Variabilité des précipitations au sahel Central et Recherche du forcage climatique par analyse du signal : la station de Maïne-Soroa (SE Niger) entre 1950 et 2005. Rainfall variability in the Central Sahel and climate forcing by signal analysis: Maïné-Soroa station (SE Niger) over the period 1950-2005

International audienceUne régression polynomiale non-paramétrique (méthode LOESS) appliquée aux précipitations annuelles de Maïné-Soroa (SE Niger) montre trois périodes : humide (1950-1967), aride (1968-1993), semi-aride (1994-2005). L'utilisation de la transformée en ondelettes continues permet de séparer la variabilité interne (haute fréquence) et la variabilité forcée (basse fréquence). Nous avons pu mettre en évidence sept modes de fréquence localisés dans le temps : deux modes intra-saisonniers (4-9jrs, 16-20jrs), deux modes saisonniers (6 mois, 1an), deux modes pluriannuels (2-4ans et 5-8ans) et un mode quasi-décennal (12-18ans). Lors du régime humide, on retrouve une forte variance des modes saisonniers liés à la ZCIT et des modes pluriannuels se succédant dans le temps (5-8ans puis 2-4ans) en liaison avec les températures de l'Atlantique Tropical Nord (TNA) puis avec l'Anticyclone des Açores. Ces modes basses fréquences sont synchrones avec une activité convective mature (mode 4-9jrs) et l'apparition d'une perturbation (mode 16-20jrs) lors de la transition entre la phase océanique et la phase continentale de la mousson. Au contraire, lors des années arides on retrouve le mode quasi-décennal, en lien avec les températures de l'Atlantique Tropical Sud (TSA), forçant une activité convective peu développée et perturbée au coeur de la phase continentale. A non-parametric polynomial regression applied to the Maine-Soroa annual rainfall timeseries reveals three periods: wet (1950-1967), arid (1968-1993) and semi-arid (1994-2005). Continuous Wavelet Transform allows crossing internal variability (high frequency) and forcing variability (low frequency). We could reveal seven frequency modes highly localized in time: two intraseasonal modes (4-9 days, 16-20 days), two seasonal modes (6mo, 1yr), two interannuals modes (2- 4yrs, 5-8yrs) and one quasidecadal mode (12-18yrs). During wet period, we notice a strong variance across seasonal modes in relation to ITCZ and the two interannual modes succeeding in time (5-8yrs then 2-4yrs) in connection with the Tropical North Atlantic temperatures (TNA) then Azores high. At the same time, we notice great convective activity (4-9days) and the oceanic/continental transition phase disturbation (16-20days). During the arid period, we notice the quasidecadal mode in relation with the Tropical South Atlantic temperatures (TSA), forcing a weak convective activity and disturbed in the medium of the continental phase

Spatiotemporal and cross-scale interactions in hydroclimate variability:a case-study in France

International audienceUnderstanding how water resources vary in response to climate at different temporal and spatial scales is crucial to inform long-term management. Climate change impacts and induced trends may indeed be substantially modulated by low-frequency (multi-year) variations, whose strength varies in time and space, with large consequences for risk forecasting systems. In this study, we present a spatial classification of precipitation, temperature, and discharge variability in France, based on a fuzzy clustering and wavelet spectra of 152 near-natural watersheds between 1958 and 2008. We also explore phase–phase and phase–amplitude causal interactions between timescales of each homogeneous region. A total of three significant timescales of variability are found in precipitation, temperature, and discharge, i.e., 1, 2–4, and 5–8 years. The magnitude of these timescales of variability is, however, not constant over the different regions. For instance, southern regions are markedly different from other regions, with much lower (5–8 years) variability and much larger (2–4 years) variability. Several temporal changes in precipitation, temperature, and discharge variability are identified during the 1980s and 1990s. Notably, in the southern regions of France, we note a decrease in annual temperature variability in the mid 1990s. Investigating cross-scale interactions, our study reveals causal and bi-directional relationships between higher- and lower-frequency variability, which may feature interactions within the coupled land–ocean–atmosphere systems. Interestingly, however, even though time frequency patterns (occurrence and timing of timescales of variability) were similar between regions, cross-scale interactions are far much complex, differ between regions, and are not systematically transferred from climate (precipitation and temperature) to hydrological variability (discharge). Phase–amplitude interactions are indeed absent in discharge variability, although significant phase–amplitude interactions are found in precipitation and temperature. This suggests that watershed characteristics cancel the negative feedback systems found in precipitation and temperature. This study allows for a multi-timescale representation of hydroclimate variability in France and provides unique insight into the complex nonlinear dynamics of this variability and its predictability

Training deep learning models with a multi-station approach and static aquifer attributes for groundwater level simulation: what’s the best way to leverage regionalised information?

In this study, we used deep learning models with recurrent structure neural networks to simulate large-scale groundwater level (GWL) fluctuations in northern France. We developed a multi-station collective training for GWL simulations, using both “dynamic” variables (i.e. climatic) and static aquifer characteristics. This large-scale approach offers the possibility of incorporating dynamic and static features to cover more reservoir heterogeneities in the study area. Further, we investigated the performance of relevant feature extraction techniques such as clustering and wavelet transform decomposition, intending to simplify network learning using regionalised information. Several modelling performance tests were conducted. Models specifically trained on different types of GWL, clustered based on the spectral properties of the data, performed significantly better than models trained on the whole dataset. Clustering-based modelling reduces complexity in the training data and targets relevant information more efficiently. Applying multi-station models without prior clustering can lead the models to learn the dominant station behavior preferentially, ignoring unique local variations. In this respect, wavelet pre-processing was found to partially compensate clustering, bringing out common temporal and spectral characteristics shared by all available time series even when these characteristics are “hidden” because of too small amplitude. When employed along with prior clustering, thanks to its capability of capturing essential features across all time scales (high and low), wavelet decomposition used as a pre-processing technique provided significant improvement in model performance, particularly for GWLs dominated by low-frequency variations. This study advances our understanding of GWL simulation using deep learning, highlighting the importance of different model training approaches, the potential of wavelet preprocessing, and the value of incorporating static attributes

Moving Beyond the catchment scale: value and opportunities in large-scale hydrology to understand our changing world

International audienc

Climate variability in the subarctic area for the last 2 millennia

To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A similar to 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas similar to 20-30- and similar to 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.Peer reviewe

Impact of the North Sea–Caspian pattern on meteorological drought and vegetation response over diverging environmental systems in western Eurasia

Emerging drought stress on vegetation over western Eurasia is linked to varying teleconnection patterns. The North Sea–Caspian Pattern (NCP) is a relatively less studied Eurasian teleconnection pattern, which has a role on drought conditions and the consequence of changing conditions on vegetation. Between 1981 and 2015, we found that the Standardized Precipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) have different trend patterns over various parts of western Eurasia. Specifically, the vegetation greenness is linked with wetter conditions over Scandinavia, and vegetation cover decreases over a drying central Asia. However, western Russia and Franceare paradoxically becoming greener under drier conditions. Using the Budyko framework, such paradoxical patterns are found in energy-limited environmental systems, where vegetation growth is primarily promoted by warmer temperatures. While most studies focused on the impacts of the North Atlantic Oscillation (NAO), we test whether the NCP explains better the variability of meteorological drought and vegetation response over western Eurasia. We hypothesised that the positive phases of the NCP are correlated to high pressure anomalies over the North Sea, which can be associated with weakening onshore moisture advection, leading to warmer and dryness conditions. These conditions are driving vegetation greening, as western Eurasia is mainly energy limited. However, we show that as the climate is warming along with the teleconnection impacts, the future ecosystem over western Eurasia will be transferred from energy-limited to water-limited systems. This suggests that the observed vegetation greening over past three decades is unlikely to sustain in the future

SNO KARST: a French network of observatories for the multidisciplinary study of critical zone processes in karst watersheds and aquifers

Karst aquifers and watersheds represent a major source of drinking water around the world. They are also known as complex and often highly vulnerable hydrosystems due to strong surface groundwater interactions. Improving the understanding of karst functioning is thus a major issue for an efficient management of karst groundwater resources. A comprehensive understanding of the various processes can be achieved only by studying karst systems over a wide range of spatio-temporal scales under different geological, geomorphological, climatic and soil cover settings. The objective of the French Karst National Observatory Service (SNO Karst) is to supply the international scientific community with appropriate data and tools, with the ambition of i) facilitating the collection of long-term observations of hydro-geo-chemical variables in karst, and ii) promoting knowledge-sharing and developing cross-disciplinary research on karst. The present paper provides an overview of the monitoring sites and of collective achievements such as the KarstMod modular modelling platform and the PaPRIKa toolbox. It also presents the research questions addressed within the framework of SNO Karst, along with major research results regarding i) the hydrological response of karst to climate and anthropogenic changes, ii) the influence of karst on geochemical balance of watersheds in the critical zone, and iii) the relationships between the structure and hydrological functioning of karst aquifers and watersheds

High-resolution sea surface reconstructions off Cape Hatteras over the last 10 ka

International audienceThis study presents high-resolution foraminiferal-based sea surface temperature, sea surface salinity and upper water column stratification reconstructions off Cape Hatteras, a region sensitive to atmospheric and thermohaline circulation changes associated with the Gulf Stream. We focus on the last 10,000 years (10 ka) to study the surface hydrology changes under our current climate conditions and discuss the centennial to millennial time scale variability. We observed opposite evolutions between the conditions off Cape Hatteras and those south of Iceland, known today for the North Atlantic Oscillation pattern. We interpret the temperature and salinity changes in both regions as co-variation of activities of the subtropical and subpolar gyres. Around 8.3 ka and 5.2-3.5 ka, positive salinity anomalies are reconstructed off Cape Hatteras. We demonstrate, for the 5.2-3.5 ka period, that the salinity increase was caused by the cessation of the low salinity surface flow coming from the north. A northward displacement of the Gulf Stream, blocking the southbound low-salinity flow, concomitant to a reduced Meridional Overturning Circulation is the most likely scenario. Finally, wavelet transform analysis revealed a 1000-year period pacing the δ18O signal over the early Holocene. This 1000-year frequency band is significantly coherent with the 1000-year frequency band of Total Solar Irradiance (TSI) between 9.5 ka and 7 ka and both signals are in phase over the rest of the studied period

Arctic hydroclimate variability during the last 2000 years: current understanding and research challenges

Reanalysis data show an increasing trend in Arctic precipitation over the 20th century, but changes are not homogenous across seasons or space. The observed hydroclimate changes are expected to continue and possibly accelerate in the coming century, not only affecting pan-Arctic natural ecosystems and human activities, but also lower latitudes through the atmospheric and ocean circulations. However, a lack of spatiotemporal observational data makes reliable quantification of Arctic hydroclimate change difficult, especially in a long-term context. To understand Arctic hydroclimate and its variability prior to the instrumental record, climate proxy records are needed. The purpose of this review is to summarise the current understanding of Arctic hydroclimate during the past 2000 years. First, the paper reviews the main natural archives and proxies used to infer past hydroclimate variations in this remote region and outlines the difficulty of disentangling the moisture from the temperature signal in these records. Second, a comparison of two sets of hydroclimate records covering the Common Era from two data-rich regions, North America and Fennoscandia, reveals inter- and intra-regional differences. Third, building on earlier work, this paper shows the potential for providing a high-resolution hydroclimate reconstruction for the Arctic and a comparison with last-millennium simulations from fully coupled climate models. In general, hydroclimate proxies and simulations indicate that the Medieval Climate Anomaly tends to have been wetter than the Little Ice Age (LIA), but there are large regional differences. However, the regional coverage of the proxy data is inadequate, with distinct data gaps in most of Eurasia and parts of North America, making robust assessments for the whole Arctic impossible at present. To fully assess pan-Arctic hydroclimate variability for the last 2 millennia, additional proxy records are required.</p