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The cosmogenic radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Combining 7Be and 10Be measurements with an atmospheric transport model can not only improve our understanding of the radionuclide transport and deposition processes but also provide an evaluation of the transport process in the model. To simulate these aerosol tracers, it is critical to evaluate the in

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

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

A prerequisite to applying 10Be in natural archives for solar and geomagnetic reconstructions is to know how 10Be deposition reflects atmospheric production changes. However, this relationship remains debated. To address this, we use two state-of-the-art global models GEOS-Chem and ECHAM6.3-HAM2.3 with the latest beryllium production model. During solar modulation, both models suggest that 10Be de

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

Cosmogenic radionuclides (e.g., 10Be) from ice cores are a powerful tool for solar reconstructions back in time. However, superimposed on the solar signal, other factors like weather/climate and volcanic influences on 10Be can complicate the interpretation of 10Be data. A comprehensive study of 10Be records over the recent period, when atmospheric 10Be production and meteorological conditions are

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

The upcoming Artificial Intelligence (AI) Act is the European Union's attempt to regulate high-risk AI systems and foundation models. We give an up-to-date overview of the act's key requirements, explain how the high-risk classification works, and highlight what matters for its operationalization.

This work presents an assessment of the precipitation deficit in the São Francisco River Basin (SFRB) based on temporal, seasonal and regional analyses of two decades of precipitation data products derived from satellite missions launched since 1997. The temporal analyses were performed by means of three 3-month SPI time series, consisting of 250 values each derived from TRMM, CHIRPS and PERSIANN-

This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sides

We consider a class of weak feedback polynomials for LFSRs in the nonlinear combiner. When feedback taps are located in small groups, a distinguishing attack can sometimes be improved considerably, compared to the common attack that uses low weight multiples. This class of weak polynomials was introduced in 2004 and the main property of the attack is that the noise variables are represented as vec

Many computing systems are constrained by power budgets. While they could temporarily draw more power, doing so creates unsustainable temperatures and unwanted electricity consumption. Developing systems that operate within power budgets is a constrained optimization problem: configuring the components within the system to maximize performance while maintaining sustainable power consumption. This