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Now showing 1 - 10 of 10
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    Regional projections of temperature and precipitation changes: Robustness and uncertainty aspects
    (Stuttgart : Gebrueder Borntraeger Verlagsbuchhandlung, 2017) Piniewski, M.; Mezghani, A.; Szczésniak, M.; Kundzewicz, Z.W.
    This study presents the analysis of bias-corrected projections of changes in temperature and precipitation in the Vistula and Odra basins, covering approximately 90% of the Polish territory and small parts of neighbouring countries in Central and Eastern Europe. The ensemble of climate projections consists of nine regional climate model simulations from the EURO-CORDEX ensemble for two future periods 2021-2050 and 2071-2100, assuming two representative concentration pathways (RCPs) 4.5 and 8.5. The robustness is measured by the ensemble models' agreement on significant changes.We found a robust increase in the annual mean of daily minimum and maximum temperature, by 1-1.4 °C in the near future and by 1.9-3.8 °C in the far future (areal-means of the ensemble mean values). Higher increases are consistently associated with minimum temperature and the gradient of change goes from SWto NE regions. Seasonal projections of both temperature variables reflect lower robustness and suggest a higher future increase in winter temperatures than in other seasons, notably in the far future under RCP 8.5 (by more than 1 °C). However, changes in annual means of precipitation are uncertain and not robust in any of the analysed cases, even though the climate models agree well on the increase. This increase is intensified with rising global temperatures and varies from 5.5% in the near future under RCP 4.5 to 15.2%in the far future under RCP 8.5. Spatial variability is substantial, although quite variable between individual climate model simulations. Although seasonal means of precipitation are projected to considerably increase in all four combinations of RCPs and projection horizons for winter and spring, the high model spread reduces considerably the robustness, especially for the far future. In contrast, the ensemble members agree well that overall, the summer and autumn (with exception of the far future under RCP 8.5) precipitation will not undergo statistically significant changes.
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    Estimating near-surface air temperature across Israel using a machine learning based hybrid approach
    (Chichester [u.a.] : Wiley, 2020) Zhou, Bin; Erell, Evyatar; Hough, Ian; Rosenblatt, Jonathan; Just, Allan C.; Novack, Victor; Kloog, Itai
    Rising global temperatures over the last decades have increased heat exposure among populations worldwide. An accurate estimate of the resulting impacts on human health demands temporally explicit and spatially resolved monitoring of near-surface air temperature (Ta). Neither ground-based nor satellite-borne observations can achieve this individually, but the combination of the two provides synergistic opportunities. In this study, we propose a two-stage machine learning-based hybrid model to estimate 1 × 1 km2 gridded intra-daily Ta from surface skin temperature (Ts) across the complex terrain of Israel during 2004–2016. We first applied a random forest (RF) regression model to impute missing Ts from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra satellites, integrating Ts from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) satellite and synoptic variables from European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA5 reanalysis data sets. The imputed Ts are in turn fed into the Stage 2 RF-based model to estimate Ta at the satellite overpass hours of each day. We evaluated the model's performance applying out-of-sample fivefold cross validation. Both stages of the hybrid model perform very well with out-of-sample fivefold cross validated R2 of 0.99 and 0.96, MAE of 0.42°C and 1.12°C, and RMSE of 0.65°C and 1.58°C (Stage 1: imputation of Ts, and Stage 2: estimation of Ta from Ts, respectively). The newly proposed model provides excellent computationally efficient estimation of near-surface air temperature at high resolution in both space and time, which helps further minimize exposure misclassification in epidemiological studies. © 2020 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.
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    On the influence of density and morphology on the Urban Heat Island intensity
    ([London] : Nature Publishing Group UK, 2020) Li, Yunfei; Schubert, Sebastian; Kropp, Jürgen P.; Rybski, Diego
    The canopy layer urban heat island (UHI) effect, as manifested by elevated near-surface air temperatures in urban areas, exposes urban dwellers to additional heat stress in many cities, specially during heat waves. We simulate the urban climate of various generated cities under the same weather conditions. For mono-centric cities, we propose a linear combination of logarithmic city area and logarithmic gross building volume, which also captures the influence of building density. By studying various city shapes, we generalise and propose a reduced form to estimate UHI intensities based only on the structure of urban sites, as well as their relative distances. We conclude that in addition to the size, the UHI intensity of a city is directly related to the density and an amplifying effect that urban sites have on each other. Our approach can serve as a UHI rule of thumb for the comparison of urban development scenarios.
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    Ensemble simulations for the RCP8.5-Scenario
    (Stuttgart : Gebrueder Borntraeger Verlagsbuchhandlung, 2015) Gerstengarbe, F.-W.; Hoffmann, P.; Österle, H.; Werner, P.C.
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    Incremental improvements of 2030 targets insufficient to achieve the Paris Agreement goals
    (Göttingen : Copernicus Publ., 2020) Geiges, Andreas; Nauels, Alexander; Yanguas Parra, Paola; Andrijevic, Marina; Hare, William; Pfleiderer, Peter; Schaeffer, Michiel; Schleussner, Carl-Friedrich
    Current global mitigation ambition up to 2030 under the Paris Agreement, reflected in the National Determined Contributions (NDCs), is insufficient to achieve the agreement's 1.5 °C long-term temperature limit. As governments are preparing new and updated NDCs for 2020, the question as to how much collective improvement is achieved is a pivotal one for the credibility of the international climate regime. The recent Special Report on Global Warming of 1.5 °C by the Intergovernmental Panel on Climate Change has assessed a wide range of scenarios that achieve the 1.5 °C limit. Those pathways are characterised by a substantial increase in near-term action and total greenhouse gas (GHG) emission levels about 50 % lower than what is implied by current NDCs. Here we assess the outcomes of different scenarios of NDC updating that fall short of achieving this 1.5 °C benchmark. We find that incremental improvements in reduction targets, even if achieved globally, are insufficient to align collective ambition with the goals of the Paris Agreement. We provide estimates for global mean temperature increase by 2100 for different incremental NDC update scenarios and illustrate climate impacts under those median scenarios for extreme temperature, long-term sea-level rise and economic damages for the most vulnerable countries. Under the assumption of maintaining ambition as reflected in current NDCs up to 2100 and beyond, we project a reduction in the gross domestic product (GDP) in tropical countries of around 60 % compared to a no-climate-change scenario and median long-term sea-level rise of close to 2 m in 2300. About half of these impacts can be avoided by limiting warming to 1.5 °C or below. Scenarios of more incremental NDC improvements do not lead to comparable reductions in climate impacts. An increase in aggregated NDC ambition of big emitters by 33 % in 2030 does not reduce presented climate impacts by more than about half compared to limiting warming to 1.5 °C. Our results underscore that a transformational increase in 2030 ambition is required to achieve the goals of the Paris Agreement and avoid the worst impacts of climate change. © 2020 SPIE. All rights reserved.
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    Potential effects of climate change on inundation patterns in the Amazon Basin
    (Chichester : John Wiley and Sons Ltd, 2013) Langerwisch, F.; Rost, S.; Gerten, D.; Poulter, B.; Rammig, A.; Cramer, W.
    Floodplain forests, namely the Várzea and Igapó, cover an area of more than 97 000 km2. A key factor for their function and diversity is annual flooding. Increasing air temperature and higher precipitation variability caused by climate change are expected to shift the flooding regime during this century, and thereby impact floodplain ecosystems, their biodiversity and riverine ecosystem services. To assess the effects of climate change on the flooding regime, we use the Dynamic Global Vegetation and Hydrology Model LPJmL, enhanced by a scheme that realistically simulates monthly flooded area. Simulation results of discharge and inundation under contemporary conditions compare well against site-level measurements and observations. The changes of calculated inundation duration and area under climate change projections from 24 IPCC AR4 climate models differ regionally towards the end of the 21st century. In all, 70% of the 24 climate projections agree on an increase of flooded area in about one third of the basin. Inundation duration increases dramatically by on average three months in western and around one month in eastern Amazonia. The time of high- and low-water peak shifts by up to three months. Additionally, we find a decrease in the number of extremely dry years and in the probability of the occurrence of three consecutive extremely dry years. The total number of extremely wet years does not change drastically but the probability of three consecutive extremely wet years decreases by up to 30% in the east and increases by up to 25% in the west. These changes implicate significant shifts in regional vegetation and climate, and will dramatically alter carbon and water cycles.
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    Albedo and heat transport in 3-D model simulations of the early Archean climate
    (München : European Geopyhsical Union, 2013) Kienert, H.; Feulner, G.; Petoukhov, V.
    At the beginning of the Archean eon (ca. 3.8 billion years ago), the Earth's climate state was significantly different from today due to the lower solar luminosity, smaller continental fraction, higher rotation rate and, presumably, significantly larger greenhouse gas concentrations. All these aspects play a role in solutions to the "faint young Sun paradox" which must explain why the ocean surface was not fully frozen at that time. Here, we present 3-D model simulations of climate states that are consistent with early Archean boundary conditions and have different CO2 concentrations, aiming at an understanding of the fundamental characteristics of the early Archean climate system. In order to do so, we have appropriately modified an intermediate complexity climate model that couples a statistical-dynamical atmosphere model (involving parameterizations of the dynamics) to an ocean general circulation model and a thermodynamic-dynamic sea-ice model. We focus on three states: one of them is ice-free, one has the same mean surface air temperature of 288 K as today's Earth and the third one is the coldest stable state in which there is still an area with liquid surface water (i.e. the critical state at the transition to a "snowball Earth"). We find a reduction in meridional heat transport compared to today, which leads to a steeper latitudinal temperature profile and has atmospheric as well as oceanic contributions. Ocean surface velocities are largely zonal, and the strength of the atmospheric meridional circulation is significantly reduced in all three states. These aspects contribute to the observed relation between global mean temperature and albedo, which we suggest as a parameterization of the ice-albedo feedback for 1-D model simulations of the early Archean and thus the faint young Sun problem.
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    Historical and idealized climate model experiments: An intercomparison of Earth system models of intermediate complexity
    (München : European Geopyhsical Union, 2013) Eby, M.; Weaver, A.J.; Alexander, K.; Zickfeld, K.; Abe-Ouchi, A.; Cimatoribus, A.A.; Crespin, E.; Drijfhout, S.S.; Edwards, N.R.; Eliseev, A.V.; Feulner, G.; Fichefet, T.; Forest, C.E.; Goosse, H.; Holden, P.B.; Joos, F.; Kawamiya, M.; Kicklighter, D.; Kienert, H.; Matsumoto, K.; Mokhov, I.I.; Monier, E.; Olsen, S.M.; Pedersen, J.O.P.; Perrette, M.; Philippon-Berthier, G.; Ridgwell, A.; Schlosser, A.; Schneider von Deimling, T.; Shaffer, G.; Smith, R.S.; Spahni, R.; Sokolov, A.P.; Steinacher, M.; Tachiiri, K.; Tokos, K.; Yoshimori, M.; Zeng, N.; Zhao, F.
    Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.
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    Long-term predictability of mean daily temperature data
    (Göttingen : Copernicus GmbH, 2005) von Bloh, W.; Romano, M.C.; Thiel, M.
    We quantify the long-term predictability of global mean daily temperature data by means of the Rényi entropy of second order K2. We are interested in the yearly amplitude fluctuations of the temperature. Hence, the data are low-pass filtered. The obtained oscillatory signal has a more or less constant frequency, depending on the geographical coordinates, but its amplitude fluctuates irregularly. Our estimate of K2 quantifies the complexity of these amplitude fluctuations. We compare the results obtained for the CRU data set (interpolated measured temperature in the years 1901-2003 with 0.5° resolution, Mitchell et al., 20051) with the ones obtained for the temperature data from a coupled ocean-atmosphere global circulation model (AOGCM, calculated at DKRZ). Furthermore, we compare the results obtained by means of K2 with the linear variance of the temperature data.
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    A simple equation for the melt elevation feedback of ice sheets
    (Katlenburg-Lindau : European Geosciences Union, 2016) Levermann, Anders; Winkelmann, Ricarda
    In recent decades, the Greenland Ice Sheet has been losing mass and has thereby contributed to global sea-level rise. The rate of ice loss is highly relevant for coastal protection worldwide. The ice loss is likely to increase under future warming. Beyond a critical temperature threshold, a meltdown of the Greenland Ice Sheet is induced by the self-enforcing feedback between its lowering surface elevation and its increasing surface mass loss: the more ice that is lost, the lower the ice surface and the warmer the surface air temperature, which fosters further melting and ice loss. The computation of this rate so far relies on complex numerical models which are the appropriate tools for capturing the complexity of the problem. By contrast we aim here at gaining a conceptual understanding by deriving a purposefully simple equation for the self-enforcing feedback which is then used to estimate the melt time for different levels of warming using three observable characteristics of the ice sheet itself and its surroundings. The analysis is purely conceptual in nature. It is missing important processes like ice dynamics for it to be useful for applications to sea-level rise on centennial timescales, but if the volume loss is dominated by the feedback, the resulting logarithmic equation unifies existing numerical simulations and shows that the melt time depends strongly on the level of warming with a critical slowdown near the threshold: the median time to lose 10 % of the present-day ice volume varies between about 3500 years for a temperature level of 0.5 °C above the threshold and 500 years for 5 °C. Unless future observations show a significantly higher melting sensitivity than currently observed, a complete meltdown is unlikely within the next 2000 years without significant ice-dynamical contributions.