Search

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests., Global Change Biology, 28 (23), ISSN:1354-1013, ISSN:1365-2486

Water scarcity is a growing concern in many regions worldwide, as demand for clean water increases and supply becomes increasingly uncertain under climate change. Already today, more than 4 billion people experience water scarcity at least one month per year (Mekonnen and Hoekstra, 2016). Developing socio-economic conditions and growing population increase water demands, while climate change leads to changes in freshwater availability. Most studies quantify water scarcity in discrete time windows, with fixed population and climate change signals (e.g., 30 years or long-term averages). Recently, however, Thiery et al. (2021) proposed a novel approach, in which climate change impacts are integrated over a person's lifetime. In this cohort perspective, lifetime impact values are comparable across generations and regions. Evaluating this perspective for natural hazards, they showed, for example, that a newborn will experience a sixfold increase in drought exposure compared to a 60-year-old (Thiery et al., 2021). In this study, we use this cohort perspective to study how much water scarcity a person experiences during their lifetime. Based on monthly fluctuations in water demand and availability, we estimate the total amount of water demand not met and refer to it as 'lifetime water deficit'. To this end, we use an ensemble of four global hydrological models (MATSIRO, CWatM, LPJmL and H08), each forced by four GCMs and two RCP scenarios from the InterSectoral Impact Model Intercomparison Project (ISIMIP2b). The simulations account for varying population and socio-economic conditions in the historical and future period, following the SSP2 scenario. Combined with country-based population, cohort distribution and life expectancies, lifetime water deficits are quantified for different generations on a country level. Our findings reveal high water lifetime deficit values for regions that are already water scarce today, such as the Mediterranean, North Africa and the Middle East. In these regions, more than 70% of the lifetime water demand is not met when needed. Further comparison reveals differences in spatial, intergenerational and climate change scenarios, and provides information on different scenarios. Overall, this study provides a new perspective on quantifying water scarcity and the climate and population impacts. References:Mekonnen, M. M., & Hoekstra, A. Y. (2016). Four billion people facing severe water scarcity. Science Advances, 2(2). https://doi.org/10.1126/sciadv.1500323Thiery, W., Lange, S., Rogelj, J., Schleussner, C. F., Gudmundsson, L., Seneviratne, S. I., Andrijevic, M., Frieler, K., Emanuel, K., Geiger, T., Bresch, D. N., Zhao, F., Willner, S. N., Büchner, M., Volkholz, J., Bauer, N., Chang, J., Ciais, P., Dury, M., … Wada, Y. (2021). Intergenerational inequities in exposure to climate extremes. Science, 374(6564), 158–160. https://doi.org/10.1126/science.abi7339

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.

16 pages, 6 figures, 3 tables, supplementary data https://doi.org/10.1016/j.pocean.2021.102659.-- Code and data availability: The experimental protocol in this paper has no code associated with it. Forcing data from CMIP5 used for the protocol, and the FishMIP model outputs presented in this paper are available on the ISIMIP servers (https://www.isimip.org/), Climate change is warming the ocean and impacting lower trophic level (LTL) organisms. Marine ecosystem models can provide estimates of how these changes will propagate to larger animals and impact societal services such as fisheries, but at present these estimates vary widely. A better understanding of what drives this inter-model variation will improve our ability to project fisheries and other ecosystem services into the future, while also helping to identify uncertainties in process understanding. Here, we explore the mechanisms that underlie the diversity of responses to changes in temperature and LTLs in eight global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP). Temperature and LTL impacts on total consumer biomass and ecosystem structure (defined as the relative change of small and large organism biomass) were isolated using a comparative experimental protocol. Total model biomass varied between −35% to +3% in response to warming, and -17% to +15% in response to LTL changes. There was little consensus about the spatial redistribution of biomass or changes in the balance between small and large organisms (ecosystem structure) in response to warming, an LTL impacts on total consumer biomass varied depending on the choice of LTL forcing terms. Overall, climate change impacts on consumer biomass and ecosystem structure are well approximated by the sum of temperature and LTL impacts, indicating an absence of nonlinear interaction between the models’ drivers. Our results highlight a lack of theoretical clarity about how to represent fundamental ecological mechanisms, most importantly how temperature impacts scale from individual to ecosystem level, and the need to better understand the two-way coupling between LTL organisms and consumers. We finish by identifying future research needs to strengthen global marine ecosystem modelling and improve projections of climate change impacts, JDE was funded by Australian Research Council Discovery Projects DP150102656 and DP190102293. MC, JS, NB and OM received financial support by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 817578 (Triatlas project). CH received funding from the Open Philanthropy Project. NB and OM also acknowledge the support of the French ANR project CIGOEF (grant ANR-17-CE32-0008-01). DPT acknowledges funding from the ISI-MIP project to support a workshop on this topic, and the Jarislowsky Foundation. EDG received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 682602, BIGSEA). RFH was funded by the Spanish Ministry of Science, Innovation and Universities through the Acciones de Programación Conjunta Internacional (PCIN-2017-115). MC acknowledges the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) to the Institute of Marine Science (ICM-CSIC). TDE acknowledges funding from the ISIMIP project to support a workshop on this topic and the Fisheries and Oceans Canada Atlantic Fisheries Fund. All authors declare no conflict of interest with respect to this study. JAFS received funding from the European Union’s Horizon 2020 FutureMARES project (#869300).

Executive Summary This report sheds light on the possible effects of climate change on development and security in the Central Sahel, namely in Burkina Faso, Mali and Niger. It examines the interactions between climatic stresses, food security, and conflict risk, by highlighting the region’s key socio-economic and political conditions, and how these could shape future vulnerability to the effects of global warming. It further discusses existing measures and policies and how these could be improved to increase the region’s resilience to climate- related challenges. Climate variability is a key issue in the Central Sahel, owing to a heavy reliance on rainfed agriculture, pastoralism and other climate- sensitive livelihoods. Yet, its effects need to be understood in a wider social and political context.

Summarization: The extent and impact of climate‐related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter‐Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross‐category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia. Presented on: Earth's Future

Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand-level, as well as remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction, and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a SQLite relational database or ASCII flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation.

6 pages, 5 figures, supporting information https://doi.org/10.1073/pnas.1900194116.-- All data reported in this paper are archived and publicly available at http://dataservices.gfz-potsdam.de/pik/showshort.php?id=escidoc:2956913., While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends, Financial support was provided by the German Federal Ministry of Education and Research through ISI-MIP (Grant01LS1201A1), the European Union’s Horizon 2020 Research and Innovation Program (Grant 678193), and the Ocean Frontier Institute (Module G). We acknowledge additional financial support as follows: to H.K.L., W.W.L.C., and B.W. from the Natural Sciences and Engineering Research Council (NSERC) of Canada; to D.P.T. from the Kanne Rasmussen Foundation Denmark; to A.B.-B. from the NSERC Transatlantic Ocean Science and Technology Program; to W.W.L.C. and T.D.E. from the Nippon Foundation-Nereus Program; to E.D.G., M.C. and J. Steenbeek from the European Union’s Horizon 2020 Re-search and Innovation Program (Grants 682602 and 689518); to E.A.F., J.L.B., andT.R. from Commonwealth Scientific and Industrial Research Organization and the Australian Research Council; to N.B., L.B., and O.M. from the French Agence Nationale de la Recherche and Pôle de Calcul et de Données pour la Mer; and to S.J. from the UK Department of Environment, Food and Rural Affairs

Climate change is shifting the abundance and distribution of marine species with consequences for ecosystem functioning, seafood supply, management and conservation. Several approaches for future projection exist but these have never been compared systematically to assess their variability. We conducted standardized ensemble projections including 6 global fisheries and marine ecosystem models, forced with 2 Earth-system models and 4 emission scenarios in a fished and unfished ocean, to derive average trends and associated uncertainties. Without fishing, mean global animal biomass decreased by 5% (±4%) under low and 17% (±11%) under high emissions by 2100, primarily driven by increasing temperature and decreasing primary production. These climate-change effects were slightly weaker for larger animals and in a fished ocean. Considerable regional variation ranged from strong biomass increases in high latitudes to strong decreases in mid-low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to differences among ecosystem or Earth-system models were similar, suggesting equal need for model improvement. Our ensemble projections provide the most comprehensive outlook on potential climate-driven ecological changes in the ocean to date. Realized future trends will largely depend on how fisheries and management adapt to these changes in a changing climate.

Model intercomparison studies in the climate and earth sciences communities have been crucial to build credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment, and consequent effects on food security, biodiversity, marine industries and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size) and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem, and implies that the assemblage of all models is more likely to include a greater number of relevant processes than is any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) CMIP5 outputs under prescribed scenarios for historic (from 1950s) and future (to 2100) time periods; it will be adapted to CMIP6 in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between, and uncertainties within, models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation and comparison of results from Fish-MIP will inform understanding of the range of plausible changes in marine ecosystems, and improve our capacity to define and convey strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.

This study investigates the effects of Lake Sobradinho, a large reservoir in Northeastern Brazil, on the local near-surface atmospheric and boundary layer conditions. For this purpose, simulations with the regional climate model COSMO-CLM are compared for two different scenarios: (1) with the lake being replaced by the average normal native vegetation cover and (2) with the lake as it exists today, for two different two-month periods reflecting average and very dry conditions, respectively. The performance of the simulation is evaluated against data from surface meteorological stations as well as satellite data in order to ensure the model’s ability to capture atmospheric conditions in the vicinity of Lake Sobradinho. The obtained results demonstrate that the lake affects the near-surface air temperature of the surrounding area as well as its humidity and wind patterns. Specifically, Lake Sobradinho cools down the air during the day and warms it up during the night by up to several ∘ C depending on the large-scale meteorological conditions. Moreover, the humidity is significantly increased as a result of the lake’s presence and causes a lake breeze. The observed effects on humidity and air temperature also extend over areas relatively far away from the lake. Deutsche Forschungsgemeinschaft

This study provides a first thorough evaluation of the COnsortium for Small scale MOdeling weather prediction model in CLimate Mode (COSMO-CLM) over South America. Simulations are driven by ERA-Interim reanalysis data. Besides precipitation, we examine the surface radiation budget, cloud cover, 2 m temperatures, and the low level circulation. We evaluate against reanalysis data as well as observations from ground stations and satellites. Our analysis focuses on the sensitivity of results to the convective parametrization in comparison to their sensitivity to the representation of non-precipitating subgrid-scale clouds in the parametrization of radiation. Specifically, we compare simulations with a relative humidity versus a statistical subgrid-scale cloud scheme, in combination with convection schemes according to Tiedtke (Mon Weather Rev 117(8):1779–1800, 1989) and from the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) cycle 33r1. The sensitivity of simulated tropical precipitation to the parametrizations of convection and subgrid-scale clouds is of similar magnitude. We show that model runs with different subgrid-scale cloud schemes produce substantially different cloud ice and liquid water contents. This impacts surface radiation budgets, and in turn convection and precipitation. Considering all evaluated variables in synopsis, the model performs best with the (both non-default) IFS and statistical schemes for convection and subgrid-scale clouds, respectively. Despite several remaining deficiencies, such as a poor simulation of the diurnal cycle of precipitation or a substantial austral summer warm bias in northern Argentina, this new setup considerably reduces long-standing model biases, which have been a feature of COSMO-CLM across tropical domains.

In this study we introduce two new node-weighted difference measures on complex networks as a tool for climate model evaluation. The approach facilitates the quantification of a model’s ability to reproduce the spatial covariability structure of climatological time series. We apply our methodology to compare the performance of a statistical and a dynamical regional climate model simulating the South American climate, as represented by the variables 2 m temperature, precipitation, sea level pressure, and geopotential height field at 500 hPa. For each variable, networks are constructed from the model outputs and evaluated against a reference network, derived from the ERA-Interim reanalysis, which also drives the models. We compare two network characteristics, the (linear) adjacency structure and the (nonlinear) clustering structure, and relate our findings to conventional methods of model evaluation. To set a benchmark, we construct different types of random networks and compare them alongside the climate model networks. Our main findings are: (1) The linear network structure is better reproduced by the statistical model statistical analogue resampling scheme (STARS) in summer and winter for all variables except the geopotential height field, where the dynamical model CCLM prevails. (2) For the nonlinear comparison, the seasonal differences are more pronounced and CCLM performs almost as well as STARS in summer (except for sea level pressure), while STARS performs better in winter for all variables.

We present numerical results for the 2-flavour Schwinger model with dynamical chiral lattice fermions. We insert an approximately chiral hypercube Dirac operator into the overlap formula to construct the overlap hypercube operator. This is an exact solution to the Ginsparg-Wilson relation, with an excellent level of locality and scaling. Due to its similarity with the hypercubic kernel, a low polynomial in this kernel provides a numerically efficient Hybrid Monte Carlo force. We measure the microscopic Dirac spectrum and discuss the corresponding scale-invariant parameter, which takes a surprising form. This is an interesting case, since Random Matrix Theory is unexplored for this setting, where the chiral condensate {\Sigma} vanishes in the chiral limit. We also measure {\Sigma} and the "pion" mass, in distinct topological sectors. In this context we discuss and probe the topological summation of observables by various methods, as well as the evaluation of the topological susceptibility. The feasibility of this summation is essential for the prospects of dynamical overlap fermions in QCD., Comment: 44 pages, LaTex, 12 tables, 17 figures, final version published in Eur. Phys. J. C

We present a numerical study of a two dimensional model of the Wess-Zumino type. We formulate this model on a sphere, where the fields are expanded in spherical harmonics. The sphere becomes fuzzy by a truncation in the angular momenta. This leads to a finite set of degrees of freedom without explicitly breaking the space symmetries. The corresponding field theory is expressed in terms of a matrix model, which can be simulated. We present first numerical results for the phase structure of a variant of this model on a fuzzy sphere. The prospect to restore exact supersymmetry in certain limits is under investigation.

We present simulation results for the 2-flavour Schwinger model with dynamical overlap fermions. In particular we apply the overlap hypercube operator at seven light fermion masses. In each case we collect sizable statistics in the topological sectors 0 and 1. Since the chiral condensate Sigma vanishes in the chiral limit, we observe densities for the microscopic Dirac spectrum, which have not been addressed yet by Random Matrix Theory (RMT). Nevertheless, by confronting the averages of the lowest eigenvalues in different topological sectors with chiral RMT in unitary ensemble we obtain -- for the very light fermion masses -- values for Sigma that follow closely the analytical predictions in the continuum., 7 pages, poster presented at LATTICE07 (Regensburg)

We present numerical results for U(1) gauge theory in 2d and 4d spaces involving a non-commutative plane. Simulations are feasible thanks to a mapping of the non-commutative plane onto a twisted matrix model. In d=2 it was a long-standing issue if Wilson loops are (partially) invariant under area-preserving diffeomorphisms. We show that non-perturbatively this invariance breaks, including the subgroup SL(2,R). In both cases, d=2 and d=4, we extrapolate our results to the continuum and infinite volume by means of a Double Scaling Limit. In d=4 this limit leads to a phase with broken translation symmetry, which is not affected by the perturbatively known IR instability. Therefore the photon may survive in a non-commutative world., Comment: 7 pages, 6 figures, talk presented by W.B. at LATTICE07

We present simulation results for the 2-flavour Schwinger model with dynamical Ginsparg-Wilson fermions. Our Dirac operator is constructed by inserting an approximately chiral hypercube operator into the overlap formula, which yields the overlap hypercube operator. Due to the similarity with the hypercubic kernel, a low polynomial of this kernel can be used as a numerically cheap way to evaluate the fermionic part of the Hybrid Monte Carlo force. We verify algorithmic requirements like area conservation and reversibility, and we discuss the viability of this approach in view of the acceptance rate. Next we confirm a high level of locality for this formulation. Finally we evaluate the chiral condensate at light fermion masses, based on the density of low lying Dirac eigenvalues in different topological sectors. The results represent one of the first measurements with dynamical overlap fermions, and they agree very well with analytic predictions.

Recent perturbative studies show that in 4d non-commutative spaces, the trivial (classically stable) vacuum of gauge theories becomes unstable at the quantum level, unless one introduces sufficiently many fermionic degrees of freedom. This is due to a negative IR-singular term in the one-loop effective potential, which appears as a result of the UV/IR mixing. We study such a system non-perturbatively in the case of pure U(1) gauge theory in four dimensions, where two directions are non-commutative. Monte Carlo simulations are performed after mapping the regularized theory onto a U(N) lattice gauge theory in d=2. At intermediate coupling strength, we find a phase in which open Wilson lines acquire non-zero vacuum expectation values, which implies the spontaneous breakdown of translational invariance. In this phase, various physical quantities obey clear scaling behaviors in the continuum limit with a fixed non-commutativity parameter $\theta$, which provides evidence for a possible continuum theory. The extent of the dynamically generated space in the non-commutative directions becomes finite in the above limit, and its dependence on $\theta$ is evaluated explicitly. We also study the dispersion relation. In the weak coupling symmetric phase, it involves a negative IR-singular term, which is responsible for the observed phase transition. In the broken phase, it reveals the existence of the Nambu-Goldstone mode associated with the spontaneous symmetry breaking., Comment: 29 pages, 23 figures, references added

Institute of Physics, University of Tsukuba,Tsukuba, Ibaraki 305-8571, JapanE-mail:volkholz@physik.hu-berlin.de,bietenho@physik.hu-berlin.de,jnishi@post.kek.jp, susaki@post.kek.jpWe present results of numerical simulations for pure U(1) gauge theory in a non-commutativespace. The theory is mapped onto a dimensionally reduced matrix model, which renders its nu-merical treatment feasible. New data on large lattices reveal the scaling of Wilson loops and theircorrelation functions in the simultaneous limit to the continuum and to infinite volume, at fixednon-commutativity. In this on-goingproject we are particularly interested in the IR behaviour,the“photo-ball” spectrum and in the photon dispersion relation.XXIIIrd International Symposium on Lattice Field Theory25-30 July 2005Trinity College, Dublin, Ireland

We present preliminary simulation results for QED in a non-commutative 4d space-time, which is discretized to a fuzzy lattice. Its numerical treatment becomes feasible after its mapping onto a dimensionally reduced twisted Eguchi-Kawai matrix model. In this formulation we investigate the Wilson loops and in particular the Creutz ratios. This is an ongoing project which aims at non-perturbative predictions for the photon, which can be confronted with phenomenology in order to verify the possible existence of non-commutativity in nature., Comment: 3 pages, 4 figures, talk presented by J. Volkholz at Lattice2004(theory)