ALBERT

Description: Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While early warning systems are frequently used to predict the magnitude, location and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services or financial loss. Complementing early warning systems with impact forecasts has a two‐fold advantage: it would provide decision makers with richer information to take informed decisions about emergency measures, and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multi‐hazard early warning systems. This review discusses the state‐of‐the‐art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.

Description: In early 2022, several extreme weather events occurred in the Southern Hemisphere. Devastating floods killed more than 500 people in South Africa (11-12 April) and 26 people in eastern Australia (24-28 February and 25-31 March), while an unprecedented heatwave broke temperature records in Antarctica (16-22 March). This study presents a multiscale analysis of the atmospheric processes associated with these extreme events from synoptic to planetary scales. Equatorward Rossby wave breaking facilitated the transport of moist air from tropical oceans to the subtropical regions affected by the extreme precipitation events, while poleward Rossby wave breaking forced an intrusion of warm and moist extratropical air masses into the Antarctic conntinent. Southern hemispheric extratropical wave activity demonstrated relatively normal conditions during February and March, while wave energy peaked for wave number 5 during April. From a planetary-scale perspective, we investigate how modes of tropical variability, including the El-Nino Southern Oscillation (ENSO; in a La Nina phase) and the Madden-Julian Oscillation (MJO), modulate large-scale atmospheric circulation patterns, extratropical wave activity, and Rossby wave breaking. Overall, this study clarifies the role of regional and remote atmospheric processes in the recent weather extremes in the Southern Hemisphere.

Description: A persistent high-pressure ridge in the upper troposphere is a vital ingredient for mid-latitude temperature extremes. Changes in the basic state for stationary synoptic-scale waves are, therefore, commonly discussed to understand the response of dynamical heatwave drivers to global warming. However, the relationship between upper-tropospheric Rossby wave phase speed and surface extremes is not fully resolved. Combining a complex principal component analysis of reanalysis data with idealized model experiments, we relate Rossby wave phase speed to baroclinic wave amplitudes and differences in the basic state. Specifically, we find an equatorward shift for both synoptic-scale wave amplitude and the zonal-mean westerly jet during low-phase speed episodes, but an enhanced Atlantic storm track and a broadened zonal-mean jet during high-phase speed episodes. This analysis allows us to understand how the occurrence and location of large monthly-mean meridional wind anomalies and increased frequencies of surface extremes depend on the dominant synoptic-scale wave phase speed.

Description: Heatwaves have disastrous impacts on human health, ecosystems, and agriculture. Heatwave impacts can be mitigated by early warnings, which were found to effectively reduce the risk from temperature extremes on the sub-seasonal prediction timescale. The quality of heatwave warnings is bound to the predictability of heatwaves, which is mainly investigated in terms of the prediction potential of heatwave intensity. The prediction of heatwave features such as heatwave onset and duration would benefit impact prediction and early warnings. For example, higher mortality risk was previously identified for heatwaves that were more intense, longer, or occurred with earlier timing in the summer. We assess the predictability of heatwave onset, duration, and intensity for the large-scale European heatwaves during 1998-2017. The predictability of heatwave characteristics is evaluated for the lead times of 1—3 weeks in the ECMWF forecast system. The highest predictability in heatwave onset and duration is found over Northern Europe, while Western Europe has the lowest bias in heatwave intensity. Furthermore, we identify the most predictable and least predictable heatwaves over Europe. The most predictable events include the Russian heatwaves of 2010 and 2017, and the 2012 event over Eastern Europe. Some of the least predictable events include the events of 2016 over Russia and of 2017 over Western Europe. The identification of the most and least predictable heatwaves sets the basis for a further investigation of the causes for differences in heatwave predictability over Europe.

Description: Socioeconomic livelihoods in the Horn of Africa (HA) are highly dependent on seasonal rainfall, which occurs during two main seasons: October-November-December (OND) and March-April-May (MAM). During the two last decades the HA region has been affected by severe and prolonged droughts, leading to acute food insecurity, shortage of drinking water, and increasing risk of disease. Sub-seasonal drought prediction over the HA, from two weeks to two months, is therefore crucial for decision making and early warnings across several sectors. The sub-seasonal prediction of high and low precipitation extremes (PEs) by dynamical forecast systems is challenging for both rainy seasons, but there may be potential for extending the current prediction timescale based on remote drivers. To investigate the sub-seasonal predictability of PEs during the OND season we build a Long Short-Term Memory (LSTM) Neural Network predicting biweekly precipitation tercile categories over the HA region. The LSTM is trained on observational and reanalysis data during the period 1981—2020 and provides predictions with lead times of one week to one month. The results show that floods can be more skillfully predicted than droughts for all lead times. Moreover, we use explainable AI methods to explore the contribution of remote drivers to the predictions and potential sub-seasonal forecast opportunities for PEs. Preliminary results show that the sea surface temperature over the tropical Pacific is important for the LSTM prediction, but further investigation is needed to determine more factors affecting the prediction skill for PEs over the HA region.

Description: The important role of stratospheric feedbacks for the climate system – most notably how the ozone layer responds to anthropogenic forcings, and how that response then feeds back on the climate itself – remains largely unexplored, apart from the effects associated with gases regulated by the Montreal Protocol. This is because most models participating to CMIP inter-comparisons do not account for the complex interplay between stratospheric composition, dynamics and radiation. Here, we provide a review of recent work highlighting the importance of such interplay on a broad range of time-scales, encompassing short-term (i.e. intra-seasonal) variability to long-term climate change. First, we show that increasing carbon dioxide levels lead to substantial changes in the ozone layer and that these changes have a substantial effect on the circulation response to that forcing in both hemispheres. Then, we explore the connection between Arctic ozone and surface climate on inter-annual time-scales, highlighting the contribution of springtime ozone depletion to surface anomalies. Lastly, we show the impacts of long-term ozone recovery on the Arctic stratosphere and stratosphere-troposphere coupling; most remarkably, we find that ozone recovery significantly offsets the effects of GHGs on the polar vortex. Such findings demonstrate that stratospheric composition feedbacks play a key role in shaping the climate response to anthropogenic forcings, both via radiative and dynamical processes. However, the coupling between ozone, the large-scale atmospheric circulation and climate is still subject to large uncertainties. We discuss sources of uncertainty and model limitations in the simulation of these effects, and implications for CMIP6.

Description: Precipitation in arid regions can have large societal impacts. On the one hand, when rainfall comes in high intensities, it can lead to deadly floods. On the other hand, precipitation can also refill freshwater resources that are typically scarce in these dry regions. Atmospheric processes that can lead to precipitation in arid regions are often studied at the regional scale and remain poorly understood from a global perspective. In this study, we identify Rossby wave breaking based on the combination of potential vorticity streamers and cutoffs in ERA5 reanalysis data, and we quantify the contribution of this atmospheric process to precipitation at the global scale using different datasets. Rossby wave breaking significantly contributes to 80-90% of daily precipitation extremes and to 70-80% of total precipitation amounts in arid regions equatorward and downstream of the midlatitude storm tracks. Portions of land surface area where Rossby wave breaking significantly contributes to precipitation increases from 10-25% in humid regions to about 50% in regions with a hyper arid climate. In subtropical arid regions, Rossby wave breaking contributes to much of the precipitation during the transition seasons and winter, whereas extratropical arid regions receive precipitation under the influence of Rossby wave breaking throughout the year. This study shows that Rossby wave breaking is a key driver of precipitation in arid regions, offering new opportunities to improve medium-range prediction of flood hazards and to better understand the role of atmospheric dynamics in projections and uncertainties of future precipitation changes in climate model simulations.