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Large-scale reforestation, afforestation, and forest restoration schemes have gained global support as climate change mitigation strategies due to their significant carbon dioxide removal (CDR) potential. However, there has been limited research into the unintended consequences of forestation from a biophysical perspective. In the Community Earth System Model version 2 (CESM2), we apply a global forestation scenario, within a Paris Agreement-compatible warming scenario, to investigate the land surface and hydroclimate response. Compared to a control scenario where land use is fixed to present-day levels, the forestation scenario is up to 2 °C cooler at low latitudes by 2100, driven by a 10 % increase in evaporative cooling in forested areas. However, afforested areas where grassland or shrubland are replaced lead to a doubling of plant water demand in some tropical regions, causing significant decreases in soil moisture (∼ 5 % globally, 5 %–10 % regionally) and water availability (∼ 10 % globally, 10 %–15 % regionally) in regions with increased forest cover. While there are some increases in low cloud and seasonal precipitation over the expanded tropical forests, with enhanced negative cloud radiative forcing, the impacts on large-scale precipitation and atmospheric circulation are limited. This contrasts with the precipitation response to simulated large-scale deforestation found in previous studies. The forestation scenario demonstrates local cooling benefits without major disruption to global hydrodynamics beyond those already projected to result from climate change, in addition to the cooling associated with CDR. However, the water demands of extensive forestation, especially afforestation, have implications for its viability, given the uncertainty in future precipitation changes. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon (DOC) is the most active carbon pool in soils, which plays critical roles in soil carbon cycling, plant productivity, and global climate change. An accurate assessment of the quantity of DOC in the soil is essential for the detailed elucidation of ecosystem functions and services. Nevertheless, the global driving factors and distribution of soil DOC remain inadequately quantified due to the scarcity of large-scale data. Here, a comprehensive global database of 12807 soil DOC concentrations derived from 975 target papers in the literature was compiled. Detailed geographic locations, climate, and soil properties were also recorded as predictors of soil DOC. Machine learning techniques were employed to assess the relative importance of various predictors in the determination of soil DOC concentrations, which were subsequently extended for their prediction on a global scale. The worldwide soil DOC concentration spanned a wide range (0.04 to 7859 mg kg-1), averaging 222.78 mg kg-1. The 12 selected variables (including soil properties, month, climate, and ecosystem) explained 65 % of the variance in soil DOC concentrations. Elevation, soil clay, and soil organic carbon were three of the most important predictors. Global soil DOC concentration increased from the equator to the poles. The soil DOC stocks in the topsoil layer (0–30 cm) amounted to 12.17 Pg, with significant variations observed across different continents. These results are instrumental for informing strategies on soil management practices, ecosystem services, and the mitigation of climate change. Furthermore, our database can be combined with other carbon pools to explore the total soil carbon turnover and constrain Earth carbon models. The dataset is publicly available at https://doi.org/10.6084/m9.figshare.26379898 (Ren and Cai, 2024). [ABSTRACT FROM AUTHOR]

In response to escalating global climate change and its increasing impacts worldwide, this study investigates the consequences of extreme weather events, focusing on the unprecedented 2022 monsoon season in the Swat River basin of Pakistan. Record-breaking rainfall, exceeding the 1960–2021 averages by 7–8 %, triggered catastrophic debris flows and floods, aggravating low-income communities' challenges. The resulting financial instability severely affected millions, causing extensive damage to homes, crops, and transportation. The study employs a multidisciplinary approach, combining field investigations, remote sensing data interpretation, and numerical simulations to identify the factors contributing to debris flow incidents. Analysis of land cover changes reveals a decrease in grasslands and an increase in barren land, indicating the adverse effects of deforestation on the region. Topography and gully morphology are crucial in initiating debris flows, with steep gradients and shallow slope failures predominant. Numerical simulations show that debris flows reached high velocities of 18 m/s and depths of 40 m within 45 minutes. Two debris flows resulted in the formation of dams along the Swat River, intensifying subsequent floods. The study emphasizes the interplay of extreme rainfall and deforestation during the rainy season, rendering the region susceptible to debris flows and hindering restoration efforts. The findings underscore the urgent need for comprehensive disaster mitigation strategies. Recommendations include climate change mitigation, reforestation initiatives, and discouraging construction activities in flood-prone and debris flow-prone regions. The study advocates for enhanced early warning systems and rigorous land use planning to protect the environment and local communities, highlighting the imperative of proactive measures in the face of escalating climate challenges. Additionally, the study investigates the spatial distribution of various events and their consequences, including potential hydro-meteorological triggers, and how such events initiate processes that change mountain landscapes. It also assesses the degree to which the 2022 monsoon can be classified as abnormal. The combination of empirical evidence and practical insights presented in this study highlights research gaps and proposes routes toward attaining a comprehensive comprehension of monsoon-triggered geological hazards and consequences. [ABSTRACT FROM AUTHOR]

The impact of climate change on crops and agricultural yield is an actual threat while being a challenging issue due to the high complexity of factors that intervene at the local scale of the crop. Assessing it, requires the use of coupled models climate-phenology, meanwhile methods to identify management and genotypes suitable for local future conditions, in order to sustain adaptation strategies. We present the implementation and use of a new integrated climate-phenology adaptation support modeling system based on regional CORDEX climate models and the CERES Maize model from DSSAT platform, with new modules for optimal management and genotype identification using a hybrid method: deterministic modeling and -ML/ genetic algorithms. It was run as a regional pilot over Romania, operating in real-time in interaction with users, performing agro-climate projections (combination of fertilization, sowing date, soil) and providing best crop management simulated under climate change projections. Multi-model ensemble simulations for two climate scenarios RCP4.5 and RCP8.5 and twelve management scenarios show new results for the region. For the actual genotype we find a projected mean decrease in yield in both climate scenarios for all sowing dates and fertilization levels tested, response shown to be sensitive to initial soil parameters. This response was linked to two factors: a shorter growing season by up to 10 % and a loss of fertilization efficiency in a warmer climate. A warning points to results showing a narrowing of agro-management opportunities for crop yield but in opposite it is shown a significant role of optimal genotype-range identification that may provide crop solutions under climate change even in extreme years. Identifying best genotype under warmer climate along sets of six cross-parameter simulations show systematic lower values of the maximal yields, but emphasizes genotype windows of increases in the intermediate yield values in scenarios compared to actual climate. The highest harvest sensitivity to genotype is shown to be to changes in the thermal time to juvenil respectively to maturity stage under warmer climate. The results sustain using a deterministic coupled modeling system combined with data-driven modeling for identifying optimal adaptation including fertilization paths that contribute to climate change mitigation. [ABSTRACT FROM AUTHOR]

The interaction between forest and climate exhibits regional differences due to a variety of biophysical mechanisms. Observational and modeling studies have investigated the impacts of forested and non-forested areas on a single climate variable, but the influences of forest cover change on a combination of temperature and precipitation (e.g., drought) have not been explored, owing to the complex relationship between drought conditions and forests. In this study, we use historical forest and climate datasets to explore the relationship between forest cover fraction and drought from 1992–2018. A set of linear models and an analysis of variance approach are utilized to investigate the effect of forest cover change, precipitation and temperature on droughts across different timescales and climate zones. Our findings reveal that precipitation is the dominant factor (among the three factors) leading to drought in the equatorial, temperate and snow regions, while temperature controls drought in the arid region. The impact of forest cover changes on droughts varies under different precipitation and temperature quantiles. Precipitation modulates forest cover's impact on long-term drought in the arid region, while temperature modulates the impact of forest cover changes on both short- and long-term drought in the arid region as well as only on long-term drought in the temperate region. Forest cover can also modulate the impacts of precipitation and temperature on drought. High forest cover leads to a combined effect of precipitation and temperature on long-term drought in arid and snow regions, while precipitation is the only dominant factor in low forest cover conditions. In contrast, low forest cover triggers a strong combined effect of precipitation and temperature on drought in the temperate region. Our findings improve the understanding of the interaction between land cover change and the climate system and further assist decision-makers to modulate land management strategies in different regions in light of climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

The subalpine forests in the Qinghai-Tibet Plateau (QTP) act as carbon sinks in the context of climate change and ecosystem dynamics. In this study, we investigated the carbon sequestration function using the in-situ observations from an eddy covariance system for the subalpine forests. With two-year contiguous observations, the factors driving the seasonal variations in carbon sequestration potential were quantified. We first revealed the seasonal characteristics of carbon dynamics in the subalpine forests during the growing and dormant seasons, respectively. The diurnal carbon exchange exhibited significant fluctuations, as high as 10.78 μmol CO2 s-1 m-2 (12:30, autumn). The period from summer to autumn was identified as the peak in carbon sequestration rate in the subalpine forests. Subsequently, we explored the climatic factors influencing the carbon sequestration function. Photosynthetically active radiation (PAR) was found to be a major climatic factor driving the net ecosystem exchange (NEE) within the same season, significantly influencing forest growth and carbon absorption. Increasing altitude negatively impacts carbon absorption at the regional scale and the rising annual temperature significantly enhances carbon uptake, while the average annual precipitation shows a minor effect on NEE. At the annual scale, the observations at the subalpine forests demonstrated a strong carbon sequestration capability, with an average NEE of 389.03 g C m-2. Furthermore, we roughly assessed the carbon sequestration status of subalpine forests in the QTP. Despite challenges caused by climate change, these forests possess enormous carbon sequestration potential. Currently, they represent the most robust carbon sequestration ecosystem in the QTP. We conclude that enhancing the protection and management of subalpine forests under future climate change scenarios will positively impact global carbon cycling and contribute to climate change mitigation. Moreover, this study provides essential insights for understanding the carbon cycling mechanism in plateau ecosystems and global carbon balance. [ABSTRACT FROM AUTHOR]

Achieving climate targets requires mitigation against climate change, but also understanding of the response of land and ocean carbon systems. In this context, global soil carbon stocks and its response to environmental changes is key. This paper quantifies the global soil carbon feedback to changes in atmospheric CO2, and associated climate changes, for Earth system models (ESMs) in CMIP6. A standard approach is used to calculate carbon cycle feedbacks, defined here as soil specific carbon-concentration (βs) and carbon-climate (γs) feedback parameters. The sensitivity to CO2 is shown to dominate soil carbon changes at least up to a doubling of atmospheric CO2. However, the sensitivity of soil carbon to climate change is found to become an increasingly important source of uncertainty under higher atmospheric CO2 concentrations. [ABSTRACT FROM AUTHOR]

Earth system models suggest that anthropogenic climate change will influence marine phytoplankton over the coming century with light-limited regions becoming more productive and nutrient-limited regions less productive. Anthropogenic climate change can influence not only the mean state but also the internal variability around the mean state, yet little is known about how internal variability in marine phytoplankton will change with time. Here, we quantify the influence of anthropogenic climate change on internal variability in marine phytoplankton biomass from 1920 to 2100 using the Community Earth System Model 1 Large Ensemble (CESM1-LE). We find a significant decrease in the internal variability of global phytoplankton carbon biomass under a high emission (RCP8.5) scenario and heterogeneous regional trends. Decreasing internal variability in biomass is most apparent in the subpolar North Atlantic and North Pacific. In these high-latitude regions, bottom-up controls (e.g., nutrient supply, temperature) influence changes in biomass internal variability. In the biogeochemically critical regions of the Southern Ocean and the equatorial Pacific, bottom-up controls (e.g., light, nutrients) and top-down controls (e.g., grazer biomass) affect changes in phytoplankton carbon internal variability, respectively. Our results suggest that climate mitigation and adaptation efforts that account for marine phytoplankton changes (e.g., fisheries, marine carbon cycling) should also consider changes in phytoplankton internal variability driven by anthropogenic warming, particularly on regional scales. [ABSTRACT FROM AUTHOR]

Effective climate change mitigation necessitates swift societal transformations. Social tipping processes, where small triggers initiate qualitative systemic shifts, are potential key mechanisms instigating societal change. A necessary foundation for societal tipping processes is the creation of enabling conditions. Here we assess future sea-level rise estimates and social survey data within the framework of a social activation model to exemplify the enabling conditions for tipping processes. We find that in many countries, climate change concern is sufficient, the enabling conditions and opportunities for social activation already exist. Further, drawing upon the interrelation between climate change concern and anticipation of future sea level rise, we report three qualitative classes of tipping potential that are regionally clustered, with greatest potential for tipping in Western Pacific rim and East Asian countries. These findings propose a transformative pathway where climate change concern increases the social tipping potential, while extended anticipation time horizons can trigger the system towards an alternative trajectory of larger social activation for climate change mitigation. [ABSTRACT FROM AUTHOR]

We use 2019 TROPOMI satellite observations of atmospheric methane in an analytical inversion to quantify methane emissions from the Middle East and North Africa at up to ∼25 km × 25 km resolution, using spatially allocated national United Nations Framework Convention on Climate Change (UNFCCC) reports as prior estimates for the fuel sector. Our resulting best estimate of anthropogenic emissions for the region is 35 % higher than the prior bottom-up inventories (+ 103 % for gas, + 53 % for waste, + 49 % for livestock, -14 % for oil) with large variability across countries. Oil and gas account for 38 % of total anthropogenic emissions in the region. TROPOMI observations can effectively optimize and separate national emissions by sector for most of the 23 countries in the region, with 6 countries accounting for most of total anthropogenic emissions including Iran (5.3 (5.0–5.5) Tg a -1 ; best estimate and uncertainty range), Turkmenistan (4.4 (2.8–5.1) Tg a -1) , Saudi Arabia (4.3 (2.4–6.0) Tg a -1) , Algeria (3.5 (2.4–4.4) Tg a -1) , Egypt (3.4 (2.5–4.0) Tg a -1) , and Turkey (3.0 (2.0–4.1) Tg a -1). Most oil–gas emissions are from the production (upstream) subsector, but Iran, Turkmenistan, and Saudi Arabia have large gas emissions from transmission and distribution subsectors. We identify a high number of annual oil–gas emission hotspots in Turkmenistan, Algeria, and Oman and offshore in the Persian Gulf. We show that oil–gas methane emissions for individual countries are not related to production, invalidating a basic premise in the construction of activity-based bottom-up inventories. Instead, local infrastructure and management practices appear to be key drivers of oil–gas emissions, emphasizing the need for including top-down information from atmospheric observations in the construction of oil–gas emission inventories. We examined the methane intensity, defined as the upstream oil–gas emission per unit of methane gas produced, as a measure of the potential for decreasing emissions from the oil–gas sector and using as reference the 0.2 % target set by the industry. We find that the methane intensity in most countries is considerably higher than this target, reflecting leaky infrastructure combined with deliberate venting or incomplete flaring of gas. However, we also find that Kuwait, Saudi Arabia, and Qatar meet the industry target and thus show that the target is achievable through the capture of associated gas, modern infrastructure, and the concentration of operations. Decreasing methane intensities across the Middle East and North Africa to 0.2 % would achieve a 90 % decrease in oil–gas upstream emissions and a 26 % decrease in total anthropogenic methane emissions in the region, making a significant contribution toward the Global Methane Pledge. [ABSTRACT FROM AUTHOR]

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO 2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO 2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO 2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO 2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO 2 yr -1) in global land-use CO 2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO 2 yr -1 for the period 2000–2020, and NGHGIs, which estimate a sink of -1.9 GtCO 2 yr -1 in the same period. Most of the gap is found on forest land (3.5 GtCO 2 yr -1), with differences also for deforestation (2.4 GtCO 2 yr -1), for fluxes from other land uses (1.0 GtCO 2 yr -1) and to a lesser extent for fluxes from organic soils (0.2 GtCO 2 yr -1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (-6.4 GtCO 2 yr -1) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO 2 yr -1) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement. Data from this study are openly available online via the Zenodo portal (Grassi et al., 2023) at 10.5281/zenodo.7650360. [ABSTRACT FROM AUTHOR]

Seagrass meadows provide valuable socio-ecological ecosystem services, including a key role in climate change mitigation and adaption. Understanding the natural history of seagrass meadows across environmental gradients is crucial to deciphering the role of seagrasses in the global ocean. In this data collation, spatial and temporal patterns in seagrass meadow structure, biomass and production data are presented as a function of biotic and abiotic habitat characteristics. The biological traits compiled include measures of meadow structure (e.g. percent cover and shoot density), biomass (e.g. above-ground biomass) and production (e.g. shoot production). Categorical factors include bioregion, geotype (coastal or estuarine), genera and year of sampling. This dataset contains data extracted from peer-reviewed publications published between 1975 and 2020 based on a Web of Science search and includes 11 data variables across 12 seagrass genera. The dataset excludes data from mesocosm and field experiments, contains 14 271 data points extracted from 390 publications and is publicly available on the PANGAEA® data repository (10.1594/PANGAEA.929968; Strydom et al., 2021). The top five most studied genera are Zostera, Thalassia, Cymodocea, Halodule and Halophila (84 % of data), and the least studied genera are Phyllospadix, Amphibolis and Thalassodendron (2.3 % of data). The data hotspot bioregion is the Tropical Indo-Pacific (25 % of data) followed by the Tropical Atlantic (21 %), whereas data for the other four bioregions are evenly spread (ranging between 13 and 15 % of total data within each bioregion). From the data compiled, 57 % related to seagrass biomass and 33 % to seagrass structure, while the least number of data were related to seagrass production (11 % of data). This data collation can inform several research fields beyond seagrass ecology, such as the development of nature-based solutions for climate change mitigation, which include readership interested in blue carbon, engineering, fisheries, global change, conservation and policy. [ABSTRACT FROM AUTHOR]

Human actions and climate change have drastically altered river flows across the world, resulting in adverse effects on riverine ecosystems. Environmental flows (EFs) have emerged as a prominent tool for safeguarding the riverine ecosystems, but at the global scale, the assessment of EFs is associated with high uncertainty related to the hydrological data and EF methods employed. Here, we present a novel, in-depth global EF assessment using environmental flow envelopes (EFEs). Sub-basin-specific EFEs are determined for approximately 4400 sub-basins at a monthly time resolution, and their derivation considers the methodological uncertainties related to global-scale EF studies. In addition to a lower bound of discharge based on existing EF methods, we introduce an upper bound of discharge in the EFE. This upper bound enables areas to be identified where streamflow has substantially increased above natural levels. Further, instead of only showing whether EFs are violated over a time period, we quantify, for the first time, the frequency, severity, and trends of EFE violations during the recent historical period. Discharge was derived from global hydrological model outputs from the ISIMIP 2b ensemble. We use pre-industrial (1801–1860) quasi-natural discharge together with a suite of hydrological EF methods to estimate the EFEs. We then compare the EFEs with recent historical (1976–2005) discharge to assess the violations of the EFE. These violations most commonly manifest as insufficient streamflow during the low-flow season, with fewer violations during the intermediate-flow season, and only a few violations during the high-flow season. The EFE violations are widespread and occur in half of the sub-basins of the world during more than 5 % of the months between 1976 and 2005, which is double compared with the pre-industrial period. The trends in EFE violations have mainly been increasing, which will likely continue in the future with the projected hydroclimatic changes and increases in anthropogenic water use. Indications of increased upper extreme streamflow through EFE upper bound violations are relatively scarce and dispersed. Although local fine-tuning is necessary for practical applications, and further research on the coupling between quantitative discharge and riverine ecosystem responses at the global scale is required, the EFEs provide a quick and globally robust way of determining environmental flow allocations at the sub-basin scale to inform global research and policies on water resources management. [ABSTRACT FROM AUTHOR]

Despite an increasing attention on the role of land in meeting countries' climate pledges under the Paris Agreement, the range of estimates of carbon fluxes from land use, land-use change, and forestry (LULUCF) in available databases is very large. A good understanding of the LULUCF data reported by countries under the United Nations Framework Convention on Climate Change (UNFCCC) – and of the differences with other datasets based on country-reported data – is crucial to increase confidence in land-based climate change mitigation efforts. Here we present a new data compilation of LULUCF fluxes of carbon dioxide (CO 2) on managed land, aiming at providing a consolidated view on the subject. Our database builds on a detailed analysis of data from national greenhouse gas inventories (NGHGIs) communicated via a range of country reports to the UNFCCC, which report anthropogenic emissions and removals based on the IPCC (Intergovernmental Panel on Climate Change) methodology. Specifically, for Annex I countries, data are sourced from annual GHG inventories. For non-Annex I countries, we compiled the most recent and complete information from different sources, including national communications, biennial update reports, submissions to the REDD + (reducing emissions from deforestation and forest degradation) framework, and nationally determined contributions. The data are disaggregated into fluxes from forest land, deforestation, organic soils, and other sources (including non-forest land uses). The CO 2 flux database is complemented by information on managed and unmanaged forest area as available in NGHGIs. To ensure completeness of time series, we filled the gaps without altering the levels and trends of the country reported data. Expert judgement was applied in a few cases when data inconsistencies existed. Results indicate a mean net global sink of -1.6 Gt CO 2 yr -1 over the period 2000–2020, largely determined by a sink on forest land (-6.4 Gt CO 2 yr -1), followed by source from deforestation (+4.4 Gt CO 2 yr -1), with smaller fluxes from organic soils (+0.9 Gt CO 2 yr -1) and other land uses (-0.6 Gt CO 2 yr -1). Furthermore, we compare our NGHGI database with two other sets of country-based data: those included in the UNFCCC GHG data interface, and those based on forest resources data reported by countries to the Food and Agriculture Organization of the United Nations (FAO) and used as inputs into estimates of GHG emissions in FAOSTAT. The first dataset, once gap filled as in our study, results in a net global LULUCF sink of -5.4 Gt CO 2 yr -1. The difference with the NGHGI database is in this case mostly explained by more updated and comprehensive data in our compilation for non-Annex I countries. The FAOSTAT GHG dataset instead estimates a net global LULUCF source of +1.1 Gt CO 2 yr -1. In this case, most of the difference to our results is due to a much greater forest sink for non-Annex I countries in the NGHGI database than in FAOSTAT. The difference between these datasets can be mostly explained by a more complete coverage in the NGHGI database, including for non-biomass carbon pools and non-forest land uses, and by different underlying data on forest land. The latter reflects the different scopes of the country reporting to FAO, which focuses on area and biomass, and to UNFCCC, which explicitly focuses on carbon fluxes. Bearing in mind the respective strengths and weaknesses, both our NGHGI database and FAO offer a fundamental, yet incomplete, source of information on carbon-related variables for the scientific and policy communities, including under the Global stocktake. Overall, while the quality and quantity of the LULUCF data submitted by countries to the UNFCCC significantly improved in recent years, important gaps still remain. Most developing countries still do not explicitly separate managed vs. unmanaged forest land, a few report implausibly high forest sinks, and several report incomplete estimates. With these limits in mind, the NGHGI database presented here represents the most up-to-date and complete compilation of LULUCF data based on country submissions to UNFCCC. Data from this study are openly available via the Zenodo portal (Grassi et al., 2022), at 10.5281/zenodo.7190601. [ABSTRACT FROM AUTHOR]

Building on CMIP6 climate simulations, updated global and regional observations, and recently introduced statistical methods, we provide an updated assessment of past and future warming over France. Following the IPCC AR6 and recent global-scale studies, we combine model results with observations to constrain climate change at the regional scale. Over mainland France, the forced warming in 2020 with respect to 1900–1930 is assessed to be 1.66 [1.41 to 1.90] ∘ C, i.e., in the upper range of the CMIP6 estimates, and is almost entirely human-induced. A refined view of the seasonality of this past warming is provided through updated daily climate normals. Projected warming in response to an intermediate emission scenario is assessed to be 3.8 ∘ C (2.9 to 4.8 ∘ C) in 2100 and rises up to 6.7 [5.2 to 8.2] ∘ C in a very high emission scenario, i.e., substantially higher than in previous ensembles of global and regional simulations. Winter warming and summer warming are expected to be about 15 % lower than and 30 % higher than the annual mean warming, respectively, for all scenarios and time periods. This work highlights the importance of combining various lines of evidence, including model and observed data, to deliver the most reliable climate information. This refined regional assessment can feed adaptation planning for a range of activities and provides additional rationale for urgent climate action. Code is made available to facilitate replication over other areas or political entities. [ABSTRACT FROM AUTHOR]

The increasing rates of CO 2 due to anthropogenic activities are causing important potential climate threats for the Mediterranean Sea: ocean acidification and warming. In this region, two seagrass species, Posidonia oceanica and Cymodocea nodosa, can play a crucial role in climate change mitigation. Seagrasses can act as carbon sinks, buffer lowering pH values during the day and storing carbon in the sediment underneath their meadows. However, available data documenting these processes are scattered and collected using different methodologies, which makes its interpretation and generalization very challenging. In this study, we analyzed published and unpublished data (collected for this study) on seagrass community metabolism to compare two methodologies, benthic chambers and multiparametric sensors, and evaluate trends through time for these two species. Furthermore, we analyzed seasonal trends of both seagrass species' metabolic rates and their variation between the eastern and western Mediterranean basins. Most evaluated meadows, 80.9 %, were autotrophic. Calculated metabolic rates differ between methodologies, with multiparametric sensors estimating rates almost an order of magnitude higher, 143.22±28.21 (SE) mmol O 2 m -2 d -1 for net community production (NCP) compared to an average of 18.75±3.80 (SE) mmol O 2 m -2 d -1 for measurements with benthic chambers. However, sensors are not able to differentiate between habitats and only useful to assess seagrass metabolism at a broader community level, whereas benthic chambers are capable of evaluating rates at the species level and confirm that P. oceanica is more productive compared to C. nodosa. We found similar metabolic rates in the eastern and western Mediterranean regions for P. oceanica with the benthic-chamber technique and higher NCP in the west based on sensor measurements. [ABSTRACT FROM AUTHOR]

Producing targeted climate information at the local scale, including major sources of climate change projection uncertainty for diverse emissions scenarios, is essential to support climate change mitigation and adaptation efforts. Here, we present the first chain of computationally efficient Earth system model (ESM) emulators that allow for the translation of any greenhouse gas emission pathway into spatially resolved annual mean temperature anomaly field time series, accounting for both forced climate response and natural variability uncertainty at the local scale. By combining the global mean, emissions-driven emulator MAGICC with the spatially resolved emulator MESMER, ESM-specific and constrained probabilistic emulated ensembles can be derived. This emulator chain can hence build on and extend large multi-ESM ensembles such as the ones produced within the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The main extensions are threefold. (i) A more thorough sampling of the forced climate response and the natural variability uncertainty is possible, with millions of emulated realizations being readily created. (ii) The same uncertainty space can be sampled for any emission pathway, which is not the case in CMIP6, where only a limited number of scenarios have been explored and some of the most societally relevant strong mitigation scenarios have been run by only a small number of ESMs. (iii) Other lines of evidence to constrain future projections, including observational constraints, can be introduced, which helps to refine projected ranges beyond the multi-ESM ensembles' estimates. In addition to presenting results from the coupled MAGICC–MESMER emulator chain, we carry out an extensive validation of MESMER, which is trained on and applied to multiple emission pathways for the first time in this study. By coupling MAGICC and MESMER, we pave the way for rapid assessments of any emission pathway's regional climate change consequences and the associated uncertainties. [ABSTRACT FROM AUTHOR]

Climate change has altered precipitation and temperature patterns in the tropical Andes. As a result, tropical glaciers have retreated significantly over the past 50 years and have even disappeared in some areas. Andean peatlands, one of the most important Andean carbon reservoirs, also seem to be affected by these climate changes, since glaciers have been recognized as one of their vital water sources. Here, we point out the important role of Andean peatlands on carbon accumulation rates (CAR), one of the highest in the world, and the impact of climate on carbon storage over the last 65 years, using four peat cores. The peat cores were radiocarbon-dated and ages were post-bomb calibrated and chronological models indicated basal ages (30 cm depth) ranging from 1957 to 1972 CE, where accumulation rates reached up 1.7 cm yr-1. For both peatlands, carbon accumulation rates are high (mean of 470 and 220 g C m-2 yr- 1 at APA 1 and APA 2 sites, respectively) and can reach up to 1010 g C m-2 yr-1. Distichia muscoides is the dominant species in the Peruvian Central Andes peatlands and the high CAR, among other factors, is a characteristic of this species. Our results point out that a marked decrease of CAR after the early 1980s at both peatlands is likely related to an increase in annual temperature, which is responsible for the retreat of glaciers. We use a new high- resolution proxy (Skrzypek et al., 2011) based on the δ13C of Distichia along the cores to evaluate the temperature variability at the site. We observed a general trend of increase in the reconstructed temperature from both studied peatlands from 1.9 to 2 ºC for the period 1970-2015 CE. Comparison with air temperature data from the NCEP-NCAR reanalysis for the higher resolution cores shows a good relationship and an increase of 2.15 °C for the same period. Temperature increase may directly affect CAR by an increase in organic matter degradation rates. The decrease in CAR during the period of study may also be due to a decrease in melt water inflow generated by the retreat of glaciers that have almost disappeared today in the catchments as a consequence of regional warming. Our findings emphasize that marked changes in carbon accumulation rates demonstrate the high ecological sensitivity of tropical high-Andean peatlands, endangering their outstanding role in the regional (and even global) C cycle as large C sinks that contribute to the mitigation of global climate change. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas, and its concentration is continuously increasing, mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and for designing mitigation strategies aimed at stabilizing CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of the column-averaged dry-air mole fraction of CO2 , i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2), and the net primary productivity (NPP) provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the anthropogenic CO2 emissions using the Generalized Regression Neural Network (GRNN) over East and West Asia. OCO-2 XCO2 , MODIS NPP, and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variability. The XCO2 anomaly, NPP, and ODIAC emission datasets from 2015 to 2018 were then used to train the GRNN model, and, finally, the anthropogenic CO2 emissions were estimated for 2019 based on the NPP and XCO2 anomalies derived for the same year. The estimated and the ODIAC CO2 emissions were compared, and the results showed good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional-scale anthropogenic CO2 emissions, and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets. [ABSTRACT FROM AUTHOR]

While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems. [ABSTRACT FROM AUTHOR]

Sequestration of soil organic carbon (SOC) on cropland has been proposed as a climate change mitigation strategy to reduce global greenhouse gas (GHG) concentrations in the atmosphere, which in particular is needed to achieve the targets proposed in the Paris Agreement to limit the increase in atmospheric temperature to well below 2 ∘ C. We analyze the historical evolution and future development of cropland SOC using the global process-based biophysical model LPJmL, which was recently extended by a detailed representation of tillage practices and residue management (version 5.0-tillage2). We find that model results for historical global estimates for SOC stocks are at the upper end of available literature, with ∼2650 Pg C of SOC stored globally in the year 2018, ∼170 Pg C of which is stored in cropland soils. In future projections, assuming no further changes in current cropland patterns and under four different management assumptions with two different climate forcings, RCP2.6 and RCP8.5, results suggest that agricultural SOC stocks decline in all scenarios, as the decomposition of SOC outweighs the increase in carbon inputs into the soil from altered management practices. Different climate change scenarios, as well as assumptions on tillage management, play a minor role in explaining differences in SOC stocks. The choice of tillage practice explains between 0.2 % and 1.3 % of total cropland SOC stock change in the year 2100. Future dynamics in cropland SOC are most strongly controlled by residue management: whether residues are left on the field or harvested. We find that on current cropland, global cropland SOC stocks decline until the end of the century by only 1.0 % to 1.4 % if residue retention management systems are generally applied and by 26.7 % to 27.3 % in the case of residue harvest. For different climatic regions, increases in cropland SOC can only be found for tropical dry, warm temperate moist, and warm temperate dry regions in management systems that retain residues. [ABSTRACT FROM AUTHOR]

Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design. [ABSTRACT FROM AUTHOR]

The detection of methane emissions from industrial activities has been identified as an effective climate change mitigation strategy. These industrial emissions, such as from oil and gas (O&G) extraction and coal mining, typically occur as large plumes of highly concentrated gas. Different satellite missions have recently shown potential to map such methane plumes from space. In this work, we report on the great potential of the WorldView-3 (WV-3) satellite mission for methane mapping. This relies on its unique very high spatial resolution (up to 3.7 m) data in the shortwave infrared part of the spectrum, which is complemented by a good spectral sampling of the methane absorption feature at 2300 nm and a high signal to noise ratio. The proposed retrieval methodology is based on the calculation of methane concentration enhancements from pixel-wise estimates of methane transmittance at WV-3 SWIR band 7 (2235-2285 nm), which is positioned at a highly sensitive methane absorption region. A sensitivity analysis based on end-to-end simulations has helped to understand retrieval errors and detection limits. The results have shown the good performance of WV-3 for methane mapping, especially over bright and homogeneous areas. The potential of WV-3 for methane mapping has been further tested with real data, which has led to the detection of 26 independent point emissions over different methane hot spot regions such as the O&G extraction fields in Algeria and Turkmenistan, and the Shanxi coal mining region in China. In particular, the detection of very small leaks (<100 kg/h) from oil pipelines in Turkmenistan shows the game-changing potential of WV-3 to map industrial methane emissions from space. [ABSTRACT FROM AUTHOR]

Producing targeted climate information at the local scale, including major sources of climate change projection uncertainty for diverse emissions scenarios, is essential to support climate change mitigation and adaptation efforts. Here, we present the first chain of computationally efficient Earth System Model (ESM) emulators allowing to rapidly translate greenhouse gas emission pathways into spatially resolved annual-mean temperature anomaly field time series, accounting for both forced climate response and natural variability uncertainty at the local scale. By combining the global-mean, emissions-driven emulator MAGICC with the spatially resolved emulator MESMER, ESM-specific as well as constrained probabilistic emulated ensembles can be derived. This emulation chain can hence build on and extend large multi-ESM ensembles such as the ones produced within the 6th phase of the Coupled Model Intercomparison Project (CMIP6). The main extensions are threefold. (i) A more thorough sampling of the forced climate response and the natural variability uncertainty is possible with millions of emulated realizations being readily created. (ii) The same uncertainty space can be sampled for any emission pathway, which is not the case in CMIP6, where some of the most societally relevant strong mitigation scenarios have been run by only a small number of ESMs. (iii) Other lines of evidence to constrain future projections, including observational constraints, can be introduced, which helps to refine projected future ranges beyond the multi-ESM ensemble's estimates. In addition to presenting results from the coupled MAGICC-MESMER emulator chain, we carry out an extensive validation of MESMER, which is trained on and applied to multiple emission pathways for the first time in this study. The newly developed MAGICC-MESMER coupled emulator will allow unprecedented assessments of the implications of manifold emissions pathways at regional scale. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas and its concentration is continuously increasing mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and designing mitigation strategies aimed at stabilizing the CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of column-averaged dry-air mole fraction of CO2 i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory 2 (OCO-2) to estimate the anthropogenic CO2 emissions using Generalized Regression Neural Network over East and West Asia. OCO-2 XCO2 and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015-2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variabilities. Then the XCO2 anomaly and ODIAC emission datasets from 2015 to 2018 were used to train the GRNN model, and finally, the anthropogenic CO2 emissions were estimated for 2019 based on the XCO2 anomalies derived for the same year. The XCO2-based estimated and the ODIAC actual CO2 emissions were compared and the results showed a good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional scale anthropogenic CO2 emissions and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets. [ABSTRACT FROM AUTHOR]

Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and thereby will directly influence future PV power generation. We use scenarios from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel dependent (SSP5-8.5) pathway, to quantify climate risk for solar PV in Europe simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, a decrease in clear-sky radiation is overcompensated by a decrease in cloud cover in SSP5-8.5, resulting in an increase of all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to effects anticipated for wind energy, we report an increase of the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Based on the most recent climate simulations, this research thus supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatio-temporal generation structure are to be expected and should be included in power system design. [ABSTRACT FROM AUTHOR]

The 4 per 1000 initiative aims to maintain and increase soil organic carbon (SOC) stocks for soil fertility, food security, and climate change adaptation and mitigation. One way to enhance SOC stocks is to increase carbon (C) inputs to the soil. In this study, we assessed the amount of organic C inputs that are necessary to reach a target of SOC stocks increase by 4 ‰yr-1 on average, for 30 years, at 14 long-term agricultural sites in Europe. We used the Century model to simulate SOC stocks and assessed the required level of additional C inputs to reach the 4 per 1000 target at these sites. Then, we analyzed how this would change under future scenarios of temperature increase. Initial stocks were simulated assuming steady state. We compared modeled C inputs to different treatments of additional C used on the experimental sites (exogenous organic matter addition and one treatment with different crop rotations). The model was calibrated to fit the control plots, i.e. conventional management without additional C inputs from exogenous organic matter or changes in crop rotations, and was able to reproduce the SOC stock dynamics. We found that, on average among the selected experimental sites, annual C inputs will have to increase by 43.15 ± 5.05 %, which is 0.66 ± 0.23 MgCha-1yr-1 (mean ± standard error), with respect to the initial C inputs in the control treatment. The simulated amount of C input required to reach the 4 ‰ SOC increase was lower than or similar to the amount of C input actually used in the majority of the additional C input treatments of the long-term experiments. However, Century might be overestimating the effect of additional C inputs on SOC stocks. At the experimental sites, we found that treatments with additional C inputs were increasing by 0.25 % on average. This means that the C inputs required to reach the 4 per 1000 target might actually be much higher. Furthermore, we estimated that annual C inputs will have to increase even more due to climate warming, that is 54 % more and 120 % more for a 1 and 5 ∘Cpage3982 warming, respectively. We showed that modeled C inputs required to reach the target depended linearly on the initial SOC stocks, raising concern on the feasibility of the 4 per 1000 objective in soils with a higher potential contribution to C sequestration, that is soils with high SOC stocks. Our work highlights the challenge of increasing SOC stocks at a large scale and in a future with a warmer climate. [ABSTRACT FROM AUTHOR]

Sequestration of soil organic carbon (SOC) on cropland has been proposed as a climate change mitigation strategy to reduce global greenhouse gas (GHG) concentrations in the atmosphere, which is in particular needed to achieve the targets proposed in the Paris Agreement to limit the increase in atmospheric temperature to well below 2 °C. We here analyze the historical evolution and future development of cropland SOC using the global process-based biophysical model LPJmL, which was recently extended by a detailed representation of tillage practices and residues management (version 5.0–tillage2). We find that model results for historical global estimates for SOC stocks are at the upper end of available literature, with ~2650 Pg C of SOC stored globally in the year 2018, of which ~170 Pg C are stored in cropland soils. In future projections, assuming no further changes in current cropland patterns and under four different management assumptions with two different climate forcings, RCP2.6, and RCP8.5, results suggest that agricultural SOC stocks decline in all scenarios, as the decomposition of SOC outweighs the increase of carbon inputs into the soil from altered management practices. Different climate-change scenarios, as well as assumptions on tillage management, play a minor role in explaining differences in SOC stocks. The choice of tillage practice explains between 0.2% and 1.3% of total cropland SOC stock change in the year 2100. Future dynamics in cropland SOC are most strongly controlled by residue management, whether residues are left on the field or harvested. We find that on current cropland, global cropland SOC stocks decline until the end of the century by only 1.0% to 1.4% if residue-retention management systems are generally applied and by 26.7% to 27.3% in case of residues harvest. For different climatic regions, increases in cropland SOC can only be found for tropical dry, warm temperate moist, and warm temperate dry regions in management systems that retain residues. [ABSTRACT FROM AUTHOR]

Assessments of climate change impacts on runoff regimes are essential to climate change adaptation and mitigation planning. Changing runoff regimes and thus changing seasonal patterns of water availability strongly influence various economic sectors such as agriculture, energy production, and fishery and also affect river ecology. In this study, we use new transient hydrological scenarios driven by the most up-to-date local climate projections for Switzerland, the Swiss Climate Change Scenarios. These provide detailed information on changes in runoff regimes and their time of emergence for 93 rivers in Switzerland under three Representative Concentration Pathways (RCPs): RCP2.6, RCP4.5, and RCP8.5. These transient scenarios also allow changes to be framed as a function of global mean temperature. The new projections for seasonal runoff changes largely confirm the sign of changes in runoff from previous hydrological scenarios with increasing winter runoff and decreasing summer and autumn runoff. Spring runoff is projected to increase in high-elevation catchments and to decrease in lower-lying catchments. Despite the increases in winter and some increases in spring, the annual mean runoff is projected to decrease in most catchments. Compared to lower-lying catchments, runoff changes in high-elevation catchments (above 1500 m a.s.l.) are larger in winter, spring, and summer due to the large influence of reduced snow accumulation and earlier snowmelt and glacier melt. The changes in runoff and the agreement between climate models on the sign of change both increase with increasing global mean temperatures and higher-emission scenarios. This amplification highlights the importance of climate change mitigation. The time of emergence is the time when the climate signal emerges significantly from natural variability. Under RCP8.5, times of emergence were found early, before the period 2036–2065, in winter and summer for catchments with mean altitudes above 1500 m a.s.l. Significant changes in catchments below 1500 m a.s.l. emerge later in the century. Not all catchments show significant changes in the distribution of seasonal means; thus, no time of emergence could be determined in these catchments. Furthermore, the significant changes of seasonal mean runoff are not persistent over time in some catchments due to nonlinear changes in runoff. [ABSTRACT FROM AUTHOR]

The increasing rates of CO2 due to anthropogenic activities are causing important potential climate threats for the Mediterranean Sea: ocean acidification and warming. In this region, two seagrass species, Posidonia oceanica and Cymodocea nodosa can play a crucial role in climate change mitigation. Through their metabolic activity, they can act as carbon sinks; buffer lowering pH values during the day and store carbon in the sediment underneath their meadows. In this study we analyse the metabolism synthesized from published data on seagrass community metabolism and from own results to evaluate trends through time of these two species comparing two methodologies: benthic chambers and multiparametric sensors. Furthermore, we analysed seasonal trends of both seagrass species' metabolic rates and their variation between the Eastern and Western Mediterranean basins, with no significant results despite the clear visual trends. Our analysis revealed that there are significant differences between methodologies, with multiparametric sensors estimating higher rates, but unable to differentiate between habitats and useful to assess seagrass metabolism at a community level whereas benthic chambers are capable to evaluate rates at a seagrass species level. We found significant differences between the two Mediterranean regions for both methodologies, with highest rates of Net Community Production found in the Easter basin. At a species level, we found that Posidonia was more productive compared to Cymodocea. Furthermore, 86.7 % of the metabolic values reflected that the meadows were acting as carbon sinks in the Western basin. [ABSTRACT FROM AUTHOR]

Future climate change projections, impacts, and mitigation targets are directly affected by how sensitive Earth's global mean surface temperature is to anthropogenic forcing, expressed via the climate sensitivity (S) and transient climate response (TCR). However, the S and TCR are poorly constrained, in part because historic observations and future climate projections consider the climate system under different response timescales with potentially different climate feedback strengths. Here, we evaluate S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available since the mid-20th century, to constrain a model with independent climate feedback components acting over multiple response timescales. Adopting a Bayesian approach, our prior uses a constrained distribution for the instantaneous Planck feedback combined with wide-ranging uniform distributions of the strengths of the fast feedbacks (acting over several days) and multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5–95 % range) ∘C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5) ∘C on a 20-year response timescale to S of 2.3 (1.4 to 6.4) ∘C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with. [ABSTRACT FROM AUTHOR]

Water infrastructure development is crucial for driving economic growth in the developing countries of the Mekong. Yet it may also alter existing hydrological and flood conditions, with serious implications for water management, agricultural production and ecosystem services, especially in the floodplain regions. Our current understanding of the hydrological and flood pattern changes associated with infrastructural development still contain several knowledge gaps, such as the consideration of overlooked prospective drivers, and the interactions between multiple drivers. This research attempts to conduct a cumulative impact assessment of flood changes in the Cambodian part of the Mekong floodplains. The developmental activity of six central sectors (hydropower, irrigation, navigation, flood protection, agricultural land use and water use) as well as climate change were considered in our modelling analysis. Our results show that the monthly, sub-seasonal, and seasonal hydrological regimes will be subject to substantial alterations under the 2020 planned development scenario, and even larger alterations under the 2040 planned development scenario. The degree of hydrological alteration under the 2040 planned development is somewhat counteracted by the effect of climate change, as well as the removal of mainstream dams in the Lower Mekong Basin and hydropower mitigation investments. The likely impact of decreasing water discharge in the early wet season (up to -34 %) will pose a critical challenge to rice production, whereas the likely increase in water discharge in the mid-dry season (up to +54 %) indicates improved water availability for coping with drought stresses and sustaining environmental flow. At the same time, these changes would have drastic impacts on total flood extent, which is projected to decline up to -18 %, having potentially negative impacts on floodplain productivity whilst at the same time reducing the flood risk to the area. Our findings urge the timely establishment of adaptation and mitigation strategies to manage such future environmental alterations in a sustainable manner. [ABSTRACT FROM AUTHOR]

Drought is a sustained period of below-normal water availability. It is a recurring and worldwide phenomenon, but the Mediterranean basin is seen as a very vulnerable environment in this perspective and understanding historical drought conditions in this area is necessary to plan mitigation strategies to further face future climate change impacts. The reported research was aimed at the description of drought conditions and evolution for the Campania region (Southern Italy), assessed by the analysis of an in-situ measurement database which covers a centennial period from 1918-2019. SPI time series were reconstructed for different accumulation time scales (from 3 to 48 months) and the Modified Man Kendall and Sen’s test were applied to identify SPI changes over time. SPI time series were mostly affected by a negative trend, significant for a very large area of the region, particularly evident for the accumulation scales larger than 12 months. Mean drought duration (MDD), severity (MDS) and peak (MDP) were furthermore investigated for both moderate (SPI = -1) and extremely severe conditions (SPI = -2). The accumulation scale affected the drought features, with longer duration and larger severity associated to the larger accumulation scales. Drought characteristics spatial patterns were not congruent for the different SPI time scales: if duration and severity were larger in the southern areas, peaks appeared mostly severe in the northern areas of the region. Extremely severe events were featured by lower durations and larger severity compared to the moderate drought events but were very less frequent (over 75% less then) and did not appeared to be focused on specific areas of the region. [ABSTRACT FROM AUTHOR]

The forest ecosystems are already responding to increased CO2 concentrations and changing environmental conditions. These ongoing developments affect how societies can utilise and benefit from the woodland areas in the future, be it e.g. climate change mitigation as carbon sinks, lumber for wood industry or preserved for nature tourism and recreational activities. We assess the effect and the relative magnitude of different uncertainty sources in ecosystem model simulations from the year 1980 to 2100 for two Finnish boreal forest sites. The models used in this study are the land ecosystem model JSBACH and the forest growth model PREBAS. The considered uncertainty sources for both models are model parameters, four prescribed climates and two RCP (Representative Concentration Pathway) scenarios. PREBAS simulations also include an additional RCP scenario and two forest management actions. We assess the effect of these sources at four different stages of the simulations on several ecosystem indicators of climate change, e.g. gross primary production (GPP), ecosystem respiration, soil moisture, recurrence of drought, length of the vegetation active period (VAP), length of the snow melting period and the stand volume. The climate model uncertainty remains roughly the same throughout the simulations and is overtaken by the RCP scenario impact halfway through the experiment. The management actions are the most dominant uncertainty factors for Hyytiälä and as important as RCP scenarios at the end of the simulations, but contribute only half as much for Sodankylä. The parameter uncertainty is the most elusive to estimate due to non-linear and adverse effects on the simulated ecosystem indicators. [ABSTRACT FROM AUTHOR]

Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. Future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human land-use change can affect the climate system through bio-geophysical and bio-geochemical effects. To investigate these interrelationships, we developed MIROC-INTEG1 (MIROC INTEGrated terrestrial model version 1), an integrated model that combines the global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land use models. In this paper, we introduce the details and interconnections of the sub-models of MIROC-INTEG1, compare historical simulations with observations, and identify the various interactions between sub-models. MIROC-INTEG1 makes it possible to quantitatively evaluate the feedback processes or nexus between climate, water resources, crop production, land use, and ecosystem, and to assess the risks, trade-offs and co-benefits associated with future climate change and prospective mitigation and adaptation policies. [ABSTRACT FROM AUTHOR]

In 2015, El Niño caused severe droughts in equatorial Asia (EA). The severe droughts enhanced fire activities in the dry seasons, leading to massive fire emissions of CO2 and aerosols. Using large event attribution ensembles of the MIROC5 atmospheric global climate model, we suggest that historical anthropogenic warming increased the chances of meteorological droughts exceeding the 2015 observations in the EA area. Large probability increases in stronger droughts than the 2015 event are found in the ensemble simulations of 1.5 °C and 2.0 °C global warming according to the Paris Agreement goals. Further drying is projected in the 3.0 °C ensemble. We combine these experiments and empirical functions between precipitation, burned area, and fire emissions of CO2 and PM2.5. Increases in the chances of the burned area and the emissions of CO2 and PM2.5 exceeding the 2015 observations due to anthropogenic climate change in the past are not significant. In contrast, there are significant increases in the burned area and CO2 and PM2.5 emissions even if the 1.5 °C and 2.0 °C goals are achieved. If global warming reaches 3.0 °C, as is expected from the current mitigation policies of nations, the chances of the burned area, CO2 and PM2.5 emissions exceeding the 2015 observed values become approximately 100 %, at least in the single model ensembles. We also compare changes in fire CO2 emissions due to climate changes and the land-use CO2 emission scenarios of five shared socio-economic pathways, where the climate change effects on fire are not considered. There are two main implications. First, in a national policy context, future EA climate policy will need to consider these climate change effects regarding both mitigation and adaptation aspects. Second, the consideration of fire increases would change global CO2 emissions and the mitigation strategy, which suggests that future climate change mitigation studies should take these factors into account. [ABSTRACT FROM AUTHOR]

Forest ecosystems play an important role in the global climate system, and are thus intensively discussed in the context of climate change mitigation. Over the past decades temperate forests were a carbon (C) sink to the atmosphere. However, it remains unclear to which degree this C uptake is driven by a recovery from past disturbances vs. ongoing climate warming, inducing high uncertainty regarding the future temperate forest C sink. Here our objectives were (i) to investigate legacies within the natural disturbance regime by empirically analyzing two disturbance episodes affecting the same landscape 90 years apart, and (ii) to unravel the effects of past disturbances and future climate on 21st century forest C uptake by means of simulation modelling. We collected historical data from archives to reconstruct vegetation and disturbance history of a forest landscape in the Austrian Alps from 1905 to 2013. The effect of past legacies and future climate was determined by simulating 32 different combinations of past disturbances (including natural disturbances and management) and future climate scenarios. We found only moderate spatial overlap between two episodes of wind and bark beetle disturbance affecting the landscape in the early 20th and 21st century, respectively. The future forest C sink was driven by past disturbances, while climate change reduced forest C uptake. Historic management (and its cessation) had a considerably stronger influence on the future C balance than the natural disturbance episodes of the past. We conclude that neglecting disturbance legacies can substantially bias assessments of future forest dynamics. [ABSTRACT FROM AUTHOR]

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (~biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (T-D, exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories, and data-driven approaches (B-U, including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003-2012 decade, global methane emissions are estimated by T-D inversions at 558 & Tg & CH4 & yr-1 (range [540-568]). About 60 & % of global emissions are anthropogenic (range [50-65 & %]). B-U approaches suggest larger global emissions (736 & Tg & CH4 & yr-1 [596-884]) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the T-D budget, it is likely that some of the individual emissions reported by the B-U approaches are overestimated, leading to too large global emissions. Latitudinal data from T-D emissions indicate a predominance of tropical emissions (~64 & % of the global budget, < & 30° & N) as compared to mid (~32 & %, 30° & N-60° & N) and high northern latitudes (~ & 4 & %, 60° & N-90° & N). T-D inversions consistently infer lower emissions in China (~58 & Tg & CH4 & yr-1 [51-72], -14 & %) and higher emissions in Africa (86 & Tg & CH4 & yr-1 [73-108], +19 & %) than B-U values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for T-D inversions than for B-U inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute for 30-40 & % on the estimated range for wetland emissions. Other priorities for improving the methane budget include: i) the development of process-based models for inland-water emissions, ii) the intensification of methane observations at local scale (flux measurements) to constrain B-U land surface models, and at regional scale (surface networks and satellites) to constrain T-D inversions, iii) improvements in the estimation of atmospheric loss by OH, and iv) improvements of the transport models integrated in T-D inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/Global_Methane_Budget_2016). [ABSTRACT FROM AUTHOR]

A 180.17m ice core was drilled at Aurora Peak in the central part of the Alaska Range, Alaska, in 2008 to allow reconstruction of centennial-scale climate change in the northern North Pacific. The 10m depth temperature in the borehole was -2.2 °C, which corresponded to the annual mean air temperature at the drilling site. In this ice core, there were many melt-refreeze layers due to high temperature and/or strong insolation during summer seasons. We analyzed stable hydrogen isotopes (δD) and chemical species in the ice core. The ice core age was determined by annual counts of δD and seasonal cycles of Na+, and we used reference horizons of tritium peaks in 1963 and 1964, major volcanic eruptions of Mount Spurr in 1992 and Mount Katmai in 1912, and a large forest fire in 2004 as age controls. Here, we show that the chronology of the Aurora Peak ice core from 95.61m to the top corresponds to the period from 1900 to the summer season of 2008, with a dating error of ±3 years. We estimated that the mean accumulation rate from 1997 to 2007 (except for 2004) was 2.04mw.eq.yr-1. Our results suggest that temporal variations in δD and annual accumulation rates are strongly related to shifts in the Pacific Decadal Oscillation index (PDOI). The remarkable increase in annual precipitation since the 1970s has likely been the result of enhanced storm activity associated with shifts in the PDOI during winter in the Gulf of Alaska. [ABSTRACT FROM AUTHOR]

The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review the conceptual differences of eLUC quantification methods and apply an Earth System Model to demonstrate that what is claimed to represent total eLUC differs by up to ∼20% when quantified from ESM vs. offine vegetation models. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offine vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies and global carbon budget accountings should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions. [ABSTRACT FROM AUTHOR]

The article presents a research which investigates the proposed framework for downscaling coarse climate change projections for oceans in the Australian region. It explores significance of the downscaling model in projecting marine impacts of climate change. The restoration of the ocean feedback on the air-sea fluxes to surface temperature and salinity is explored. It notes that the framework offers an attractive way to explore the impact of climate change on mesoscale ocean environment.

The article reports on the implementation of the HadGEM2-ES Coupled Model Intercomparison Project (CMIP5), a standard experimental protocol for studying the output of general circulation models (GCMs). It covers the greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the experiments. It also details how the HadGEM2-ES ensemble members were initialised from the control run.

S. Nordio1-2, F. Flapp1-2, S. Fumich3This presentation is about an educational experience in which high school students are comparing historical end recent strong wind events and investigating traditional architectures which were designed to resist such weather phenomena and which may now provide interesting insights for local climate change adaptation strategies.The experience is being carried out in Friuli Venezia Giulia (FVG) region (1.200.000 inhabitants, about 8.000 km2) in northeastern Italy and it is part of a long standing educational project regarding weather and climate science, which has been developed by a high school (Liceo Scientifico "Galilei") in Trieste in collaboration with the regional meteorological observatory (OSMER) belonging to the Regional Environmental Protection Agency (ARPA FVG) and with the non-profit organization UMFVG - Meteorological Union of FVG. Such educational activities are highly interactive and are often carried out through a peer-tutoring approach. In 2018 the Liceo "Galilei" students were also involved in promoting a survey about knowledge, perception and attitudes concerning climate change among their peers. 620 high school students answered the on-line questionnaire: some results will be presented as well.The most recent activity in the educational project focuses on wind, adaptation and climate change.The city of Trieste and the surrounding Carso highland are typically swept by a strong wind, the Bora, blowing from east-northeast in gusts often exceeding 110-120 km/h and reaching occasionally 160-170 km/h (daily average wind speed about 80-100 km/h). Over the centuries, people living in the area developed spontaneous architectures and building techniques in order to resist this strong wind, but in recent years other areas in Friuli Venezia Giulia have been affected by unusually strong wind events, related to severe weather phenomena (such as storms, thunderstorms, downbursts) and/or peculiar mesoscale meteorological situations. The impacts were serious and, as such situations are likely to occur more frequently because of climate change, local adaptation strategies and measures will be necessary in order to prevent and reduce risks and damages.In this context, thirty "Galilei" high school students (age 17-19) are being involved in:• analyzing climate statistics regarding the winds in FVG region;• investigating both extreme wind (Bora) events that took place in the past in the area of Trieste and the most recent ones that occurred in other areas of FVG region;• collecting information and evidence about spontaneous architectures and building techniques employed in Trieste and Carso houses, industrial facilities, harbor area etc. in order to resist the Bora gusts;• learning about global and local climate change and about mitigation and adaptation concepts.This process is helping students to become aware of the importance of adapting to the local climate and, increasingly, to a changing climate. Identifying adaptive solutions to resist strong wind events may provide cues for discussing possible adaptation strategies also with local stakeholders and decision makers. The outcomes of this work, together with the results of the 2018 survey, will be presented to the other students of the school and to the public, through conferences, online videos, radio broadcasts etc. [ABSTRACT FROM AUTHOR]

The protection, restoration and use of vegetated coastal habitats in eco-engineering solutions for coastal protection are increasingly being accepted as providing a promising strategy, delivering significant capacity for climate change mitigation and adaption. In some cases, managed realignment of dykes, providing space for dynamic coastal movement and the reversion of natural wetlands back to their original state have been identified as a viable conservation and adaptation method to current and future risks associated with climate change; thereby reducing dyke maintenance costs and re-directing resources to areas of greatest need. This implementation however is not without its challenges and there is a lack of demonstrated, well-documented success outside of Europe. While previous efforts to restore coastal wetlands in Atlantic Canada focused primarily on the restoration of resilient and self-sufficient habitats, the increasingly tangible impacts of climate change combined with changing economic landscapes, regulations, and land use practices have shifted and broadened the objectives of these projects. In addition, social, historical and cultural components of the landscape and stakeholders are increasingly needed to be integrated into project design and implementation, thereby increasing their complexity. The Making Room for Wetlands project is building resilience to climate change impacts of dykelands in the Bay of Fundy, Canada by developing a framework for implementing managed dyke realignment and demonstrating the success of these strategies. Demonstration sites were selected in collaboration with the Provincial body responsible for dyke maintenance, after a comprehensive dyke vulnerability assessment and builds upon over a decade of collaboration and experience in tidal wetland restoration. Completed and on-going managed realignment projects in Nova Scotia will be used as a framework for a discussion on the challenges and opportunities presented for coastal habitat restoration for climate change adaptation and 'making room for wetlands'. The design, implementation and monitored restoration trajectory at multiple sites (Onslow-North River, Converse, Cornwallis, St. Croix and Belcher St. Marsh) will be presented to inform feasibility and design of future projects. [ABSTRACT FROM AUTHOR]

Effectively preparing for the long-term challenges posed by future climate change requires decision-makers to have access to relevant climate impact assessments that are based on the best available science and communicated in a clear and consistent manner. By developing an online climate-services portal, the ISIpedia project aims to deliver subcontinental to national-level, state-of-the-art climate impact assessments with broad sector coverage to the varied public of climate adaptation planners (e.g. involved in National Adaptation Plans, NAPs, the Sendai framework, or the SDGs) and practitioners, regional knowledge hubs, trans- and interdisciplinary scientists including climate economists, and regional climate experts from the private sector, such as (re-)insurance companies. The societally and user-relevant climate-impact information generated and communicated through ISIpedia, both its content and form, is the result of an intense and ongoing dialogue – shaped by a series of workshops and a survey - between the ISIpedia project team, scientist involved in the Inter-Sectoral Impact Model Intercomparison Project (www.isimip.org) and its potential end-users. In this contribution, we will describe the current state and latest developments of the ISIpedia portal with a main focus on the global water sector. In doing so, we will show the latest climate impact assessments for the global water sector as developed under the ISIMIP2b simulation round and communicated through ISIpedia and we will demonstrate how they can be of use to a varied group of policy makers and practitioners, for example to (a) assess the potential water-related impacts and risks under climate-change and design adaptation strategies accordingly; (b) evaluate the potential benefits of following a 1.5 degree Celsius climate mitigation pathway compared to the business-as-usual; (c) to evaluate potential co-benefits and trade-offs for alternative climate impact sectors such as agriculture, energy, biodiversity, and health; and (d) to prioritize short- to long-term capacity steering of disaster risk reduction agencies, global investors, and (re-)insurance companies with the aim to foster a robust, sustainable, and risk-resilient development of societies towards the future.Next to presenting the latest scientific results, we will reflect on the lessons learnt from the stakeholder dialogues and the process of co-creation and development of such an online platform with a diverse team consisting of scientists, web-designers, and stakeholders. We will conclude with sharing ideas for further developing its design, functionalities and assessment content and by sketching our envisaged time-line towards full launch of the ISIpedia portal. [ABSTRACT FROM AUTHOR]

To make sound decisions in the face of climate change, governmental agencies as well as policymakers and private stakeholders require the most accurate information on future climatic changes on local to regional scales. As such, the new Swiss climate change scenarios CH2018 form an important working basis for the government's adaptation strategy. In addition, they also highlight the potential of global mitigation efforts. The new climate change scenarios are the result of a joint collaboration among the Federal Office of Meteorology and Climatology MeteoSwiss, ETH Zurich and the Center for Climate Systems Modeling (C2SM) as main partners. The CH2018 scenarios represent the third generation of national climate scenarios in Switzerland. From the start of the project, CH2018 has been set up as a climate service, being one of the priority areas of the Swiss National Centre for Climate Services (NCCS). The new scenarios are based on the EURO-CORDEX regional climate projections. They reveal four main changes that will shape the climate in Switzerland by mid-century in the absence of strong mitigation efforts:1. Dry summers: Near-surface air temperature will rise in the summer months by 2.5°C to 4.5°C in comparison to today. At the same time, there is up to a quarter less rainfall, and the longest dry period without precipitation lasts nearly three weeks.2. More hot days: On the hottest days, it will be 2°C to 5.5°C warmer than now. Hot summers such as those of the record years 2003 and 2018 could thus become the norm. Heatwaves will become more frequent and more extreme. 3. Heavy precipitation: Individual heavy precipitation events will be more frequent and more intense in the future than today. The intensity of a 100-year precipitation event will increase by about 20%. The projected changes in the intensity of heavy precipitation events on daily to hourly time scales are consistent with an increase of 6 - 7 % per degree warming.4. Snow-scarce winters: Winters will be significantly warmer than current ones. The zero-degree line could climb from today 850 m to 1500 m above sea level. Snow will therefore become less frequent. With strong climate mitigation efforts, about half of the potential changes in Switzerland's climate could be avoided by mid-century.Besides the presentation of these main results, our contribution will also outline the communication approach we followed to increase the uptake of the scenarios among the user community in Switzerland, including our lessons learnt from interaction with users. [ABSTRACT FROM AUTHOR]

Coastal areas are highly vulnerable to flooding, due to hydrological extreme events such heavy rainfalls and/or storm surges. Such events are supposed to be increasing in the next future due to the emission in atmosphere of anthropogenic greenhouse gases, although such predictions are affected by notable uncertainties, especially at the local scale. Due the particular value of coastal regions, which generally are densely populated areas, as well as, sites of agriculture and industrial activities, is crucial the assessment of the future hydraulic risks associated to hydrological extreme events, and then the identification of policies to mitigate such risks taking into account such climate uncertainties, e.g. a global sea level rise. In this study, in order to assess the future hydraulic risk in coastal regions, as well as, to identify optimal adaptive defence policies, a risk analysis model is developed to calculate the present day and future flood risk, accounting for climate change uncertainties and mitigation measures. Such model juxtaposes a number of coupled/nested models as: a) downscaling model to link heavy rainfall events at the local scale to large scale atmospheric circulation patterns; b) bivariate extreme value model to estimate the statistical dependence between rainfall extreme occurrence and sea level rise due storm surge; c) hydraulic simulation-optimization model to identify the optimal flood defence infrastructure size for given probability distribution of occurrence of hydrological extreme events; d) mathematical decision model which is aimed to identify the best policies of mitigation of hydraulic risk and the times taking in account the uncertainties in hydrological extreme event predictions. Sea level pressure and meridional and zonal winds fields were used to calculate storm surges. Bivariate Point Process Method (BPPM) is used to calculate Joint probability density function between extreme daily rainfall amount and daily extreme storm tide depth. The simulation-optimization model calculates, for assigned extreme rainfall events and sea levels joint density probability functions, sets of Pareto optimal solutions which are obtained by defining two optimality criteria consisting in: minimizing both the cost of the flood defence infrastructure system and the flooding hydraulic risk. This latter is calculated as Expected Annual Damage (EAD) expressed as the joint probability density function between extreme rainfall and storm surge and damages, which are related to a given defence system state, water depth – damage curve and land use (CORINE Land Cover). Then, we developed an adaptive dynamic decision process to select, among the different optimal Pareto solution sets, the most appropriate set of interventions to make in a flood defence system and the right time to make these interventions. The adaptive dynamic risk analysis model is applied to the study case of Pontina Plain, a large reclamation region (about 100000 ha) in the south of Lazio region (Italy), particularly vulnerable to extreme events - as extreme rainfall amount and sea level rise due to storm surge at the sea outfall of the river- which in the past caused the crisis of hydraulic network system with flooding of large areas and collapse of levees. [ABSTRACT FROM AUTHOR]

Electricity infrastructure is critical to economic growth and social development. Interruptions in the energy power supply can have severe consequences, such as breakdowns of communication, transportation, utility systems and industrial production processes that threaten the stability and economy of entire regions. Electricity infrastructure faces a wide range of natural hazards that affect their operation that have either geophysical origin, like earthquakes, or are triggered by hydro-meteorological conditions. Regarding the second category, recent data suggest that climate change leads to sea level rise and to an increased number of extreme weather events that increase the likelihood of severe impacts on electricity infrastructure. Thus, it is urgent to assess the resilience of existing electricity infrastructure to provide valuable information for decision making on mitigation measures and climate proofing design to avoid severe energy blackouts. In this context, the present work focuses on an integrated methodology for resilience assessment in a multi-hazard environment. The methodology is applied to energy infrastructure case studies in Mediterranean regions that have been identified as vulnerable to climate change. First, potential hazards considering climate change are recorded and hazard scenarios are selected. The next step is to identify vulnerability indicators and quantify vulnerability in systemic level considering infrastructure specific data. To evaluate resilience, loss estimation in terms of energy supply losses and rehabilitation costs is conducted. After the resilience assessment, mitigation measures are proposed and the assessment methodology is applied for each measure scenario. The analysis results are compared and their impact on resilience is discussed. The studied methodology can be a useful tool in the hands of stakeholders to avoid energy supply interruptions from natural hazards. The conclusions derived highlight the importance of estimating the resilience of energy infrastructure to natural hazards, climate change's role and how mitigation strategies can be applied to reduce disaster risk. [ABSTRACT FROM AUTHOR]

Global forecasts for the growth of urban agglomerations and the expected effects of ongoing climate changes highlight the need to reflect on urban and regional planning issues.The real challenge is to combine urban growth with adequate density and compactness to prevent and contain land use change, loss of productive land and reduction of ecosystem services.The city is therefore observed because its compact or dispersed form and its regulation through appropriate planning tools can make an important contribution both in terms of mitigation and adaptation to climate change, and in limiting future impacts.The present work aims to provide a useful methodology to investigate the relationship between the increase of urbanized areas and their growth dynamics, and the surface temperatures variation recorded within urban, peri-urban and rural contexts.The building environment evolution and the Land Surface Temperatures (LST) time series surveyed by Modis satellites are jointly analyzed in the context of the Basilicata region. The results show a strong relationship between the increase in recorded minimum temperatures and urban areas expansion, especially where the main growth dynamics is compaction. [ABSTRACT FROM AUTHOR]

Climate variability can trigger short- and long-term impacts on society and environment. In the last decades, climate change has become a major topic for policy makers at various levels, and adaptation to climate change equally challenge the national, international and local decision-makers and stakeholders. The scientific community strives for providing tools and arguments to fundament climate change adaptation needs, and the spatial, temporal and functional coherence of the strategies is the key for a successful implementation.Europe, and especially the European Union (EU), has reacted promptly to the climate change challenges. Since 2005, many member states have embraced national adaptation strategies (NAS) and national and/or sectoral adaptation plans (NAP/SAP), while an EU strategy on adaptation to climate change was adopted in 2013, aiming to enhance the resilience of the continent to climate change. With an efficient transfer to lower spatial levels and with new technologies and innovative approaches, the regional and local communities would reach an improved preparedness and higher mitigation capacity to the future climate.The water and vegetation (blue and green) largely contribute to alleviating some climate threats (i.e. excessive heat) and secure the climatic comfort of any region. Cities are mainly targeted by blue and green-based interventions. This study investigates (i) the compatibility and consistency between different spatial scales of the climate change adaptation strategies (i.e. transnational, national, local), (ii) the role of the blue-green infrastructures in the climate change adaptation strategies, (iii) regional differences and temporal dynamic of the NASs and NAP/SAPs at European scale [ABSTRACT FROM AUTHOR]