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The paper reviews and evaluates a 30-year-long atmospheric CO2 data series measured at the Hegyhátsál tall-tower greenhouse gas monitoring site, a member of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW), US National Oceanic and Atmospheric Administration (NOAA), and pan-European Integrated Carbon Observation System (ICOS) networks. The paper also gives the technical description of the monitoring system and its changes over time and introduces the environment of the station. This low-elevation (248 m above mean sea level – m a.m.s.l.), mid-continental central European site shows a 3.90 ± 0.83 µmolmol-1 offset relative to the latitudinally representative marine boundary layer reference concentration, presumably due to European net anthropogenic emissions. The long-term trend (2.20 µmolmol-1yr-1) closely follows the global tendencies. In the concentration growth rate, the ENSO effect is clearly detectable with a 6–7-month lag time. The summer diurnal concentration amplitude is slightly decreasing due to the faster-than-average increase in the nighttime concentrations, which is related to the warming climate. The warming climate also caused a 0.96 ± 0.41 dyr-1 advance at the beginning of the summer CO2 -deficit season in the first half of the measurement period, which did not continue later. The summer CO2 -deficit season was extended by 9.0 ± 6.1 d during the measurement period. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation is one of most promising means to prevent global warming in the present Japan. Since solar panels mounted on building façades are expected to come into wide use in urban areas, accurate estimation of PV potential of building façades is necessary for urban energy management planning. Accordingly, we have developed a system to estimate PV potential of urban buildings using a 3D city model. The system has two significant features: rapid estimation of hourly solar irradiance of points densely distributed on a building surface, and more flexible estimation of PV potential considering an arrangement of solar panels on a building surface. The paper reports our newly developed method to estimate PV potential of urban buildings considering an arrangement of solar panels using dense solar irradiance distribution on a building surface. The rapid estimation of dense solar irradiance distribution on a building surface enables the system to handle more flexible arrangement of solar panels with providing width and height of a solar panel, and clearance around solar panels. Considering some restrictions such as minimum solar irradiance of a solar panel makes PV potential estimated by the system become more realistic. The paper reports experiments conducted in seven urban districts in Japan to investigate the flexibility of the method by using various settings of panel installing conditions. Experiment results indicate that our developed method can estimate PV potential flexibly considering an arrangement of solar panels corresponding to various settings of panel installing conditions such as size of a solar panel. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation is one of most promising means to prevent global warming in the present Japan. Since solar panels mounted on building façades are expected to come into wide use in urban areas, accurate estimation of PV potential of building façades is necessary for urban energy management planning. Accordingly, we decided to develop a system to estimate PV potential of urban buildings using a 3D city model. The system has two significant features: rapid estimation of hourly solar irradiance of points densely distributed on a building surface, and more flexible estimation of PV potential considering an arrangement of solar panels on a building surface. The paper reports our newly developed algorithm to estimate solar irradiance of urban buildings. The algorithm adopts the idea that "whether the sun can see us or not" indicates "whether we have sunshine or not" for calculation of hourly solar irradiance of a point on a building surface. In estimation of solar irradiance distributions on roofs and façades, utilization of projection images viewed from the sun created by using computer graphics (CG) techniques such as the depth buffer (Z-buffer) algorithm makes our system have much less computation time than most of existing systems using a hemispherical viewsheds or ray tracing. Results of an experiment conducted in Yokohama of Japan demonstrate that the algorithm would be able to estimate solar irradiance on not only roofs but also façades of urban buildings using a 3D city model accurately enough. [ABSTRACT FROM AUTHOR]

The paper reviews and evaluates a 30-year-long atmospheric CO2 data series measured at Hegyhátsál tall-tower greenhouse gas monitoring site, a member of WMO GAW, NOAA, and ICOS networks (id. code: HUN). The paper also gives the technical description of the monitoring system, and that of the physical environment of the station. This low elevation (248 m above m.s.l.), mid-continental Central European site shows a 3.90±0.83 µmol mol‑1 offset relative to the latitudinally representative marine boundary layer reference concentration presumably due to the European net anthropogenic emissions. The long-term trend (2.20 µmol mol‑1 year‑1) closely follows the global tendencies. In the concentration growth rate, the ENSO effect is clearly detectable with a 6–7 months lag-time. The summer diurnal concentration amplitude is slightly decreasing due to the faster-than-average increase of the nighttime concentrations, which is related to the warming climate. The warming climate also caused a 0.96±0.41 day year‑1 advance in the beginning of the summer CO2-deficit season in the first half of the measurement period, which did not continue later. [ABSTRACT FROM AUTHOR]

Floods are the primary natural hazard in the French Mediterranean area, causing damages and fatalities every year. These floods are triggered by heavy precipitation events (HPEs) characterized by limited temporal and spatial extents. A new generation of regional climate models at the kilometer scale have been developed, allowing an explicit representation of deep convection and improved simulations of local-scale phenomena such as HPEs. Convection-permitting regional climate models (CPMs) have been scarcely used in hydrological impact studies, and future projections of Mediterranean floods remain uncertain with regional climate models (RCMs). In this paper, we use the CNRM-AROME CPM (2.5 km) and its driving CNRM-ALADIN RCM (12 km) at the hourly timescale to simulate floods over the Gardon d'Anduze catchment located in the French Mediterranean region. Climate simulations are bias-corrected with the CDF-t method. Two hydrological models, a lumped and conceptual model (GR5H) and a process-based distributed model (CREST), forced with historical and future climate simulations from the CPM and from the RCM, have been used. The CPM model confirms its ability to better reproduce extreme hourly rainfall compared to the RCM. This added value is propagated on flood simulation with a better reproduction of flood peaks. Future projections are consistent between the hydrological models but differ between the two climate models. Using the CNRM-ALADIN RCM, the magnitude of all floods is projected to increase. With the CNRM-AROME CPM, a threshold effect is found: the magnitude of the largest floods is expected to intensify, while the magnitude of the less severe floods is expected to decrease. In addition, different flood event characteristics indicate that floods are expected to become flashier in a warmer climate, with shorter lag time between rainfall and runoff peak and a smaller contribution of base flow, regardless of the model. This study is a first step for impact studies driven by CPMs over the Mediterranean. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau stands as one of China's largest middle and low latitude permafrost regions. However, the effects of global warming and human activities have led to permafrost thawing, inducing surface instability and posing significant threats to infrastructure and indigenous communities. The deployment of Lu Tan-1 (LT-1), China's premier L-band synthetic aperture radar (SAR) satellite constellation, offers a novel opportunity to assess these changes. This paper evaluates the deformation of critical engineering corridors, such as the Qinghai-Tibet Railway (QTR) and the Qinghai-Tibet Highway (QTH), utilizing time-series InSAR techniques with LT-1 SAR constellation data. We introduce both Stacking InSAR and a multi-baseline persistent scatterer multitemporal (MT-InSAR) method to enhance permafrost and engineering corridor deformation detection capabilities. Results obtained through the MT-InSAR approach reveal line-of-sight (LOS) deformation velocities of permafrost in the Beiluhe region ranging from -90 mm/y to approximately 70 mm/y, with an average velocity amplitude of 0.06 m/y. Differential displacement between alpine meadows and alpine deserts across the Beiluhe region is successfully discerned using LT-1 SAR data. Deformation velocities of QTR, QTH were found to be lower than that of permafrost, with average velocities of 0.027 m/y. These findings underscore the LT-1 SAR constellation's potential to serve as a valuable SAR data source for monitoring engineering corridor deformation within the Tibetan Plateau permafrost region. [ABSTRACT FROM AUTHOR]

In climates with a warm and a cold season, low flows are generated by different processes, which violates the homogeneity assumption of extreme value statistics. In this second part of a two-part series, we extend the mixed probability estimator of the companion paper to deal with dependency of seasonal events. We formulate a copula-based estimator for seasonal minima series and examine it in a hydrological context. The estimator is a valid generalization of the annual probability estimator and provides a consistent framework for estimating return periods of summer, winter, and annual events. Using archetypal examples we show that differences in the mixed estimator are always observed in the upper part of the distribution, which is less relevant for low-flow frequency analysis. The differences decrease as the return period increases so that both models coincide for the severest events. In a quantitative evaluation, we test the performance of the copula estimator on a pan-European data set. We find a large gain of both mixed distribution approaches over the annual estimator, making these approaches highly relevant for Europe as a whole. We then examine the relative performance gain of the mixed copula versus the mixed distribution approach in more detail. The analysis shows that the differences in the 100-year event are actually minimal. However, the differences in 2-year events are considerable in some of the catchments, with a relative deviation of -15 % to -25 % in the most affected regions. This points to a prediction bias of the mixed probability estimator that can be corrected using the copula approach. Using multiple regression models, we show that the performance gain can be well explained on hydrological grounds, with weak seasonality leading to a high potential for corrections and strong seasonal correlation reinforcing the need to take this potential into account. Accordingly, the greatest differences can be observed in mid-mountain regions in cold and temperate climates, where rivers have a strongly mixed low-flow regime. This finding is of particular relevance for event mapping, where regional severity can be misinterpreted when the seasonal correlation is neglected. We conclude that the two mixed probability estimators are quite similar, and both are conceptually more adequate than the annual minima approach for mixed summer and winter low-flow regimes. In regions with strong seasonal correlation the mixed copula estimator appears most appropriate and should be preferred over the mixed distribution approach. [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs), defined as prolonged period of extremely warm sea surface temperature (SST), have been receiving a lot of attention in the past decade as their frequency and intensity increase in a warming climate. This paper investigates the extent to which the seasonal occurrence and duration of MHWs can be predicted with the European Centre for Medium-Range Weather Forecast (ECMWF) operational seasonal forecast system. The prediction of the occurrence of MHW events, the number of MHW days per season, and their intensity and spatial extent are derived from seasonal SST forecasts and evaluated against an observation-based SST analysis using both deterministic and probabilistic metrics over the 1982–2021 period. Forecast scores show useful skill in predicting the occurrence of MHWs globally for the two seasons following the starting date. The skill is the highest in the El Niño region, the Caribbean, the wider tropics, the north-eastern extra-tropical Pacific, and southwest of the extra-tropical basins. The skill is not as good for other midlatitude eastern basins nor for the Mediterranean, with the forecast system being able to represent the low-frequency modulation of MHWs but showing poor skill in predicting the interannual variability of the MHW characteristics. Linear trend analysis shows an increase in MHW occurrence at a global scale, which the forecasts capture well. [ABSTRACT FROM AUTHOR]

Since 2003, the state-of-the-art Canadian Coast Guard Ship (CCGS) research icebreaker Amundsen has furrowed the Canadian Arctic waters to support novel research endeavors and collect oceanographic data. This paper presents the data acquisition, the processing methods and an overview of the data collected during the 2021 expedition as the ship traveled over 30 000 km during 122 d across the Canadian Arctic Ocean, collecting sea surface, atmospheric and seabed underway measurements. A total of 266 casts of a conductivity, temperature and depth profiler mounted on a Conductivity Temperature Depth rosette (CTD Rosette) were also conducted to monitor the main physical, chemical and biological parameters of the water column. More specifically, the data presented here were collected with the CTD Rosette across historical sampling transects in Davis Strait, the North Water Polynya (NOW) and Cape Bathurst. A 182 km dedicated survey using the Moving Vessel Profiler® (MVP), equipped with CTD, transmissometer, dissolved oxygen, fluorescence and sound velocity sensors, was conducted across Hudson Strait. We also present an overview of the data collected by the underway systems (seabed, thermosalinograph and atmospheric). Such data are essential in understanding the impacts of climate warming on the unique environments of the Canadian Arctic Ocean. Amundsen Science supports and promotes easy access and sharing of such valuable data to the scientific community. [ABSTRACT FROM AUTHOR]

As the climate warms, the grounded ice sheet and floating ice shelves surrounding Antarctica are melting and releasing additional freshwater into the Southern Ocean. Nonetheless, almost all existing coupled climate models have fixed ice sheets and lack the physics required to represent the dominant sources of Antarctic melt. These missing ice dynamics represent a key uncertainty that is typically unaccounted for in current global climate change projections. Previous modelling studies that have imposed additional Antarctic meltwater have demonstrated regional impacts on Southern Ocean stratification, circulation, and sea ice, as well as remote changes in atmospheric circulation, tropical precipitation, and global temperature. However, these previous studies have used widely varying rates of freshwater forcing, have been conducted using different climate models and configurations, and have reached differing conclusions on the magnitude of meltwater–climate feedbacks. The Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative brings together a team of scientists to quantify the climate system response to Antarctic meltwater input along with key aspects of the uncertainty. In this paper, we summarize the state of knowledge on meltwater discharge from the Antarctic ice sheet and ice shelves to the Southern Ocean and explain the scientific objectives of our initiative. We propose a series of coupled and ocean–sea ice model experiments, including idealized meltwater experiments, historical experiments with observationally consistent meltwater input, and future scenarios driven by meltwater inputs derived from stand-alone ice sheet models. Through coordinating a multi-model ensemble of simulations using a common experimental design, open data archiving, and facilitating scientific collaboration, SOFIA aims to move the community toward better constraining our understanding of the climate system response to Antarctic melt. [ABSTRACT FROM AUTHOR]

Following the projected increase in extreme precipitation, an increase in extreme snowfall may be expected in cold regions, e.g., for high latitudes or at high elevations. By contrast, in low- to medium-elevation areas, the probability of experiencing rainfall instead of snowfall is generally projected to increase due to warming conditions. Yet, in mountainous areas, despite the likely existence of these contrasted trends according to elevation, changes in extreme snowfall with warming remain poorly quantified. This paper assesses projected changes in heavy and extreme snowfall, i.e., in mean annual maxima and 100-year return levels, in the French Alps as a function of elevation and global warming level. We apply a recent methodology, based on the analysis of annual maxima with non-stationary extreme value models, to an ensemble of 20 adjusted general circulation model–regional climate model (GCM–RCM) pairs from the EURO-CORDEX experiment under the Representative Concentration Pathway 8.5 (RCP8.5) scenario. For each of the 23 massifs of the French Alps, maxima in the hydrological sense (1 August to 31 July) are provided from 1951 to 2100 and every 300 m of elevations between 900 and 3600 m. Results rely on relative or absolute changes computed with respect to current climate conditions (corresponding here to +1 ∘ C global warming level) at the massif scale and averaged over all massifs. Overall, daily mean annual maxima of snowfall are projected to decrease below 3000 m and increase above 3600 m, while 100-year return levels are projected to decrease below 2400 m and increase above 3300 m. At elevations in between, values are on average projected to increase until +3 ∘ C of global warming and then decrease. At +4 ∘ C, average relative changes in mean annual maxima and 100-year return levels, respectively, vary from -26% and -15% at 900 m to +3% and +8% at 3600 m. Finally, for each global warming level between +1.5 and +4 ∘ C, we compute the elevation threshold that separates contrasted trends, i.e., where the average relative change equals zero. This elevation threshold is shown to be lower for higher return periods, and it is projected to rise from 3000 m at +1.5 ∘ C to 3350 m at +4 ∘ C for mean annual maxima and from 2600 to 3000 m for 100-year return levels. These results have implications for the management of risks related to extreme snowfall. [ABSTRACT FROM AUTHOR]

Examination of climatic and oceanographic changes through the Holocene (11.75 ka–present) allows for an improved understanding and contextualization of modern climate change. Climate records of the Holocene can be utilized as a "baseline" from which to compare modern climate and can also provide insights into how environments experience and recover from change. However, individual studies on Holocene climate in the literature tend to focus on a distinct geographic location, a specific proxy record, or a certain aspect of climate (e.g., upwelling or precipitation), resulting in localized, record-specific trends rather than a comprehensive view of climate variability through the Holocene. Here we synthesize the major oceanographic and terrestrial changes that have occurred in the Western United States (bounded by 30 to 52 ∘ N and 115 to 130 ∘ W) through the most recent 11.75 kyr and explore the impacts of these changes on marine and terrestrial ecosystems. We present a novel spatiotemporal analysis of Holocene marine and terrestrial temperature, hydroclimate, and fire activity across the Early, Middle, and Late Holocene using a coded analysis of over 40 published studies. Following coded analysis of temperature, hydroclimate, and fire activity in the paper, we include a broader literature review of environmental change through the Holocene, including an examination of the impacts of multi-millennial climate trends on ecological communities. We find that the Early Holocene is characterized by warming relative to pre-Holocene conditions, including warm sea surface conditions, a warm and dry Pacific Northwest, a warm and wet Southwest, and overall spatial and temporal stability. In the Middle Holocene, these patterns reverse; this interval is characterized by cool sea surface temperatures, a cool and wet Pacific Northwest and warm and dry Southwest. The Late Holocene is the most variable interval, both spatially and temporally, and a novel spatial trend appears in terrestrial climate with warmer coastal areas and cooler inland areas. Human communities interacted with the environment throughout the entire Holocene, as evidenced in archeological and paleoenvironmental records, yet the recent Era of Colonization (1850–present) represents an unprecedented environmental interval in many records. Broadly, our analysis shows linkages between terrestrial and oceanographic conditions, distinct environmental phases through time, and emphasizes the importance of local factors in controlling climate through the dynamic Holocene. [ABSTRACT FROM AUTHOR]

Lightning can cause natural hazards that result in human and animal injuries and fatalities, infrastructure destruction, and wildfire ignition. Lightning-produced NOx (L NOx), a major NOx (NOx=NO+NO2) source, plays a vital role in atmospheric chemistry and global climate. The Earth has experienced marked global warming and changes in aerosol and aerosol precursor emissions (AeroPEs) since the 1960s. Investigating long-term historical (1960–2014) lightning and LNOx trends can provide important indicators for all lightning-related phenomena and for LNOx effects on atmospheric chemistry and global climate. Understanding how global warming and changes in AeroPEs influence historical lightning and LNOx trends can be helpful in providing a scientific basis for assessing future lightning and LNOx trends. Moreover, global lightning activities' responses to large volcanic eruptions such as the 1991 Pinatubo eruption are not well elucidated and are worth exploring. This study employed the widely used cloud top height lightning scheme (CTH scheme) and the newly developed ice-based ECMWF-McCAUL lightning scheme to investigate historical (1960–2014) lightning and LNOx trends and variations as well as their influencing factors (global warming, increases in AeroPEs, and the Pinatubo eruption) in the framework of the CHASER (MIROC) chemistry–climate model. The results of the sensitivity experiments indicate that both lightning schemes simulated almost flat global mean lightning flash rate anomaly trends during 1960–2014 in CHASER (the Mann–Kendall trend test (significance inferred as 5 %) shows no trend for the ECMWF-McCAUL scheme, but a 0.03 %yr-1 significant increasing trend is detected for the CTH scheme). Moreover, both lightning schemes suggest that past global warming enhances historical trends for global mean lightning density and global LNOx emissions in a positive direction (around 0.03 %yr-1 or 3 %K-1). However, past increases in AeroPEs exert an opposite effect on the lightning and LNOx trends (- 0.07 % to - 0.04 %yr-1 for lightning and - 0.08 % to - 0.03 %yr-1 for L NOx) when one considers only the aerosol radiative effects in the cumulus convection scheme. Additionally, effects of past global warming and increases in AeroPEs in lightning trends were found to be heterogeneous across different regions when analyzing lightning trends on the global map. Lastly, this paper is the first of study results suggesting that global lightning activities were markedly suppressed during the first year after the Pinatubo eruption as shown in both lightning schemes (global lightning activities decreased by as much as 18.10 % as simulated by the ECMWF-McCAUL scheme). Based on the simulated suppressed lightning activities after the Pinatubo eruption, the findings also indicate that global LNOx emissions decreased after the 2- to 3-year Pinatubo eruption (1.99 %–8.47 % for the annual percentage reduction). Model intercomparisons of lightning flash rate trends and variations between our study (CHASER) and other Coupled Model Intercomparison Project Phase 6 (CMIP6) models indicate great uncertainties in historical (1960–2014) global lightning trend simulations. Such uncertainties must be investigated further. [ABSTRACT FROM AUTHOR]

The oceans are losing oxygen (O 2) , and oxygen minimum zones are expanding due to climate warming (lower O 2 solubility) and eutrophication related to agriculture. This trend is challenging for most marine taxa that are not well adapted to O 2 depletion. For other taxa this trend might be advantageous because they can withstand low O 2 concentrations or thrive under O 2 -depleted or even anoxic conditions. Benthic foraminifera are a group of protists that include taxa with adaptations to partly extreme environmental conditions. Several species possess adaptations to O 2 depletion that are rare amongst eukaryotes, and these species might benefit from ongoing ocean deoxygenation. In addition, since some foraminifera can calcify even under anoxic conditions, they are important archives for paleoceanographic reconstruction in O 2 -depleted environments. This paper reviews the current state of knowledge about foraminifera from low-O 2 environments. Recent advances in our understanding of specific survival strategies of foraminifera to withstand O 2 depletion are summarized and discussed. These adaptations include an anaerobic metabolism, heterotrophic denitrification, symbiosis with bacteria, kleptoplasty and dormancy and have a strong impact on their preferred microhabitat in the sediments, especially the ability of some benthic foraminiferal species to denitrify. Benthic foraminifera also differ regarding their trophic strategies, which has an additional impact on the selection of their microhabitat. For example, some species are strict herbivores that feed exclusively on fresh phytodetritus and live close to the sediment surface, while some species are non-selective detrivores that occupy intermediate to deep infaunal habitats. There is evidence that foraminifers have the capacity to undergo phagocytosis, even under anoxia, and some foraminiferal species which can withstand low-O 2 conditions seem to prey on meiofauna. Also, due to their high abundances in O 2 -depleted environments and their metabolic adaptations, benthic foraminifera are key players in marine nutrient cycling, especially within the marine N and P cycles. This review summarizes the denitrification rates for the species that are known to denitrify and the intracellular nitrate concentrations of the species that are known to intracellularly store nitrate. Finally, equations are provided that can be used to estimate the intracellular nutrient storage and denitrification rates of foraminifera and might be integrated into biogeochemical models. [ABSTRACT FROM AUTHOR]

With the gradual warming of the global climate, frequent floods have caused huge losses to human life and property. Flood mapping by SAR image has been an important topic, and it is increasingly important to use deep learning method to extract flood information. In order to achieve automatic flood extent extraction, this paper proposes an attention mechanism-based water body extraction network with GF3 images, and successfully use it for flood detection in Xinxiang, Henan, China. In this paper, the proposed network incorporates the channel attention mechanism and position attention mechanism based on U-Net, to improve the efficiency and accuracy of water extraction, ignore the unimportant information by learning the weight and make the model focus toward the important information related to the water body. The OA of our method can reach 0.959 and Recall can reach 0.942 by verifying four sets of test data. Experiments show fast flood mapping in Xinxiang can be achieved by our method. [ABSTRACT FROM AUTHOR]

Climate warming increases the intensity of extreme precipitation. Studying extreme precipitation patterns and changes is vital to reducing risk. This paper investigates thresholds, changes and timescales for extreme precipitation using sub-daily records from meteorological stations in the Ganjiang River basin. We use the gamma distribution and select the L-moment method to estimate the parameters α and β. Results show that (1) continuous precipitation events of 36 h contributed the most precipitation to the total but with lower frequency, which would be key events for flood monitoring; (2) the intensity and the occasional probability of extreme precipitation will increase in spring in the future in stations like Yifeng, Zhangshu and Ningdu, which will in turn increase the risk of storm floods; and (3) spatial distribution of extreme precipitation risk shows that the risk increases as elevation increases in the northern lowland and the Jitai Basin in the midstream region, while the risk in the southern mountainous region decreases as elevation increases. These findings will facilitate emergency preparedness, including risk management and disaster assistance, in the study areas. [ABSTRACT FROM AUTHOR]

In seasonal climates with a warm and a cold season, low flows are generated by different processes so that the annual extreme series will be a mixture of summer and winter low-flow events. This leads to a violation of the homogeneity assumption for all statistics derived from the annual series and gives rise to inaccurate conclusions. In this first part of a two-paper series, a mixed distribution approach to perform frequency analysis in catchments with mixed low-flow regimes is proposed. We formulate the theoretical basis of the mixed distribution approach for the lower extremes based on annual minima series. The main strength of the model is that it allows the user to estimate return periods of summer low flows, winter low flows, and annual return periods in a theoretically sound and consistent way. Using archetypal examples, we show how the model behaves for a range of low-flow regimes, from distinct winter and summer regimes to mixed regimes where seasonal occurrence in summer and winter is equally likely. The examples show in a qualitative way the loss in accuracy one has to expect with conventional extreme value statistics performed with the annual extremes series. The model is then applied to a comprehensive Austrian data set to quantify the expected gain of using the mixed distribution approach compared to conventional frequency analysis. Results indicate that the gain of using a mixed distribution approach is indeed large. On average, the relative deviation is 21 %, 39 %, and 63 % when estimating the low flow with a 20-, 50-, and 100-year return period. For the 100-year event, 75 % of stations show a performance gain of >10 %, 41 % of stations > 50 %, and 25 % of stations > 80.6 %. This points to a broad relevance of the approach that goes beyond highly mixed seasonal regimes to include the strongly seasonal ones. We finally correlate the performance gain with seasonality indices in order to show the expected gain conditional to the strength of seasonality expressed by the ratio of average summer and winter low flow seasonality ratio (SR). For the 100-year event, the expected gain is about 70 % for SR=1.0 , 20 % for SR=1.5 , and 10 % for SR=2.0. The performance gain is further allocated to the spatial patterns of SR in the study area. The results suggest that the mixed estimator is relevant not only for mountain forelands but to a much wider range of catchment typologies. The mixed distribution approach provides one consistent approach for summer, winter, and annual probabilities and should be used by default in seasonal climates with a cold winter season where summer and winter low flows can occur. [ABSTRACT FROM AUTHOR]

Climate warming in mountain regions is resulting in glacier shrinking, seasonal snow cover reduction, and changes in the amount and seasonality of meltwater runoff, with consequences on water availability. Droughts are expected to become more severe in the future with economical and environmental losses both locally and downstream. Effective adaptation strategies involve multiple timescales, and seasonal forecasts can help in the optimization of the available snow and water resources with a lead time of several months. We developed a prototype to generate seasonal forecasts of snow depth and snow water equivalent with a starting date of 1 November and a lead time of 7 months, so up to 31 May of the following year. The prototype has been co-designed with end users in the field of water management, hydropower production and mountain ski tourism, meeting their needs in terms of indicators, time resolution of the forecasts and visualization of the forecast outputs. In this paper we present the modelling chain, based on the seasonal forecasts of the ECMWF and Météo-France seasonal prediction systems, made available through the Copernicus Climate Change Service (C3S) Climate Data Store. Seasonal forecasts of precipitation, near-surface air temperature, radiative fluxes, wind and relative humidity are bias-corrected and downscaled to three sites in the Western Italian Alps and finally used as input for the physically based multi-layer snow model SNOWPACK. Precipitation is bias-corrected with a quantile mapping method using ERA5 reanalysis as a reference and then downscaled with the RainFARM stochastic procedure in order to allow an estimate of uncertainties due to the downscaling method. The impacts of precipitation bias adjustment and downscaling on the forecast skill have been investigated. The skill of the prototype in predicting the deviation of monthly snow depth with respect to the normal conditions from November to May in each season of the hindcast period 1995–2015 is demonstrated using both deterministic and probabilistic metrics. Forecast skills are determined with respect to a simple forecasting method based on the climatology, and station measurements are used as reference data. The prototype shows good skills at predicting the tercile category, i.e. snow depth below and above normal, in the winter (lead times: 2–3–4 months) and spring (lead times: 5–6–7 months) ahead: snow depth is predicted with higher accuracy (Brier skill score) and higher discrimination (area under the relative operating characteristics (ROC) curve skill score) with respect to a simple forecasting method based on the climatology. Ensemble mean monthly snow depth forecasts are significantly correlated with observations not only at short lead times of 1 and 2 months (November and December) but also at lead times of 5 and 6 months (March and April) when employing the ECMWFS5 forcing. Moreover the prototype shows skill at predicting extremely dry seasons, i.e. seasons with snow depth below the 10th percentile, while skills at predicting snow depth above the 90th percentile are model-, station- and score-dependent. The bias correction of precipitation forecasts is essential in the case of large biases in the global seasonal forecast system (MFS6) to reconstruct a realistic snow depth climatology; however, no remarkable differences are found among the skill scores when the precipitation input is bias-corrected, downscaled, or bias-corrected and downscaled, compared to the case in which raw data are employed, suggesting that skill scores are weakly sensitive to the treatment of the precipitation input. [ABSTRACT FROM AUTHOR]

There is now substantial literature on climate model studies of equatorial or tropical stratospheric SO 2 injections that aim to counteract the surface warming produced by rising concentrations of greenhouse gases. Here we present the results from the first systematic intercomparison of climate responses in three Earth system models wherein the injection of SO 2 occurs at different latitudes in the lower stratosphere: CESM2-WACCM6, UKESM1.0 and GISS-E2.1-G. The first two use a modal aerosol microphysics scheme, while two versions of GISS-E2.1-G use a bulk aerosol (One-Moment Aerosol, OMA) and a two-moment (Multiconfiguration Aerosol TRacker of mIXing state, MATRIX) microphysics approach, respectively. Our aim in this work is to determine commonalities and differences between the climate model responses in terms of the distribution of the optically reflective sulfate aerosols produced from the oxidation of SO 2 and in terms of the surface response to the resulting reduction in solar radiation. A focus on understanding the contribution of characteristics of models transport alongside their microphysical and chemical schemes, and on evaluating the resulting stratospheric responses in different models, is given in the companion paper. The goal of this exercise is not to evaluate these single-point injection simulations as stand-alone proposed strategies to counteract global warming; instead we determine sources and areas of agreement and uncertainty in the simulated responses and, ultimately, the possibility of designing a comprehensive intervention strategy capable of managing multiple simultaneous climate goals through the combination of different injection locations. We find large disagreements between GISS-E2.1-G and the CESM2-WACCM6 and UKESM1.0 models regarding the magnitude of cooling per unit of aerosol optical depth (AOD) produced, which varies from 4.7 K per unit of AOD in CESM2-WACCM6 to 16.7 K in the GISS-E2.1-G version with two-moment aerosol microphysics. By normalizing the results with the global mean response in each of the models and thus assuming that the amount of SO 2 injected is a free parameter that can be managed independently, we highlight some commonalities in the overall distributions of the aerosols, in the inter-hemispheric surface temperature response and in shifts to the Intertropical Convergence Zone, as well as some areas of disagreement, such as the extent of the aerosol confinement in the equatorial region and the efficiency of the transport to polar latitudes. In conclusion, we demonstrate that it is possible to use these simulations to produce more comprehensive injection strategies in multiple climate models. However, large differences in the injection magnitudes can be expected, potentially increasing inter-model spreads in some stratospheric quantities (such as aerosol distribution) while reducing the spread in the surface response in terms of temperature and precipitation; furthermore, the selection of the injection locations may be dependent on the models' specific stratospheric transport. [ABSTRACT FROM AUTHOR]

There is no more consequential scientific matter today than global warming. The societal and policy implications, however, hinge upon the attribution of that warming to human activity and, specifically, continued societal reliance on the burning of fossil fuels. It was recently suggested that this warming could be explained by the non-anthropogenic factor of seismic activity. If that is the case, it would have profound implications. We have assessed the validity of the claim using a statistical technique (the method of conditional dispersion) that evaluates the existence of causal connections between variables, finding no evidence for any causal relationship between seismic activity and global warming. [ABSTRACT FROM AUTHOR]

The negative surface mass balance of glaciers and ice caps under a warming climate impacts local ecosystems, influencing the volume and timing of water flow in local catchments, while also contributing to global sea level rise. Peripheral glaciers distinct to the Greenland ice sheet respond faster to climate change than the main ice sheet. Accurate assessment of surface mass balance depends on in-situ observations of near-surface climate and ice ablation, but very few in-situ observations of near-surface climate and ice ablation are freely available for Greenland’s peripheral glaciers. The transect of three automated weather and ablation stations on the peripheral A. P. Olsen ice cap in northeast Greenland is an example of this much needed data. The transect has been monitored since 2008, and in 2022 the old weather and ablation stations were replaced by a new standardized setup. In order to ensure comparable data quality from the old and new monitoring station setups, it was necessary to re-evaluate the data collected between 2008 and 2022. This paper presents the fully reprocessed near-surface climate and ablation data from the A. P. Olsen ice cap transect from 2008 to 2022, with a focus on data quality and the usability for ice ablation process studies. The usability and some quality issues are exemplified by using the data in an energy balance melt model for two different years. We showed that the inherent uncertainties of the data resulted in an accurate reproduction of ice ablation for just one of the two years. A transect of three automatic ablation and weather stations of this length is unique for Greenland’s peripheral glaciers and it has a broad scale of usage from input to climate reanalysis to detailed surface ablation studies. The dataset can be downloaded here: https://doi.org/10.22008/FK2/X9X9GN (Larsen and Citterio, 2023). Future refinements will be uploaded as new versions and the continuation of the transect time series are available via. [ABSTRACT FROM AUTHOR]

Global warming modifies the climate balance. Warming parameters are observed by many Earth Observation satellite systems, and the huge amount of data modifies the way to process them. This paper presents a few studies relative to damage detection on buildings, occurred during natural disasters. Recent advances in deep learning techniques are used for the building detection such as EfficientNet networks. Additional networks as Siamese models are used to evaluate the damage level with pre- and post-event images. Different techniques to merge detection masks are described and compared to a multiclass segmentation network. Results are presented and performances of the different solutions are compared. [ABSTRACT FROM AUTHOR]

Due to global warming, the decline in the Arctic sea ice has been accelerating over the last 4 decades, with a rate that was not anticipated by climate models. To improve these models, there is the need to rely on comprehensive field data. Seismic methods are known for their potential to estimate sea-ice thickness and mechanical properties with very good accuracy. However, with the hostile environment and logistical difficulties imposed by the polar regions, seismic studies have remained rare. Due to the rapid technological and methodological progress of the last decade, there has been a recent reconsideration of such approaches. This paper introduces a methodological approach for passive monitoring of both sea-ice thickness and mechanical properties. To demonstrate this concept, we use data from a seismic experiment where an array of 247 geophones was deployed on sea ice in a fjord at Svalbard, between 1 and 24 March 2019. From the continuous recording of the ambient seismic field, the empirical Green function of the seismic waves guided in the ice layer was recovered via the so-called "noise correlation function". Using specific array processing, the multi-modal dispersion curves of the ice layer were calculated from the noise correlation function, and then inverted for the thickness and elastic properties of the sea ice via Bayesian inference. The evolution of sea-ice properties was monitored for 24 d, and values are consistent with the literature, as well as with measurements made directly in the field. [ABSTRACT FROM AUTHOR]

Solid precipitation measurements in Antarctica are crucial as snowfall represents the main water input term for the polar cap, and its probable increase in the coming century can mitigate sea-level rise caused by global warming. This paper presents 7 years of Micro Rain Radar (Metek MRR-2) data at the Dumont d'Urville station in coastal Adélie Land, East Antarctica. Statistics are calculated on 3 radar variables (equivalent reflectivity, mean Doppler velocity and signal-to-noise ratio) to outline the main characteristics of the radar dataset. Seasonal and interannual variabilities are also investigated, but no significant temporal trends are detected except for the seasonal mean Doppler velocity which is higher in summer and lower in winter. We then use the snowfall rate (S) data from a colocated snow-gauge to estimate the MRR precipitation profile from the radar equivalent reflectivity (Ze) through a locally derived Ze-S relation. We find the relation Ze = 43.3 S0.88. The processing method used to obtain this relation, data quality and uncertainty considerations are discussed in the manuscript. In order to give an example of application of the dataset, a brief statistical comparison of the MRR precipitation rate along the vertical with model data from the ERA5 reanalysis and the LMDZ climate model is performed, and notably shows that models underestimate heavy precipitation events. [ABSTRACT FROM AUTHOR]

Since 2003, the state-of-the-art Canadian Coast Guard Ship (CCGS) research icebreaker Amundsen furrows the Canadian Arctic waters to support novel research endeavors and collect oceanographic data. This paper presents the data acquisition, the processing methods and an overview of the data collected during the 2021 expedition as the ship traveled over 30 000 km during 122 days across the Canadian Arctic Ocean, collecting sea surface, atmospheric and seabed underway measurements. A total of 266 casts of a conductivity, temperature and depth profiler mounted on a rosette (CTD-Rosette) were also conducted to monitor the main physical, chemical and biological parameters of the water column. More specifically, the data here presented were collected with the CTD-Rosette across historical sampling transects in Davis Strait, the NorthWater Polynya (NOW), and Cape Bathurst. A 182 km dedicated survey of Moving Vessel Profiler (MVP), equipped with CTD, transmissometer, dissolved oxygen, fluorescence, sound velocity sensors, was conducted across Hudson Strait. We also present an overview of the data collected by the underway systems (seabed, thermosalinograph and atmospheric). Such data are essential in understanding the impacts of climate warming on the unique environments of the Canadian Arctic Ocean. Amundsen Science supports and promotes easy access and sharing of such valuable data to the scientific community. [ABSTRACT FROM AUTHOR]

Floods are the primary natural hazard in the French Mediterranean area causing damages and fatalities every year. These floods are triggered by heavy precipitation events (HPEs) characterized by limited temporal and spatial extents. A new generation of regional climate models at the kilometer scale have been developed, allowing an explicit representation of deep convection and improved simulations of local-scale phenomena such as HPEs. Convection-Permitting regional climate Models (CPMs) have been scarcely used in hydrological impact studies, and future projections of Mediterranean floods remain uncertain with Regional Climate Models (RCMs). In this paper, we use the CNRM-AROME CPM (2.5 km) and its driving CNRM-ALADIN RCM (12 km) at the hourly timescale to simulate floods over the Gardon at Anduze catchment located in the French Mediterranean region. Climate simulations are bias-corrected with the CDF-t method. Two hydrological models, a lumped and conceptual model (GR5H), and a process-based distributed model (CREST), forced with historical and future climate simulations from the CPM and from the RCM, have been used. The CPM model confirms its ability to better reproduce extreme hourly rainfall compared to the RCM. This added value is propagated on flood simulation with a better reproduction of flood peaks. Future projections are consistent between the hydrological models, but differ between the two climate models. With the CNRM-ALADIN RCM, all floods are projected to increase, whereas a threshold effect is found for simulations driven by the CNRM-AROME CPM, where the magnitude of the largest floods is expected to increase while the moderate floods are expected to decrease. In addition, different flood event characteristics indicate that floods are expected to become flashier in a warmer climate, regardless of the model. This study is a first step for impact studies driven by CPMs over the Mediterranean. [ABSTRACT FROM AUTHOR]

The oceans are losing oxygen (O2) and oxygen minimum zones are expanding, due to climate warming (lower O2 solubility) and artificial fertilization related to agriculture. This ongoing trend is challenging for most marine taxa that are not well adapted to O2 depletion. For other taxa this trend might be advantageous, because they can withstand low O2 concentrations or thrive under anaerobic or even anoxic conditions. Benthic foraminifera are a group of protists that might benefit from ongoing ocean deoxygenation, since several foraminifera species possess adaptations to O2 depletion that are unique amongst eukaryotes. This paper reviews the current state of knowledge about foraminifera from low O2 environments. The specific survival strategies of foraminifera to withstand O2 depletion include an anaerobic metabolism, heterotrophic denitrification, symbiosis with bacteria, kleptoplasty and dormancy. These adaptations, especially the ability to denitrify by some benthic foraminiferal species, have a strong impact on their preferred microhabitat in the sediments, which will be discussed in detail. In addition, due to their high abundances in O2 depleted environments and their metabolic adaptations, benthic foraminifera are key players in marine nutrient cycling, especially within the marine N and P cycles. Studies about the ecology of benthic foraminifera are scarce but there is evidence that foraminifers have the capacity of phagocytosis, even under anoxia, and some foraminiferal species, which can withstand low O2 conditions, even seem to prey on meiofauna. Finally, the fact that foraminifera can calcify even under anaerobic conditions makes them important archives for paleoceanographic applications. So this review will briefly summarize O2 proxies based on foraminiferal morphology, shell geochemistry and composition of foraminiferal assemblages. [ABSTRACT FROM AUTHOR]

Annual reductions in Arctic sea ice extent (SIE) due to global warming. According to International Panel on Climate Change (IPCC) climate model projections, the summer Arctic will be nearly sea ice free in the 50s of the 21st century, resulting in sea level rise and thus affecting human life. Therefore, it is important to predict SIE accurately. For the most current studies, the majority of deep learning-based SIE prediction models focus on single-step prediction, and they not only have short lead times but also have limited forecasting skills. In addition, these models often lack interpretability. In this study paper, we construct the Ice Temporal Fusion Transformer (IceTFT) model, which consists mainly of the variable selection network (VSN), the long short-term memory (LSTM) encoder, and multi-headed attention mechanism. Then we select 11 predictors for IceTFT model, including SIE, atmospheric, and ocean variables according to the physical mechanisms influencing sea ice development. And the VSN in IceTFT can automatically adjust the weights of predictors and filter spuriously correlated variables. We also evaluate the IceTFT model from the division of the training set, the slicing methods of input data, and the length of input. The IceTFT model directly generates 12-month SIE with average monthly prediction errors of less than 0.21 106 km2. And it predicts the September SIE nine months in advance with prediction error of less than 0.1 106 km2, which is superior to the models from Sea Ice Outlook (SIO). Furthermore, we analyze the sensitivity of the selected predictors to the SIE prediction. It verifies that the IceTFT model has some physical interpretability. And the variable sensitivities also provide some reference for understanding the mechanisms governing sea ice development and selecting the assimilation variables in dynamic models. [ABSTRACT FROM AUTHOR]

Canada has major sources of atmospheric methane (CH4), with the world's second-largest boreal wetland and the world's fourth-largest natural gas production. However, Canada's CH4 emissions remain uncertain among estimates. Better quantification and characterization of Canada's CH4 emissions are critical for climate mitigation strategies. To improve our understanding of Canada's CH4 emissions, we performed an ensemble regional inversion for 2007–2017 constrained with the Environment and Climate Change Canada (ECCC) surface measurement network. The decadal CH4 estimates show no significant trend, unlike some studies that reported long-term trends. The total CH4 estimate is 17.4 (15.3–19.5) TgCH4yr-1 , partitioned into natural and anthropogenic sources at 10.8 (7.5–13.2) and 6.6 (6.2–7.8) TgCH4yr-1 , respectively. The estimated anthropogenic emission is higher than inventories, mainly in western Canada (with the fossil fuel industry). Furthermore, the results reveal notable spatiotemporal characteristics. First, the modelled differences in atmospheric CH4 among the sites show improvement after inversion when compared to observations, implying the CH4 observation differences could help in verifying the inversion results. Second, the seasonal variations show slow onset and a late-summer maximum, indicating wetland CH4 flux has hysteretic dependence on air temperature. Third, the boreal winter natural CH4 emissions, usually treated as negligible, appear quantifiable (≥ 20 % of annual emissions). Understanding winter emission is important for climate prediction, as the winter in Canada is warming faster than the summer. Fourth, the inter-annual variability in estimated CH4 emissions is positively correlated with summer air temperature anomalies. This could enhance Canada's natural CH4 emission in the warming climate. [ABSTRACT FROM AUTHOR]

The Northeast Greenland Shelf is a region currently considered to be an annual net sink of carbon dioxide (CO2) from the atmosphere. Water from the Northeast Greenland Shelf is advected to the formation regions of North Atlantic Deep Water; therefore, any carbon stored in the region may be retained in the global oceans on the timescales of the thermohaline circulation. We present the most extensive study of carbon chemistry on the Northeast Greenland Shelf to date, made possible by opportunistic sampling due to a sudden decrease in the sea ice concentration in late-August and September 2017. These are the first full-depth measurements of total alkalinity and dissolved inorganic carbon at latitudes between 75 and 79° N, with additional data collected in the region of the Northeast Water Polynya and outside of Young Sound. We find that surface mixed-layer concentrations are variable and (for many stations) higher than the interpolated atmospheric concentration for the region during the sampling period. Below the surface mixed layer, CO2 concentrations increase linearly with decreasing apparent oxygen utilisation. The mixed layer deepens during the study period; this is associated with apparent changes in CO2 uptake. The Northeast Greenland Shelf is a hydrologically complex region with many processes influencing the carbonate system at smaller scales than our sampling density. The scatter in the dataset represents more than mere outliers, and the lack of relationship between the outliers and any measured variable indicates a strong influence of a currently undescribed (set of) variable(s) and/or process(es) at the sampled scales. These data were collected during a time of radically low sea ice concentrations for the region and may be an indication of future conditions. As they indicate the potential of the region to act as a seasonal source of CO2 to the atmosphere, this may modify our current estimate of the region as a strong annual net sink that is relatively protected from the immediate influence of atmospheric warming and climate change. [ABSTRACT FROM AUTHOR]

"Global change" significantly alters organic matter and element cycling, but many of the underlying processes and consequences remain poorly understood. The interface of plants and soil plays a central role, coupling the atmosphere, hydrosphere, biosphere and lithosphere and integrating biological and geochemical processes. The contributions to this special issue address questions on both biotic and abiotic interactions underlying responses of terrestrial biogeochemical cycling to a range of global changes, including increases in atmospheric CO 2 concentrations, warming, drought and altered water regimes. In this overview, we synthesize key findings of the contributing empirical, conceptual and modelling-based studies covering responses of plants to elevated CO 2 ; the role of soil organisms in modulating responses to warming; impacts of global change on soil organic carbon, nitrogen, and mineral nutrient availability; and the influence of altered water-table depth caused by global change on greenhouse gas emissions. The showcased studies were conducted in regions from the Arctic to the tropics and highlight the manifold impacts of global change on various ecosystem components controlling biogeochemical processes occurring at the plant–soil interface. This multi-ecosystem interdisciplinary understanding is crucial for deciphering feedbacks of terrestrial ecosystems to the climate system. [ABSTRACT FROM AUTHOR]

Climate warming exacerbates the degradation of the mountain cryosphere, including glacier retreat, permafrost degradation, and snow cover reduction. These changes dramatically alter the local and downstream hydrological regime, posing significant threats to basin-scale water resource management and sustainable development. However, this issue is still not adequately addressed, particularly in mountainous catchments. We developed an integrated cryospheric–hydrologic model, the FLEX-Cryo model, to comprehensively consider glaciers, snow cover, and frozen soil and their dynamic impacts on hydrological processes. Taking the mountainous Hulu catchment located in the upper Heihe River of China as a case study, we utilized the state-of-the-art climate change projection data under two scenarios (SSP2-4.5 and SSP5-8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate the future changes in the mountainous cryosphere and their impacts on hydrology. Our findings showed that under the medium-emission scenario (SSP2-4.5) and high-emission scenario (SSP5-8.5), by the end of the 21st century, the glacier will completely melt out around the years 2051 and 2045, respectively. The annual maximum snow water equivalent is projected to decrease by 41.4 % and 46.0 %, while the duration of snow cover will be reduced by approximately 45 and 70 d. The freeze onset of seasonally frozen soil is expected to be delayed by 10 and 22 d, while the thaw onset of permafrost is likely to advance by 19 and 32 d. Moreover, the maximum freeze depth of seasonally frozen soil is projected to decrease by 5.2 and 10.9 cm per decade, and the depth of the active layer will increase by 8.2 and 15.5 cm per decade. Regarding hydrology, catchment total runoff exhibits a decreasing trend, and the tipping point of glacier runoff occurs approximately between 2019 and 2021. Permafrost degradation will likely reduce the duration of low runoff in the early thawing season; the discontinuous baseflow recession gradually transitions into linear recessions, and the baseflow increases. Our results highlight the significant changes expected in the mountainous cryosphere and hydrology in the future. These findings enhance our understanding of cold-region hydrological processes and have the potential to assist local and downstream water resource management in addressing the challenges posed by climate change. [ABSTRACT FROM AUTHOR]

This study evaluates the seasonal and inter-seasonal temperature regime of small tundra ponds ubiquitous to an extensive, low-gradient wetland in the Canadian High Arctic. Pond temperatures can modify evaporation and ground thaw rates, impact losses of greenhouse gases, and control the timing and emergence of insects and larvae critical for migratory-bird feeding habits. We focus our study on thaw ponds with a range of hydrologic linkages and sizes across Nanuit Itillinga, formerly known as Polar Bear Pass (PBP), Bathurst Island, and compare their thermal signals to other Arctic ponds. Pond temperatures and water levels were evaluated using temperature and water level loggers and verified by regular manual measurements. Other environmental data collected included microclimate, frost table depths, and water conductivity. Our results show that there is much variability in pond thermal regimes over seasons, years, and space. Cumulative relative pond temperatures were similar across years, with ponds normally reaching 10–15 °C for short to longer periods, except in 2013, which experienced a cold summer season during which pond temperatures never exceeded 5 °C. Pond frost tables and water conductivities respond to variable substrate conditions and pond thermal patterns. This study contributes to the ongoing discussion on climate warming and its impact on Arctic landscapes. [ABSTRACT FROM AUTHOR]

Emissions from agricultural sources substantially contribute to global warming. The inverse dispersion method (IDM) has been successfully used for emission measurements from various agricultural sources. The IDM has also been validated in multiple studies with artificial gas releases mostly in open fields. Release experiments from buildings have rarely been conducted and were partly affected by additional nearby sources of the target gas. Specific release studies for naturally ventilated animal housings are lacking. In this study, a known and predefined amount of methane (CH 4) was released from an artificial source inside a barn that mimicked a naturally ventilated dairy housing, and IDM recovery rates, using a backward Lagrangian stochastic (bLS) model, were determined. For concentration measurements, open-path devices (OPs) with a path length of 110 m were placed in a downwind direction of the barn at fetches of 2.0 h , 5.3 h , 8.6 h , and 12 h (h equals the height of the highest obstacle), and a 3D ultrasonic anemometer (UA) was placed in the middle of the first three OP paths. Upwind of the barn, an additional OP and a UA were installed. The median IDM recovery rates determined with the UA placed upwind of the barn and the downwind OP ranged between 0.55–0.75. It is concluded that, for the present study case, the effect of the building and a tree in the main wind axis led to a systematic underestimation of the IDM-derived emission rate probably due to deviations in the wind field and turbulent dispersion from the underlying assumptions of the used dispersion model. [ABSTRACT FROM AUTHOR]

Observations and models indicate that climate warming is associated with the loss of dissolved oxygen from the ocean. Dissolved oxygen is a fundamental requirement for heterotrophic marine organisms (except marine mammals) and, since the basal metabolism of ectotherms increases with temperature, warming increases organisms' oxygen demands. Therefore, warming and deoxygenation pose a compound threat to marine ecosystems. In this study, we leverage an ecophysiological framework and a compilation of empirical trait data quantifying the temperature sensitivity and oxygen requirements of metabolic rates for a range of marine species ("ecotypes"). Using the Community Earth System Model Large Ensemble, we investigate how natural climate variability and anthropogenic forcing impact the ability of marine environments to support aerobic metabolisms on interannual to multi-decadal timescales. Warming and deoxygenation projected over the next several decades will yield a reduction in the volume of viable ocean habitats. We find that fluctuations in temperature and oxygen associated with natural variability are distinct from those associated with anthropogenic forcing in the upper ocean. Further, the joint temperature–oxygen anthropogenic signal emerges sooner than temperature and oxygen independently from natural variability. Our results demonstrate that anthropogenic perturbations underway in the ocean will strongly exceed those associated with the natural system; in many regions, organisms will be pushed closer to or beyond their physiological limits, leaving the ecosystem more vulnerable to extreme temperature–oxygen events. [ABSTRACT FROM AUTHOR]

Speed restrictions for ships have been introduced locally to reduce the waves and turbulence causing erosion, and safety hazards, and to mitigate the air and underwater noise emissions. Ship speed restrictions could be used to minimize the climate impact of maritime transport since many air pollutants in ship exhaust gas are reduced when travelling at lower speeds. However, for example, methane and black carbon emissions do not linearly correlate with the load of internal combustion engines. Therefore, the effect of speed restrictions may not be trivial. Black carbon concentrations from ship plumes were examined at a remote marine site in the southwestern Finnish archipelago. Ships with service speeds over 15 kn and equipped with an exhaust gas cleaning system were analysed for black carbon emissions as a function of speed. Both unadjusted and weather-adjusted main engine loads were modelled to determine load-based emission factors. Black carbon concentration per kilogram of fuel decreased as a function of engine load. However, calculated per hour, the black carbon emission increased as a function of ship speed, reaching peak values at around 15–20 kn and decreasing thereafter. In terms of local air quality, total black carbon emission per nautical mile was the highest around the halved speeds, 10–13 kn, or when the speed was higher than 20–23 kn. From a climate warming perspective, the CO 2 emissions dominated the exhaust gas, and reducing the speed decreased the global warming potential in CO 2 equivalent, both per hour and per nautical mile. [ABSTRACT FROM AUTHOR]

The use of different primary energy sources in human society has led to two major polluting emissions in the environment: energy (mostly heat), and chemical substances (mostly carbon dioxide). In this paper, a new approach, based on the similarity between sensible heat and CO2 transfer properties, was used to determine the effect of anthropogenic heat release on the global air temperature. The total global anthropogenic emissions of sensible heat were divided into two separate streams: directly transferred to: (1) water and land, and (2) to the atmosphere. The direct emissions of heat to the atmosphere during the industrial era (years 1850-2018) were determined and their effect on the change of global atmospheric temperature was calculated. The global atmospheric temperature increase caused by anthropogenic heat emissions was estimated. The resulting calculations showed that at least half of the actual atmospheric temperature rise recorded during the last 170-year period, was due to the anthropogenic heat release. These results suggest that the temperature change of the atmosphere (global warming) is strongly affected by anthropogenic heat emissions. [ABSTRACT FROM AUTHOR]

Recent observation-based studies suggest that the Amazon rainforest has lost substantial resilience since 1990, indicating that the forest might undergo a critical transition in the near future due to global warming and deforestation. The idea is to use trends in a lag-1 auto-correlation of leaf density as an early-warning signal of an imminent critical threshold for rainforest dieback. Here we test whether the observed change in auto-correlations could arise from internal variability using historical and control simulations of nine sixth-generation Earth system model ensembles (Phase 6 of the Coupled Model Intercomparison Project, CMIP6). We quantify trends in the leaf area index auto-correlation from both models and satellite-observed vegetation optical depth from 1990 to 2017. Four models reproduce the observed trend with at least one historical realization whereby the observations lie at the upper limit of model variability. Three out of these four models exhibit similar behavior in control runs, suggesting that historical forcing is not necessary for simulating the observed trends. Furthermore, we do not observe a critical transition in any future runs under the strongest greenhouse gas emission scenario (SSP5-8.5) until 2100 in the four models that best reproduce the past observed trends. Hence, the currently observed trends could be caused simply by internal variability and, unless the data records are extended, have limited applicability as an early-warning signal. Our results suggest that the current rapid decline in the Amazon rainforest coverage is not foremost caused by global warming. [ABSTRACT FROM AUTHOR]

While climate models broadly agree on the changes expected to occur over the Arctic with global warming on a pan-Arctic scale (i.e. polar amplification, sea ice loss, and increased precipitation), the magnitude and patterns of these changes at regional and local scales remain uncertain. This limits the usability of climate model projections for risk assessments and their impact on human activities or ecosystems (e.g. fires and permafrost thawing). Whereas any single or ensemble mean projection may be of limited use to stakeholders, recent studies have shown the value of the storyline approach in providing a comprehensive and tractable set of climate projections that can be used to evaluate changes in environmental or societal risks associated with global warming. Here, we apply the storyline approach to a large ensemble of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with the aim of distilling the wide spread in model predictions into four physically plausible outcomes of Arctic summertime climate change. This is made possible by leveraging strong covariability in the climate system associated with well-known but poorly constrained teleconnections and local processes; specifically, we find that differences in Barents–Kara sea warming and lower-tropospheric warming over polar regions among CMIP6 models explain most of the inter-model variability in pan-Arctic surface summer climate response to global warming. Based on this novel finding, we compare regional disparities in climate change across the four storylines. Our storyline analysis highlights the fact that for a given amount of global warming, certain climate risks can be intensified, while others may be lessened, relative to a "middle-of-the-road" ensemble mean projection. We find this to be particularly relevant when comparing climate change over terrestrial and marine areas of the Arctic which can show substantial differences in their sensitivity to global warming. We conclude by discussing the potential implications of our findings for modelling climate change impacts on ecosystems and human activities. [ABSTRACT FROM AUTHOR]

The East Asian Monsoon (EAM) dominates the climate over the densely populated region of eastern China and adjacent regions and therefore influences a fifth of the world's population. Thus, it is highly relevant to assess the changes in the central characteristics of the East Asian Summer Monsoon (EASM) under future warming in the latest generation of coupled climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6). We apply a set of selection criteria to 34 CMIP6 models to identify the six best performing (TOP6) models that best capture the EASM in the reference period 1995–2014. All of these models project an increase in June–August rainfall independent of the underlying emission scenario. The multi-model mean increase is 16.5 % under SSP5-8.5, 11.8 % under SSP3-7.0, 12.7 % under SSP2-4.5 and 9.3 % under SSP1-2.6 in the period 2081–2100 compared to 1995–2014. For China, the projected monsoon increase is slightly higher (12.6 % under SSP1-2.6 and 18.1 % under SSP5-8.5). The EASM rainfall will particularly intensify in southeastern China, Taiwan and North Korea. The multi-model mean indicates a linear relationship of the EASM rainfall depending on the global mean temperature that is relatively independent of the underlying scenario: per degree of global warming, the rainfall is projected to increase by 0.17 mm d -1 , which refers to 3.1 % of rainfall in the reference period. It is thus predominately showing a "wet regions get wetter" pattern. The changes in the wind fields in the region are relatively small indicating the minor importance of dynamic factors, while pointing towards thermodynamic factors as responsible for the rainfall increase. The interannual variability is also robustly projected to increase between 17.6 % under SSP1-2.6 and 23.8 % under SSP5-8.5 in the multi-model mean between 2051–2100 and 1965–2014. Comparing the same periods, extremely wet seasons are projected to occur 7 times more often under SSP5-8.5. [ABSTRACT FROM AUTHOR]

The mid-Pliocene is the most recent geological period with similar atmospheric CO2 concentration to the present day and similar surface temperatures to those projected at the end of this century for a moderate warming scenario. While not a perfect analogue, the mid-Pliocene can be used to study the functioning of the Earth system under similar forcings to a near future, especially regarding features in the climate system for which uncertainties exist in future projections. According to the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), the variability in the El Niño–Southern Oscillation (ENSO) was suppressed. In this study, we investigate how teleconnections of ENSO, specifically variability in the North Pacific atmosphere, respond to a suppressed ENSO according to PlioMIP2. The multi-model mean (MMM) shows a similar sea-level pressure (SLP) variability in the Aleutian Low (AL) in the mid-Pliocene and pre-industrial, but a per-model view reveals that the change in AL variability is related to the change in ENSO variability. Even though ENSO is suppressed, the teleconnection between ENSO sea-surface temperature (SST) anomalies, tropical precipitation, and North Pacific SLP anomalies is quite robust in the mid-Pliocene. We split AL variability in a part that is ENSO-related, and a residual variability which is related to internal stochastic variability, and find that the change in ENSO-related AL variability is strongly related to the change in ENSO variability itself, while the change in residual AL variability is unrelated to ENSO change. Since the internal atmospheric variability, which is the dominant forcing of the AL variability, is largely unchanged, we are able to understand that the AL variability is largely similar even though ENSO variability is suppressed. We find that the specific change in ENSO and AL variability depends on both the model equilibrium climate sensitivity and Earth system sensitivity. Finally, we present a perspective of (extra-)tropical Pacific variability in PlioMIP2, combining our results with literature findings on changes in the tropical mean climate and in the Pacific Decadal Oscillation (PDO). [ABSTRACT FROM AUTHOR]

Global mean sea level during the mid-Pliocene epoch (∼3 Ma), when CO2 and temperatures were above present levels, was notably higher than today due to reduced global ice sheet coverage. Nevertheless, the extent to which ice sheets responded to Pliocene warmth remains in question owing to high levels of uncertainty in proxy-based sea level reconstructions as well as solid Earth dynamic models that have been used to evaluate a limited number of data constraints. Here, we present a global dataset of 10 wave-cut scarps that formed by successive Pliocene sea level oscillations and which are observed today at elevations ranging from ∼6 to 109 m above sea level. The present-day elevations of these features have been identified using a combination of high-resolution digital elevation models and field mapping. Using the MATLAB interface TerraceM, we extrapolate the cliff and platform surfaces to determine the elevation of the scarp toe, which in most settings is buried under meters of talus. We correct the scarp-toe elevations for glacial isostatic adjustment and find that this process alone cannot explain observed differences in Pliocene paleo-shoreline elevations around the globe. We next determine the signal associated with mantle dynamic topography by back-advecting the present-day three-dimensional buoyancy structure of the mantle and calculating the difference in radial surface stresses over the last 3 Myr using the convection code ASPECT. We include a wide range of present-day mantle structures (buoyancy and viscosity) constrained by seismic tomography models, geodynamic observations, and rock mechanics laboratory experiments. Finally, we identify preferred dynamic topography change predictions based on their agreement with scarp elevations and use our most confident result to estimate a Pliocene global mean sea level based on one scarp from De Hoop, South Africa. This inference (11.6 ± 5.2 m) is a downward revision and may imply that ice sheets were relatively resistant to warm Pliocene climate conditions. We also conclude, however, that more targeted model development is needed to more reliably infer mid-Pliocene global mean sea level based on all scarps mapped in this study. [ABSTRACT FROM AUTHOR]

The Oligocene (33.9–23.03 Ma) had warm climates with flattened meridional temperature gradients, while Antarctica retained a significant cryosphere. These may pose imperfect analogues to distant future climate states with unipolar icehouse conditions. Although local and regional climate and environmental reconstructions of Oligocene conditions are available, the community lacks synthesis of regional reconstructions. To provide a comprehensive overview of marine and terrestrial climate and environmental conditions in the Oligocene, and a reconstruction of trends through time, we review marine and terrestrial proxy records and compare these to numerical climate model simulations of the Oligocene. Results, based on the present relatively sparse data, suggest temperatures around the Equator that are similar to modern temperatures. Sea surface temperatures (SSTs) show patterns similar to land temperatures, with warm conditions at mid- and high latitudes (∼60 –90°), especially in the Southern Hemisphere (SH). Vegetation-based precipitation reconstructions of the Oligocene suggest regionally drier conditions compared to modern times around the Equator. When compared to proxy data, climate model simulations overestimate Oligocene precipitation in most areas, particularly the tropics. Temperatures around the mid- to high latitudes are generally underestimated in models compared to proxy data and tend to overestimate the warming in the tropics. In line with previous proxy-to-model comparisons, we find that models underestimate polar amplification and overestimate the Equator-to-pole temperature gradient suggested from the available proxy data. This further stresses the urgency of solving this widely recorded problem for past warm climates, such as the Oligocene. [ABSTRACT FROM AUTHOR]

Global warming has enduring consequences in the ocean, leading to increased sea surface temperatures (SSTs) and subsequent environmental impacts, including coral bleaching and intensified tropical storms. It is imperative to monitor these trends to enable informed decision-making and adaptation. In this study, we comprehensively examine the methods for extracting long-term temperature trends, including STL, seasonal-trend decomposition procedure based on LOESS (locally estimated scatterplot smoothing), and the linear regression family, which comprises the ordinary least-squares regression (OLSR), orthogonal regression (OR), and geometric-mean regression (GMR). The applicability and limitations of these methods are assessed based on experimental and simulated data. STL may stand out as the most accurate method for extracting long-term trends. However, it is associated with notably sizable computational time. In contrast, linear regression methods are far more efficient. Among these methods, GMR is not suitable due to its inherent assumption of a random temporal component. OLSR and OR are preferable for general tasks but require correction to accurately account for seasonal signal-induced bias resulting from the phase–distance imbalance. We observe that this bias can be effectively addressed by trimming the SST data to ensure that the time series becomes an even function before applying linear regression, which is named "evenization". We compare our methods with two commonly used methods in the climate community. Our proposed method is unbiased and better than the conventional SST anomaly method. While our method may have a larger degree of uncertainty than combined linear and sinusoidal fitting, this uncertainty remains within an acceptable range. Furthermore, linear and sinusoidal fitting can be unstable when applied to natural data containing significant noise. [ABSTRACT FROM AUTHOR]

The porous layer of snow and firn on the Greenland Ice Sheet stores meltwater and limits the rate at which the ice sheet contributes to sea level rise. This buffer is threatened in a warming climate. To better understand the nature and timescales of firn's response to air temperature change on the Greenland Ice Sheet, we use a physics-based model to assess the effects of atmospheric warming and cooling on Greenland's firn air content in idealized climate experiments. We identify an asymmetric response of Greenland's firn to air temperature: firn loses more air content due to warming compared to the amount gained from commensurate cooling. 100 years after a 1 °C temperature perturbation, warming decreases the spatially integrated air content by 9.7 %, and cooling increases it by 8.3 %. In dry firn, this asymmetry is driven by the highly nonlinear relationship between temperature and firn compaction, as well as the dependence of thermal conductivity on the composition of the firn. The influence of liquid water accentuates this asymmetry. In wet firn areas, melt increases nonlinearly with atmospheric warming, thus enhancing firn refreezing and further warming the snowpack through increased latent heat release. Our results highlight the vulnerability of Greenland firn to temperature change and demonstrate that firn air content is more efficiently depleted than generated. This asymmetry in the temperature–firn relationship may contribute to the overall temporally asymmetric mass change of the Greenland Ice Sheet in a changing climate across many timescales. [ABSTRACT FROM AUTHOR]

Climate warming has a stronger impact on Arctic climate and sea ice cover (SIC) decline than previously thought. Better understanding and characterization of the relationship between sea ice and clouds and the implications for surface radiation is key to improving our confidence in Arctic climate projections. Here we analyze the relationship between sea ice, cloud phase and surface radiation over the Arctic, defined as north of 60° N, using active- and passive-sensor satellite observations from three different datasets. We find that all datasets agree on the climatology of and seasonal variability in total and liquid-bearing (liquid and mixed-phase) cloud covers. Similarly, our results show a robust relationship between decreased SIC and increased liquid-bearing clouds in the lowest levels (below 3 km) for all seasons (strongest in winter) but summer, while increased SIC and ice clouds are positively correlated in two of the three datasets. A refined map correlation analysis indicates that the relationship between SIC and liquid-bearing clouds can change sign over the Bering, Barents and Laptev seas, likely because of intrusions of warm air from low latitudes during winter and spring. Finally, the increase in liquid clouds resulting from decreasing SIC is associated with enhanced radiative cooling at the surface. Our findings indicate that the newly formed liquid clouds reflect more shortwave (SW) radiation back to space compared to the surface, generating a cooling effect of the surface, while their downward longwave (LW) radiation is similar to the upward LW surface emission, which has a negligible radiative impact on the surface. This overall cooling effect should contribute to dampening future Arctic surface warming as SIC continues to decline. [ABSTRACT FROM AUTHOR]

Earth system model experiments presented here explore how the centennial response in the Southern Ocean can drive ongoing global warming even with zero CO 2 emissions and declining atmospheric CO 2 concentrations. These projections were simulated by the earth system model version of the Australian Community Climate and Earth System Simulator (ACCESS-ESM1.5) and motivated by the Zero Emissions Commitment Model Intercomparison Project (ZECMIP); ACCESS-ESM1.5 simulated ongoing warming in the ZECMIP experiment that switched or branched to zero emissions after 2000 PgC had been emitted. New experiments presented here each simulated 300 years and included intermediate branch points. In each experiment that branched after emitting more than 1000 PgC, the global climate continues to warm. For the experiment that branched after 2000 PgC, or after 3.5 °C of warming from a preindustrial climate, there is 0.37 ± 0.08 °C of extra warming after 50 years of zero emissions, which increases to 0.83 ± 0.08 °C after 200 years. All branches show ongoing Southern Ocean warming. The circulation of the Southern Ocean is modified early in the warming climate, which contributes to changes in the distribution of both physical and biogeochemical subsurface ocean tracers, such as ongoing warming at intermediate depths and a reduction in deep oxygen south of 60° S. A simple slab model emulates the global temperatures of the ACCESS-ESM1.5 experiments demonstrating the response here is primarily due to the slow response of the ocean and the Southern Ocean in particular. Centennial global warming persists when the slab model is forced with CO 2 diagnosed from late-branching experiments with other ZECMIP models, confirming the dominant role of ocean physics at these timescales. However, decadal responses changed due to the larger drawdown of CO 2 from other models. Slow ongoing warming in the Southern Ocean can be found in ZEC scenarios of most models, though the amplitude and global influence varies. [ABSTRACT FROM AUTHOR]

Cold extremes have large impacts on human society. Understanding the physical processes dominating the changes in cold extremes is crucial for a reliable projection of future climate change. The observed cold extremes have decreased during the last several decades, and this trend will continue under future global warming. Here, we quantitatively identify the contributions of dynamic (changes in large-scale atmospheric circulation) and thermodynamic (rising temperatures resulting from global warming) effects to East Asian cold extremes in the past several decades and in a future warm climate by using two sets of large-ensemble simulations of climate models. We show that the dynamic component accounts for over 80 % of the cold-month (coldest 5 % boreal winter months) surface air temperature (SAT) anomaly over the past 5 decades. However, in a future warm climate, the thermodynamic change is the main contributor to the decreases in the intensity and occurrence probability of East Asian cold extremes, while the dynamic change is also contributive. The intensity of East Asian cold extremes will decrease by around 5 °C at the end of the 21st century, in which the thermodynamic (dynamic) change contributes approximately 75 % (25 %). The present-day (1986–2005) East Asian cold extremes will almost never occur after around 2035, and this will happen 10 years later due solely to thermodynamic change. The upward trend of a positive Arctic Oscillation-like sea level pressure pattern dominates the changes in the dynamic component. The finding provides a useful reference for policymakers in climate change adaptation activities. [ABSTRACT FROM AUTHOR]

Hydrofluorocarbons (HFCs) are powerful anthropogenic greenhouse gases (GHGs) with high global-warming potentials (GWPs). They have been widely used as refrigerants, insulation foam-blowing agents, aerosol propellants, and fire suppression agents. Since the mid-1990s, emissions of HFCs have been increasing rapidly as they are used in many applications to replace ozone-depleting chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) whose consumption and production have been phased out under the Montreal Protocol (MP). Due to the high GWP of HFCs, the Kigali Amendment to the MP requires the phasedown of production and consumption of HFCs to gradually achieve an 80 %–85 % reduction by 2047, starting in 2019 for non-Article 5 (developed) countries with a 10 % reduction against each defined baseline and later schedules for Article 5 (developing) countries. In this study, we have examined long-term high-precision measurements of atmospheric abundances of five major HFCs (HFC-134a, HFC-143a, HFC-32, HFC-125, and HFC-152a) at Gosan station, Jeju Island, South Korea, from 2008 to 2020. Background abundances of HFCs gradually increased, and the inflow of polluted air masses with elevated abundances from surrounding source regions were detected over the entire period. From these pollution events, we inferred regional and country-specific HFC emission estimates using two independent Lagrangian particle dispersion models and Bayesian inversion frameworks (FLEXPART-FLEXINVERT + and NAME-InTEM). The spatial distribution of the derived "top-down" (measurement based) emissions for all HFCs shows large fluxes from megacities and industrial areas in the region. Our most important finding is that HFC emissions in eastern China and Japan have sharply increased from 2016 to 2018. The contribution of East Asian HFC emissions to the global total increased from 9 % (2008–2014) to 13 % (2016–2020). In particular, HFC emissions in Japan (Annex I country) rose rapidly from 2016 onward, with accumulated total inferred HFC emissions being ∼ 114 Gg yr -1 , which is ∼ 76 Gg yr -1 higher for 2016–2020 than the "bottom-up" (i.e., based on activity data and emission factors) emissions of ∼ 38 Gg yr -1 reported to the United Nations Framework Convention on Climate Change (UNFCCC). This is likely related to the increase in domestic demand in Japan for refrigerants and air-conditioning-system-related products and incomplete accounting. A downward trend of HFC emissions that started in 2019 reflects the effectiveness of the F-gas policy in Japan. Eastern China and South Korea, though not obligated to report to the UNFCCC, voluntarily reported emissions, which also show differences between top-down and bottom-up emission estimates, demonstrating the need for atmospheric measurements, comprehensive data analysis, and accurate reporting for precise emission management. Further, the proportional contribution of each country's CO 2 -equivalent HFC emissions has changed over time, with HFC-134a decreasing and HFC-125 increasing. This demonstrates the transition in the predominant HFC substances contributing to global warming in each country. [ABSTRACT FROM AUTHOR]

Melting polar and alpine ice sheets in response to global warming pose ecological and societal risks but will also hamper our ability to reconstruct past climate and atmospheric composition across the globe. Since polar ice caps are crucial environmental archives but highly sensitive to ongoing climate warming, the Arctic and Antarctic research community is increasingly faced with melt-affected ice cores, which are already common in alpine settings of the lower latitudes. Here, we review the characteristics and effects of near-surface melting on ice-core records, focusing on a polar readership and making recommendations for melt-prone study regions. This review first covers melt layer formation, identification and quantification of melt, and structural characteristics of melt features. Subsequently, it discusses effects of melting on records of chemical impurities, i.e. major ions, trace elements, black carbon, and organic species as well as stable water isotopic signatures, gas records, and applications of melt layers as environmental proxies. Melting occurs during positive surface energy balance events, which are shaped by global to local meteorological forcing, regional orography, glacier surface conditions and subsurface characteristics. Meltwater flow ranges from homogeneous wetting to spatially heterogeneous preferential flow paths and is determined by temperature, thermal conductivity and stratigraphy of the snowpack. Melt layers and lenses are the most common consequent features in ice cores and are usually recorded manually or using line scanning. Chemical ice-core proxy records of water-soluble species are generally less preserved than insoluble particles such as black carbon or mineral dust due to their strong elution behaviour during percolation. However, high solubility in ice as observed for ions like F - , Cl - , NH 4+ or ultra-trace elements can counteract the high mobility of these species due to burial in the ice interior. Stable water isotope records like δ18 O are often preserved but appear smoothed if significant amounts of meltwater are involved. Melt-affected ice cores are further faced with questions about the permeability of the firn column for gas movement, and gas concentrations can be increased through dissolution and in situ production. Noble gas ratios can be useful tools for identifying melt-affected profile sections in deep ice. Despite challenges for ice-core climate reconstruction based on chemical records, melt layers are a proxy of warm temperatures above freezing, which is most sensitive in the dry snow and percolation zone. Bringing together insights from snow physics, firn hydrology, and ice-core proxy research, we aim to foster a more comprehensive understanding of ice cores as climate and environmental archives, provide a reference on how to approach melt-affected records, and raise awareness of the limitations and potential of melt layers in ice cores. [ABSTRACT FROM AUTHOR]