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.
“Climate tipping elements” often refer to large-scale earth systems with the potential to respond nonlinearly to anthropogenic climate change by transitioning towards substantially different long-term states upon passing key thresholds, frequently referred to as “tipping points.” In some but not all cases, such changes could produce additional greenhouse gas emissions or radiative forcing that could compound global warming. Improving understanding of tipping elements is important for predicting future climate risks. Here we review mechanisms, predictions, impacts, and knowledge gaps associated with ten notable earth systems proposed to be climate tipping elements. We evaluate which tipping elements are more imminent and whether shifts will likely manifest rapidly or over longer timescales. Some tipping elements are significant to future global climate and will likely affect major ecosystems, climate patterns, and/or carbon cycling within the 21st century. However, assessments under different emissions scenarios indicate a strong potential to reduce or avoid impacts associated with many tipping elements through climate change mitigation. Most tipping elements do not possess the potential for abrupt future change within years, and some proposed tipping elements may not exhibit tipping behavior, rather responding more predictably and directly to the magnitude of forcing. Nevertheless, significant uncertainties remain associated with many tipping elements, highlighting an acute need for further research and modeling to better constrain risks.
Ice nucleation in mixed-phase clouds has recently been identified as a critical factor in projections of future climate. Here we explore how this process influences climate sensitivity using the Community Earth System Model 2 (CESM2). We find that ice nucleation affects simulated cloud feedbacks over most regions and levels of the troposphere, not just extratropical low clouds. Ice nucleation’s impact on climate sensitivity is found to primarily operate through this process’s role setting global-scale cloud phase. Conversely, whether ice nucleation is treated as aerosol-sensitive is of limited importance. In satellite-constrained model experiments, dissimilar ice nucleation realizations all result in a strongly positive total cloud feedback, as in the default CESM2. A microphysics update from CESM1 to CESM2 had substantially weakened ice nucleation, due partly to a model issue. Our findings suggest that this contributed to increased climate sensitivity by reducing global cloud phase bias, resulting in more realistic mixed-phase clouds.
Antarctic landfast sea ice (fast ice) is stationary sea ice that is attached to the coast, grounded icebergs, ice shelves, or other protrusions on the continental shelf. Fast ice forms in narrow (generally up to 200 km wide) bands, and ranges in thickness from centimeters to tens of meters. In most regions, it forms in autumn, persists through the winter and melts in spring/summer, but can remain throughout the summer in particular locations. Despite its relatively limited horizontal extent (comprising between about 4 and 13 \% of overall sea ice), its presence, variability and seasonality are drivers of a wide range of physical, biological and biogeochemical processes, with both local and far-ranging ramifications for various Earth systems. Antarctic fast ice has, until quite recently, been overlooked in studies, likely due to insufficient knowledge of its distribution, leading to its reputation as a “missing piece of the Antarctic puzzle”. This review presents a synthesis of current knowledge of the physical, biogeochemical and biological aspects of fast ice, based on the sub-domains of: fast ice growth, properties and seasonality; remote-sensing and distribution; interactions with the atmosphere and the ocean; biogeochemical interactions; its role in primary production; and fast ice as a habitat for grazers. Finally, we consider the potential state of Antarctic fast ice at the end of the 21st Century, underpinned by Coupled Model Intercomparison Project model projections. This review also gives recommendations for targeted future work to increase our understanding of this critically-important element of the global cryosphere.
Using model simulations, we demonstrate that the response of top-of-atmosphere radiative fluxes to localized tropical sea surface temperature (SST) perturbations exhibits numerous non-linearities. Most pronounced is an ‘asymmetry’ in the response to positive and negative SST perturbations. Additionally, we identify a ‘magnitude-dependence’ of response on the size of the SST perturbation. We then explain how these non-linearities arise as a robust consequence of convective quasi-equilibrium and weak (but non-zero) temperature gradients in the tropical free-troposphere, which we encapsulate in a ‘circus tent’ model of the tropical atmosphere. These results demonstrate that the climate response to SST perturbations is fundamentally non-linear, and highlight potential deficiencies in work which has assumed linearity in the response.
Extreme precipitation events, including those associated with weather fronts, have wide-ranging impacts across the world. Here we use a deep learning algorithm to identify weather fronts in high resolution Community Earth System Model (CESM) simulations over the contiguous United States (CONUS), and evaluate the results using observational and reanalysis products. We further compare results between CESM simulations using present-day and future climate forcing, to study how these features might change with climate change. We find that detected front frequencies in CESM have seasonally varying spatial patterns and responses to climate change and are found to be associated with modeled changes in large scale circulation such as the jet stream. We also associate the detected fronts with precipitation and find that total and extreme frontal precipitation mostly decreases with climate change, with some seasonal and regional differences. Decreases in Northern Hemisphere summer frontal precipitation are largely driven by changes in the frequency of different front types, especially cold and stationary fronts. On the other hand, Northern Hemisphere winter exhibits some regional increases in frontal precipitation that are largely driven by changes in frontal precipitation intensity. While CONUS mean and extreme precipitation generally increase during all seasons in these climate change simulations, the likelihood of frontal extreme precipitation decreases, demonstrating that extreme precipitation has seasonally varying sources and mechanisms that will continue to evolve with climate change.
This study focuses on the projections and time of emergence (TOE) for temperature extremes over Australian regions in the phase 6 of Coupled Model Intercomparison Project (CMIP6) models. The model outputs are based on the Shared Socioeconomic Pathways (SSPs) from the Tier 1 experiments (i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) in the Scenario Model Intercomparison Project (ScenarioMIP), which is compared with the Representative Concentration Pathways (RCPs) in CMIP5 (i.e., RCP2.6, RCP4.5 and RCP8.5). Furthermore, two large ensembles (LEs) in CMIP6 are used to investigate the effects of internal variability on the projected changes and TOE. As shown in the temporal evolution and spatial distribution, the strongest warming levels are projected under the highest future scenario and the changes for some extremes follow a “warm-get-warmer” pattern over Australia. Over subregions, tropical Australia usually shows the highest warming. Compared to the RCPs in CMIP5, the multi-model medians in SSPs are higher for some indices and commonly exhibit wider spreads, likely related to the different forcings and higher climate sensitivity in a subset of the CMIP6 models. Based on a signal-to-noise framework, we confirm that the emergence patterns differ greatly for different extreme indices and the large uncertainty in TOE can result from the inter-model ranges of both signal and noise, for which internal variability contributes to the determination of the signal. We further demonstrate that the internally-generated variations influence the noise. Our findings can provide useful information for mitigation strategies and adaptation planning over Australia.
Greenhouse gases (GHGs) are gases that absorb and emit thermal energy. In a warming climate, GHGs modulate the thermal cooling to space from the surface and atmosphere, which is a fundamental feedback process that affects climate sensitivity. Previous studies have stated that the thermal cooling to space with global warming is primarily emitted from the surface, rather than the atmosphere. Using a millennium-length coupled general circulation model (Geophysical Fluid Dynamics Laboratory’s CM3) and accurate line-by-line radiative transfer calculations, here we show that the atmospheric cooling to space accounts for 12 % to 50 % of Earth’s clear-sky longwave feedback parameter from the poles to the tropics. The atmospheric cooling to space is an efficient stabilizing feedback process because water vapor and non-condensable GHGs tend to emit at higher temperatures with surface warming as the thermodynamic structure of the atmosphere evolves. A simple yet comprehensive model is proposed in this study for predicting the clear-sky longwave feedback over a wide range of surface temperatures. It achieves good spectral agreement when compared to line-by-line calculations. Our study provides a theoretical way for assessing Earth’s climate sensitivity, with important implications for Earth-like planets.
Claims of paleodata periodicity are many and controversial, so that, for example, superimposing Phanerozoic (0–541 My) mass-extinction periods renders life on Earth impossible. This period hunt coincided with the modernization of geochronology, which now ties geological timescales to orbital frequencies. Such tuneup simplifies energy-band (variance-) stratification of information contents, enabling the separation of astronomical signals from harmonics, e.g., using variance-based spectral analysis. I thus show on diverse data (geomagnetic polarity, cratering, extinction episodes) as a proxy of planetary paleodynamics that many-body subharmonic entrainment induces a resonant response of the Earth to astronomical forcing so that the 2π-phase-shifted axial precession p=26 ky, and its Pi=2πp/i; i=1,…,n harmonics, get resonantly responsible for virtually all paleodata periods. This resonantly quasiperiodic nature of strata is co-triggered by a p'/4-lockstep to the p'=41-ky obliquity (also 2π-phase-shifted, to P'=3.5-My superperiod). For verification, residuals analysis after suppressing 2πp (and thus Pi, too) in the current polarity-reversals GPTS-95 timescale’s calibration extending to end-Campanian (0–83 My) successfully detected weak signals of Earth-Mars planetary resonances, reported previously from older epochs. The significant intrinsic residual signal is 26.5-My Rampino period — the carrier wave of crushing deflections co-responsible for transformative polarity reversals. While the (2πp, Pi) resonant response of the Earth to orbital forcing is the long-sought energy transfer mechanism of the Milankovitch theory, fundamental system properties — 2π-phase-shift, ¼ lockstep to a forcer, and the discrete time translation symmetry (multiplied or halved periods) — previously thought confined to (quantum) time crystal, here appear macroscopic, rendering the concept of time crystal unremarkable. In turn, such a surprising cross-scale outcome has confirmed the main result: that of planetary precession being a cataclysmic geodynamic phenomenon as claimed in the past, e.g., as the mechanism for Earth expansion; then a time crystal in quantum dynamics could be due to particle entrainment, such as the collisions resulting in Feshbach resonances.
Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov ), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson ), which are formed concomitantly with soot (Pugmire ). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark ). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The rocket combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles (SpaceX, Hanwha) therefore also need larger fuels loads to achieve the same launched/transferred mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer ; Sheaffer ), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.
The forthcoming Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new datasets for both gaged and ungaged basins. SWOT discharge products will provide discharge for all river reaches wider than 100 m, but at lower accuracy and temporal resolution than what is possible in situ. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present here for the first time a complete estimate of SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge timeseries. We expect that discharge uncertainty will be less than 30% for two thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge timeseries will be dominated by random error and are expected to be estimated to within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.
Heatwaves damage societies globally and are intensifying with global warming. Several mechanistic drivers of heatwaves, such as atmospheric blocking and soil moisture-atmosphere feedback, are well-known for their ability to raise surface air temperature. However, what limits the maximum surface air temperature in heatwaves remains unknown; this became evident during recent Northern Hemisphere heatwaves which achieved temperatures far beyond the upper tail of the observed statistical distribution. Here, we present the hypothesis, with corroborating evidence, that convective instability limits annual maximum surface air temperatures (TXx) over midlatitude land. We provide a theory for the upper bound of midlatitude temperatures, which accurately describes the observed relationship between temperatures at the surface and in the mid-troposphere. Known heatwave drivers shift the position of the atmospheric state in the phase space described by the theory, changing its proximity to the upper bound.Our theory suggests that the upper bound for midlatitude TXx should increase 1.9 times as fast as 500-hPa temperatures. Using empirical 500-hPa warming, we project that the upper bound of TXx over Northern Hemisphere midlatitude land (40°N-65°N) will increase about twice as fast as global mean surface air temperature, and TXx will increase faster than this bound over regions that dry on the hottest days.
The variability of the Southern Hemisphere (SH) extratropical large-scale circulation is dominated by the Southern Annular Mode (SAM), whose timescale is extensively used as a key metric in evaluating state-of-the-art climate models. Past observational and theoretical studies suggest that the SAM lacks any internally generated (intrinsic) periodicity. Here, we show, using observations and a climate model hierarchy, that the SAM has an intrinsic 150-day periodicity. This periodicity is robustly detectable in the power spectra and principal oscillation patterns (aka dynamical mode decomposition) of the zonal-mean circulation, and in hemispheric-scale precipitation and ocean surface wind stress. The 150-day period is consistent with the predictions of a new reduced-order model for the SAM, which suggests that this periodicity is tied with a complex interaction of turbulent eddies and zonal wind anomalies, as the latter propagate from low to high latitudes. These findings present a rare example of periodic oscillations arising from the internal dynamics of the extratropical turbulent circulations. Based on these findings, we further propose a new metric for evaluating climate models, and show that some of the previously reported shortcomings and improvements in simulating SAM’s variability connect to the models’ ability in reproducing this periodicity. We argue that this periodicity should be considered in evaluating climate models and understanding the past, current, and projected Southern Hemisphere climate variability.
In the coming decades, the frequency of coastal flooding will increase due to sea-level rise and changes in climate extremes. We force the Global Tide and Surge Model (GTSM) with a climate model ensemble from the CMIP6 High Resolution Model Intercomparison Project (HighResMIP) to produce global projections of extreme sea levels (defined as tides and storm surge) from 1950 to 2050. This is the first time that an ensemble of global ~25km resolution climate models is used for this purpose, which increases the credibility of projected storm surges. Here we validate the historical simulations (1985-2014) against the ERA5 climate reanalysis. The overall performance of the HighResMIP ensemble is good with mean bias smaller than 0.1 m. However, there is a strong large-scale spatial bias. Future projections for the high emission SSP5-8.5 scenario indicate changes up to 0.1 m or 20% in 10-year return period surge level from 1951-1980 to 2021-2050. Increases are seen in parts of the coastline of the Caribbean, Madagascar and Mozambique, Alaska, and northern Australia, whereas the Mediterranean region may see a decrease. The full dataset underlying this analysis, including timeseries and statistics, is openly available on the Climate Data Store and can be used to inform broad-scale assessment of coastal impacts under future climate change.
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.
WWLLN (World Wide Lightning Location Network) data on global lightning are used to investigate the increase of total lightning strokes at Arctic latitudes. We focus on the summertime data from June, July and August, which average >200,000 strokes each year above 65o North latitude, for each of the years from 2010 – 2020. The influence of WWLLN network detection efficiency increases is minimized by normalizing to the total global strokes for each northern summer. The ratio of strokes occurring above 65o increases with latitude, showing that the Arctic is becoming much more influenced by lightning. We compare the increasing fraction of strokes with the global temperature anomaly for those months, and find that the fraction of strokes above 65o to total global strokes for these months increases linearly with the temperature anomaly and grows by a factor of 3 as the anomaly increases from 0.65 to 0.95 degrees C.
Through machine learning and remote sensing, a high-end model with a finer resolution for groundwater recharge has been developed for the region of South-East Asia. The groundwater recharge coefficient can be found by the application of Random Forest regression followed by the implication of the water budget method to calculate the Groundwater Recharge values. Climatic factors such as precipitation and actual evapotranspiration to map Groundwater Recharge has been framed with a sophisticated machine learning method to be considered as a scale predicting model. A comprehensive visualization of the dataset has been done; the accuracy of the model is noted through random forest regression. Thus, the model can be used for various regions of the dataset specifically for the area where there is a lack of reach for data. It can be successfully used to form a sophisticated end-to-end ML model. Keywords: Machine Learning, Remote Sensing, Groundwater Recharge, Climate science.