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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

CAPSULE

Midlatitude weather systems contain large gradients in greenhouse gases (GHG), reflecting regional fluxes and continental inflow. ACT-America carbon weather observations provide a synoptic-scale benchmark for GHG flux and transport models.

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Adam A. Scaife, Elizabeth Good, Ying Sun, Zhongwei Yan, Nick Dunstone, Hong-Li Ren, Chaofan Li, Riyu Lu, Peili Wu, Zongjian Ke, Zhuguo Ma, Kalli Furtado, Tongwen Wu, Tianjun Zhou, Tyrone Dunbar, Chris Hewitt, Nicola Golding, Peiqun Zhang, Rob Allan, Kirstine Dale, Fraser C. Lott, Peter A. Stott, Sean Milton, Lianchun Song, and Stephen Belcher

Abstract

We present results from the first 6 years of this major UK government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between UK and Chinese climate scientists and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modelling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over three hundred peer reviewed studies generated jointly by UK and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skilful predictions of important aspects of Chinese climate such as East Asian Summer Monsoon rainfall. In addition, the development of improved modelling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real time climate services. Participation of dozens of institutes through sub-projects in this programme, which is governed by the Met Office Hadley Centre, the China Meteorological Administration and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services.

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Eric Rappin, Rezaul Mahmood, Udaysankar Nair, Roger A. Pielke Sr., William Brown, Steve Oncley, Joshua Wurman, Karen Kosiba, Aaron Kaulfus, Chris Phillips, Emilee Lachenmeier, Joseph Santanello Jr., Edward Kim, and Patricia Lawston-Parker

Abstract

Extensive expansion in irrigated agriculture has taken place over the last half century. Due to increased irrigation and resultant land use land cover change, the central United States has seen a decrease in temperature and changes in precipitation during the second half of 20th century. To investigate the impacts of widespread commencement of irrigation at the beginning of the growing season and continued irrigation throughout the summer on local and regional weather, the Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 in southeastern Nebraska. GRAINEX consisted of two, 15-day intensive observation periods. Observational platforms from multiple agencies and universities were deployed to investigate the role of irrigation in surface moisture content, heat fluxes, diurnal boundary layer evolution, and local precipitation.

This article provides an overview of the data collected and an analysis of the role of irrigation in land-atmosphere interactions on time scales from the seasonal to the diurnal. The analysis shows that a clear irrigation signal was apparent during the peak growing season in mid-July. This paper shows the strong impact of irrigation on surface fluxes, near-surface temperature and humidity, as well as boundary layer growth and decay.

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Christa D. Peters-Lidard, David M. Mocko, Lu Su, Dennis P. Lettenmaier, Pierre Gentine, and Michael Barlage

Abstract

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

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Dino Zardi, Marco Falocchi, Lorenzo Giovannini, Werner Tirler, Elena Tomasi, Gianluca Antonacci, Enrico Ferrero, Stefano Alessandrini, Pedro A. Jimenez, Branko Kosovic, and Luca Delle Monache

Abstract

The paper describes the observational and modeling efforts performed under the Bolzano Tracer Experiment (BTEX). BTEX focused on the basin surrounding the city of Bolzano, at the junction of three tributary valleys on the southern side of the Alps, to characterize the ground-level impact of pollutants emitted by a waste incinerator close to the city, and atmospheric factors controlling dispersion processes in the whole basin, under different winter weather situations. As part of the experiment, two controlled releases of a passive gas tracer (sulfur hexafluoride, SF6) were performed through the stack of the incinerator on 14 February 2017 at two different times, starting respectively at 0700 and 1245 LST, representative of distinct phases of the daily cycle. Samples of ambient air were collected at target sites, and later analyzed using a mass spectrometer, allowing a detectability limit down to 30 ppt. Meanwhile, meteorological conditions were continuously monitored by means of a high-resolution, nonconventional network of ground-based instruments, including 15 weather stations, one temperature profiler, one sodar, and one Doppler wind lidar. Data from the above measurements represent one of the rare examples of integrated datasets available to the community for the characterization of dispersion processes in a typical mountainous environment. In particular, they offered a reference benchmark for testing and calibrating a series of combined numerical modeling suites for weather prediction and pollutant dispersion simulation in such a complex terrain, as shown in the paper.

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Jiaojiao Gou, Chiyuan Miao, Luis Samaniego, Mu Xiao, Jingwen Wu, and Xiaoying Guo

Abstract

Reliable, spatiotemporally continuous runoff records are necessary for identifying climate change impacts and planning effective water management strategies. Existing Chinese runoff data to date have been produced from sparse, poor-quality gauge measurements at different time scales. We have developed a new, quality-controlled gridded runoff dataset, the China Natural Runoff Dataset version 1.0 (CNRD v1.0), which provides daily, monthly, and annual 0.25° runoff estimates for the period 1961–2018 over China. CNRD v1.0 was generated using the Variable Infiltration Capacity (VIC) model. A comprehensive parameter uncertainty analysis framework incorporating parameter sensitivity analysis, optimization, and regionalization with 200 natural or near-natural gauge catchments was used to train the VIC model. Overall, the results show well-calibrated parameters for most gauged catchments except arid and semiarid areas, and the skill scores present high values for all catchments. For the pseudo-/test-ungauged catchments, the model parameters estimated by the multiscale parameter regionalization technique offer the best regionalization solution. CNRD v1.0 is the first free public dataset of gridded natural runoff estimated using a comprehensive model parameter uncertainty analysis framework for China. These results indicate that CNRD v1.0 has high potential for application to long-term hydrological and climate studies in China and to improve international runoff databases for global-scale studies.

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Robbie Iacovazzi, Quanhua “Mark” Liu, and Changyong Cao
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Qing Yang, Xinyi Shen, Emmanouil N. Anagnostou, Chongxun Mo, Jack R. Eggleston, and Albert J. Kettner

Abstract

Most existing inundation inventories are based on surveys, news, or passive remote sensing imagery. Affected by spatiotemporal resolution or weather conditions, these inventories are limited in spatial details or coverage. Satellite synthetic aperture radar (SAR) data have recently enabled flood mapping at unprecedented spatiotemporal resolution. However, the bottleneck in producing SAR-based flood maps is the requirement of expert manual processing to maintain acceptable accuracy by most SAR-driven mapping techniques. To fill the vacancy, we generate a high-resolution (10 m) flood inundation dataset over the contiguous United States (CONUS) from nearly the entire Sentinel-1 SAR archive (from January 2016 to the present), using a recently developed automated Radar Produced Inundation Diary (RAPID) system. RAPID uses U.S. Geological Survey (USGS) water watch system and accumulated precipitation to identify SAR images that potentially overlap a flood event. The dataset include inundation events with the temporal scale from several days to months. Concluded from all 559 overlapping images in the period from 2016 to the first half of 2019, the comparison of the proposed dataset against the USGS Dynamic Surface Water Extent (DSWE) product yields an overall, user, producer agreements, and critical success index of 99.06%, 87.63%, 91.76%, and 81.23%, respectively, demonstrating the high accuracy of the proposed dataset and the robustness of the automated system. We anticipate this archive to facilitate many applications, including large-scale flood loss and risk assessment, and inundation model calibration and validation.

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Nirnimesh Kumar, James A. Lerczak, Tongtong Xu, Amy F. Waterhouse, Jim Thomson, Eric J. Terrill, Christy Swann, Sutara H. Suanda, Matthew S. Spydell, Pieter B. Smit, Alexandra Simpson, Roland Romeiser, Stephen D. Pierce, Tony de Paolo, André Palóczy, Annika O’Dea, Lisa Nyman, James N. Moum, Melissa Moulton, Andrew M. Moore, Arthur J. Miller, Ryan S. Mieras, Sophia T. Merrifield, Kendall Melville, Jacqueline M. McSweeney, Jamie MacMahan, Jennifer A. MacKinnon, Björn Lund, Emanuele Di Lorenzo, Luc Lenain, Michael Kovatch, Tim T. Janssen, Sean R. Haney, Merrick C. Haller, Kevin Haas, Derek J. Grimes, Hans C. Graber, Matt K. Gough, David A. Fertitta, Falk Feddersen, Christopher A. Edwards, William Crawford, John Colosi, C. Chris Chickadel, Sean Celona, Joseph Calantoni, Edward F. Braithwaite III, Johannes Becherer, John A. Barth, and Seongho Ahn

Abstract

The inner shelf, the transition zone between the surfzone and the midshelf, is a dynamically complex region with the evolution of circulation and stratification driven by multiple physical processes. Cross-shelf exchange through the inner shelf has important implications for coastal water quality, ecological connectivity, and lateral movement of sediment and heat. The Inner-Shelf Dynamics Experiment (ISDE) was an intensive, coordinated, multi-institution field experiment from September–October 2017, conducted from the midshelf, through the inner shelf, and into the surfzone near Point Sal, California. Satellite, airborne, shore- and ship-based remote sensing, in-water moorings and ship-based sampling, and numerical ocean circulation models forced by winds, waves, and tides were used to investigate the dynamics governing the circulation and transport in the inner shelf and the role of coastline variability on regional circulation dynamics. Here, the following physical processes are highlighted: internal wave dynamics from the midshelf to the inner shelf; flow separation and eddy shedding off Point Sal; offshore ejection of surfzone waters from rip currents; and wind-driven subtidal circulation dynamics. The extensive dataset from ISDE allows for unprecedented investigations into the role of physical processes in creating spatial heterogeneity, and nonlinear interactions between various inner-shelf physical processes. Overall, the highly spatially and temporally resolved oceanographic measurements and numerical simulations of ISDE provide a central framework for studies exploring this complex and fascinating region of the ocean.

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K. Holmlund, J. Grandell, J. Schmetz, R. Stuhlmann, B. Bojkov, R. Munro, M. Lekouara, D. Coppens, B. Viticchie, T. August, B. Theodore, P. Watts, M. Dobber, G. Fowler, S. Bojinski, A. Schmid, K. Salonen, S. Tjemkes, D. Aminou, and P. Blythe

Abstract

Within the next couple of years, the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) will start the deployment of its next-generation geostationary meteorological satellites. The Meteosat Third Generation (MTG) is composed of four imaging (MTG-I) and two sounding (MTG-S) platforms. The satellites are three-axis stabilized, unlike the two previous generations of Meteosat that were spin stabilized, and carry two sets of remote sensing instruments each. Hence, in addition to providing continuity, the new system will provide an unprecedented capability from geostationary orbit. The payload on the MTG-I satellites are the 16-channel Flexible Combined Imager (FCI) and the Lightning Imager (LI). The payloads on the MTG-S satellites are the hyperspectral Infrared Sounder (IRS) and a high-resolution Ultraviolet–Visible–Near-Infrared (UVN) sounder Sentinel-4/UVN, provided by the European Commission. Today, hyperspectral sounding from geostationary orbit is provided by the Chinese Fengyun-4A (FY-4A) satellite Geostationary Interferometric Infrared Sounder (GIIRS) instrument, and lightning mappers are available on FY-4A and on the National Oceanic and Atmospheric Administration (NOAA) GOES-16 and GOES-17 satellites. Consequently, the development of science and applications for these types of instruments have a solid foundation. However, the IRS, LI, and Sentinel-4/UVN are a challenging first for Europe in a geostationary orbit. The four MTG-I and two MTG-S satellites are designed to provide 20 and 15.5 years of operational service, respectively. The launch of the first MTG-I is expected at the end of 2022 and the first MTG-S roughly a year later. This article describes the four instruments, outlines products and services, and addresses the evolution of the further applications.

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