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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
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Silke Trömel, Christian Chwala, Carina Furusho, Cintia Carbajal Henken, Julius Polz, Roland Potthast, Ricardo Reinoso-Rondinel, and Clemens Simmer
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A. Gettelman, G. R. Carmichael, G. Feingold, A. M. Da Silva, and S. C. Van Den Heever
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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
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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.

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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.

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

Abstract

In a context that fosters the evolution of hydro-climate services, it is crucial to support and train users in making the best possible forecast-based decisions. Here, we analyze how decision-making is influenced by the seasonal forecast performance based on the Call For Water serious game in which participants manage a water supply reservoir. The aim is twofold: (1) train participants in the concepts of forecast sharpness and reliability, and (2) collect participants’ decisions to investigate the levels of forecast sharpness and reliability needed to make informed decisions. In the first game round, participants are provided with forecasts of varying reliability and sharpness, while in the second round, they have the possibility to pay for systematically reliable and sharp forecasts (improved forecasts). Exploitable answers were collected from 367 participants, predominantly researchers, forecasters and consultants in the water resources and energy sectors. Results show that improved forecasts led to better decisions, enabling participants to step out of purely conservative strategies and successfully take risks. Reliability levels of 60% are necessary for decision-making while both reliability levels above 70% and sharpness are required for informed risk-prone strategies. Improved forecasts are judged more valuable in extreme years, for instance when hedging against water shortage risks. Additionally, participants working in the energy, air quality and agriculture sectors, as well as traders, decision-makers and forecasters invested the most in forecasts. Finally, we discuss the potential of serious games to foster capacity development in hydro-climate services, and provide recommendations for forecast-based service development.

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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.

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

Capsule

Regional air pollution forecasting can complement the information provided by global models, especially over South America, where acute air pollution episodes due to wildfires in the Amazon are usually observed.

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ARIANE MIDDEL, SAUD ALKHALED, FLORIAN A. SCHNEIDER, BJOERN HAGEN, and PAUL COSEO

Capsule summary

Human-biometeorological observations show that shade from urban form and engineered structures effectively reduces daytime thermal exposure and can be a viable alternative to trees in areas with infrastructure challenges.

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