Climate Forcing Research Articles

A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations

Abstract. Cloud condensation nuclei (CCN) are mediators of aerosol–cloud interactions (ACIs), contributing to the largest uncertainties in the understandings of global climate change. We present a novel remote-sensing-based algorithm that quantifies the vertically resolved CCN number concentrations (NCCN) using aerosol optical properties measured by a multiwavelength lidar. The algorithm considers five distinct aerosol subtypes with bimodal size distributions. The inversion used the lookup tables developed in this study, based on the observations from the Aerosol Robotic Network, to efficiently retrieve optimal particle size distributions from lidar measurements. The method derives dry aerosol optical properties by implementing hygroscopic enhancement factors in lidar measurements. The retrieved optically equivalent particle size distributions and aerosol-type-dependent particle composition are utilized to calculate critical diameters using κ-Köhler theory and NCCN at six supersaturations ranging from 0.07 % to 1.0 %. Sensitivity analyses indicate that uncertainties in extinction coefficients and relative humidity greatly influence the retrieval error in NCCN. The potential of this algorithm is further evaluated by retrieving NCCN using airborne lidar from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and is validated against simultaneous measurements from the CCN counter. The independent validation with robust correlation demonstrates promising results. Furthermore, the NCCN has been retrieved for the first time using a proposed algorithm from spaceborne lidar – Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) – measurements. The application of this new capability demonstrates the potential for constructing a 3D CCN climatology at a global scale, which helps to better quantify ACI effects and thus reduce the uncertainty in aerosol climate forcing.

Assessing hydrothermal changes in the upper Yellow River Basin amidst permafrost degradation

Since the 20th century, the temperature on the Qinghai–Tibetan Plateau (QTP) has increased at a rate of 2–3 times that of global warming. Consequently, the soil temperature and active layer thickness have also increased, which have directly caused severe degradation of the frozen ground on the QTP. Using a hydrological model driven by climate and vegetation forcing, the spatial and temporal changes in the hydrothermal characteristics of the Upper Yellow River Basin (UYRB) from 1960 to 2019 were modeled and the mechanism of the changes was analyzed. During the past six decades, the soil temperature in the UYRB exhibited an increasing trend. The degradation of permafrost in the UYRB was accompanied by thickening of the active layer, a reduction of the maximum depth of the seasonal frost penetration, and continuous extension of the basin thawing time. This degradation was also associated with the increase in the soil moisture content and decrease in the soil ice content, resulting in degradation of the permafrost area by one-tenth of the total area in the UYRB. The reduction of the permafrost area and the thickening of the active layer can profoundly impact hydrological processes and ecosystems. These findings play a critical role in designing efficient strategies to manage and protect frozen ground and serve as a valuable reference for understanding the consequences of frozen ground degradation globally.

Global Evaluation of Simulated High and Low Flows from 23 Macroscale Models

Abstract Macroscale hydrological/land surface models are important tools for assessing historical and predicting future characteristics of extreme hydrological events, yet quantitative understandings of how these large-scale models perform in simulating extreme hydrological characteristics remain limited. Here we evaluate simulated high and low flows from 23 macroscale models within three modeling experiments (i.e., 14 climate models from CMIP6, 6 global hydrological models from ISIMIP2a, and 3 land surface models from GLDAS) against observation in 633 unimpaired catchments globally over 1971–2010. Our findings reveal limitations in simulating extreme flow characteristics by these models. Specifically, we find that (i) most models overestimate high-flow magnitudes (bias range: from +15% to +70%) and underestimate low-flow magnitudes (bias range: from −80% to −20%); (ii) interannual variability in high and low flows is reasonably reproduced by ISIMIP2a and GLDAS models but poorly reproduced by CMIP6 models; (iii) no model consistently replicates the observed trend direction in high and low flows in over two-thirds of the catchments, and most models overestimate high-flow trends and underestimate low-flow trends; and (iv) CMIP6 and GLDAS models show timing biases, with early high flows and late low flows, while ISIMIP2a models exhibit the opposite pattern. Furthermore, all models performed better in more humid environments and noncold regions, with model structure and parameterization contributing more to uncertainties than climatic forcings. Overall, our results demonstrate that extreme flow characteristics simulated from current state-of-the-art macroscale models still contain large uncertainties and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs. Significance Statement Macroscale hydrological and land surface models represent crucial tools for assessing historical trends and making predictions about future hydrological changes. Nevertheless, our current understanding of the quantitative performance of these large-scale models in simulating extreme hydrological characteristics remains limited. Here, we evaluate simulated high and low flows from 23 state-of-the-art macroscale models against observation in 633 unimpaired catchments globally over 1971–2010. Our results reveal important limitations in the extreme flow characteristics simulated from these models and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs. The model evaluation performed herein serves as a pivotal, offering valuable insights to inform the development of the next generation of macroscale hydrological and land surface models.

Feasibility of contrail avoidance in a commercial flight planning system: an operational analysis

Aircraft condensation trails, also known as contrails, contribute a substantial portion of aviation’s overall climate footprint. Contrail impacts can be reduced through smart flight planning that avoids contrail-forming regions of the atmosphere. While previous studies have explored the operational impacts of contrail avoidance in simulated environments, this paper aims to characterize the feasibility and cost of contrail avoidance precisely within a commercial flight planning system. This study leverages the commercial Flightkeys 5D algorithm, developed by Flightkeys GmbH, with a prototypical contrail forecast model based on the Contrail Cirrus Prediction (CoCiP) model to simulate contrail avoidance on 49 411 flights during the first two weeks of June 2023, and 35 429 flights during the first two weeks of January 2024. The utilization of a commercial flight planning system enables high-accuracy estimates of additional cost and fuel investments by operators to achieve estimated reductions in contrail-energy forcing and overall flight global warming potential. The results show that navigational contrail avoidance will require minimal additional cost (0.08%) and fuel (0.11%) investments to achieve notable reductions in contrail climate forcing (−73.0%). This simulation provides evidence that contrail mitigation entails very low operational risks, even regarding fuel. This study aims to serve as an incentive for operators and air traffic controllers to initiate contrail mitigation testing as soon as possible and begin reducing aviation’s non- CO2 emissions.

Anthropogenic climate change has influenced global river flow seasonality.

Riverine ecosystems have adapted to natural discharge variations across seasons. However, evidence suggesting that climate change has already impacted magnitudes of river flow seasonality is limited to local studies, mainly focusing on changes of mean or extreme flows. This study introduces the use of apportionment entropy as a robust measure to assess flow-volume nonuniformity across seasons, enabling a global analysis. We found that ~21% of long-term river gauging stations exhibit significant alterations in seasonal flow distributions, but two-thirds of these are unrelated to trends in annual mean discharge. By combining a data-driven runoff reconstruction with state-of-the-art hydrological simulations, we identified a discernible weakening of river flow seasonality in northern high latitudes (above 50°N), a phenomenon directly linked to anthropogenic climate forcing.

Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3

Abstract. In this paper we describe the implementation of the carbon isotopes 13C and 14C (radiocarbon) into the marine biogeochemistry model REcoM3. The implementation is tested in long-term equilibrium simulations where REcoM3 is coupled with the ocean general circulation model FESOM2.1, applying a low-resolution configuration and idealized climate forcing. Focusing on the carbon-isotopic composition of dissolved inorganic carbon (δ13CDIC and Δ14CDIC), our model results are largely consistent with reconstructions for the pre-anthropogenic period. Our simulations also exhibit discrepancies, e.g. in upwelling regions and the interior of the North Pacific. Some of these differences are due to the limitations of our ocean circulation model setup, which results in a rather shallow meridional overturning circulation. We additionally study the accuracy of two simplified modelling approaches for dissolved inorganic 14C, which are faster (15 % and about a factor of five, respectively) than the complete consideration of the marine radiocarbon cycle. The accuracy of both simplified approaches is better than 5 %, which should be sufficient for most studies of Δ14CDIC.

Assessment of anthropogenic and climate-driven water storage variations over water-stressed river basins of Ethiopia

Abstract Globally, surface water, groundwater, soil moisture, snow storage, canopy water, and wet biomass constituents make up water storage, which plays a significant role in the hydrological water balance. Evaluating the variations in water storage anomalies associated with climate forcing and human activities over river basins is crucial for assessing water scarcity and predicting potential pressures on water resources in the future. In this study, we assessed the impacts of climatic and anthropogenic drivers on the change in water storage in the river basins of Ethiopia by using the independent component analysis to examine Gravity Recovery and Climate Experiment with the Global Land Data Assimilate System-based water storage and comparing the independent component analysis with hydro-meteorological data and statistical data related to human activities. It is of great significance for helping people better understand the evaluation of terrestrial water storage anomalies under the combined influence of climatic change and anthropogenic activities and providing information for better protection and utilization of water resources at river basin level. It is crucial to take effective measures to protect these precious land and water resources and prevent their further deterioration. The estimated result will be essential for sustainable water management and protection.

Acceleration and interannual variability of creep rates in mountain permafrost landforms (rock glacier velocities) in the European Alps in 1995–2022

Cryospheric long-term timeseries get increasingly important. To document climate-related effects on long-term viscous creep of ice-rich mountain permafrost, we investigated timeseries (1995–2022) of geodetically-derived Rock Glacier Velocity (RGV), i.e. spatially averaged interannual velocity timeseries related to a rock glacier (RG) unit or part of it. We considered 50 RGV from 43 RGs spatially covering the entire European Alps. Eight of these RGs are destabilized. Results show that RGV are distinctly variable ranging from 0.04 to 6.23 m a−1. Acceleration and deceleration at many RGs are highly correlated with similar behaviour over 2.5 decades for 15 timeseries. In addition to a general long-term, warming-induced trend of increasing velocities, three main phases of distinct acceleration (2000–2004, 2008–2015, 2018–2020), interrupted by deceleration or steady state conditions, were identified. The evolution is attributed to climate forcing and underlines the significance of RGV as a product of the Essential Climate Variable (ECV) permafrost. We show that RGV data are valuable as climate indicators, but such data should always be assessed critically considering changing local factors (geomorphic, thermal, hydrologic) and monitoring approaches. To extract a climate signal, larger RGV ensembles should be analysed. Criteria for selecting new RGV-sites are proposed.

Seasonal variability and predictability of monsoon precipitation in Southern Africa

Rainfed agriculture is the mainstay of economies across Southern Africa (SA), where most precipitation is received during the austral summer monsoon. This study aims to further our understanding of monsoon precipitation predictability over SA. We use three natural climate forcings, El Niño–Southern Oscillation, Indian Ocean Dipole (IOD), and the Indian Ocean Precipitation Dipole (IOPD)—the dominant precipitation variability mode—to construct an empirical model that exhibits significant skill over SA during monsoon in explaining precipitation variability and in forecasting it with a five-month lead. While most explained precipitation variance (50%–75%) comes from contemporaneous IOD and IOPD, preconditioning all three forcings is key in predicting monsoon precipitation with a zero to five-month lead. Seasonal forecasting systems accurately represent the interplay of the three forcings but show varying skills in representing their teleconnection over SA. This makes them less effective at predicting monsoon precipitation than the empirical model.

Technical note: A method for calculating offsets to ozone depletion and climate impacts of ozone-depleting substances

Abstract. By phasing out production and consumption of most ozone-depleting substances (ODSs), the Montreal Protocol on Substances that Deplete the Ozone Layer (Montreal Protocol) has avoided consequences of increased ultraviolet (UV) radiation and will restore stratospheric ozone to pre-1980 conditions by mid-century, assuming compliance with the phaseout. However, several studies have documented an unexpected increase in emissions and suggested unreported production of trichlorofluoromethane (CFC-11) and potentially other ODSs after 2012 despite production phaseouts under the Montreal Protocol. Furthermore, because most ODSs are powerful greenhouse gases (GHGs), there are significant climate protection benefits in collecting and destroying the substantial quantities of historically allowed production of chemicals under the Montreal Protocol that are contained in existing equipment and products and referred to as ODS “banks”. This technical note presents a framework for considering offsets to ozone depletion, climate forcing, and other environmental impacts arising from occurrences of unexpected emissions and unreported production of Montreal Protocol controlled substances, as recently experienced and likely to be experienced again. We also show how this methodology could be applied to the destruction of banks of controlled ODSs and GHGs or to halon or other production allowed under a Montreal Protocol Essential Use Exemption or Critical Use Exemption. Further, we roughly estimate the magnitude of offset each type of action could provide for ozone depletion, climate, and other environmental impacts that Montreal Protocol Parties agree warrant remedial action.

Growth Response of Thai Pine (Pinus latteri) to Climate Drivers in Tak Province of Northwestern Thailand

The long-term effects of climate change and climate extremes have been associated with changes in tree growth and forest productivity worldwide, and dendrochronological analyses are important tools that can be used to investigate the influence of climatic forces on tree growth at a particular site. In this study, a 180-year tree ring width chronology (spanning from 1843 to 2022) of living pine trees (Pinus latteri) in Tak province, northwestern Thailand, was developed. The analysis of the climate–tree growth relationship indicated the influences of the annual total rainfall (r = 0.60, p < 0.001) and annual averaged relative humidity (r = 0.47, p < 0.001) on tree growth in this area. Anomalously high (for example, in 1853, 1984, 2011, and 2018) and low growths (for example, in 1954, 1983, 1992, and 1996) were found. Growth anomalies in the Thai pine in this study were related to changes in abnormal and extreme rainfall (r = 0.94, p < 0.001) and the El Niño Southern Oscillation (ENSO). Our results confirm that rainfall and relative humidity are the main climatic factors regulating the radial growth of Thai pine. This finding could be an important contribution to further research on the effects of climate change and extreme weather events on the vulnerability of tropical and subtropical trees in this region.

A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)

Abstract. Many scientific and societal questions that draw on ice sheet modeling necessitate sampling a wide range of potential climatic changes and realizations of internal climate variability. For example, coastal planning literature demonstrates a demand for probabilistic sea level projections with quantified uncertainty. Further, robust attribution of past and future ice sheet change to specific processes or forcings requires a full understanding of the space of possible ice sheet behaviors. The wide sampling required to address such questions is computationally infeasible with sophisticated numerical climate models at the resolution required to accurately force ice sheet models. Stochastic generation of climate forcing of ice sheets offers a complementary alternative. Here, we describe a method to construct a stochastic generator for ice sheet surface mass balance varying in time and space. We demonstrate the method with an application to Greenland Ice Sheet surface mass balance for 1980–2012. We account for spatial correlations among glacier catchments using sparse covariance techniques, and we apply an elevation-dependent downscaling to recover gridded surface mass balance fields suitable for forcing an ice sheet model while including feedback from changing ice sheet surface elevation. The efficiency gained in the stochastic method supports large-ensemble simulations of ice sheet change in a new stochastic ice sheet model. We provide open source Python workflows to support use of our stochastic approach for a broad range of applications.

Towards an integrated view on microbial CH4, N2O and N2 cycles in brackish coastal marsh soils: A comparative analysis of two sites

Coastal ecosystems, facing threats from global change and human activities like excessive nutrients, undergo alterations impacting their function and appearance. This study explores the intertwined microbial cycles of carbon (C) and nitrogen (N), encompassing methane (CH4), nitrous oxide (N2O), and nitrogen gas (N2) fluxes, to determine nutrient transformation processes between the soil-plant-atmosphere continuum in the coastal ecosystems with brackish water. Water salinity negatively impacted denitrification, bacterial nitrification, N fixation, and n-DAMO processes, but did not significantly affect archaeal nitrification, COMAMMOX, DNRA, and ANAMMOX processes in the N cycle. Plant species age and biomass influenced CH4 and N2O emissions. The highest CH4 emissions were from old Spartina and mixed Spartina and Scirpus sites, while Phragmites sites emitted the most N2O. Nitrification and incomplete denitrification mainly governed N2O emissions depending on the environmental conditions and plants. The higher genetic potential of ANAMMOX reduced excessive N by converting it to N2 in the sites with higher average temperatures. The presence of plants led to a decrease in the N fixers' abundance. Plant biomass negatively affected methanogenetic mcrA genes. Microbes involved in n-DAMO processes helped mitigate CH4 emissions. Over 93 % of the total climate forcing came from CH4 emissions, except for the Chinese bare site where the climate forcing was negative, and for Phragmites sites, where almost 60 % of the climate forcing came from N2O emissions. Our findings indicate that nutrient cycles, CH4, and N2O fluxes in soils are context-dependent and influenced by environmental factors and vegetation. This underscores the need for empirical analysis of both C and N cycles at various levels (soil-plant-atmosphere) to understand how habitats or plants affect nutrient cycles and greenhouse gas emissions.

Graphics-processing-unit-accelerated ice flow solver for unstructured meshes using the Shallow-Shelf Approximation (FastIceFlo v1.0.1)

Abstract. Ice-sheet flow models capable of accurately projecting their future mass balance constitute tools to improve flood risk assessment and assist sea-level rise mitigation associated with enhanced ice discharge. Some processes that need to be captured, such as grounding-line migration, require high spatial resolution (under the kilometer scale). Conventional ice flow models mainly execute on central processing units (CPUs), which feature limited parallel processing capabilities and peak memory bandwidth. This may hinder model scalability and result in long run times, requiring significant computational resources. As an alternative, graphics processing units (GPUs) are ideally suited for high spatial resolution, as the calculations can be performed concurrently by thousands of threads, processing most of the computational domain simultaneously. In this study, we combine a GPU-based approach with the pseudo-transient (PT) method, an accelerated iterative and matrix-free solution strategy, and investigate its performance for finite elements and unstructured meshes with application to two-dimensional (2-D) models of real glaciers at a regional scale. For both the Jakobshavn and Pine Island glacier models, the number of nonlinear PT iterations required to converge a given number of vertices (N) scales in the order of 𝒪(N1.2) or better. We further compare the performance of the PT CUDA C implementation with a standard finite-element CPU-based implementation using the price-to-performance metric. The price of a single Tesla V100 GPU is 1.5 times that of two Intel Xeon Gold 6140 CPUs. We expect a minimum speedup of at least 1.5 times to justify the Tesla V100 GPU price to performance. Our developments result in a GPU-based implementation that achieves this goal with a speedup beyond 1.5 times. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions. The insights gained will benefit efforts to diminish spatial resolution constraints at higher computing performance. The higher computing performance will allow for ensembles of ice-sheet flow simulations to be run at the continental scale and higher resolution, a previously challenging task. The advances will further enable the quantification of model sensitivity to changes in upcoming climate forcings. These findings will significantly benefit process-oriented sea-level-projection studies over the coming decades.

Upper Colorado River Streamflow Dependencies on Summertime Synoptic Circulations and Hydroclimate Variability

Abstract The southwestern United States is highly sensitive to drought, prompting efforts to understand and predict its hydroclimate. Oftentimes, the emphasis is on wintertime precipitation variability, yet the southwestern United States exhibits a summertime monsoon where a significant portion of annual precipitation falls through daily convection activities manifested by a midtropospheric ridge of high pressure. Here, we examine synoptic patterns of the southwestern ridge through a k-means clustering analysis and assess how these synoptic patterns translate into streamflow changes in the upper Colorado River basin. A linear perspective suggests ∼17% of upper Colorado River discharge at the Lee’s Ferry, Arizona, gauge comes from summertime monsoon rains. The ridge of high pressure exhibits diversity in its intensity, structure, and position, inducing changes in moisture advection and precipitation. A ridge shifted north or east of its climatological center increases moisture and precipitation over the southwestern United States, while a ridge toward the south or northwest inhibits precipitation. A ridge east of its climatological center contributes to increased streamflow, whereas a ridge west or northwest of its climatological center decreases streamflow. Cooling in the central tropical Pacific and the Pacific meridional mode region favors an eastward shift of the ridge of high pressure corresponding to wet days. Eastern tropical Pacific warming favors a southward shift of the ridge corresponding to dry days. These results support an intermediate scale between climate forcing and summertime Colorado River discharge through changes in the intensity, structure, and position of the southwestern ridge of high pressure, integral to the U.S. Southwest hydroclimate.

STUDYING THE RELIABILITY OF AN INTERNAL COMBUSTION ENGINE BASED ON AN ANALYSIS OF ENGINE OIL

Specifically, greenhouse gases (CH4, N2O, CO2, CO, SO2), are strong climate forcers, and articulate pollution all have detrimental health effects. Vehicle on-road traffic is a major contributor to air pollutants in urban areas that affect human population health, the environment at local and regional scales, and the global climate.[1] This study forces a numerical study of engine oil by engine conditions by using different type of fuels. Engine oil main parameters and internal combustion engines were investigated under real-world conditions for driving cycles typical for Tashkent urban environments. Three kinds of laboratory equipment and ISO standards were utilized. Our study shows that by using different types of fuel, the life cycle point of motor oil varies. Total base number (TBN), Total acid number (TAN), viscosity and flash points were taken as basic parameters of engine oil. The viscosity value of oil dominated the other characteristics. In general, in our study to improve engine performance, we must consider engine oil, which is one of the key parameters.

Spatial flows of ecosystem services under future climate and land-use changes

Increasing global pressure on natural capital requires sustainable solutions to ensure long-term provision of ecosystem services (ES) which have complex flow dynamics. Although the importance of ES flows has been increasingly recognized during the past years, little is known about how they will be affected by future climate and land-use changes. Here, we integrated ES flows into a scenario-based assessment framework, and evaluated it by clarifying the local and distant effects of ES flows in the Black River basin, China. The spatiotemporal variations of ES flows were investigated by considering different land policies and climate scenarios, and the drivers of ES flow variations were explored. We found increasing inter-regional ES flows toward 2100. Compared to land-use change, the intra-regional flows were more sensitive to climate change, with greater shifts of flow size and synergistic areas identified under a moderate climatic forcing scenario with sustainable management strategies. Precipitation directly affected water retention flow, yet affected flood mitigation flow both directly and indirectly through changing vegetation cover, which was the major driver of soil retention flow. Biodiversity mediated the positive effects of precipitation and vegetation cover on soil retention flow. Our study highlights the importance of embracing the spatiotemporal features of ES flows in sustainable transboundary management and adaptation strategies.

Evaluating modelled tropospheric columns of CH4, CO, and O3 in the Arctic using ground-based Fourier transform infrared (FTIR) measurements

Abstract. This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

Holocene climatic and tectonic forcing of decadal hydroclimate variation on the north-eastern Tibetan Plateau

A better understanding of past climate and landscape variability in high resolution on the Tibetan Plateau is of critical importance for the understanding of fundamental mechanisms and interactions in the global climate system. However, due to relatively few datasets in decadal-resolution available for analyzing possible seasonal effects and seismic activity on the northeastern Tibetan Plateau, further high-resolution lake records as an integration need to be explored to test the significance of the seasonal variations of surface processes and climatic phenomena as well as tectonic impact on a decadal scale. The rhomb-shaped pull-apart Lake Donggi Cona along the modern monsoon marginal zone on the north-eastern TP is considered an excellent archive that monitors neotectonic and climatic changes through time. We obtained new high-resolution (mean 20 yr) proxy records from a 488 cm-long sediment core from the lake and compare them directly with paleoclimate records from nearby lakes. A decadal-resolution oxygen stable isotope (δ18O) record co-varies positively with carbonate content and demonstrates the profound and varying contribution of glacier/snow melt (winter/spring moisture) to lake hydrology at different lake evolution stages. This is also indicated by the grain size composition and related endmember modelling (EMMA) results. During 11.8–9.4 cal Ka BP, the lake experienced a swamp status, apart from the major lake body followed by water rise towards the littoral zone until 7.5 cal Ka BP. Glacier melt water supply started to be active since the late Younger Dryas and led to the strong excursions of carbonate contents and δ18O values according to insolation increase. This phase was dominated by the westerlies and characterized as low seasonality with long winter duration. Water rose to its highest level during 7.5–6.5 cal Ka BP and fluctuated with deep water phases until 4.7 cal Ka BP, due to glacier melt maxima and potential increase of summer (convective) moisture preserved in the oxygen isotopic signals. Water cover dropped and remained low until 2.9 cal Ka BP due to the reduced glacier melt and colder climate. However, the low δ18O values at a reduced water budget points to the still active contribution of spring glacier/snow melt that kept the lake not dry-up unlike other lakes with no glacier melt water supply. After 2.9 cal Ka BP water level dropped towards a pond/lagoon situation until 2.0 cal Ka BP, albeit temperature rise after a long cold climatic interlude. It might be caused by another phase of lake deepening triggered by subsidence and related sediment relocation from the shore, rather than by climatic factors. However, water level increased again afterwards and fluctuated towards the present level due to non-summer moisture supply in long freezing winters. We assume profound signatures of high seasonality in climate after 7.5 cal Ka BP and the lake became open since1.3 cal Ka BP. We suggest that combined thermal forcing by glacier/snow melt and tectonics play a significant role together with solar forcing, governing hydroclimate changes on the north-eastern Tibetan Plateau with decadal to millennial cycles.

Heterogeneous Basal Thermal Conditions Underpinning the Adélie‐George V Coast, East Antarctica

AbstractAdélie‐George V Land in East Antarctica, encompassing the vast Wilkes Subglacial Basin, has a configuration that could be prone to ice sheet instability: the basin's retrograde bed slope could make its marine terminating glaciers vulnerable to warm seawater intrusion and irreversible retreat under predicted climate forcing. However, future projections are uncertain, due in part to limited subglacial observations near the grounding zone. Here, we develop a novel statistical approach to characterize subglacial conditions from radar sounding observations. Our method reveals intermixed frozen and thawed bed within 100 km of the grounding‐zone near the Wilkes Subglacial Basin outflow, and enables comparisons to ice sheet model‐inferred thermal states. The signs of intermixed or near thawed conditions raises the possibility that changes in basal thermal state could impact the stability of Adélie‐George V Land, adding to the region's potentially vulnerable topographic configuration and sensitivity to ocean forcing driven grounding line retreat.