J. Durden, Christopher R. Florian, Trevor J. Iglinski, Eric L. Kruger, Kathleen Lantz, Temple R. Lee, Tilden P. Meyers, James K. Mineau, Erik R. Olson, Steven P. Oncley, Sreenath Paleri, Rosalyn A. Pertzborn, Claire Pettersen, David M. Plummer, Laura D. Riihimaki, Eliceo Ruiz Guzman, Joseph Sedlar, Elizabeth N. Smith, Johannes Speidel, Paul C. Stoy, Matthias Sühring, Jonathan E. Thom, David D. Turner, Michael P. Vermeuel, Timothy J. Wagner, Zhien Wang, Luise Wanner, Loren D. White, James M. Wilczak, Daniel B. Wright, and Ting Zheng

Abstract

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

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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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Rolf H. Reichle, Gabrielle J. M. De Lannoy, Qing Liu, Joseph V. Ardizzone, Andreas Colliander, Austin Conaty, Wade Crow, Thomas J. Jackson, Lucas A. Jones, John S. Kimball, Randal D. Koster, Sarith P. Mahanama, Edmond B. Smith, Aaron Berg, Simone Bircher, David Bosch, Todd G. Caldwell, Michael Cosh, Ángel González-Zamora, Chandra D. Holifield Collins, Karsten H. Jensen, Stan Livingston, Ernesto Lopez-Baeza, José Martínez-Fernández, Heather McNairn, Mahta Moghaddam, Anna Pacheco, Thierry Pellarin, John Prueger, Tracy Rowlandson, Mark Seyfried, Patrick Starks, Zhongbo Su, Marc Thibeault, Rogier van der Velde, Jeffrey Walker, Xiaoling Wu, and Yijian Zeng

Abstract

The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 m3 m−3 or better. The ubRMSE for L4_SM surface (root zone) soil moisture is 0.038 m3 m−3 (0.030 m3 m−3) at the 9-km scale and 0.035 m3 m−3 (0.026 m3 m−3) at the 36-km scale. The L4_SM estimates improve (significantly at the 5% level for surface soil moisture) over model-only estimates, which do not benefit from the assimilation of SMAP brightness temperature observations and have a 9-km surface (root zone) ubRMSE of 0.042 m3 m−3 (0.032 m3 m−3). Time series correlations exhibit similar relative performance. The sparse network results corroborate these findings over a greater variety of climate and land cover conditions.

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