CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies

Current changes in the world's climate increasingly impact a wide variety of sectors globally, from agriculture and ecosystems to water and energy supply or human health. Many impacts of climate on these sectors happen at high spatio-temporal resolutions that are not covered by current global climate datasets. Here we present CHELSA-W5E5 (https://doi.org/10.48364/ISIMIP.836809.3, Karger et al., 2022): a climate forcing dataset at daily temporal resolution and 30 arcsec spatial resolution for air temperatures, precipitation rates, and downwelling shortwave solar radiation. This dataset is a spatially downscaled version of the 0.5∘ W5E5 dataset using the CHELSA V2 topographic downscaling algorithm. We show that the downscaling generally increases the accuracy of climate data by decreasing the bias and increasing the correlation with measurements from meteorological stations. Bias reductions are largest in topographically complex terrain. Limitations arise for minimum near-surface air temperatures in regions that are prone to cold-air pooling or at the upper extreme end of surface downwelling shortwave radiation. We further show that our topographically downscaled climate data compare well with the results of dynamical downscaling using the Weather Research and Forecasting (WRF) regional climate model, as time series from both sources are similarly well correlated to station observations. This is remarkable given the lower computational cost of the CHELSA V2 algorithm compared to WRF and similar models. Overall, we conclude that the downscaling can provide higher-resolution climate data with increased accuracy. Hence, the dataset will be of value for a wide range of climate change impact studies both at global level and for applications that cover more than one region and benefit from using a consistent dataset across these regions

Greener, Safer and Better Performing Aqueous Binder for Positive Electrode Manufacturing of Sodium Ion Batteries

P2-type cobalt-free MnNi-based layered oxides are promising cathode materials for sodium-ion batteries (SIBs) due to their high reversible capacity and well chemical stability. However, the phase transformations during repeated (dis)charge steps lead to rapid capacity decay and deteriorated Na+ diffusion kinetics. Moreover, the electrode manufacturing based on polyvinylidene difluoride (PVDF) binder system has been reported with severely defluorination issue as well as the energy intensive and expensive process due to the use of toxic and volatile N-methyl-2-pyrrolidone (NMP) solvent. It calls for designing a sustainable, better performing, and cost-effective binder for positive electrode manufacturing. In this work, we investigated inorganic sodium metasilicate (SMS) as a viable binder in conjunction with P2-Na0.67Mn0.55Ni0.25Fe0.1Ti0.1O2 (NMNFT) cathode material for SIBs. The NMNFT-SMS electrode delivered a superior electrochemical performance compared to carboxy methylcellulose (CMC) and PVDF based electrodes with a reversible capacity of ~161 mAh/g and retaining ~83 % after 200 cycles. Lower cell impedance and faster Na+ diffusion was also observed in this binder system. Meanwhile, with the assistance of TEM technique, SMS is suggested to form a uniform and stable nanoscale layer over the cathode particle surface, protecting the particle from exfoliation/cracking due to electrolyte attack. It effectively maintained the electrode connectivity and suppressed early phase transitions during cycling as confirmed by operando XRD study. With these findings, SMS binder can be proposed as a powerful multifunctional binder to enable positive electrode manufacturing of SIBs and to overall reduce battery manufacturing costs

Multi-budgeted Directed Cuts

In this paper, we study multi-budgeted variants of the classic minimum cut problem and graph separation problems that turned out to be important in parameterized complexity: SKEW MULTICUT and DIRECTED FEEDBACK ARC SET. In our generalization, we assign colors 1, 2,..., l to some edges and give separate budgets k(1), k(2),..., k(l) for colors 1, 2,..., l. For every color i is an element of {1,..., l}, let E-i be the set of edges of color i. The solution C for the multi-budgeted variant of a graph separation problem not only needs to satisfy the usual separation requirements (i.e., be a cut, a skew multicut, or a directed feedback arc set, respectively), but also needs to satisfy that vertical bar C boolean AND E-i vertical bar <= k(i) for every i is an element of {1,..., l}. Contrary to the classic minimum cut problem, the multi-budgeted variant turns out to be NP-hard even for l = 2. We propose FPT algorithms parameterized by k = k(1) + ... + k(l) for all three problems. To this end, we develop a branching procedure for the multi-budgeted minimum cut problem that measures the progress of the algorithm not by reducing k as usual, by but elevating the capacity of some edges and thus increasing the size of maximum source-to-sink flow. Using the fact that a similar strategy is used to enumerate all important separators of a given size, we merge this process with the flow-guided branching and show an FPT bound on the number of (appropriately defined) important multi-budgeted separators. This allows us to extend our algorithm to the Skew Multicut and Directed Feedback Arc Set problems. Furthermore, we show connections of the multi-budgeted variants with weighted variants of the directed cut problems and the Chain l-SATproblem, whose parameterized complexity remains an open problem. We show that these problems admit a bounded-in-parameter number of "maximally pushed" solutions (in a similar spirit as important separators are maximally pushed), giving somewhat weak evidence towards their tractability

Vegetation type is an important predictor of the arctic summer land surface energy budget

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-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Phenotypic effects of mutations observed in the neuraminidase of human origin H5N1 influenza A viruses

Global spread and regional endemicity of H5Nx Goose/Guangdong avian influenza viruses (AIV) pose a continuous threat for poultry production and zoonotic, potentially pre-pandemic, transmission to humans. Little is known about the role of mutations in the viral neuraminidase (NA) that accompanied bird-to-human transmission to support AIV infection of mammals. Here, after detailed analysis of the NA sequence of human H5N1 viruses, we studied the role of A46D, L204M, S319F and S430G mutations in virus fitness in vitro and in vivo. Although H5N1 AIV carrying avian- or human-like NAs had similar replication efficiency in avian cells, human-like NA enhanced virus replication in human airway epithelia. The L204M substitution consistently reduced NA activity of H5N1 and nine other influenza viruses carrying NA of groups 1 and 2, indicating a universal effect. Compared to the avian ancestor, human-like H5N1 virus has less NA incorporated in the virion, reduced levels of viral NA RNA replication and NA expression. We also demonstrate increased accumulation of NA at the plasma membrane, reduced virus release and enhanced cell-to-cell spread. Furthermore, NA mutations increased virus binding to human-type receptors. While not affecting high virulence of H5N1 in chickens, the studied NA mutations modulated virulence and replication of H5N1 AIV in mice and to a lesser extent in ferrets. Together, mutations in the NA of human H5N1 viruses play different roles in infection of mammals without affecting virulence or transmission in chickens. These results are important to understand the genetic determinants for replication of AIV in mammals and should assist in the prediction of AIV with zoonotic potential

Vegetation type is an important predictor of the arctic summer land surface energy budget

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-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

Scenario set-up and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Model Intercomparison Project (ISIMIP3a)

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, www.isimip.org) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6