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Marlene Kretschmer, Samantha V. Adams, Alberto Arribas, Rachel Prudden, Niall Robinson, Elena Saggioro, and Theodore G. Shepherd

Abstract

Teleconnections are sources of predictability for regional weather and climate but the relative contributions of different teleconnections to regional anomalies are usually not understood. While physical knowledge about the involved mechanisms is often available, how to quantify a particular causal pathway from data is usually unclear. Here we argue for adopting a causal inference-based framework in the statistical analysis of teleconnections to overcome this challenge. A causal approach requires explicitly including expert knowledge in the statistical analysis, which allows one to draw quantitative conclusions. We illustrate some of the key concepts of this theory with concrete examples of well-known atmospheric teleconnections. We further discuss the particular challenges and advantages these imply for climate science and argue that a systematic causal approach to statistical inference should become standard practice in the study of teleconnections.

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Dorian J. Burnette
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Aaron R. Naeger, Michael J. Newchurch, Tom Moore, Kelly Chance, Xiong Liu, Susan Alexander, Kelley Murphy, and Bo Wang
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Jonathan Zawislak, Robert F. Rogers, Sim D. Aberson, Ghassan J. Alaka Jr., George Alvey, Altug Aksoy, Lisa Bucci, Joseph Cione, Neal Dorst, Jason Dunion, Michael Fischer, John Gamache, Sundararaman Gopalakrishnan, Andrew Hazelton, Heather M. Holbach, John Kaplan, Hua Leighton, Frank Marks, Shirley T. Murillo, Paul Reasor, Kelly Ryan, Kathryn Sellwood, Jason A. Sippel, and Jun A. Zhang

Abstract

Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic andMeteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and G-IV Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions towards improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the “next generation” of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.

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Yuan Yang, Ming Pan, Peirong Lin, Hylke E. Beck, Zhenzhong Zeng, Dai Yamazaki, Cédric H. David, Hui Lu, Kun Yang, Yang Hong, and Eric F. Wood

Abstract

Better understanding and quantification of river floods for very local and flashy events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-year period of 1980-2019. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-year return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) sub-daily modeling. This data record, referred as Global Reach-level Flood Reanalysis (GRFR), is publicly available at https://www.reachhydro.org/home/records/grfr.

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James O. Pinto, Anders A. Jensen, Matthias Steiner, Debbie O’Sullivan, Stewart Taylor, Jack Elston, C. Bruce Baker, David Hotz, Curtis Marshall, Jamey Jacob, Konrad Bärfuss, Bruno Piguet, Greg Roberts, Nadja Omanovic, Martin Fengler, and Adam Houston

Capsule

Small weather-sensing Uncrewed Aircraft Systems are becoming reliable and accurate enough to be considered as a cost-effective solution for filling observational gaps that could enhance National Meteorological and Hydrological Services around the world.

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Neil A. Jacobs

Abstract

Despite having the largest associated research community and a rapidly growing private sector, the lack of a well-coordinated national research and development effort for U.S. numerical weather prediction continues to impede our ability to utilize more of the scientific and technical capacity of the Nation more efficiently. Over the last few years, considerable progress has been made towards developing a community-friendly Unified Forecast System (UFS) by embracing an open innovation approach that is mutually beneficial to the public, private, and academic sectors. Once fully implemented, the UFS has the potential to catalyze a significant increase in the efficacy of our Nation’s weather, water, and climate science and prediction.

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Maude Dinan, Emile Elias, Nicholas P. Webb, Greg Zwicke, Timothy S. Dye, Skye Aney, Michael Brady, Joel R. Brown, Robert R. Dobos, Dave DuBois, Brandon L. Edwards, Sierra Heimel, Nicholas Luke, Caitlin M. Rottler, and Caitriana Steele
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A. Marshak, A. Ackerman, A. Da Silva, T. Eck, B. Holben, R. Kahn, R. Kleidman, K. Knobelspiesse, R. Levy, A. Lyapustin, L. Oreopoulos, L. Remer, O. Torres, T. Varnai, G. Wen, and J. Yorks

Abstract

Aerosol properties are fundamentally different near clouds than distant from clouds. This paper reviews the current state of knowledge of aerosol properties in the near low cloud environment and quantitatively compares them with aerosols far from clouds, limited in scope to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote-sensing retrievals. This study is timely in view of science definition studies for NASA’s Aerosols-Clouds, Convection and Precipitation (ACCP) mission, which will also seek to directly links aerosol properties to nearby clouds.

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Susan C. van den Heever, Leah D. Grant, Sean W. Freeman, Peter J. Marinescu, Julie Barnum, Jennie Bukowski, Eleanor Casas, Aryeh J. Drager, Brody Fuchs, Gregory R. Herman, Stacey M. Hitchcock, Patrick C. Kennedy, Erik R. Nielsen, J. Minnie Park, Kristen Rasmussen, Muhammad Naufal Razin, Ryan Riesenberg, Emily Riley Dellaripa, Christopher J. Slocum, Benjamin A. Toms, and Adrian van den Heever

Abstract

The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C3LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.

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