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This chapter describes the Back to the Future (BTF) approach with illustrations of different data sets and their conclusions and stimulates the growth of such studies. The BTF Project included several studies that "discovered" old data sets, digitized them, carried out analyses and made data and analyses available in publications. An important aspect of the BTF approach is that the evidence of cha

We introduce a scalable observer architecture to estimate the states of a discrete-time linear-time-invariant (LTI) system whose sensors can be manipulated by an attacker. Given the maximum number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel multi-modal Luenberger (MML) observer based on efficient Satisfiability

Time synchronization is crucial for wireless sensor networks (WSNs), where operations often rely on time ordering of events. WSNs are deployed in different scenarios, and therefore their timing requirements are often related to the peculiar characteristics of the specific environment they have to act in. Synchronization is anyway always an issue: transactional applications need monotonicity of the

The “wooded-meadows system” is a multifunctional use of vegetation resources widespread in Europesince the Neolithic, and well documented in the Ligurian Apennines (NW Italy) between the MiddleAges and the first half of the 19th century. The management of wooded-meadows included: collectionof fallen and dead branches in spring, later used for fuel; mowing and grazing in summer; collection ofsecond

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-component

Over the past decades, global warming has led to a lengthening of the time window during which temperatures remain favorable for carbon assimilation and tree growth, resulting in a lengthening of the green season. The extent to which forest green seasons have tracked the lengthening of this favorable period under climate warming, however, has not been quantified to date. Here, we used remote sensi

The investigation of triggers causing the onset and intensification of Northern Hemisphere Glaciation (NHG) during the late Pliocene is essential for understanding the global climate system, with important implications for projecting future climate changes. Despite their critical roles in the global climate system, influences of land-ocean interactions on high-latitude ice sheets remain largely un

Variations in solar activity have been proposed to play an important role in recent and past climate change. To study this link on longer timescales, it is essential to know how the Sun has varied over the past millennia. Direct observations of solar variability based on sunspot numbers are limited to the past 400 years, and beyond this we rely on records of cosmogenic radionuclides, such as 14C a

Text i utställningskatalog till utställningen: AS IF HERE – Samaneh Reyhani & Marcus Matt på Trelleborgs museer 8 June 2024- 1 September 2024.

The remote forcing from land surface changes in the Sahara is hypothesized to play a pivotal role in modulating the intensity of the East Asian summer monsoon (EASM) through ocean-atmospheric teleconnections. This modulation has far-reaching consequences, particularly in facilitating societal shifts documented in northern China. Here, we present a well-dated lake-level record from the Daihai Lake

Cardiometabolic disease is a major threat to global health. Precision medicine has great potential to help to reduce the burden of this common and complex disease cluster, and to enhance contemporary evidence-based medicine. Its key pillars are diagnostics; prediction (of the primary disease); prevention (of the primary disease); prognosis (prediction of complications of the primary disease); trea

Drought is a natural disaster that occurs globally and can damage the environment, disrupt agricultural production and cause large economic losses. The accurate prediction of drought can effectively reduce the impacts of droughts. Deep learning methods have shown promise in drought prediction, with convolutional neural networks (CNNs) being particularly effective in handling spatial information. I

Global warming has largely advanced spring vegetation phenology, which has subsequently affected terrestrial carbon and water cycles. However, further shifts in vegetation phenology under future climate change remain unclear. We estimated the start of the growing season (SOS) by applying multiple extraction methods based on the NDVI3g data set, and then parameterized and evaluated 11 spring vegeta

The Sun’s energy is effectively limitless. While resources such as coal or gas are finite, if you are able to capture and use solar power it doesn’t prevent anyone else from also using as much sunshine as they need.Except that isn’t quite the full story. Beyond a certain size, solar farms become large enough to affect the weather around them and ultimately the climate as a whole. In our new resear

An Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi-global land by combining three independent precipitation products. The performance of the ETCC-merged product was then evaluated against three refere

Because of varied topography and landscape heterogeneity，Tianshan Mountain has extremely complex hydrological processes. Considering that the climate change poses a great threat to the water security，it’s necessary to simulate the change of water elements quantitatively and systematically along with elevation. In this study，we applied the modified FLEXG-Δh model to four classic river basins in Tia

We study input and state constrained inverse optimal control problems starting from a stabilizing controller with a control Lyapunov function, where the goal is to make the controller an explicit solution of the resulting constrained optimal control problem. For an appropriate cost design and initial states for which a sublevel set of the Lyapunov function is contained in the state constraint set

The three leading modes of the North Atlantic atmospheric circulation explain about 70% of the winter climate variability. Although climate models generally can capture these modes, biases may induce large uncertainties in regional climate predictions. Here, we evaluate the leading winter modes simulated by CMIP5-PMIP3 and CMIP6-PMIP4 models from the last millennium to future scenarios in comparis