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Laura D. Riihimaki, Connor Flynn, Allison McComiskey, Dan Lubin, Yann Blanchard, J. Christine Chiu, Graham Feingold, Daniel R. Feldman, Jake J. Gristey, Christian Herrera, Gary Hodges, Evgueni Kassianov, Samuel E. LeBlanc, Alexander Marshak, Joseph J. Michalsky, Peter Pilewskie, Sebastian Schmidt, Ryan C. Scott, Yolanda Shea, Kurtis Thome, Richard Wagener, and Bruce Wielicki

Abstract

Industry advances have greatly reduced the cost and size of ground-based shortwave (SW) sensors for the ultraviolet, visible, and near-infrared spectral ranges that make up the solar spectrum, while simultaneously increasing their ruggedness, reliability, and calibration accuracy needed for outdoor operation. These sensors and collocated meteorological equipment are an important part of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility, which has supported parallel integrated measurements of atmospheric and surface properties for more than two decades at fixed and mobile sites around the world. The versatile capability of these ground-based measurements includes 1) rich spectral information required for retrieving cloud and aerosol microphysical properties, such as cloud phase, cloud particle size, and aerosol size distributions, and 2) high temporal resolution needed for capturing fast evolution of cloud microphysical properties in response to rapid changes in meteorological conditions. Here we describe examples of how ARM’s spectral radiation measurements are being used to improve understanding of the complex processes governing microphysical, optical, and radiative properties of clouds and aerosol.

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Stéphane Vannitsem, John Bjørnar Bremnes, Jonathan Demaeyer, Gavin R. Evans, Jonathan Flowerdew, Stephan Hemri, Sebastian Lerch, Nigel Roberts, Susanne Theis, Aitor Atencia, Zied Ben Bouallègue, Jonas Bhend, Markus Dabernig, Lesley De Cruz, Leila Hieta, Olivier Mestre, Lionel Moret, Iris Odak Plenković, Maurice Schmeits, Maxime Taillardat, Joris Van den Bergh, Bert Van Schaeybroeck, Kirien Whan, and Jussi Ylhaisi

Abstract

Statistical postprocessing techniques are nowadays key components of the forecasting suites in many national meteorological services (NMS), with, for most of them, the objective of correcting the impact of different types of errors on the forecasts. The final aim is to provide optimal, automated, seamless forecasts for end users. Many techniques are now flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias corrections to very sophisticated distribution-adjusting techniques that incorporate correlations among the prognostic variables. The paper is an attempt to summarize the main activities going on in this area from theoretical developments to operational applications, with a focus on the current challenges and potential avenues in the field. Among these challenges is the shift in NMS toward running ensemble numerical weather prediction (NWP) systems at the kilometer scale that produce very large datasets and require high-density high-quality observations, the necessity to preserve space–time correlation of high-dimensional corrected fields, the need to reduce the impact of model changes affecting the parameters of the corrections, the necessity for techniques to merge different types of forecasts and ensembles with different behaviors, and finally the ability to transfer research on statistical postprocessing to operations. Potential new avenues are also discussed.

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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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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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David M. Schultz and Daniel Keyser

Abstract

Two widely accepted conceptual models of extratropical cyclone structure and evolution exist: the Norwegian and Shapiro–Keyser cyclone models. The Norwegian cyclone model was developed around 1920 by the Bergen School meteorologists. This model has come to feature an acute angle between the cold and warm fronts, with the reduction in the area of the warm sector during the evolution of the cyclone corresponding to the formation of an occluded front. The Shapiro–Keyser cyclone model was developed around 1990 and was motivated by the recognition of alternative frontal structures depicted in model simulations and observations of rapidly developing extratropical cyclones. This model features a right angle between the cold and warm fronts (T-bone), a weakening of the poleward portion of the cold front (frontal fracture), an extension of the warm or occluded front to the rear of and around the cyclone (bent-back front), and the wrapping around of the bent-back front to form a warm-core seclusion of post-cold-frontal air. Although the Norwegian cyclone model preceded the Shapiro–Keyser cyclone model by 70 years, antecedents of features of the Shapiro–Keyser cyclone model were apparent in observations, analyses, and conceptual models presented by the Bergen School meteorologists, their adherents, and their progeny. These “lost” antecedents are collected here for the first time to show that the Bergen School meteorologists were aware of them, although not all of the antecedents survived until their reintroduction into the Shapiro–Keyser cyclone model in 1990. Thus, the Shapiro–Keyser cyclone model can be viewed as a synthesis of various elements of cyclone structure and evolution recognized by the Bergen School meteorologists.

Open access
H. J. S. Fernando, I. Gultepe, C. Dorman, E. Pardyjak, Q. Wang, S. W Hoch, D. Richter, E. Creegan, S. Gaberšek, T. Bullock, C. Hocut, R. Chang, D. Alappattu, R. Dimitrova, D. Flagg, A. Grachev, R. Krishnamurthy, D. K. Singh, I. Lozovatsky, B. Nagare, A. Sharma, S. Wagh, C. Wainwright, M. Wroblewski, R. Yamaguchi, S. Bardoel, R. S. Coppersmith, N. Chisholm, E. Gonzalez, N. Gunawardena, O. Hyde, T. Morrison, A. Olson, A. Perelet, W. Perrie, S. Wang, and B. Wauer

Abstract

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

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