Dynamical constraints for the predictability of heat waves in current and future...
In summer 2018, a devastating heat wave affected the entire Northern Hemisphere. Climate change projections indicate that the severity and frequency of such heat waves will further increase over the next decades. At the same time,...
In summer 2018, a devastating heat wave affected the entire Northern Hemisphere. Climate change projections indicate that the severity and frequency of such heat waves will further increase over the next decades. At the same time, models remain unable to predict heat waves at lead times of a few weeks – a crucial planning timescale. The poor prediction skill at timescales of weeks to months is to a large extent due to an incomplete understanding of the underlying physical drivers of heat waves. In particular, the atmospheric fluid dynamics responsible for heat waves and their prediction are not sufficiently understood and tend to be biased in models. The seasonal cycle further modulates the drivers and predictability of heat waves. Climate change projections disagree on the changes in atmospheric dynamics responsible for heat waves. The proposed research takes an unconventional path to address these open questions by building a process-based hierarchy of prediction systems ranging from a dry dynamical core to a prediction system using full physics. This hierarchy approach is novel for prediction systems. By systematically adding processes to the model, the relative contribution of atmospheric dynamics and surface drivers for heat waves and their predictability can be estimated throughout the seasonal cycle and for the projected changes in heat waves with climate change. While solving a fundamental question in atmospheric fluid dynamics, the proposed research aims to significantly extend the warning horizon and thereby minimize the societal consequences for future heat waves, which are expected to increase in frequency but so far remain unpredictable. This project combines the experience and strengths of the PI in atmospheric dynamics, predictability, and their application in a timely manner by increasing the connections between the dynamics and predictability communities that will benefit the study of atmospheric fluid dynamics and predictability beyond heat waves.ver más
Seleccionando "Aceptar todas las cookies" acepta el uso de cookies para ayudarnos a brindarle una mejor experiencia de usuario y para analizar el uso del sitio web. Al hacer clic en "Ajustar tus preferencias" puede elegir qué cookies permitir. Solo las cookies esenciales son necesarias para el correcto funcionamiento de nuestro sitio web y no se pueden rechazar.
Cookie settings
Nuestro sitio web almacena cuatro tipos de cookies. En cualquier momento puede elegir qué cookies acepta y cuáles rechaza. Puede obtener más información sobre qué son las cookies y qué tipos de cookies almacenamos en nuestra Política de cookies.
Son necesarias por razones técnicas. Sin ellas, este sitio web podría no funcionar correctamente.
Son necesarias para una funcionalidad específica en el sitio web. Sin ellos, algunas características pueden estar deshabilitadas.
Nos permite analizar el uso del sitio web y mejorar la experiencia del visitante.
Nos permite personalizar su experiencia y enviarle contenido y ofertas relevantes, en este sitio web y en otros sitios web.