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Accurately representing and predicting hydrological processes in terrestrial ecosystems is crucial for understanding the impacts of global environmental change, particularly climate change. This doctoral thesis aims to advance the understanding of vegetation-hydrology interactions and provides new modelling approaches to enhance hydrological prediction abilities. The thesis is grounded in the eval
This study investigates seasonal changes in near-surface wind speeds in the Arctic using the regional climate model (RCM) simulations with RCA4 driven by four global climate models (GCMs) CMIP5 under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. In addition, the RCM RCA-GUESS (RCA4 with interactive vegetation dynamics) is used to investigate the role of biogeophysical feedback
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-
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
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
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
Under global warming, flooding has become one of the most destructive natural disasters along the China–Pakistan Economic Corridor (CPEC), which significantly jeopardizes the construction and ongoing stability of the CPEC. The assessment of regional flood potential is, therefore, crucial for effective flood prevention and relief measures. In light of this, our study applied MIKE 11 hydrodynamic mo
Drawing on collective experience from ten collaborative research projects focused on the Global South, we identify three major challenges that impede the translation of research on sustainability and resilience into better-informed choices by individuals and policy-makers that in turn can support transformation to a sustainable future. The three challenges comprise: (i) converting knowledge produc
The response of clouds to the changes in climate is uncertain, and the representation of the cloud-climate feedback is a key challenge in the global circulation models (GCM) for future climate projections. Factors contributing to this uncertainty include processes that involve particles of various sizes and phases, as well as the interactions between these particles and the surrounding atmosphere.
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
Build a linear accelerator to demonstrate spallation – the source of high-energy neutrons used by the new European Spallation Source being built in Sweden.In this activity, we build a model of a linear accelerator (linac) called a Gauss cannon. It uses magnetic attraction and momentum transfer to accelerate a series of steel balls, representing protons. At the end of the track, one ‘proton’ will c
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
The rainfall product derived from the SM2RAIN (Soil Moisture to Rain) algorithm has been widely used. However, there is still a large uncertainty partly due to the soil moisture input and parameters estimation of the SM2RAIN algorithm, which limits the application of the model in alpine regions. Here, the SM2RAIN-BayesOpt algorithm was developed by integrating the SM2RAIN algorithm and Bayesian op
The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice-water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Diff
Cold-season methane (CH4) emissions may be poorly constrained in wetland models. We examined cold-season CH4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.
Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological r
