ORCID Profile
0000-0002-1463-929X
Current Organisations
ETH Zurich
,
Université de Lausanne
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Publisher: American Geophysical Union (AGU)
Date: 22-01-2020
DOI: 10.1029/2019JD030923
Publisher: American Geophysical Union (AGU)
Date: 22-01-2020
DOI: 10.1029/2019JD030920
Publisher: American Meteorological Society
Date: 06-2020
Abstract: Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation initialization shock and drift understanding the onset of model systematic errors bias correction, calibration, and forecast quality assessment model resolution atmosphere–ocean coupling sources and expectations for predictability and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.
Publisher: Copernicus GmbH
Date: 03-03-2022
Publisher: Copernicus GmbH
Date: 03-03-2022
DOI: 10.5194/WCD-2022-12
Abstract: Abstract. The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper troposphere/lower stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme vortex event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability of the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for sub-seasonal to seasonal forecast systems, and further our understanding of the role of the stratosphere for predictive skill in the troposphere.
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-7483
Abstract: & & El Ni& #241 o-Southern Oscillation can influence the Tropical North Atlantic (TNA), leading to anomalous sea surface temperatures (SST) at a lag of several months. Several mechanisms have been proposed to explain this teleconnection. These mechanisms include both tropical and extratropical pathways, contributing to anomalous trade winds and static stability over the TNA region. The TNA SST response to ENSO has been suggested to be nonlinear. Yet the overall linearity of the ENSO-TNA teleconnection via the two pathways remains unclear. Here we use reanalysis data to confirm that the SST anomaly (SSTA) in the TNA is nonlinear with respect to the strength of the SST forcing in the tropical Pacific, as further increases in El Ni& #241 o magnitudes cease to create further increases of the TNA SSTA. We further show that the tropical pathway is more linear than the extratropical pathway by sub- iding the inter-basin connection into extratropical and tropical pathways. The extratropical pathway is modulated by the North Atlantic Oscillation (NAO) and the location of the SSTA in the Pacific, but this modulation insufficiently explains the nonlinearity in TNA SSTA. As neither extratropical nor tropical pathways can explain the nonlinearity, this suggests that external factors are at play. Further analysis shows that the TNA SSTA is highly influenced by the preconditioning of the tropical Atlantic SST. This preconditioning is found to be associated with the NAO through SST-tripole patterns.& &
Publisher: Springer Science and Business Media LLC
Date: 03-09-2020
DOI: 10.1007/S00382-020-05442-9
Abstract: South-Eastern Brazil experienced a devastating drought associated with significant agricultural losses in austral summer 2014. The drought was linked to the development of a quasi-stationary anticyclone in the South Atlantic in early 2014 that affected local precipitation patterns over South-East Brazil. Previous studies have suggested that the unusual blocking was triggered by tropical Pacific sea surface temperature (SST) anomalies and, more recently, by convection over the Indian Ocean related to the Madden–Julian Oscillation. Further investigation of the proposed teleconnections appears crucial for anticipating future economic impacts. In this study, we use numerical experiments with an idealized atmospheric general circulation model forced with the observed 2013/2014 SST anomalies in different ocean basins to understand the dominant mechanism that initiated the 2014 South Atlantic anticyclonic anomaly. We show that a forcing with global 2013/2014 SST anomalies enhances the chance for the occurrence of positive geopotential height anomalies in the South Atlantic. However, further sensitivity experiments with SST forcings in separate ocean basins suggest that neither the Indian Ocean nor tropical Pacific SST anomalies alone have contributed significantly to the anomalous atmospheric circulation that led to the 2014 South-East Brazil drought. The model study rather points to an important role of remote forcing from the South Pacific, local South Atlantic SSTs, and internal atmospheric variability in driving the persistent blocking over the South Atlantic.
Publisher: Copernicus GmbH
Date: 19-08-2022
Abstract: Abstract. The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere.
Location: No location found
Location: United Kingdom of Great Britain and Northern Ireland
Location: United States of America
No related grants have been discovered for Daniela Domeisen.