Freshwater ecosystems provide vital services, yet are facing increasing risks from global change. In particular, lake thermal dynamics have been altered around the world as a result of climate change, necessitating a predictive understanding of how climate will continue to alter lakes in the future as well as the associated uncertainty in these predictions. Numerous sources of uncertainty affect projections of future lake conditions but few are quantified, limiting the use of lake modeling projections as management tools. To quantify and evaluate the effects of two potentially important sources of uncertainty, lake model selection uncertainty and climate model selection uncertainty, we developed ensemble projections of lake thermal dynamics for a dimictic lake in New Hampshire, USA (Lake Sunapee). Our ensemble projections used four different climate models as inputs to five vertical one-dimensional (1-D) hydrodynamic lake models under three different climate change scenarios to simulate thermal metrics from 2006 to 2099. We found that almost all the lake thermal metrics modeled (surface water temperature, bottom water temperature, Schmidt stability, stratification duration, and ice cover, but not thermocline depth) are projected to change over the next century. Importantly, we found that the dominant source of uncertainty varied among the thermal metrics, as thermal metrics associated with the surface waters (surface water temperature, total ice duration) were driven primarily by climate model selection uncertainty, while metrics associated with deeper depths (bottom water temperature, stratification duration) were dominated by lake model selection uncertainty. Consequently, our results indicate that researchers generating projections of lake bottom water metrics should prioritize including multiple lake models for best capturing projection uncertainty, while those focusing on lake surface metrics should prioritize including multiple climate models. Overall, our ensemble modeling study reveals important information on how climate change will affect lake thermal properties, and also provides some of the first analyses on how climate model selection uncertainty and lake model selection uncertainty interact to affect projections of future lake dynamics.
Persistent warming and water cycle change due to anthropogenic climate change modifies the temperature and salinity distribution of the ocean over time. This ‘forced’ signal of temperature and salinity change is often masked by the background internal variability of the climate system. Analysing temperature and salinity change in watermass-based coordinate systems has been proposed as an alternative to traditional Eulerian (e.g., fixed-depth, zonally-averaged) co-ordinate systems. The impact of internal variability is thought to be reduced in watermass co-ordinates, enabling a cleaner separation of the forced signal from background variability - or a higher ‘signal-to-noise’ ratio. Building on previous analyses comparing Eulerian and water-mass-based one-dimensional coordinates, here we recast two-dimensional co-ordinate systems - temperature-salinity (𝑇 − 𝑆), latitude-longitude and latitude-depth - onto a directly comparable equal-volume framework. We compare the internal variability, or ‘noise’ in temperature and salinity between these remapped two-dimensional co-ordinate systems in a 500 year pre-industrial control run from a CMIP6 climate model. We find that the median internal variability is lowest (and roughly equivalent) in 𝑇 − 𝑆 and latitude-depth space, compared with latitude-longitude co-ordinates. A large proportion of variability in 𝑇 − 𝑆 and latitude-depth space can be attributed to processes which operate over a timescale greater than 10 years. Overall, the signal-to-noise ratio in 𝑇 − 𝑆 co-ordinates is roughly comparable to latitude-depth co-ordinates, but is greater in regions of high historical temperature change. Conversely, latitude-depth co-ordinates have greater signal-to-noise ratio in regions of historical salinity change. Thus, we conclude that the climatic temperature change signal can be more robustly identified in watermass-co-ordinates.
The Hunga Tonga-Hunga Ha’apai (HTHH) volcanic eruption in January 2022 injected extreme amounts of water vapor (H2O) and a moderate amount of the aerosol precursor (SO2) into the Southern Hemisphere (SH) stratosphere. The H2O and aerosol perturbations have persisted and resulted in large-scale SH stratospheric cooling, equatorward shift of the Antarctic polar vortex, and slowing of the Brewer-Dobson circulation associated with a substantial ozone reduction in the SH winter midlatitudes. Chemistry-climate model simulations forced by realistic HTHH inputs of H2O and SO2 reproduce the observed stratospheric cooling and circulation effects, demonstrating the observed behavior is due to the volcanic influences. Furthermore, the combination of aerosol transport to polar latitudes and a cold polar vortex enhances springtime Antarctic ozone loss, consistent with observed polar ozone behavior in 2022.
Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Their seasonal development features fast and local changes in fractions of surface types demonstrating the necessity of improving melt pond fraction (MPF) products. We present a renewed method to extract MPF from Sentinel-2 satellite imagery, which is evaluated by MPF products from higher resolution satellite and helicopter-borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs amount to 17 % before and 23 % after the major drainage. Arctic-wide analysis of MPF for years 2017-2021 shows a consistent seasonal cycle in all regions and years.
In a context of climate change, the stakes surrounding water availability are getting higher. Decomposing and quantifying the effects of climate on discharge allows to better understand their impact on water resources. We propose a methodology to separate the effect of change in annual mean of climate variables from the effect of intra-annual distribution of precipitations. It combines the Budyko framework with outputs from a Land Surface Model (LSM). The LSM is used to reproduces the behavior of 2134 reconstructed watersheds over Europe between 1902 and 2010, with climate inputs as the only source of change. We fit to the LSM outputs a one parameter approximation to the Budyko framework. It accounts for the evolution of annual mean in precipitation (P) and potential evapotranspiration (PET). We introduce a time-varying parameter in the equation which represents the effect of long-term variations in the intra-annual distribution of P and PET. To better assess the effects of changes in annual means or in intra-annual distribution of P, we construct synthetic forcings fixing one or the other. The results over Europe show that the changes in discharge due to climate are dominated by the trends in the annual averages of P. The second main climate driver is PET, except over the Mediterranean area where changes in intra-annual variations of P have a higher impact on discharge than trends in PET. Therefore the effects of changes in intra-annual distribution of climate variables are not to be neglected when looking at changes in annual discharge.
Vegetation turnover time (τ) is a central ecosystem property to quantify the global vegetation carbon dynamics. However, our understanding of vegetation dynamics is hampered by the lack of long-term observations of the changes in vegetation biomass. Here we challenge the steady state assumption of τ by using annual changes in vegetation biomass that derived from remote-sensing observations. We evaluate the changes in magnitude, spatial patterns, and uncertainties in vegetation carbon turnover times from 1992 to 2016. We found that the forest ecosystem is close to a steady state at global scale, contrasting with the larger differences between τ under steady state and τ under non-steady state at the grid cell level. The observation that terrestrial ecosystems are not in a steady state locally is deemed crucial when studying vegetation dynamics and the potential response of biomass to disturbance and climatic changes.
Changes in atmospheric iron (Fe) deposition to the open ocean affect net primary productivity, nitrogen fixation, and carbon uptake rates. We investigate the changes in soluble Fe (SFe) deposition from the pre-industrial period to the late 21st century using the EC-Earth3-Iron Earth System model, which stands out for its comprehensive representation of the atmospheric oxalate, sulfate, and Fe cycles. We show how anthropogenic activity has modified the magnitude and spatial distribution of SFe deposition by increasing combustion Fe emissions along with atmospheric acidity and oxalate levels. We find that SFe deposition has doubled since the early Industrial Era using the Coupled Model Intercomparison Project Phase 6 (CMIP6) emission inventory, with acidity being the main solubilization pathway for dust Fe, and ligand-promoted (oxalate) processing dominating the solubilization of combustion Fe. We project a global SFe deposition increase of 40% by the late 21st century relative to present day under Shared Socioeconomic Pathway (SSP) 3-7.0, which assumes weak climate change mitigation policies. In contrast, sustainable and business-as-usual SSPs (1-2.6 and 2-4.5) result in 35% and 10% global decreases, respectively. Despite these differences, SFe deposition consistently increases and decreases across SSPs over the (high nutrient low chlorophyl) equatorial Pacific and Southern Ocean (SO), respectively. Future changes in dust and wildfires with climate remains a key challenge for constraining SFe projections. We show that the equatorial Pacific and the SO would be sensitive not only to changes in Australian or South American dust emissions, but also to those in North Africa.
The causes of the variations in CO2 of the past million years remain poorly understood. Imbalances between the input of elements from rock weathering and their removal from the atmosphere-ocean-biosphere system to the lithosphere likely contributed to reconstructed changes. We employ the Bern3D Earth system model of intermediate complexity to investigate carbon-climate responses to step-changes in the weathering input of phosphorus, alkalinity, carbon, and carbon isotope ratio (δ13C) in simulations extending up to 600,000 years. CO2 and climate approach a new equilibrium within a few ten thousand years, whereas the equilibration lasts several hundred thousand years for δ13C. These timescales represent a challenge for the initialization of sediment-enabled models and unintended drifts may be larger than forced signals in simulations of the last glacial-interglacial cycle. Changes in dissolved CO2 change isotopic fractionation during marine photosynthesis and δ13C of organic matter. This mechanism and changes in the organic matter export cause distinct spatio-temporal perturbations in δ13C of dissolved inorganic carbon. A cost-efficient emulator is built with the Bern3D responses and applied in contrasting literature-based weathering histories for the past 800,000 years. Differences between scenarios for carbonate rock weathering reach around a third of the glacial-interglacial CO2 amplitude, 0.05 ‰ for δ13C, and exceed reconstructed variations in marine carbonate ion. Plausible input from the decomposition of organic matter on shelves causes variations of up to 10 ppm in CO2 , 4 mmol m−3 in CO2−3, and 0.09‰ in δ13C. Our results demonstrate that weathering-burial imbalances are important for past climate variations.
Significant multi-centennial climate variability with a clear peak at approximately 200 years is found in a pre-industrial control simulation conducted with the EC-Earth3 climate model. The oscillation mainly emerges from the North Atlantic and appears to be closely associated with the Atlantic Meridional Overturning Circulation (AMOC). By examining the salinity advection feedback, we find that the perturbation flow of mean subtropical-subpolar salinity gradients in the subpolar area governs as positive feedback to the AMOC anomaly. Meanwhile, the mean advection of salinity anomalies and the vertical mixing or convection acts as negative feedback to restrain the AMOC anomaly. In a warmer climate, although the AMOC becomes weaker, such low-frequency variability still exists, indicating the robustness of the salinity advection feedback mechanism.
While Hg in sediments is increasingly used as a proxy for deep-time volcanic activity, the behaviour of Hg in OM-rich sediments as they undergo thermal maturation is not well understood. In this study, we evaluate the effects of thermal maturation on sedimentary Hg contents and, thereby, the impact of thermal maturity on the use of the Hg/TOC proxy for large igneous province (LIP) volcanism. We investigate three cores (marine organic matter) with different levels of thermal maturity in lowermost Toarcian sediments (Posidonienschiefer) from the Lower Saxony Basin in Germany. We present Hg content, bulk organic geochemistry, and total sulfur in three cores with different levels of thermal maturity. The comparison of Hg data between the three cores indicates that Hg content in the mature/overmature sediments have increased > 2-fold compared to Hg in the immature deposits. Although difficult to confirm with the present data, we speculate that redistribution within the sedimentary sequence caused by the mobility and volatility of the element under relatively high temperatures may have contributed to Hg enrichment in distinct stratigraphic levels of the mature cores. Regardless of the exact mechanism, elevated Hg content together with organic-carbon loss by thermal maturation exaggerate the value of Hg/TOC in mature sediments, suggesting that thermal effects have to be considered when using TOC-normalised Hg as a proxy for far-field volcanic activity.
Poem to imagine the “essence” of water as it circulates through the Earth universe, synergistically supporting all environments and living ecosystems, forming, and shaping land and life. The poem links key elements of the interactive global water cycle and international programs to sustainably manage natural, and socioeconomic resources, given the challenge of climate change. It is in awareness of: –Essential Water Variables (EWVs) of the Group on Earth Observations (GEO) Global Water Sustainability (GEOGLOWS) initiative; Earth Observations (EO) for the Water-Energy-Food Nexus (EO4WEF) community activity; UN Sustainable Development Goals (UN SDGs), UNFCCC–Climate Change. The poem hopes to bring water to the forefront of consciousness. Readers are invited to comment on the intangible “feelings” evoked by the poem.
We examine the effects of the submesoscale in mediating the response to projected warming of phytoplankton new production and export using idealized biogeochemical tracers in a high-resolution regional model of the Porcupine Abyssal Plain region of the North Atlantic. We quantify submesoscale effects by comparing our control run to an integration in which submesoscale motions have been suppressed using increased viscosity. The warming climate over the 21st century reduces resolved submesoscale activity by a factor of 2-3. Annual new production is slightly reduced by submesoscale motions in a climate representative of the early 21st-century and slightly increased by submesoscale motions in a climate representative of the late 21st-century. Resolving the submesoscale, however, does not strongly impact the projected reduction in annual production under representative warming. Organic carbon export from the surface ocean includes both direct sinking of detritus (the biological gravitational pump) and advective transport mediated pathways; the sinking component is larger than advectively mediated transport by up to an order of magnitude across a wide range of imposed sinking rates. Submesoscales are responsible for most of the advective carbon export, however, which is thus largely reduced by a warming climate. In summary, our results demonstrate that resolving more of the submesoscale has a modest effect on present-day new production, a small effect on simulated reductions in new production under global warming, and a large effect on advectively-mediated export fluxes.
Insight and other observations of the Martian surface at different locations have recorded the diurnal variation in surface pressure (Ps) with two rapid fluctuations that occur at dawn and dusk (around LT0800 and LT2000). These short-period surface pressure perturbations at specific local times are typically observed near Martian equinox. Similar phase-locked surface pressure fluctuations over most areas of the middle and low latitudes are simulated by the Martian General Circulation Model at the Dynamic Meteorology Laboratory (LMD). This phenomenon is thus likely to be global rather than local. By reconstructing the surface pressure variation from the horizontal mass flux, the pressure fluctuations in a sol can be attributed to the diurnal variation in the horizontal wind divergence and convergence in the Martain tropical troposphere in the GCM simulations. The background diurnal variation in Ps is related to the diurnal migrating tidal wind, while the enhanced convergence due to the overlap of the 4-hour and 6-hour tides before LT0800 and LT2000 is responsible for the Ps peaks occurring at dawn and twilgith. Although the amplitudes of the 4-hour and 6-hour tides are smaller than those of diurnal tides, the phases of these tides remain similar in the Martain troposphere, which suggests that the convergences and divergences due to 4 h/6 h tidal winds at different altitudes are in phase and together create a mass flux comparable to that induced by diurnal/semidiurnal components and lead to rapid pressure fluctuations.
The various extreme weather events that occurred globally in 2021, from Europe to China to North America, served as yet another reminder that robust strategies for climate adaptation are crucial at a time of rapid global warming. Building resilient communities and lessening the impact that natural disasters have on vulnerable infrastructure can be aided by automated systems driven by machine learning algorithms trained on Earth observation data. When deployed, computer vision models can analyze satellite imagery in real time and inform decision makers and nongovernmental organizations about the timely and targeted allocation of resources and humanitarian aid personnel to affected areas. Here, we overview several specific 2021 extreme events and the factors that caused the loss of life, damage to infrastructure, and economic loss. The events surveyed include flooding in Germany, wildfires in Greece, and Hurricane Ida in the Eastern United States. Taking this information into account, we further discuss barriers to the large-scale deployment of current machine learning technologies, especially models trained on Earth observation data. We examine the limitations of satellite imagery and big data applications in detecting damage and building collapse and how Interferometric Synthetic Aperture Radar (InSAR) can be a tool to resolve existing issues. The aim of this work is to understand why many state-of-the-art models being developed have not yet been successfully and extensively deployed in the real world and to foster discussion about optimizing the use of deep learning technology to save lives and lead effective disaster management efforts.
The water cycle is an important component of the earth system and it plays a key role in many facets of society, including energy production, agriculture, and human health and safety. In this study, the Energy Exascale Earth System Model version 1 (E3SMv1) is run with low-resolution (roughly 110 km) and high-resolution (roughly 25 km) configurations — as established by the High Resolution Model Intercomparison Project protocol — to evaluate the atmospheric and terrestrial water budgets over the conterminous United States (CONUS) at the large watershed scale. The water cycle slows down in the HR experiment relative to the LR, with decreasing fluxes of precipitation, evapotranspiration, atmospheric moisture convergence, and runoff. The reductions in these terms exacerbate biases for some watersheds, while reducing them in others. For example, precipitation biases are exacerbated at HR over the Eastern and Central CONUS watersheds, while precipitation biases are reduced at HR over the Western CONUS watersheds. The most pronounced changes to the water cycle come from reductions in precipitation and evapotranspiration, the latter of which results from decreases in evaporative fraction. While the HR simulation is warmer than the LR, moisture convergence decreases despite the increased atmospheric water vapor, suggesting circulation biases are an important factor. Additional exploratory metrics show improvements to water cycle extremes (both in precipitation and streamflow), fractional contributions of different storm types to total precipitation, and mountain snowpack.
In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.
Stable carbon (δ¹³C) and oxygen (δ¹⁸O) isotope measurements in lacustrine ostracodes are widely used to infer past climatic conditions. Previous work has used individual ostracode valves to resolve seasonal and subdecadal climate signals, yet environmental controls on geochemical variability within co-occurring specimens from modern samples are poorly constrained. Here we focus on individual ostracode valves in modern-aged Lake Turkana sediments, an alkaline desert lake in tropical East Africa. We present individual ostracode valve analyses (IOVA) of δ¹³C and δ¹⁸O measurements (n = 329) of extant species Sclerocypris clavularis from 17 sites spanning the entire lake (n-avg ~19 specimens per site). We demonstrate that the pooled statistics of individual valve measurements at each site overcome inter-specimen isotopic variance and are driven by hydrological variability in the lake. Mean IOVA-δ¹³C and -δ¹⁸O across the sites exhibit strong spatial trends with higher values at more southerly latitudes, modulated by distance from the inflow of the Omo River. Whereas the latitudinal δ¹³C gradient reflects low riverine δ¹³C and decreasing lacustrine productivity towards the southern part of the lake, the δ¹⁸O gradient is controlled by evaporation superimposed on the waning influence of low-δ¹⁸O Omo River waters, sourced from the Ethiopian highlands. We show that ostracode δ¹⁸Oproximal to Omo River inflow is deposited under near-equilibrium conditions and that inter-specimen δ¹⁸O variability across the basin is consistent with observed temperature and lake water δ¹⁸O variability. IOVA can provide skillful constraints on high-frequency paleoenvironmental signals and, in Omo-Turkana sediments, yield quantitative insights into East African paleohydrology.