Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes

The frequency of climate extremes will change in response to shifts in both mean climate and climate variability. These individual contributions, and thus the fundamental mechanisms behind changes in climate extremes, remain largely unknown. Here we apply the probability ratio concept in large-ensemble climate simulations to attribute changes in extreme events to either changes in mean climate or climate variability. We show that increased occurrence of monthly high-temperature events is governed by a warming mean climate. In contrast, future changes in monthly heavy-precipitation events depend to a considerable degree on trends in climate variability. Spatial variations are substantial however, highlighting the relevance of regional processes. The contributions of mean and variability to the probability ratio are largely independent of event threshold, magnitude of warming and climate model. Hence projections of temperature extremes are more robust than those of precipitation extremes, since the mean climate is better understood than climate variability

Tunneling to Holographic Traversable Wormholes

We study nonperturbative effects of quantum gravity in a system consisting of a coupled pair of holographic CFTs. The AdS$_4$/CFT$_3$ system has three possible ground states: two copies of empty AdS, a pair of extremal AdS black holes, and an eternal AdS traversable wormhole. We give a recipe for calculating transition rates via gravitational instantons and test it by calculating the emission rate of radiation shells from a black hole. We calculate the nucleation rate of a traversable wormhole between a pair of AdS-RN black holes in the canonical and microcanonical ensembles. Our results give predictions of nonpertubative quantum gravity that can be tested in a holographic simulation.Comment: 65 pages, 2 figure

Arctic tern flyways and the changing Atlantic Ocean wind patterns

Migratory bird trajectories are the result of their own speed and direction in combination with wind speed and direction. Several studies have focused on the interplay between bird migration and general wind patterns, however, the majority of them did not take into account climate change and used a small number of individuals. By integrating tracking data from two populations of Arctic terns (n = 72) with ERA5 and Earth System Model (ESM) wind data, we were able to study the current conditions and the potential effects of climate change on them.The Svalbard birds experienced wind support values around 3 m/s with a relatively low variability, while the Dutch population experienced almost no wind support with a greater variability. Svalbard terns exhibited better adjustment of their flyways to daily and annually varying wind conditions, and responded to crosswinds by drifting over extended periods/regions (median Drift Ratio ± standard deviation: 0.51 ± 0.18) while the Dutch population mostly compensated (0 ± 0.31). We suggest that the Svalbard birds will be able to adapt their flyways to future Atlantic Ocean wind pattern changes, while we are uncertain whether the Dutch population can keep compensating for future changes or not.We examine the robustness of our results by using a selection of ESMs and by including metrics for several uncertainty sources (ESMs, wind variability, tracking method etc.). This study highlights the importance of wind as a flyway-shaping factor and points out the possibility for different responses to wind by different populations of the same species, in different Ocean regions and seasons

The Stranger Things of Symmetric Product Orbifold CFTs

Symmetric product orbifold theories are valuable due to their universal features at large $N$. Here we will demonstrate that they have features that are not as pervasive: we provide evidence of strange behaviour under deformations within their moduli space. To this end, we consider the symmetric product orbifold of tensor products of $\mathcal{N}=2$ super-Virasoro minimal models, and classify them according to two criteria. The first criterion is the existence of a single-trace twisted exactly marginal operator that triggers the deformation. The second criterion is a sparseness condition on the growth of light states in the elliptic genera. In this context we encounter a strange variety: theories that obey the first criterion but the second criterion falls into a Hagedorn-like growth. We explain why this may be counter-intuitive and discuss how it might be accounted for in conformal perturbation theory. We also find a new infinite class of theories that obey both criteria, which are necessary conditions for each moduli space to contain a supergravity point.Comment: 34 pages, 3 figure

The impact of Arctic warming on increased rainfall

Abstract The Arctic region is warming two to three times faster than the global mean, intensifying the hydrological cycle in the high north. Both enhanced regional evaporation and poleward moisture transport contribute to a 50–60% increase in Arctic precipitation over the 21st century. The additional precipitation is diagnosed to fall primarily as rain, but the physical and dynamical constraints governing the transition to a rain-dominated Arctic are unknown. Here we use actual precipitation, snowfall, rainfall output of 37 global climate models in standardised 21st-century simulations to demonstrate that, on average, the main contributor to additional Arctic (70–90°N) rainfall is local warming (~70%), whereas non-local (thermo)dynamical processes associated with precipitation changes contribute only 30%. Surprisingly, the effect of local warming peaks in the frigid high Arctic, where modest summer temperature changes exert a much larger effect on rainfall changes than strong wintertime warming. This counterintuitive seasonality exhibits steep geographical gradients, however, governed by non-linear changes in the temperature-dependent snowfall fraction, thereby obscuring regional-scale attribution of enhanced Arctic rainfall to climate warming. Detailed knowledge of the underlying causes behind Arctic snow/rainfall changes will contribute to more accurate assessments of the (possibly irreversible) impacts on hydrology/run-off, permafrost thawing, ecosystems, sea ice retreat, and glacier melt

Big Changes in How Students are Tested

For the past decade, school accountability has relied on tests for which the essential format has remained unchanged. Educators are familiar with the yearly testing routine: schools are given curriculum frameworks, teachers use the frameworks to guide instruction, students take one big test at year’s end which relies heavily upon multiple-choice bubble items, and then school leaders wait anxiously to find out whether enough of their students scored at or above proficiency to meet state standards. All this will change with the adoption of Common Core standards. Testing and accountability aren’t going away. Instead, they are developing and expanding in ways that aim to address many of the present shortcomings of state testing routines. Most importantly, these new tests will be computer-based. As such, they will potentially shorten testing time, increase tests’ precision, and provide immediate feedback to students and teachers

Arctic decadal variability in a warming world

Natural decadal variability of surface air temperature might obscure Arctic temperature trends induced by anthropogenic forcing. It is therefore imperative to know how Arctic decadal variability (ADV) will change as the climate warms. In this study, we evaluate ADV characteristics in three equilibrium climates with present-day, double, and quadrupled atmospheric CO2 forcing. The dominant region of variability, which is located over the Barents and Greenland Sea at present, shifts to the central Arctic and Siberian regions as the climate warms. The maximum variability in sea ice cover and surface air temperature occurs in the CO2 doubling climate when sea ice becomes more vulnerable to melt over vast stretches of the Arctic. Furthermore, the links between dominant atmospheric circulation modes and Arctic surface climate characteristics vary strongly with climate change. For instance, a positive Arctic Oscillation index is associated with a colder Arctic in warmer climates, instead of a warmer Arctic at present. Such changing relationships are partly related to the retreat of sea ice because altered wind patterns influence the sea ice distribution and hence the associated local surface fluxes. The atmospheric pressure distributions governing ADV and the associated large-scale dynamics also change with climate warming. The changing character of the ADV shows that it is vital to consider (changes in) ADV when addressing Arctic warming in climate model projections

Seasonal and regional contrasts of future trends in interannual arctic climate variability

Future changes in interannual variability (IAV) of Arctic climate indicators such as sea ice and precipitation are still fairly uncertain. Alongside global warming-induced changes in means, a thorough understanding of IAV is needed to more accurately predict sea ice variability, distinguish trends and natural variability, as well as to reduce uncertainty around the likelihood of extreme events. In this study we rank and select CMIP6 models based on their ability to replicate observations, and quantify simulated IAV trends (1981–2100) of Arctic surface air temperature, evaporation, precipitation, and sea ice concentration under continued global warming. We argue that calculating IAV on grid points before area-averaging allows for a more realistic picture of Arctic-wide changes. Large model ensembles suggest that on shorter time scales (30 years), IAV of all variables is strongly dominated by natural variability (e.g. 93% for sea ice area in March). Long-term trends of IAV are more robust, and reveal strong seasonal and regional differences in their magnitude or even sign. For example, IAV of surface temperature increases in the Central Arctic, but decreases in lower latitudes. Arctic precipitation variability increases more in summer than in winter; especially over land, where in the future it will dominantly fall as rain. Our results emphasize the need to address such seasonal and regional differences when portraying future trends of Arctic climate variability.</p

Conformal field theories dual to quantum gravity with strongly coupled matter

A holographic conformal field theory is dual to semi-classical general relativity in Anti-de Sitter space coupled to matter fields. If the CFT factorizes in the large-$N$ limit, then all couplings in its dual are suppressed by the Planck scale, making the matter fields weakly interacting. We propose a mechanism to produce CFTs whose dual matter fields couple weakly to gravity, but interact strongly with each other. We achieve this by turning on exactly marginal multi-trace deformations, and quantify the effect using conformal perturbation theory.Comment: 5 pages, v3: minor changes, version as published in Phys. Rev.

The KNMI Large Ensemble Time Slice (KNMI-LENTIS)

Large-ensemble modelling has become an increasingly popular approach to studying the mean climate and the climate system's internal variability in response to external forcing. Here we present the Royal Netherlands Meteorological Institute (KNMI) Large Ensemble Time Slice (KNMI-LENTIS): a new large ensemble produced with the re-tuned version of the global climate model EC-Earth3. The ensemble consists of two distinct time slices of 10 years each: a present-day time slice and a +2ĝ€¯K warmer future time slice relative to the present day. The initial conditions for the ensemble members are generated with a combination of micro- and macro-perturbations. The 10-year length of a single time slice is assumed to be too short to show a significant forced climate change signal, and the ensemble size of 1600 years (160ĝ€¯×ĝ€¯10 years) is assumed to be sufficient to sample the full distribution of climate variability. The time slice approach makes it possible to study extreme events on sub-daily timescales as well as events that span multiple years such as multi-year droughts and preconditioned compound events. KNMI-LENTIS is therefore uniquely suited to study internal variability and extreme events both at a given climate state and resulting from forced changes due to external radiative forcing. A unique feature of this ensemble is the high temporal output frequency of the surface water balance and surface energy balance variables, which are stored in 3-hourly intervals, allowing for detailed studies into extreme events. The large ensemble is particularly geared towards research in the land-atmosphere domain. EC-Earth3 has a considerable warm bias in the Southern Ocean and over Antarctica. Hence, users of KNMI-LENTIS are advised to make in-depth comparisons with observational or reanalysis data, especially if their studies focus on ocean processes, on locations in the Southern Hemisphere, or on teleconnections involving both hemispheres. In this paper, we will give some examples to demonstrate the added value of KNMI-LENTIS for extreme- and compound-event research and for climate-impact modelling.</p