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Rachel H. White
,
Kai Kornhuber
,
Olivia Martius
, and
Volkmar Wirth

Abstract

A notable number of high-impact weather extremes have occurred in recent years, often associated with persistent, strongly meandering atmospheric circulation patterns known as Rossby waves. Because of the high societal and ecosystem impacts, it is of great interest to be able to accurately project how such extreme events will change with climate change, and to predict these events on seasonal-to-subseasonal (S2S) time scales. There are multiple physical links connecting upper-atmosphere circulation patterns to surface weather extremes, and it is asking a lot of our dynamical models to accurately simulate all of these. Subsequently, our confidence in future projections and S2S forecasts of extreme events connected to Rossby waves remains relatively low. We also lack full fundamental theories for the growth and propagation of Rossby waves on the spatial and temporal scales relevant to extreme events, particularly under strongly nonlinear conditions. By focusing on one of the first links in the chain from upper-atmospheric conditions to surface extremes—the Rossby waveguide—it may be possible to circumvent some model biases in later links. To further our understanding of the nature of waveguides, links to persistent surface weather events and their representation in models, we recommend exploring these links in model hierarchies of increasing complexity, developing fundamental theory, exploiting novel large ensemble datasets, harnessing deep learning, and increased community collaboration. This would help increase understanding and confidence in both S2S predictions of extremes and of projections of the impact of climate change on extreme weather events.

Full access
George C. Craig
,
Andreas H. Fink
,
Corinna Hoose
,
Tijana Janjić
,
Peter Knippertz
,
Audine Laurian
,
Sebastian Lerch
,
Bernhard Mayer
,
Annette Miltenberger
,
Robert Redl
,
Michael Riemer
,
Kirsten I. Tempest
, and
Volkmar Wirth

Abstract

Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-yr phase of our planned duration of 12 years and employ 36 doctoral and postdoctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely, upscale error growth, errors associated with cloud processes, and probabilistic prediction of high-impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early-career scientists, and to support education, equal opportunities, and outreach, which are also described here.

Open access
Clemens Simmer
,
Gerhard Adrian
,
Sarah Jones
,
Volkmar Wirth
,
Martin Göber
,
Cathy Hohenegger
,
Tijana Janjic´
,
Jan Keller
,
Christian Ohlwein
,
Axel Seifert
,
Silke Trömel
,
Thorsten Ulbrich
,
Kathrin Wapler
,
Martin Weissmann
,
Julia Keller
,
Matthieu Masbou
,
Stefanie Meilinger
,
Nicole Riß
,
Annika Schomburg
,
Arnd Vormann
, and
Christa Weingärtner

Abstract

In 2011, the German Federal Ministry of Transport, Building and Urban Development laid the foundation of the Hans-Ertel Centre for Weather Research [Hans-Ertel-Zentrum für Wetterforschung (HErZ)] in order to better connect fundamental meteorological research and teaching at German universities and atmospheric research centers with the needs of the German national weather service Deutscher Wetterdienst (DWD). The concept for HErZ was developed by DWD and its scientific advisory board with input from the entire German meteorological community. It foresees core research funding of about €2,000,000 yr−1 over a 12-yr period, during which time permanent research groups must be established and DWD subjects strengthened in the university curriculum. Five priority research areas were identified: atmospheric dynamics and predictability, data assimilation, model development, climate monitoring and diagnostics, and the optimal use of information from weather forecasting and climate monitoring for the benefit of society. Following an open call, five groups were selected for funding for the first 4-yr phase by an international review panel. A dual project leadership with one leader employed by the academic institute and the other by DWD ensures that research and teaching in HErZ is attuned to DWD needs and priorities, fosters a close collaboration with DWD, and facilitates the transfer of fundamental research into operations. In this article, we describe the rationale behind HErZ and the road to its establishment, present some scientific highlights from the initial five research groups, and discuss the merits and future development of this new concept to better link academic research with the needs and challenges of a national weather service.

Full access