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Cold extremes are anticipated to warm at a faster rate than both hot extremes and average temperatures for much of the Northern Hemisphere. Anomalously warm cold extremes can affect numerous sectors, including human health, tourism and various ecosystems that are sensitive to cold temperatures. Using a selection of global climate models, this paper explores the accelerated warming of seasonal cold extremes relative to seasonal mean temperatures in the Northern Hemisphere extratropics. The potential driving physical mechanisms are investigated by assessing conditions on or prior to the day when the cold extreme occurs to understand how the different environmental fields are related. During winter, North America, Europe and much of Eurasia show amplified warming of cold extremes projected for the late 21st century, compared to the mid-20th century. This is shown to be largely driven by reductions in cold air temperature advection, suggested as a likely consequence of Arctic amplification. In spring and autumn, cold extremes are expected to warm faster than average temperatures for most of the Northern Hemisphere mid-latitudes to high latitudes, particularly Alaska, northern Canada and northern Eurasia. In the shoulder seasons, projected decreases in snow cover and associated reductions in surface albedo are suggested as the largest contributor affecting the accelerated rates of warming in cold extremes. The key findings of this study improve our understanding of the environmental conditions that contribute to the accelerated warming of cold extremes relative to mean temperatures. This study was supported by the Australian Research Council (ARC) Centre of Excellence for Climate Extremes (grant CE170100023). Markus G. Donat received funding from the ARC (grant DE150100456) and the Spanish Ministry for the Economy, Industry and Competitiveness Ramón y Cajal 2017 grant reference RYC-2017-22964. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Table 1 of this paper) for producing and making their model output available.

11 pages, 6 figures, supplementary information https://doi.org/10.1038/s41612-021-00188-5.-- Data availability; The data generated and analyzed during the current study are available from the corresponding author YRR on reasonable request, Atlantic multidecadal variability (AMV) has been linked to the observed slowdown of global warming over 1998–2012 through its impact on the tropical Pacific. Given the global importance of tropical Pacific variability, better understanding this Atlantic–Pacific teleconnection is key for improving climate predictions, but the robustness and strength of this link are uncertain. Analyzing a multi-model set of sensitivity experiments, we find that models differ by a factor of 10 in simulating the amplitude of the Equatorial Pacific cooling response to observed AMV warming. The inter-model spread is mainly driven by different amounts of moist static energy injection from the tropical Atlantic surface into the upper troposphere. We reduce this inter-model uncertainty by analytically correcting models for their mean precipitation biases and we quantify that, following an observed 0.26 °C AMV warming, the equatorial Pacific cools by 0.11 °C with an inter-model standard deviation of 0.03 °C, Y.R.-R. was founded by the European Union’s Horizon 2020 Research and Innovation Program in the framework of the Marie Skłodowska-Curie grant INADEC (Grant agreement 800154). E.M.-C. acknowledges funding from the European Commission’s Horizon 2020 projects PRIMAVERA (Grant Agreement 641727). X.L. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433. A.B. and D.N. acknowledge funding from the European Commission’s Horizon 2020 project EUCP (Grant agreement 776613). F.C. and G.D. were supported by the US National Science Foundation (NSF) under the Collaborative Research EaSM2 Grant OCE-1243015 to NCAR and by the US National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under the Climate Variability and Predictability Program Grant NA13OAR4310138. NCAR is a major facility sponsored by the US NSF under Cooperative Agreement 1852977. [...] R.E., N.D., L.H., and D.S. were supported by the Met Office Hadley Center 522 Climate Program funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP 523 project (GA 776613). J.L.-P. was funded by the European Union’s Horizon 2020 Research and Innovation Program in the framework of the PRIMAVERA project (Grant Agreement 641727). J.R. and D.H. were funded by NERC via NCAS and the ACSIS project (NE/N018001/1), and JR was also funded by the NERC SMURPHS project (NE/N006054/1). M.M.-R. was funded by the European Union’s Horizon 2020 Research and Innovation Program in the framework of the Marie Skłodowska-Curie grant FESTIVAL (Grant agreement 797236). E.T. has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 748750 (SPFireSD project), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

The enhanced warming trend and precipitation decline in the Mediterranean region make it a climate change hotspot. We compare projections of multiple Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) historical and future scenario simulations to quantify the impacts of the already changing climate in the region. In particular, we investigate changes in temperature and precipitation during the 21st century following scenarios RCP2.6, RCP4.5 and RCP8.5 for CMIP5 and SSP1-2.6, SSP2-4.5 and SSP5-8.5 from CMIP6, as well as for the HighResMIP high-resolution experiments. A model weighting scheme is applied to obtain constrained estimates of projected changes, which accounts for historical model performance and inter-independence in the multi-model ensembles, using an observational ensemble as reference. Results indicate a robust and significant warming over the Mediterranean region during the 21st century over all seasons, ensembles and experiments. The temperature changes vary between CMIPs, CMIP6 being the ensemble that projects a stronger warming. The Mediterranean amplified warming with respect to the global mean is mainly found during summer. The projected Mediterranean warming during the summer season can span from 1.83 to 8.49 ∘C in CMIP6 and 1.22 to 6.63 ∘C in CMIP5 considering three different scenarios and the 50 % of inter-model spread by the end of the century. Contrarily to temperature projections, precipitation changes show greater uncertainties and spatial heterogeneity. However, a robust and significant precipitation decline is projected over large parts of the region during summer by the end of the century and for the high emission scenario (−49 % to −16 % in CMIP6 and −47 % to −22 % in CMIP5). While there is less disagreement in projected precipitation than in temperature between CMIP5 and CMIP6, the latter shows larger precipitation declines in some regions. Results obtained from the model weighting scheme indicate larger warming trends in CMIP5 and a weaker warming trend in CMIP6, thereby reducing the difference between the multi-model ensemble means from 1.32 ∘C before weighting to 0.68 ∘C after weighting.

Under the influence of global warming, heatwaves are becoming a major threat in many parts of the world, affecting human health and mortality, food security, forest fires, biodiversity, energy consumption, as well as the production and transportation networks. Seasonal forecasting is a promising tool to help mitigate these impacts on society. Previous studies have highlighted some predictive capacity of seasonal forecast systems for specific strong heatwaves such as those of 2003 and 2010. To our knowledge, this study is thus the first of its kind to systematically assess the prediction skill of heatwaves over Europe in a state-of-the-art seasonal forecast system. One major prerequisite to do so is to appropriately define heatwaves. Existing heatwave indices, built to measure heatwave duration and severity, are often designed for specific impacts and thus have limited robustness for an analysis of heatwave variability. In this study, we investigate the seasonal prediction skill of European summer heatwaves in the ECMWF System 5 operational forecast system by means of several dedicated metrics, as well as its added-value compared to a simple statistical model based on the linear trend. We are able to show, for the first time, that seasonal forecasts initialized in early May can provide potentially useful information of summer heatwave propensity, which is the tendency of a season to be predisposed to the occurrence of heatwaves. This work is a contribution to the HyMeX program through the project ERA4CS-MEDSCOPE, co-funded by the Horizon 2020 Framework Program of the European Union (Grant agreement 690462). Chloe Prodhomme and Javier García-Serrano were supported by the Spanish Juan de la Cierva (IJCI-2016-30802) and Ramon y Cajal (RYC-2016-21181) programs, respectively. Rachel H. White received funding from the European Unions Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement 797961.

Microwave radiometry at L-band is sensitive to sea ice thickness (SIT) up to ∼ 60 cm. Current methods to infer SIT depend on ice-physical properties and data provided by the ESA’s Soil Moisture and Ocean Salinity (SMOS) mission. However, retrieval accuracy is limited due to seasonally and regionally variable surface conditions during the formation and melting of sea ice. In this work, Arctic sea ice is segmented using a Bayesian unsupervised learning algorithm aiming to recognize spatial patterns by harnessing multi-incidence angle brightness temperature observations. The approach considers both statistical characteristics and spatial correlations of the observations. The temporal stability and separability of classes are analyzed to distinguish ambiguous from well-determined regions. Model uncertainty is quantified from class membership probabilities using information entropy. The presented approach opens up a new scope to improve current SIT retrieval algorithms, and can be particularly beneficial to investigate merged satellite products., There are no perceived conicts of inter-est for the lead author or coauthors. The lead author received the support of a fellowship from “la Caixa” Foundation (ID 100010434). The fellowship code is LCF/BQ/DI18/11660050. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 713673. It was also funded through the award “Unidad de Excelencia María de Maeztu” MDM-2016-0600, by the Spanish Ministry of Science and Innovation through the project “L-band” ESP2017-89463-C3-2-R, and the project “Sensing with Pioneering Opportunistic Techniques (SPOT)” RTI2018-099008-B-C21/AEI/10.13039/501100011033

Special issue Selected Papers from the 2019 IMEKO TC-19 International Workshop on Metrology for the Sea.-- 17 pages, 11 figures, 1 table, 1 appendix, supplementary material https://doi.org/10.3390/s20092658, Since 2014, the global land and sea surface temperature has scaled 0.23 °C above the decadal average (2009–2018). Reports indicate that Mediterranean Sea temperatures have been rising at faster rates than in the global ocean. Oceanographic time series of physical and biogeochemical data collected from an onboard and a multisensor mooring array in the northwestern Mediterranean Sea (Blanes submarine canyon, Balearic Sea) during 2009–2018 revealed an abrupt temperature rising since 2014, in line with regional and global warming. Since 2014, the oligotrophic conditions of the water column have intensified, with temperature increasing 0.61 °C on the surface and 0.47 °C in the whole water column in continental shelf waters. Water transparency has increased due to a decrease in turbidity anomaly of −0.1 FTU. Since 2013, inshore chlorophyll a concentration remained below the average (−0.15 mg·l−1) and silicates showed a declining trend. The mixed layer depth showed deepening in winter and remained steady in summer. The net surface heat fluxes did not show any trend linked to the local warming, probably due to the influence of incoming offshore waters produced by the interaction between the Northern Current and the submarine canyon. Present regional and global water heating pattern is increasing the stress of highly diverse coastal ecosystems at unprecedented levels, as reported by the literature. The strengthening of the oligotrophic conditions in the study area may also apply as a cautionary warning to similar coastal ecosystems around the world following the global warming trend, The OOCS was initially funded by the Spanish National Research Project OAMMS Ref. CTM2008-03983 (PI. A.C). The research projects ADEPT Ref. CTM2011-23458 Ref. CTM2008-03983 (PI. F.P) and CONECTA Ref. CTM2014-54648-C2−1-R (PI J.B.C) partially contributed to the OOCS operations, With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

The carbon footprint of synthetic natural gas production from biogas catalytic methanation was determined. The material and energy data inputs required to produce 1 kWh of synthetic natural gas were experimentally collected from a pilot plant operating in a waste water treatment plant as a relevant environment. The experimental plant had a capacity of 37 kW and consisted of biogas and water conditioning, water electrolysis and 2-step carbon dioxide catalytic methanation unit, by compact technology of micro-reactor and micro-size catalysts al mild pressure conditions. The technology evaluated in this study is ready for scalability to MW-scale. The carbon footprint was evaluated by means of the Global Warming potential impact in kg CO2-eq/kWh. Life Cycle Assessment methodology was used according to ISO:14040 and ISO:14067 thorough Ecoinvent data. The carbon footprint analysis showed that producing synthetic natural gas using the current electricity mix led to high carbon impact. However, the utilization of renewable electricity sources and a more efficient electrolyzer technology is able to reduce the carbon footprint to 0.100 kg CO2-eq/kWh. This value represents an interesting reduction of the climate change impact of 57%, using currently available technologies. Therefore, synthetic natural gas from biogas catalytic methanation process represents a feasible option to partially decarbonize the gas grid infrastructure. In this way, synthetic natural gas can support the penetration of random renewable sources by allowing its seasonal storage, as well as, to provide a low-carbon gas alternative.

The paper proposes a new strategy against the global warming, which if applied on large scale is able to turn our cities into green oasis, decreasing their actual carbon footprint and increasing their carbon offset. Our approach is to replace conventional roofs with integrated rooftop greenhouses IRTG, which are connected with the interior of the building by controlled flows of energy, oxygen, carbon dioxide and water. The main IRTG feature is the tight human-plant symbiosis ensured by a two flows ventilation system, conveying O 2 enriched air from RTG to building and CO 2 enriched air from building to RTG. To be applicable at large scale with no particular infrastructure demands, IRTGs systems are provided with renewable energy devices suited to the local climate: heat pumps (water to water for building’s basement and air to air for greenhouse), solar panels, etc. and also with Internet of Things equipment. Such way IRTGs can harvest local renewable energy resources (geo-thermal, solar, wind, etc.), store them and manage them together with the water resources. Besides future dedicated projects, inserting IRTGs into the existing urban infrastructures is possible, depending of the buildings’ condition, so nowadays cities may be gradually turned into Smart Green Skyline Cities.

Plankton respiration rate is a major component of global CO2 production and is forecasted to increase rapidly in the Arctic with warming. Yet, existing assessments in the Arctic evaluated plankton respiration in the dark. Evidence that plankton respiration may be stimulated in the light is particularly relevant for the high Arctic where plankton communities experience continuous daylight in spring and summer. Here we demonstrate that plankton community respiration evaluated under the continuous daylight conditions present in situ, tends to be higher than that evaluated in the dark. The ratio between community respiration measured in the light (Rlight) and in the dark (Rdark) increased as the 2/3 power of Rlight so that the Rlight:Rdark ratio increased from an average value of 1.37 at the median Rlight measured here (3.62 µmol O2 L−1 d−1) to an average value of 17.56 at the highest Rlight measured here (15.8 µmol O2 L−1 d−1). The role of respiratory processes as a source of CO2 in the Arctic has, therefore, been underestimated and is far more important than previously believed, particularly in the late spring, with 24 h photoperiods, when community respiration rates are highest., ARCTICMET and ATOS, funded by the Spanish Ministry of Economy and Competitiveness (CTM2011-15792-E and POL2006-00550/CTM, respectively), the ATP project funded by the FP-7 of the EU (CTM2009-07781-E), and the CarbonBridge project (no. 226415) funded by the Norwegian Research Council. Work in Young Sound was funded by the Greenland Ecosystem Monitoring (GEM) program.

In this study we analyzed the spatial distribution, temporal variability and trends in reference evapotranspiration (ET0) in Spain from 1961 to 2011. Twelve methods were analyzed to quantify ET0 from quality controlled and homogeneous series of various meteorological variables measured at 46 meteorological stations. Some of the models used are temperature based (e.g., Thornthwaite, Hargreaves, Linacre), whereas others are more complex and require more meteorological variables for calculation (e.g., Priestley-Taylor, Papadakis, FAO-Blaney-Criddle). The Penman-Monteith equation was used as a reference to quantify ET0, and for comparison among the other methods applied in the study. No major differences in the spatial distribution of the average ET0 were evident among the various methods. At annual and seasonal scales some of the ET0 methods requiring only temperature data for calculation provided better results than more complex methods requiring more variables. Among them the Hargreaves (HG) equation provided the best results, at both the annual and seasonal scales. The analysis of the temporal variability and trends in the magnitude of ET0 indicated that all methods show a marked increase in ET0 at the seasonal and annual time scales. Nevertheless, results obtained suggested substantial uncertainties among the methods assessed to determine ET0 changes, due to differences in temporal variability of the resulting time series, but mainly for the differences in the magnitude of change of ET0 and its spatial distribution. This suggests that ET0 trends obtained by means of methods that only require temperature data for ET0 calculations should be evaluated carefully under the current global warming scenario. © 2014 Elsevier B.V., The authors wish to acknowledge the two anonymous reviewers for their detailed and helpful comments to the original manuscript. We would also like to thank the Spanish State Meteorological Agency (AEMET) for providing the database used in this study. This work has been supported by the research projects CGL2011-27574-C02-01, CGL2011-27574-CO2-02, CGL2011-27536 and CGL2010-18546 financed by the Spanish Commission of Science and Technology and FEDER, “Demonstration and validation of innovative methodology for regional climate change adaptation in the Mediterranean area (LIFE MEDACC)” financed by the LIFE programme of the European Commission, CTTP1/12 financed by the Comunidad de Trabajo de los Pirineos and Consolidated Research groups: >Clima, Agua, Cambio Global y Sistemas Naturales> and >Geomorfología y Cambio Global> financed by the Gobierno Regional de Aragón DGA-FSE. The second author was granted by the postdoctoral JAE-DOC043 (CSIC) and JCI-2011-10263 (Spanish Ministry of Science and Innovation) grants. The third author was supported by the >Secretaria per a Universitats i Recerca del Departament d'Economia i Coneixement, de la Generalitat de Catalunya i del programa Cofund de les Accions Marie Curie del 7e Programa marc d'R+D de la Unio Europea> (2011 BP-B 00078) and the postdoctoral fellowship JCI-2012-12508. The fourth author was supported by the predoctoral FPU program 2010 (Spanish Ministry of Education, Culture and Sports).

Crops and forests are already responding to rising atmospheric carbon dioxide and air temperatures. Increasing atmospheric CO2 concentrations are expected to enhance plant photosynthesis. Nevertheless, after long-term exposure, plants acclimate and show a reduction in photosynthetic activity (i.e. down-regulation). If in the future the Earth’s temperature is allowed to rise further, plant ecosystems and food security will both face significant threats. The scientific community has recognized that an increase in global temperatures should remain below 2°C in order to combat climate change. All this evidence suggests that, in parallel with reductions in CO 2 emissions, a more direct approach to mitigate global warming should be considered. We propose here that global warming could be partially mitigated directly through local bio-geoengineering approaches. For example, this could be done through the management of solar radiation at surface level, i.e. by increasing global albedo. Such an effect has been documented in the south-eastern part of Spain, where a significant surface air temperature trend of -0.3 ° C per decade has been observed due to a dramatic expansion of greenhouse horticulture.

N2O is a GHG of environmental concern. It is generated from the nitrous material contained in wastewater and is the sixth most important contributor to N2O emissions. There is a great variety of methods to quantify the emission of N2O in a wastewater treatment plant (WWTP), which present variants among them, such as predetermined values and operational data of the plants. In this paper, we compared three different methods to quantify the N2O emission in 2015 from WWTP in two metropolitan areas with high population density: Mexico City and the Metropolitan Area of Barcelona (MAB). MAB has advanced treatment plants that remove nutrients from wastewater, and Mexico City has only traditional treatment plants. The N2O emission/inhabitant from WWTPs in MAB (3,214,211 inhabitants served) was 40% lower than the plants in Mexico City (1,806,440 inhabitants served). The MAB emission was 0.009 tCO2e/inhabitant and 0.013 tCO2e/inhabitant in Mexico City; these emission values could be considered statistically different with a risk error of 5%. This difference could be due to the fact that MAB has nutrient removal (42% of inhabitants served), and Mexico City has only traditional treatment plants. The results obtained may be influenced by the default emission factors of each methodology. In addition, per capita protein consumption and water consumption per inhabitant are different parameters that must be considered between these zones to quantify and compare the emission of N2O. The integral methods are closer to the reality of the N2O emission when the operating parameters of each plant and wastewater are considered. There should be more research on the reduction of this GHG in wastewater treatment for a correct quantification of these emissions, and more especially in the estimation of N2O emission factors suitable for each treatment plant and study area.