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Michael Peterson

Abstract

The Geostationary Lightning Mappers (GLMs) on NOAA’s current Geostationary Operational Environmental Satellites (GOES) map the lateral development of lightning flashes across the Western Hemisphere up to 54° latitude. As staring instruments that continuously observe the Americas (GOES-16) and the Pacific Ocean (GOES-17), the GLMs resolve the spatial extent of even the rarest and most exceptional lightning flashes. GOES-16 GLM observations that include the Americas’ hotspots for the largest and longest-lasting lightning “megaflashes” are used to document where and when mesoscale lightning occurs that exceeds the largest (321 km) and longest-lasting (7.74 s) flashes that have been measured by ground-based instruments. The most exceptional GLM megaflashes in terms of extent (709 km) and duration (16.730 s) were recently recognized as global lightning extremes by the World Meteorological Organization (WMO). These world record cases beat the next-largest flash by 36 km and the next-longest-lasting flash by 1.5 s. The top GLM megaflashes between 1 January 2018 and 15 January 2020 that exceed the previous LMA records are concentrated in the central United States (most frequently along the Oklahoma–Arkansas border) and southern Brazil (Rio Grande do Sul) and Uruguay. The top North American megaflashes are most common from April through June and occur on between 4 and 14 nights per month. The top South American megaflashes are most frequent between October and January and likewise have a nocturnal preference following the diurnal cycle of mesoscale convective systems (MCSs). Potential future field programs that aim to observe extreme megaflashes should focus on these regions and seasons.

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Joseph M. Prospero, Anthony C. Delany, Audrey C. Delany, and Toby N. Carlson

CAPSULE

Over fifty years ago, African dust was serendipitously discovered in the Caribbean in three separate efforts one of which led to a fundamental understanding of the phenomenon.

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Eun-Pa Lim, Harry H. Hendon, Amy H. Butler, David W. J. Thompson, Zachary Lawrence, Adam A. Scaife, Theodore G. Shepherd, Inna Polichtchouk, Hisashi Nakamura, Chiaki Kobayashi, Ruth Comer, Lawrence Coy, Andrew Dowdy, Rene D. Garreaud, Paul A. Newman, and Guomin Wang

Capsule Summary

During austral spring 2019 the Antarctic stratosphere experienced record-breaking warming and a near-record polar vortex weakening, resulting in predictable extreme climate conditions throughout the Southern Hemisphere through December 2019.

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Catherine A Senior, John H Marsham, Sègoléne Berthou, Laura E Burgin, Sonja S Folwell, Elizabeth J Kendon, Cornelia M Klein, Richard G Jones, Neha Mittal, David P Rowell, Lorenzo Tomassini, Thèo Vischel, Bernd Becker, Cathryn E Birch, Julia Crook, Andrew J Dougill, Declan L Finney, Richard J Graham, Neil C G Hart, Christopher D Jack, Lawrence S Jackson, Rachel James, Bettina Koelle, Herbert Misiani, Brenda Mwalukanga, Douglas J Parker, Rachel A Stratton, Christopher M Taylor, Simon O Tucker, Caroline M Wainwright, Richard Washington, and Martin R Willet

Abstract

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly effects of explicit convection affect not only projected changes in rainfall extremes, dry-spells and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change mean that we can provide regional decision makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the UK Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international co-ordination of such computationally, and human-resource expensive simulations as effectively as possible.

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Mark S. Kulie, Claire Pettersen, Aronne J. Merrelli, Timothy J. Wagner, Norman B. Wood, Michael Dutter, David Beachler, Todd Kluber, Robin Turner, Marian Mateling, John Lenters, Peter Blanken, Maximilian Maahn, Christopher Spence, Stefan Kneifel, Paul A. Kucera, Ali Tokay, Larry F. Bliven, David B. Wolff, and Walter A. Petersen

BAMS Capsule:

Profiling radar and ground-based in situ observations reveal the ubiquity of snowfall produced by shallow clouds, the importance of near-surface snowfall enhancement processes, and regime-dependent snow particle microphysical variability in the Northern Great Lakes Region.

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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 has 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 includes 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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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

Capsule Summary

EUMETSAT will deploy its next generation geostationary satellite system, Meteosat Third Generation in the coming years. This article gives an overview of the instruments and capabilities of the new system.

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Mark R Jury

Abstract

This study reviews Kenya’s fluctuating hydro-climate (3S-4N, 35-40E) and evaluates products that describe its area-averaged daily rainfall 2008-2018, monthly evaporation 2000-2018, and catchment hydrology via gauge, satellite, and model hindcast/forecast.

Using the correlation of rainfall as a metric of skill we found: daily satellite vs model hindcasts achieved 75%; while model forecasts at 2- to 6-day lead achieved 55-58%. The daily satellite vs model soil moisture had a significant correlation (84%); and model run-off vs gauge streamflow reached 61%. A two day delay was noted between rainfall and streamflow response in recent flood events; however long-range predictability was found to be poor (35%).

These outcomes were considered at a local workshop, and ways to sustainably improve the real-time reporting of key hydro-climate parameters for operational data assimilation were suggested as steps toward better monitoring and forecast services in Kenya

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Daniel B. Wright, Constantine Samaras, and Tania Lopez-Cantu

Capsule:

Updating extreme rainfall information in a changing climate is essential for communities and infrastructure and requires an inclusive, science-driven process.

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S. Kalluri, C. Cao, A. Heidinger, A. Ignatov, J. Key, and T. Smith

Abstract

The Advanced Very High Resolution Radiometers (AVHRR), which have been flying on National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting weather satellites since 1978, provide the longest global record of Earth observations from a visible–infrared imager. Experience gained through AVHRRs has been integral to the development of the new-generation sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and associated data processing algorithms in the United States, as well as a similar class of sensor by space agencies around the world. Over four decades of data have been vital for studying Earth and its change. The MetOp-C satellite that was successfully launched in 2018 carries the last AVHRR. This article reviews the contributions of AVHRR in building a continuous global data record over the last 40 years on the occasion of its last launch.

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