Hyperboloidal data and evolution

We discuss the hyperboloidal evolution problem in general relativity from a numerical perspective, and present some new results. Families of initial data which are the hyperboloidal analogue of Brill waves are constructed numerically, and a systematic search for apparent horizons is performed. Schwarzschild-Kruskal spacetime is discussed as a first application of Friedrich's general conformal field equations in spherical symmetry, and the Maxwell equations are discussed on a nontrivial background as a toy model for continuum instabilities.Comment: 11 pages, 9 figures. To appear in the Proceedings of the Spanish Relativity Meeting (ERE 2005), Oviedo, Spain, 6-10 Sept 200

Symmetries, Safety, and Self-Supervision

Collider searches face the challenge of defining a representation of high-dimensional data such that physical symmetries are manifest, the discriminating features are retained, and the choice of representation is new-physics agnostic. We introduce JetCLR to solve the mapping from low-level data to optimized observables though self-supervised contrastive learning. As an example, we construct a data representation for top and QCD jets using a permutation-invariant transformer-encoder network and visualize its symmetry properties. We compare the JetCLR representation with alternative representations using linear classifier tests and find it to work quite well

Statistical forecasts for the occurrence of precipitation outperform global models over northern Tropical Africa

Short‐term global ensemble predictions of rainfall currently have no skill over northern tropical Africa when compared to simple climatology‐based forecasts, even after sophisticated statistical postprocessing. Here, we demonstrate that 1‐day statistical forecasts for the probability of precipitation occurrence based on a simple logistic regression model have considerable potential for improvement. The new approach we present here relies on gridded rainfall estimates from the Tropical Rainfall Measuring Mission for July‐September 1998–2017 and uses rainfall amounts from the pixels that show the highest positive and negative correlations on the previous two days as input. Forecasts using this model are reliable and have a higher resolution and better skill than climatology‐based forecasts. The good performance is related to westward propagating African easterly waves and embedded mesoscale convective systems. The statistical model is outmatched by the postprocessed dynamical forecast in the dry outer tropics only, where extratropical influences are important.Plain Language Summary: Forecasts of precipitation for the next few days based on state‐of‐the‐art weather models are currently inaccurate over northern tropical Africa, even after systematic forecast errors are corrected statistically. In this paper, we show that we can use rainfall observations from the previous 2 days to improve 1‐day predictions of precipitation occurrence. Such an approach works well over this region, as rainfall systems tend to travel from the east to the west organized by flow patterns several kilometers above the ground, called African easterly waves. This statistical forecast model requires training over a longer time period (here 19 years) to establish robust relationships on which future predictions can be based. The input data employed are gridded rainfall estimates based on satellite data for the African summer monsoon in July to September. The new method outperforms all other methods currently available on a day‐to‐day basis over the region, except for the dry outer tropics, where influences from midlatitudes, which are better captured by weather models, become more important.Key Points: Raw and statistically postprocessed global ensemble forecasts fail to predict West African rainfall occurrence. A logistic regression model using observations from preceding days outperforms all other types of forecasts. The skill of the statistical model is mainly related to propagating African easterly waves and mesoscale convective systems.Deutsche ForschungsgemeinschaftKlaus Tschira Stiftun

Perennial Forages as Second Generation Bioenergy Crops

The lignocellulose in forage crops represents a second generation of biomass feedstock for conversion into energy-related end products. Some of the most extensively studied species for cellulosic feedstock production include forages such as switchgrass (Panicum virgatum L.), reed canarygrass (Phalaris arundinacea L.), and alfalfa (Medicago sativa L.). An advantage of using forages as bioenergy crops is that farmers are familiar with their management and already have the capacity to grow, harvest, store, and transport them. Forage crops offer additional flexibility in management because they can be used for biomass or forage and the land can be returned to other uses or put into crop rotation. Estimates indicate about 22.3 million ha of cropland, idle cropland, and cropland pasture will be needed for biomass production in 2030. Converting these lands to large scale cellulosic energy farming could push the traditional forage-livestock industry to ever more marginal lands. Furthermore, encouraging bioenergy production from marginal lands could directly compete with forage-livestock production

Grassland Resistance and Resilience after Drought Depends on Management Intensity and Species Richness

The degree to which biodiversity may promote the stability of grasslands in the light of climatic variability, such as prolonged summer drought, has attracted considerable interest. Studies so far yielded inconsistent results and in addition, the effect of different grassland management practices on their response to drought remains an open question. We experimentally combined the manipulation of prolonged summer drought (sheltered vs. unsheltered sites), plant species loss (6 levels of 60 down to 1 species) and management intensity (4 levels varying in mowing frequency and amount of fertilizer application). Stability was measured as resistance and resilience of aboveground biomass production in grasslands against decreased summer precipitation, where resistance is the difference between drought treatments directly after drought induction and resilience is the difference between drought treatments in spring of the following year. We hypothesized that (i) management intensification amplifies biomass decrease under drought, (ii) resistance decreases with increasing species richness and with management intensification and (iii) resilience increases with increasing species richness and with management intensification

Acute hepatitis C: Current status and remaining challenges

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Biodiversity increases and decreases ecosystem stability

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Plant diversity effects on grassland productivity are robust to both nutrient enrichment and drought

Global change drivers are rapidly altering resource availability and biodiversity. While there is consensus that greater biodiversity increases the functioning of ecosystems, the extent to which biodiversity buffers ecosystem productivity in response to changes in resource availability remains unclear. We use data from 16 grassland experiments across North America and Europe that manipulated plant species richness and one of two essential resources—soil nutrients or water—to assess the direction and strength of the interaction between plant diversity and resource alteration on above-ground productivity and net biodiversity, complementarity, and selection effects. Despite strong increases in productivity with nutrient addition and decreases in productivity with drought, we found that resource alterations did not alter biodiversity–ecosystem functioning relationships. Our results suggest that these relationships are largely determined by increases in complementarity effects along plant species richness gradients. Although nutrient addition reduced complementarity effects at high diversity, this appears to be due to high biomass in monocultures under nutrient enrichment. Our results indicate that diversity and the complementarity of species are important regulators of grassland ecosystem productivity, regardless of changes in other drivers of ecosystem function