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Hochman, A., Alpert, P., Harpaz, T., Saaroni, H. & Messori, G. (2019). A new dynamical systems perspective on atmospheric predictability: Eastern Mediterranean weather regimes as a case study. Science Advances, 5(6), Article ID eaau0936.
Open this publication in new window or tab >>A new dynamical systems perspective on atmospheric predictability: Eastern Mediterranean weather regimes as a case study
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2019 (English)In: Science Advances, E-ISSN 2375-2548, Vol. 5, no 6, article id eaau0936Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
AMER ASSOC ADVANCEMENT SCIENCE, 2019
National Category
Meteorology and Atmospheric Sciences Climate Research
Identifiers
urn:nbn:se:uu:diva-390649 (URN)10.1126/sciadv.aau0936 (DOI)000473798500004 ()31183396 (PubMedID)
Funder
Swedish Research Council, 2016-03724
Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-13Bibliographically approved
Messori, G., Ruiz-Perez, G., Manzoni, S. & Vico, G. (2019). Climate drivers of the terrestrial carbon cycle variability in Europe. Environmental Research Letters, 14(6), Article ID 063001.
Open this publication in new window or tab >>Climate drivers of the terrestrial carbon cycle variability in Europe
2019 (English)In: Environmental Research Letters, ISSN 1748-9326, E-ISSN 1748-9326, Vol. 14, no 6, article id 063001Article, review/survey (Refereed) Published
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.

Keywords
carbon cycle, climate, Europe, vegetation, soil
National Category
Climate Research
Identifiers
urn:nbn:se:uu:diva-387989 (URN)10.1088/1748-9326/ab1ac0 (DOI)000469809700001 ()
Funder
Swedish Research Council, 2016-06313Swedish Research Council, 2016-04146Swedish Research Council, 2016-03724Swedish Research Council Formas, 2018-01820Swedish Research Council Formas, 2018-00968
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-27Bibliographically approved
Scher, S. & Messori, G. (2019). How Global Warming Changes the Difficulty of Synoptic Weather Forecasting. Geophysical Research Letters, 46(5), 2931-2939
Open this publication in new window or tab >>How Global Warming Changes the Difficulty of Synoptic Weather Forecasting
2019 (English)In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 46, no 5, p. 2931-2939Article in journal (Refereed) Published
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.

Keywords
ensemble forecasts, climate change, forecast uncertainty, synoptic meteorology
National Category
Meteorology and Atmospheric Sciences Climate Research
Identifiers
urn:nbn:se:uu:diva-381820 (URN)10.1029/2018GL081856 (DOI)000462612900066 ()
Funder
Swedish Research Council, 2016-03724Swedish National Infrastructure for Computing (SNIC)
Available from: 2019-04-24 Created: 2019-04-24 Last updated: 2019-04-24Bibliographically approved
Lembo, V., Messori, G., Graversen, R. & Lucarini, V. (2019). Spectral Decomposition and Extremes of Atmospheric Meridional Energy Transport in the Northern Hemisphere Midlatitudes. Geophysical Research Letters, 46(13), 7602-7613
Open this publication in new window or tab >>Spectral Decomposition and Extremes of Atmospheric Meridional Energy Transport in the Northern Hemisphere Midlatitudes
2019 (English)In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 46, no 13, p. 7602-7613Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
AMER GEOPHYSICAL UNION, 2019
National Category
Meteorology and Atmospheric Sciences
Identifiers
urn:nbn:se:uu:diva-391942 (URN)10.1029/2019GL082105 (DOI)000476960100061 ()
Funder
Swedish Research Council, 2016-03724EU, Horizon 2020, 727852The Research Council of Norway, 280727
Available from: 2019-08-29 Created: 2019-08-29 Last updated: 2019-08-29Bibliographically approved
Faranda, D., Alvarez-Castro, M. C., Messori, G., Rodrigues, D. & Yiou, P. (2019). The hammam effect or how a warm ocean enhances large scale atmospheric predictability. Nature Communications, 10, Article ID 1316.
Open this publication in new window or tab >>The hammam effect or how a warm ocean enhances large scale atmospheric predictability
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2019 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 1316Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2019
National Category
Climate Research
Identifiers
urn:nbn:se:uu:diva-381124 (URN)10.1038/s41467-019-09305-8 (DOI)000461881700021 ()30899008 (PubMedID)
Funder
EU, European Research Council, 338965-A2C2Swedish Research Council, 2016-03724Swedish Research Council, C0629701
Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-04-04Bibliographically approved
Messori, G., Gaetani, M., Zhang, Q., Zhang, Q. & Pausata, F. S. R. (2019). The water cycle of the mid-Holocene West African monsoon: The role of vegetation and dust emission changes. International Journal of Climatology, 39(4), 1927-1939
Open this publication in new window or tab >>The water cycle of the mid-Holocene West African monsoon: The role of vegetation and dust emission changes
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2019 (English)In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088, Vol. 39, no 4, p. 1927-1939Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
WILEY, 2019
Keywords
dust, Green Sahara, mid-Holocene, precipitation recycling, water cycle, African monsoon
National Category
Climate Research
Identifiers
urn:nbn:se:uu:diva-385579 (URN)10.1002/joc.5924 (DOI)000465456400008 ()
Funder
Swedish Research Council Formas, FR-2016-0001Swedish Research Council Formas, 2016-217Swedish Research Council, 2017-04232Swedish Research Council, 2016-03724
Available from: 2019-06-17 Created: 2019-06-17 Last updated: 2019-06-17Bibliographically approved
Scher, S. & Messori, G. (2019). Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground. Geoscientific Model Development, 12(7), 2797-2809
Open this publication in new window or tab >>Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground
2019 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 7, p. 2797-2809Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
COPERNICUS GESELLSCHAFT MBH, 2019
National Category
Meteorology and Atmospheric Sciences Climate Research
Identifiers
urn:nbn:se:uu:diva-390793 (URN)10.5194/gmd-12-2797-2019 (DOI)000474740000001 ()
Funder
Swedish Research Council, 2016-03724
Available from: 2019-08-14 Created: 2019-08-14 Last updated: 2019-08-14Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2032-5211

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