| 1. |
- Berg, Alexis, et al.
(författare)
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Land-atmosphere feedbacks amplify aridity increase over land under global warming
- 2016
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Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 6:9, s. 869-874
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Tidskriftsartikel (refereegranskat)abstract
- The response of the terrestrial water cycle to global warming is central to issues including water resources, agriculture and ecosystem health. Recent studies indicate that aridity, defined in terms of atmospheric supply (precipitation, P) and demand (potential evapotranspiration, E p) of water at the land surface, will increase globally in a warmer world. Recently proposed mechanisms for this response emphasize the driving role of oceanic warming and associated atmospheric processes. Here we show that the aridity response is substantially amplified by land-atmosphere feedbacks associated with the land surface's response to climate and CO 2 change. Using simulations from the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we show that global aridity is enhanced by the feedbacks of projected soil moisture decrease on land surface temperature, relative humidity and precipitation. The physiological impact of increasing atmospheric CO 2 on vegetation exerts a qualitatively similar control on aridity. We reconcile these findings with previously proposed mechanisms by showing that the moist enthalpy change over land is unaffected by the land hydrological response. Thus, although oceanic warming constrains the combined moisture and temperature changes over land, land hydrology modulates the partitioning of this enthalpy increase towards increased aridity.
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| 2. |
- Berntell, Ellen, 1989-
(författare)
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Understanding West African Monsoon Variability : Insights from Paleoclimate Modelling of Past Warm Climates
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The Sahel, a water-vulnerable region in West Africa, relies heavily on rainfed agriculture. The region experienced pronounced droughts during the 20th Century, emphasising the socio-economic importance of understanding the drivers of the rainfall variability. However, future rainfall projections remain uncertain due to the complex nature of the West African Monsoon (WAM), which is influenced by internal climate variability, external forcing, and feedback processes. Limited observational records in West Africa and the need for longer time series further complicate the understanding of these drivers. This thesis uses paleoclimate modelling to investigate internal and external drivers of monsoon variability in West Africa across four distinct periods. Our study confirms that atmosphere-only model simulations can capture the observed multidecadal rainfall variability in the 20th Century, even though reanalyses struggle to reproduce the correct timing. Analysis of a last millennium simulation using the Earth System Model EC-Earth3 identified two drivers of multidecadal rainfall variability, accounting for 90% of the total co-variability between the West African rainfall and Atlantic sea surface temperatures (SSTs). This finding strengthens our understanding of SST-WAM relationships observed during the 20th Century. An ensemble of climate model simulations (PlioMIP2) shows that high CO2 levels and a different paleogeography during the mid-Pliocene Warm Period led to increased rainfall and a strengthened WAM. Our study emphasised vegetation's crucial role in enhancing the monsoon in past climates. However, simulations forced with prescribed vegetation only capture a one-directional forcing. A mid-Holocene simulation using an Earth System Model with dynamic vegetation revealed that vegetation feedbacks strengthen the WAM response to external orbital forcing but are insufficient to shift the monsoon northward or increase vegetation cover over the Sahara. These results reveal a dry bias and under-representation of simulated vegetation compared to proxy records, highlighting the importance of model development and the need for additional feedback processes in driving an enhanced, northward WAM and extending vegetation to the Sahara. Overall, this thesis advances our understanding of the drivers of West African monsoon variability and provides valuable insights for improving future rainfall projections in this vulnerable region.
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| 3. |
- Bonte, Pieter, et al.
(författare)
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Grounding Stream Reasoning Research
- 2024
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Ingår i: Transactions on Graph Data and Knowledge (TGDK). - Wadern, Germany : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH. - 2942-7517. ; 2:1, s. 1-47
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Tidskriftsartikel (refereegranskat)abstract
- In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic.In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream.This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.
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| 4. |
- Salih, Abubakr A. M., 1980-
(författare)
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On Sahelian-Sudan rainfall and its moisture sources
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The African Sahel is one of the most vulnerable regions to climate variability at different time scales. It is an arid to semi-arid region with limited water resources. The summer rainfall is one of these sources, but it exhibits pronounced interannual variability. This thesis presents several aspects of Sahelian Sudan rainfall. Sudan is located at the eastern fringe of the Sahel and its least studied part. We have examined the impact of tropical deforestation on the rainfall, the moisture sources of the region and the temporal characteristics of the observed and modeled rainfall. In a sensitivity study we performed three simulations, one control simulation and then setting the surface condition of South Sudan to either grass or desert conditions. The rainfall was reduced by 0.1 − 0.9 in the grass scenario and by 0.1 − 2.1 mm day−1 (hereafter mm d−1) in the desert scenario. These changes also propagated northward into Sahelian Sudan, indicating a remote impact. The total moisture convergence into Sahelian Sudan was reduced by 11.5% and 21.9% for grass and desert conditions, respectively. The change in moisture convergence into the region motivated a comprehensive analysis of the moisture sources for the region. Two different modeling approaches, Lagrangian and Eulerian, were applied to identify the moisture sources and quantify their contributions to the total annual rainfall budget. The analysis shows that atmospheric flows associated with the Inter-Tropical Convergence Zone (ITCZ), e.g. from Guinea Coast, Central African and Western Sahel, brings about 40% − 50% of the annual moisture supply, while local evaporation adds about 20%. The rest of the moisture comes from the Mediterranean, Arabian Peninsula and the Southern part of the Indian Ocean. While there were differences in the details between the results from the two modeling approaches, they agree on the larger scale results. In an attempt to characterize the temporal character of the rainfall, observed and modeled daily rainfall from different regional climate models was classified into five categories: weak (0.1 −1.0), moderate (>1.0 − 10.0), moderately strong (>10.0 − 20.0), strong (>20.0 − 30.0), and very strong (>30.0) mm d−1. We found that most rain-days were in the weak to moderate rainfall categories, accounting for 60% − 75%. Days that have strong rainfall represent about 6% of the total rain-days, yet they represent about 28% − 48% of the total amount of the annual rainfall. Regional climate models fail to produce the strong rainfall, instead most of the modeled rain-days are in the moderate category and consequently the models overestimated the number of rain-days per year.
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