Browse

You are looking at 21 - 30 of 23,191 items for :

  • Bulletin of the American Meteorological Society x
  • Refine by Access: All Content x
Clear All
Emily Shroyer, Amit Tandon, Debasis Sengupta, Harindra J.S. Fernando, Andrew J. Lucas, J. Thomas Farrar, Rajib Chattopadhyay, Simon de Szoeke, Maria Flatau, Adam Rydbeck, Hemantha Wijesekera, Michael McPhaden, Hyodae Seo, Aneesh Subramanian, R Venkatesan, Jossia Joseph, S. Ramsundaram, Arnold L. Gordon, Shannon M. Bohman, Jaynise Pérez, Iury T. Simoes-Sousa, Steven R. Jayne, Robert E. Todd, G.S. Bhat, Matthias Lankhorst, Tamara Schlosser, Katherine Adams, S.U.P Jinadasa, Manikandan Mathur, M. Mohapatra, E. Pattabhi Rama Rao, A. K. Sahai, Rashmi Sharma, Craig Lee, Luc Rainville, Deepak Cherian, Kerstin Cullen, Luca R. Centurioni, Verena Hormann, Jennifer MacKinnon, Uwe Send, Arachaporn Anutaliya, Amy Waterhouse, Garrett S. Black, Jeremy A. Dehart, Kaitlyn M. Woods, Edward Creegan, Gad Levy, Lakshmi H Kantha, and Bulusu Subrahmanyam

Capsule

The MISO-BoB program sampled oceanic and atmospheric conditions during the transition from active to break conditions subsequent to the onset of the 2018 summer monsoon in the Bay of Bengal.

Full access
Maude Dinan, Emile Elias, Nicholas P. Webb, Greg Zwicke, Timothy S. Dy, 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
Full access
Silke Trömel, Christian Chwala, Carina Furusho, Cintia Carbajal Henken, Julius Polz, Roland Potthast, Ricardo Reinoso-Rondinel, and Clemens Simmer
Full access
A. Gettelman, G. R. Carmichael, G. Feingold, A. M. Da Silva, and S. C. Van Den Heever
Full access
Robert Palmer, David Whelan, David Bodine, Pierre Kirstetter, Matthew Kumjian, Justin Metcalf, Mark Yeary, Tian-You Yu, Ramesh Rao, John Cho, David Draper, Stephen Durden, Stephen English, Pavlos Kollias, Karen Kosiba, Masakazu Wada, Joshua Wurman, William Blackwell, Howard Bluestein, Scott Collis, Jordan Gerth, Aaron Tuttle, Xuguang Wang, and Dusan Zrnic
Full access
Robert Spirig, Christian Feigenwinter, Markus Kalberer, Eberhard Parlow, and Roland Vogt

Abstract

Dolueg is a two-component framework to dynamically display time series. It serves as outreach to other researchers and the local public, educational resource and quality control tool. The first component is a set of Python functions. These create different types of visualisation with meta information about the data in the zoomable, modern SVG format. The second component is a simple but highly customizable website, that groups these figures according to the displayed data. We provide the code in two separate repositories on GitHub for interested parties including more detailed instructions for the installation.

Full access
Yunxia Zhao, Hamid Norouzi, Marzi Azarderakhsh, and Amir AghaKouchak

Abstract

Most previous studies of extreme temperatures have primarily focused on atmospheric temperatures. Using 18 years of the latest version of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, we globally investigate the spatial patterns of hot and cold extremes as well as diurnal temperature range (DTR). We show that the world’s highest LST of 80.8 °C, observed in the Lut Desert in Iran and the Sonoran Desert in Mexico, is over ten degrees above the previous global record of 70.7 °C observed in 2005. The coldest place on Earth is Antarctica with the record low temperature of -110.9 °C. The world’s maximum DTR of 81.8 °C is observed in a desert environment in China. We see strong latitudinal patterns in hot and cold extremes as well as DTR. Biomes worldwide are faced with different levels of temperature extremes and DTR: we observe the highest zonal average maximum LST of 61.1 ± 5.3 °C in the deserts and xeric shrublands; the lowest zonal average minimum LST of -66.6 ± 14.8 °C in the Tundra; and the highest zonal average maximum DTR of 43.5 ± 9.9 °C in the montane grasslands and shrublands. This global exploration of extreme LST and DTR across different biomes sheds light on the type of extremes different ecosystems are faced with.

Full access
Louise Crochemore, Carolina Cantone, Ilias G. Pechlivanidis, and Christiana S. Photiadou

Capsule

A serious game on forecast-based decision-making investigates the levels of forecast performance needed for informed decision-making, and provides recommendations for future hydro-climate service development.

Full access
Jonathan D. W. Kahl, Brandon R. Selbig, and Austin R. Harris

Abstract

Wind gusts are common to everyday life and affect a wide range of interests including wind energy, structural design, forestry, and fire danger. Strong gusts are a common environmental hazard that can damage buildings, bridges, aircraft, and trains, and interrupt electric power distribution, air traffic, waterways transport, and port operations. Despite representing the component of wind most likely to be associated with serious and costly hazards, reliable forecasts of peak wind gusts have remained elusive. A project at the University of Wisconsin-Milwaukee is addressing the need for improved peak gust forecasts with the development of the meteorologically stratified gust factor (MSGF) model. The MSGF model combines gust factors (the ratio of peak wind gust to average wind speed) with wind speed and direction forecasts to predict hourly peak wind gusts. The MSGF method thus represents a simple, viable option for the operational prediction of peak wind gusts. Here we describe the results of a project designed to provide the site-specific gust factors necessary for operational use of the MSGF model at a large number of locations across the United States. Gust web diagrams depicting the wind speed- and wind direction-stratified gust factors, as well as peak gust climatologies, are presented for all sites analyzed.

Full access
Angel Liduvino Vara-Vela, Dirceu Luís Herdies, Débora Souza Alvim, Éder Paulo Vendrasco, Silvio Nilo Figueroa, Jayant Pendharkar, and Julio Pablo Reyes Fernandez

Abstract

Aerosol particles from forest fire events in the Amazon can be effectively transported to urban areas in southeastern South America, thus affecting the air quality over those regions. A combination of observational data and a comprehensive air quality modeling system capable of anticipating acute air pollution episodes is therefore required. A new predictive framework for Amazon forest fire smoke dispersion over South America has been developed based on the Weather Research and Forecasting with Chemistry community (WRF-Chem) model. Two experiments of 48-hour simulations over South America were performed by using this system at 20 km horizontal resolution, on a daily basis, during August and September of 2018 and 2019. The experiment in 2019 included the very strong 3-week forest fire event, when the São Paulo Metropolitan Area, located in southeastern South America, was plunged into darkness on August 19. The model results were satisfactorily compared against satellite-based data products and in situ measurements collected from air quality monitoring sites. The system is executed daily immediately after the CPTEC Satellite Division releases the latest active fire locations data and provides 48-hour forecasts of regional distributions of chemical species such as CO, PM2.5 and O3. The new modeling system will be used as a benchmark within the framework of the Chemistry of the Atmosphere - Field Experiment in Brazil (CAFE-Brazil) project, which will take place in 2022 over the Amazon.

Full access