uu.seUppsala University Publications
Change search
Refine search result
1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Faranda, Davide
    et al.
    Univ Paris Saclay, UVSQ, CNRS, LSCE,IPSL,CEA,CEA Saclay Orme Merisiers,UMR 8212, F-91191 Gif Sur Yvette, France;London Math Lab, 8 Margravine Gardens, London W68RH, England.
    Alvarez-Castro, M. Carmen
    Univ Paris Saclay, UVSQ, CNRS, LSCE,IPSL,CEA,CEA Saclay Orme Merisiers,UMR 8212, F-91191 Gif Sur Yvette, France;Ctr Euromediterraneo Cambiamenti Climat, Climate Simulat & Predict Div, I-40127 Bologna, Italy.
    Messori, Gabriele
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Paris Saclay, UVSQ, CNRS, LSCE,IPSL,CEA,CEA Saclay Orme Merisiers,UMR 8212, F-91191 Gif Sur Yvette, France;Stockholm Univ, Dept Meteorol, S-10691 Stockholm, Sweden;Bolin Ctr Climate Res, S-10691 Stockholm, Sweden.
    Rodrigues, David
    Univ Paris Saclay, UVSQ, CNRS, LSCE,IPSL,CEA,CEA Saclay Orme Merisiers,UMR 8212, F-91191 Gif Sur Yvette, France.
    Yiou, Pascal
    Univ Paris Saclay, UVSQ, CNRS, LSCE,IPSL,CEA,CEA Saclay Orme Merisiers,UMR 8212, F-91191 Gif Sur Yvette, France.
    The hammam effect or how a warm ocean enhances large scale atmospheric predictability2019In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 1316Article in journal (Refereed)
    Abstract [en]

    The atmosphere's chaotic nature limits its short-term predictability. Furthermore, there is little knowledge on how the difficulty of forecasting weather may be affected by anthropogenic climate change. Here, we address this question by employing metrics issued from dynamical systems theory to describe the atmospheric circulation and infer the dynamical properties of the climate system. Specifically, we evaluate the changes in the sub-seasonal predictability of the large-scale atmospheric circulation over the North Atlantic for the historical period and under anthropogenic forcing, using centennial reanalyses and CMIP5 simulations. For the future period, most datasets point to an increase in the atmosphere's predictability. AMIP simulations with 4K warmer oceans and 4 x atmospheric CO2 concentrations highlight the prominent role of a warmer ocean in driving this increase. We term this the hammam effect. Such effect is linked to enhanced zonal atmospheric patterns, which are more predictable than meridional configurations.

  • 2.
    Hochman, Assaf
    et al.
    Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geophys, IL-69978 Tel Aviv, Israel;Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geog & Human Environm, IL-69978 Tel Aviv, Israel;Tel Aviv Univ, Porter Sch Environm & Earth Sci, Porter Sch Environm Studies, IL-69978 Tel Aviv, Israel.
    Alpert, Pinhas
    Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geophys, IL-69978 Tel Aviv, Israel.
    Harpaz, Tzvi
    Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geophys, IL-69978 Tel Aviv, Israel;Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geog & Human Environm, IL-69978 Tel Aviv, Israel.
    Saaroni, Hadas
    Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geophys, IL-69978 Tel Aviv, Israel;Tel Aviv Univ, Porter Sch Environm & Earth Sci, Porter Sch Environm Studies, IL-69978 Tel Aviv, Israel.
    Messori, Gabriele
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    A new dynamical systems perspective on atmospheric predictability: Eastern Mediterranean weather regimes as a case study2019In: Science Advances, E-ISSN 2375-2548, Vol. 5, no 6, article id eaau0936Article in journal (Refereed)
    Abstract [en]

    The atmosphere is a chaotic system displaying recurrent large-scale configurations. Recent developments in dynamical systems theory allow us to describe these configurations in terms of the local dimension-a proxy for the active number of degrees of freedom-and persistence in phase space, which can be interpreted as persistence in time. These properties provide information on the intrinsic predictability of an atmospheric state. Here, this technique is applied to atmospheric configurations in the eastern Mediterranean, grouped into synoptic classifications (SCs). It is shown that local dimension and persistence, derived from reanalysis and CMIP5 models' daily sea-level pressure fields, can serve as an extremely informative qualitative method for evaluating the predictability of the different SCs. These metrics, combined with the SC transitional probability approach, may be a valuable complement to operational weather forecasts and effective tools for climate model evaluation. This new perspective can be extended to other geographical regions.

  • 3.
    Lembo, V.
    et al.
    Univ Hamburg, Meteorol Inst, Hamburg, Germany.
    Messori, Gabriele
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    Graversen, R.
    Univ Tromso, Dept Phys & Technol, Tromso, Norway.
    Lucarini, V.
    Univ Hamburg, Meteorol Inst, Hamburg, Germany;Univ Reading, Dept Math & Stat, Reading, Berks, England;Univ Reading, Ctr Math Planet Earth, Dept Math & Stat, Reading, Berks, England.
    Spectral Decomposition and Extremes of Atmospheric Meridional Energy Transport in the Northern Hemisphere Midlatitudes2019In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 46, no 13, p. 7602-7613Article in journal (Refereed)
    Abstract [en]

    The atmospheric meridional energy transport in the Northern Hemisphere midlatitudes is mainly accomplished by planetary and synoptic waves. A decomposition into wave components highlights the strong seasonal dependence of the transport, with both the total transport and the contributions from planetary and synoptic waves peaking in winter. In both winter and summer months, poleward transport extremes primarily result from a constructive interference between planetary and synoptic motions. The contribution of the mean meridional circulation is close to climatology. Equatorward transport extremes feature a mean meridional equatorward transport in winter, while the planetary and synoptic modes mostly transport energy poleward. In summer, a systematic destructive interference occurs, with planetary modes mostly transporting energy equatorward and synoptic modes again poleward. This underscores that baroclinic conversion dominates regardless of season in the synoptic wave modes, whereas the planetary waves can be either free or forced, depending on the season. Plain Language Summary The atmospheric heat transport from low to high latitudes is the main mechanism through which the climate reequilibrates the latitudinally uneven absorption of solar radiation. The atmospheric transport is fueled by instabilities driven by the presence of temperature differences between low and high latitudes and acts in such a way to reduce such gradient. This is one of the main stabilizing mechanisms of the climate system. In this work, we investigate how motions of different spatial scales contribute to atmospheric heat transports in the Northern Hemisphere. We discover that the relative importance of synoptic and planetary scale atmospheric motions is different in summer and winter. Our analysis delves into the analysis of events associated with extreme heat transport toward high latitudes, where we see a compensating mechanism between synoptic and planetary atmospheric motions. We further study days characterized by very large and very small (or even negative) heat transport toward the high latitudes. These "extreme events" are driven by complex interactions between the different scales. Our results are relevant for elucidating basic dynamical and thermodynamical properties of the atmosphere and can be used to benchmark the performance of climate models.

  • 4.
    Messori, Gabriele
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    Gaetani, Marco
    Sorbonne Univ, UVSQ, CNRS, LATMOS IPSL, Paris, France.
    Zhang, Qiang
    Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden;Stockholm Univ, Dept Phys Geog, Stockholm, Sweden.
    Zhang, Qiong
    Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden;Stockholm Univ, Dept Phys Geog, Stockholm, Sweden.
    Pausata, Francesco S. R.
    Univ Quebec, Dept Sci Terre & Atmosphere, Montreal, PQ, Canada.
    The water cycle of the mid-Holocene West African monsoon: The role of vegetation and dust emission changes2019In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088, Vol. 39, no 4, p. 1927-1939Article in journal (Refereed)
    Abstract [en]

    During the mid-Holocene (6 kyr BP), West Africa experienced a much stronger and geographically extensive monsoon than in the present day. Changes in orbital forcing, vegetation and dust emissions from the Sahara have been identified as key factors driving this intensification. Here, we analyse how the timing, origin and convergence of moisture fluxes contributing to the monsoonal precipitation change under a range of scenarios: orbital forcing only; orbital and vegetation forcings (Green Sahara); orbital, vegetation and dust forcings (Green Sahara-reduced dust). We further compare our results to a range of reconstructions of mid-Holocene precipitation from palaeoclimate archives. In our simulations, the greening of the Sahara leads to a cyclonic water vapour flux anomaly over North Africa with an anomalous westerly flow bringing large amounts of moisture into the Sahel from the Atlantic Ocean. Changes in atmospheric dust under a vegetated Sahara shift the anomalous moisture advection pattern northwards, increasing both moisture convergence and precipitation recycling over the northern Sahel and Sahara and the associated precipitation during the boreal summer. During this season, under both the Green Sahara and Green Sahara-reduced dust scenarios, local recycling in the Saharan domain exceeds that of the Sahel. This points to local recycling as an important factor modulating vegetation-precipitation feedbacks and the impact of Saharan dust emissions. Our results also show that temperature and evapotranspiration over the Sahara in the mid-Holocene are close to Sahelian pre-industrial values. This suggests that pollen-based paleoclimate reconstructions of precipitation during the Green Sahara period are likely not biased by possible large evapotranspiration changes in the region.

  • 5.
    Messori, Gabriele
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Bolin Ctr Climate Res, Stockholm, Sweden.
    Ruiz-Perez, G.
    Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Swedish Univ Agr Sci SLU, Dept Crop Prod Ecol, Uppsala, Sweden.
    Manzoni, S.
    Bolin Ctr Climate Res, Stockholm, Sweden;Stockholm Univ, Dept Phys Geog, Stockholm, Sweden.
    Vico, G.
    Swedish Univ Agr Sci SLU, Dept Crop Prod Ecol, Uppsala, Sweden.
    Climate drivers of the terrestrial carbon cycle variability in Europe2019In: Environmental Research Letters, ISSN 1748-9326, E-ISSN 1748-9326, Vol. 14, no 6, article id 063001Article, review/survey (Refereed)
    Abstract [en]

    The terrestrial biosphere is a key component of the global carbon cycle and is heavily influenced by climate. Climate variability can be diagnosed through metrics ranging from individual environmental variables, to collections of variables, to the so-called climate modes of variability. Similarly, the impact of a given climate variation on the terrestrial carbon cycle can be described using several metrics, including vegetation indices, measures of ecosystem respiration and productivity and net biosphere-atmosphere fluxes. The wide range of temporal (from sub-daily to paleoclimatic) and spatial (from local to continental and global) scales involved requires a scale-dependent investigation of the interactions between the carbon cycle and climate. However, a comprehensive picture of the physical links and correlations between climate drivers and carbon cycle metrics at different scales remains elusive, framing the scope of this contribution. Here, we specifically explore how climate variability metrics (from single variables to complex indices) relate to the variability of the carbon cycle at sub-daily to interannual scales (i.e. excluding long-term trends). The focus is on the interactions most relevant to the European terrestrial carbon cycle. We underline the broad areas of agreement and disagreement in the literature, and conclude by outlining some existing knowledge gaps and by proposing avenues for improving our holistic understanding of the role of climate drivers in modulating the terrestrial carbon cycle.

  • 6.
    Scher, S.
    et al.
    Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    Messori, Gabriele
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    How Global Warming Changes the Difficulty of Synoptic Weather Forecasting2019In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 46, no 5, p. 2931-2939Article in journal (Refereed)
    Abstract [en]

    Global warming projections point to a wide range of impacts on the climate system, including changes in storm track activity and more frequent and intense extreme weather events. Little is however known on whether and how global warming may affect the atmosphere's predictability and thus our ability to produce accurate weather forecasts. Here, we combine a state-of-the-art climate and a state-of-the-art ensemble weather prediction model to show that, in a business-as-usual 21st century setting, global warming could significantly change the predictability of the atmosphere, defined here via the expected error of weather predictions. Predictability of synoptic weather situations could significantly increase, especially in the Northern Hemisphere. This can be explained by a decrease in the meridional temperature gradient. Contrarily, summertime predictability of weekly rainfall sums might significantly decrease in most regions.

    Plain Language Summary

    Due to the chaotic nature of the atmosphere, it is impossible to make weather forecasts that are completely accurate. Therefore, all weather forecasts are inherently uncertain to a certain degree. However, this uncertainty-and thus the "difficulty" of making good forecastsis not the same for all forecasts. This opens up the highly important question whether global warming will affect the difficulty of weather forecasts. Due to the enormous socioeconomic importance of accurate weather forecasts, it is essential to know whether climate change adaption policies also need to take into account potential changes in the difficulty and accuracy of weather forecasts. We show that in a warmer world, it will be easier to predict fields such as temperature and pressure. Contrarily, it will be harder to make accurate precipitation forecasts, which might strongly affect both disaster prevention and rainfall-dependent industries such as the energy sector, all of which heavily rely on accurate precipitation forecasts. Additionally, we show that the uncertainty of predictions of pressure fields is to a large extent controlled by fluctuations in the temperature difference between the North Pole and the equator. This is a new and important insight into the fundamentals of weather forecast uncertainty.

  • 7.
    Scher, Sebastian
    et al.
    Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    Messori, Gabriele
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Stockholm Univ, Dept Meteorol, Stockholm, Sweden;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
    Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground2019In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 7, p. 2797-2809Article in journal (Refereed)
    Abstract [en]

    Recently, there has been growing interest in the possibility of using neural networks for both weather forecasting and the generation of climate datasets. We use a bottom-up approach for assessing whether it should, in principle, be possible to do this. We use the relatively simple general circulation models (GCMs) PUMA and PLASIM as a simplified reality on which we train deep neural networks, which we then use for predicting the model weather at lead times of a few days. We specifically assess how the complexity of the climate model affects the neural network's forecast skill and how dependent the skill is on the length of the provided training period. Additionally, we show that using the neural networks to reproduce the climate of general circulation models including a seasonal cycle remains challenging - in contrast to earlier promising results on a model without seasonal cycle.

1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf