The eruption of Hunga Tonga in January 2022 injected an amount of water vapor into the stratosphere that is unprecedented in the satellite era. In the ensuing months Aura Microwave Limb Sounder (MLS) measurements showed that this plume of water vapor spread from its original injection site at 20.5⁰S to Mauna Loa, Hawaii at 19.5⁰N, where an increase was observed in April by the ground-based Water Vapor Millimeter-wave Spectrometer (WVMS) instruments. Interannual variations in water vapor occur over Mauna Loa due to both dynamical variations in the tropical stratosphere and variations in the amount of water vapor crossing the tropical tropopause, and we place the observed stratospheric water vapor increase from Hunga Tonga into context of these other variations that have been observed since 2013.

Land-atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small-scale variations in surface characteristics and co-located turbulent and momentum fluxes can significantly impact the atmosphere. Recent model development efforts have attempted to capture this phenomenon by coupling existing representations of subgrid-scale (SGS) heterogeneity between land and atmosphere models. Such approaches are in their infancy and it is not yet clear if they can produce a realistic atmospheric response to surface heterogeneity. Here, we implement a parameterization to capture the effects of SGS heterogeneity in the Community Earth System Model (CESM2), and compare single-column simulations against high-resolution Weather Research and Forecasting (WRF) large-eddy simulations (LESs), which we use as a proxy for observations. The CESM2 experiments increase the temperature and humidity variances in the lowest atmospheric levels, but the response is weaker than in WRF-LES. In part, this is attributed to an underestimate of surface heterogeneity in the land model due to a lack of SGS meteorology, a separation between deep and shallow convection schemes in the atmosphere, and a lack of explicitly represented mesoscale secondary circulations. These results highlight the complex processes involved in capturing the effects of SGS heterogeneity and suggest the need for parameterizations that communicate their influence not only at the surface but also vertically.

It has been widely recognized that tropical cyclone (TC) genesis requires favorable large-scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large-scale environmental favorabilities in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relation between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer-learning technique to train ensembles of CNNs first on suites of high-resolution climate simulations with realistic seasonal TC activities and large-scale environmental conditions, and then subsequently on the state-of-the-art reanalysis from 1950 to 2019. Our CNNs can remarkably reproduce the historical TC records, and yields significant seasonal prediction skills when the large-scale environmental inputs are provided by operational climate forecasts. Furthermore, by forcing the ensemble CNNs with 20th century reanalysis products and phase 6 of the Coupled Model Intercomparison Project (CMIP6) experiments, we attempted to investigate TC variabilities and their changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our dynamic projections using TC-permitting high-resolution coupled climate model.

Resistivity imaging obtained by a short period magnetotelluric survey identified the electrical resistivity patterns below Vulcano Island to a depth of 2 km below sea level. In the 3D resistivity model, clear contrasts generally characterized the caldera faults, whereas volcanic edifices, craters, volcanic conduits, and/or eruptive fissures corresponded to superficially high resistivity anomalies. Among the most prominent detected structures, a resistive anomaly located below La Fossa crater, which extends 2 km below the surface, likely represents a “conduit” structure, along which magmatic fluids preferably ascend. Other resistivity anomalies, mainly aligned in the N‒S direction, characterized the island sector where considerable amounts of deep subsurface fluids accumulate and mix with the ascending magmas related to the most recent volcanic dynamics. The interpretation of the main features reconstructed through the magnetotelluric investigation significantly contributes to understanding the current unrest at Vulcano.

Atmospheric aerosols influence the radiation budget, cloud amount, cloud properties, and surface albedos of sea ice and snow over the Arctic. In spite of their climatic importance, Arctic aerosol contains large uncertainties due to limited observations. This study evaluates the Arctic aerosol variability in three reanalyses, JRAero, CAMSRA, and MERRA2, in terms of the aerosol optical depth (AOD), and its relationship to the atmospheric disturbances on synoptic timescales. The AOD becomes highest in July–August over most of the Arctic regions, except for the North Atlantic and Greenland, where monthly variability is rather small. The three reanalyses show a general consistency in the horizontal distribution and temporal variability of the total AOD in summer. In contrast, the contributions of individual aerosol species to the total AOD are quite different among the reanalyses. Compared with observations, the AOD variability is represented well in all reanalyses in summer with high correlation coefficients, albeit exhibiting errors as large as the average AOD. The composite analysis shows that large aerosol emissions in Northern Eurasia and Alaska and transport by a typical atmospheric circulation pattern contribute to the high aerosol loading events in each area of the Arctic. Meanwhile, the empirical orthogonal function analysis depicts that the first- and second-largest AOD variabilities on the synoptic timescales appear over Northern Eurasia. Our results indicate that these summertime AOD variabilities mainly result from aerosol transportation and deposition due to the atmospheric disturbances on synoptic scales, suggesting an essential role played by Arctic cyclones.

The transport of meltwater through porous snow is a fundamental process in hydrology that remains poorly understood but essential for more robust prediction of how the cryosphere will respond under climate change. Here we propose a continuum model that resolves the nonlinear coupling of preferential melt flow and the nonequilibrium thermodynamics of ice-melt phase change at the Darcy scale. We assume that the commonly observed unstable melt infiltration is due to the gravity fingering instabililty, and capture it using the modified Richards equation that is extended with a higher-order term in saturation. Our model accounts for changes in porosity and the thermal budget of the snowpack caused by melt refreezing at the continuum scale, based on a mechanistic estimate of the ice-water phase change kinetics formulated at the pore scale. We validate the model in 1D against field data and laboratory experiments of infiltration in snow and find generally good agreement. Compared to existing theory of stable melt infiltration, our 2D simulation results show that preferential infiltration delivers melt faster to deeper depths, and as a result, changes in porosity and temperature can occur at deeper parts of the snow. The simulations also capture the formation of vertical low porosity annulus known as ice pipes, which have been observed in the field but lack mechanistic understanding to date. Our results demonstrate how melt refreezing and unstable infiltration reshape the porosity structure of snow and impacts thermal and mass transport in highly nonlinear ways, which are not captured by simpler models.

Wave- and current-supported turbidity currents (WCSTCs) are one of the sediment delivery mechanisms from the inner shelf to the shelf break. Therefore, they play a significant role in the global cycles of geo-chemically important particulate matter. Recent observations suggest that WCSTCs can transform into self-driven turbidity currents close to the continental margin. However, little is known regarding the critical conditions that grow self-driven turbidity currents on WCSTCs. This is in part due to the knowledge gaps in the dynamics of WCSTCs regarding the role of density stratification. Especially the effect of sediment entrainment, and the parameters thereof, on density stratification and the amount of sediment suspension, has been overlooked. To this end, this study revisits the existing theoretical framework for a simplified WCSTC, in which waves are absent, i.e., alongshelf current-supported turbidity current (ACSTC). A depth-integrated advection model is developed for suspended sediment concentration. The analyses of the model, which are verified by turbulence-resolving simulations, indicate that the amount of suspended sediment load is regulated by the equilibrium among density stratification, positive feedback between entrainment and cross-shelf gravity force, and settling flux dissociated with density stratification. It is also found that critical density stratification is not a necessary condition for equilibrium. A quantitative relation is developed for the critical conditions for self-driven turbidity currents, which is a function of bed shear stress, entrainment parameters, bed slope, and sediment settling velocity. In addition, the suspended sediment load is analytically estimated from the model developed.

A document by Qian Liu. Click on the document to view its contents.

Nickel (Ni) is a micronutrient that plays a role in nitrogen uptake and fixation in the modern ocean may have impacted rates of methanogenesis on geological timescales. Here we present the results of a diagnostic model of global ocean Ni fluxes which addresses key questions about the biogeochemical processes which cycle Ni in the modern oceans. Our approach starts with extrapolating the sparse available observations of Ni data from the GEOTRACES project into a global gridded climatology of ocean Ni concentrations. Three different machine learning techniques were tested, each relying on marine tracers with better observational coverage such as macronutrient concentrations and physical parameters. The ocean transport of this global Ni concentration field is then estimated using the OCIM2 ocean circulation inverse model, revealing regions of net convergence or divergence. These diagnostics are not based on any assumption about Ni biogeochemical cycling, but their spatial patterns can be interpreted as reflecting biogeochemical processes. We find that the spatial pattern of Ni uptake in the surface ocean is similar to phosphate (P) uptake, but not silicate (Si) uptake, suggesting that Ni is not incorporated into diatom frustules. We find that Ni:P ratios at uptake do not decrease with Ni concentrations approaching 2 nM, which challenges the hypothesis of a ~2 nM pool of non-bioavailable Ni in the surface ocean. Finally, the net regeneration of Ni occurs deeper in the ocean than P remineralization, which could be explained by reversible scavenging or the presence of a refractory Ni phase.

The composite structure of the Madden-Julian Oscillation (MJO) has long been known to feature pronounced Rossby gyres in the subtropical upper troposphere, whose existence can be interpreted as the forced response to convective heating anomalies in the presence of a subtropical westerly jet. Here we inquire as to whether these forced gyre circulations have any subsequent effects on divergence patterns in the tropics. A nonlinear spherical shallow water model is used to investigate how the introduction of different background jet profiles affects the model’s steady-state response to an imposed MJO-like thermal forcing. Results show that a stronger jet leads to a stronger Kelvin-mode response in the tropics up to a critical jet speed, along with stronger divergence anomalies in the vicinity of the forcing. To understand this behavior, additional calculations are performed in which a localized vorticity forcing is imposed in the extratropics, without any thermal forcing in the tropics. The response is once again seen to include pronounced equatorial Kelvin waves, provided the jet is of sufficient amplitude. A detailed analysis of the vorticity budget reveals that the zonal-mean zonal wind shear plays a key role in amplifying the Kelvin-mode divergent winds near the equator. These results help to explain why the MJO tends to be strongest during boreal winter when the Indo-Pacific jet is typically at its strongest.

Surface water nutrient pollution, the primary cause of eutrophication, remains a major environmental concern in Western Lake Erie despite intergovernmental efforts to regulate nutrient sources. The Maumee River Basin has been the largest nutrient contributor. The two primary nutrients sources are inorganic fertilizer and livestock manure applied to croplands, which are later carried to the streams via runoff and soil erosion. Prior studies on nutrient source attribution have focused on large watersheds or counties at long time scales. Source attribution at finer spatiotemporal scales, which enables more effective nutrient management, remains a substantial challenge. This study aims to address this challenge by developing a portable network model framework for phosphorus source attribution at the subwatershed (HUC-12) scale. Since phosphorus release is uncertain, we combine excess phosphorus derived from manure and fertilizer application and crop uptake data, flow dynamics simulated by the SWAT model, and in-stream water quality measurements into a probabilistic framework and apply Approximate Bayesian Computation to attribute phosphorus contributions from subwatersheds. Our results show significant variability in subwatershed-scale phosphorus release that is lost in coarse-scale attribution. Phosphorus contributions attributed to the subwatersheds are on average lower than the excess phosphorus estimated by the nutrient balance approach adopted by environmental agencies. Phosphorus release is higher during spring planting than the growing period, with manure contributing more than inorganic fertilizer. By enabling source attribution at high spatiotemporal resolution, our lightweight and portable model framework is suitable for broad applications in environmental regulation and enforcement for other regions and pollutants.

Benthic carbonates in perennially ice-covered Lake Fryxell (Mc-Murdo Dry Valleys, Antarctica) precipitated from pore waters in microbial mats as calcite rhombs, acicular botryoids and interfering bundles. Carbonates span the pronounced Lake Fryxell oxycline; variations in carbonate-associated manganese and iron concentrations are consistent with local oxycline conditions and seasonal fluctuations in pore water oxygenation. Precipitation is most abundant in shallow oxic waters, but extended through the oxycline during a discrete episode lasting multiple years, as evidenced by patterns of cathodoluminescence consistent with predicted seasonal changes in redox modulating dissolved manganese and iron concentrations. Carbonates did not precipitate in isotopic equilibrium with the water column, and are enriched in 18 O relative to predicted equilibrium values. Carbonate layer 18 O values vary by >20‰ at the mm-scale, suggesting precipitation was driven by mixing of isotopically heterogeneous fluids in the mat pore waters. Correlation of carbonate geochemistry and mat morphology with historical observations indicates that precipitation postdates recent lake level rise. Further investigation of the physical and geochemical carbonate proxies from Lake Fryxell and other ice-covered lakes in the Dry Valleys promises to provide a valuable framework for interpreting Antarctic carbonates as records of modern and ancient climate, Antarctic biogeochemical and hydrological systems, and the drivers of carbonate precipitation at polar climate extremes.

Solar-induced fluorescence (SIF) shows enormous promise as a proxy for photosynthesis and as a tool for modeling variability in gross primary productivity (GPP) and net biosphere exchange (NBE). In this study, we explore the skill of SIF and other vegetation indicators in predicting variability in global atmospheric CO2 observations, and thus global variability in NBE. We do so using a four-year record of global CO2 observations from NASA’s Orbiting Carbon Observatory 2 (OCO-2) satellite and using a geostatistical inverse model. We find that existing SIF products closely correlate with space-time variability in atmospheric CO2 observations in the extra-tropics but show weaker explanatory power across the tropics. In the extra-tropics, all SIF products exhibit greater skill in explaining variability in atmospheric CO2 observations compared to an ensemble of process-based CO2 flux models and other vegetation indicators. Furthermore, we find that using SIF as a predictor variable in the geosatistical inverse model shifts the seasonal cycle of estimated NBE and yields an earlier end to the growing season relative to other vegetation indicators. In tropical biomes, by contrast, the seasonal cycles of SIF products and estimated NBE are out of phase, and existing respiration and biomass burning estimates do not reconcile this discrepancy. Overall, our results highlight several advantages and challenges of using SIF products to help predict global variability in GPP and NBE.

Optical properties of seawater can provide valuable insight into distributions of dissolved organic carbon (DOC) and particulate organic carbon (POC), provided that their interrelationships are well understood. We examined relationships between DOC and POC, and absorption, backscatter, and fluorescence in a river-fed lagoon system in the coastal Alaskan Arctic during late summer of 2018 and 2019. Over both years analytically measured DOC levels were inversely correlated with salinity (r2 = 0.97) and DOC was positively correlated with dissolved organic material fluorescence (fDOM; r2 = 0.67). However, DOC showed strong correlation with the absorption coefficient at 440 nm (ag(440)) only in 2018 (r2 = 0.95 versus r2 = 0.00056 in 2019). Vertical structure of fDOM in our study area corresponded with density profiles more strongly in 2018 than in 2019, but higher levels of fDOM, ag(440), and backscatter near the bottom in 2019 suggest prior wind-driven mixing or bottom resuspension events. In 2018 and 2019, the spectral slope of the absorption coefficient between 412 and 550 nm was strongly correlated with DOC concentration (r2 = 0.70), and spectral backscattering coefficients were well correlated with POC concentration (r2 = 0.90, 0.71, and 0.59 for 470, 532, and 660 nm respectively). These interannual patterns in the distribution of DOC and POC and their respective relationships with optical proxies likely reflect regional climatological factors such as precipitation over the adjacent watersheds, wind patterns, and residual sea ice in late summer.

Upper thermosphere mass density over the declining phase of solar cycle 23 are investigated using a day-to-night ratio (DNR) of thermosphere properties as a metric to evaluate how much relative change occurs climatologically between day and night. CHAMP observations from 2002-2009, MSIS 2.0 output, and TIEGCM V2.0 simulations are analyzed to assess their relative response in DNR. The CHAMP observations demonstrate nightside densities decrease more significantly than dayside densities as solar flux decreases. This causes a steadily increasing CHAMP mass density DNR from two to four with decreasing solar flux. The MSIS 2.0 nightside densities decrease more significantly than the dayside, resulting in the same trend as CHAMP. TIEGCM V2.0 displays an opposing trend in density DNR with decreasing solar flux due to dayside densities decreasing more significantly than nightside densities. A sensitivity analysis of the two models reveals the TIEGCM V2.0 to have greater sensitivity in temperature to levels of solar flux, while MSIS 2.0 displayed a greater sensitivity in mean molecular weight. The pressure DNR from both models contributed the most to the density DNR value at 400 km. As solar flux decreases, the two models’ estimate of pressure DNR deviate appreciably and trend in opposite directions. The TIEGCM V2.0 dayside temperatures during middle-to-low solar flux are too cold relative to MSIS 2.0. Increasing the dayside temperature values by about 50 – 100 K and decreasing the nightside temperature slightly would bring the TIEGCM V2.0 into better agreement with MSIS 2.0 and CHAMP observations.

Electron temperature anisotropy-driven instabilities such as the electron firehose instability (EFI) are especially significant in space collisionless plasmas, where collisions are so scarce that wave-particle interactions are the leading mechanisms in the isotropization of the distribution function and energy transfer. Observational statistical studies provided convincing evidence in favor of the EFI constraining the electron distribution function and limiting the electron temperature anisotropy. Magnetic reconnection is characterized by regions of enhanced temperature anisotropy that could drive instabilities – including the electron firehose instability – affecting the particle dynamics and the energy conversion. However, in situ observations of the fluctuations generated by the EFI are still lacking and the interplay between magnetic reconnection and EFI is still largely unknown. In this study, we use high-resolution in situ measurements by the Magnetospheric Multiscale (MMS) spacecraft to identify and investigate EFI fluctuations in the magnetic reconnection exhaust in the Earth’s magnetotail. We find that the wave properties of the observed fluctuations largely agree with theoretical predictions of the non-propagating EF mode. These findings are further supported by comparison with the linear kinetic dispersion relation. Our results demonstrate that the magnetic reconnection outflow can be the seedbed of EFI and provide the first direct in situ observations of EFI-generated fluctuations.

The wintertime Kuroshio sea surface temperature (SST) front have the significant climate effects on southern China. The study demonstrates a close relationship between heavy precipitation over Southern China and Kuroshio SST front in winter. More than half winter heavy rainfall events in Southern China are proved to be resulted from strong High-frequency Variability events of the sea surface Wind Coupled with Precipitation (HV-WCP) over Kuroshio SST front. One day before strong HV-WCP events, the initial precipitation appears over Middle-lower Yangtze River due to the significantly enhanced frontal intensity. Then the precipitation generates low level cyclone and southeasterly wind anomalies, after it moving into Kuroshio front area because of the winter monsoon. The significant marine atmospheric boundary layer (MABL) height gradient over Kuroshio leads to plentiful moisture transporting from MABL into free atmosphere and enhances the local precipitation again. This process further causes the large-scale stratus rainband extending to Southern China and enhancing the heavy rainfall locally. Especially in 2008 winter, several processes of a strong HV-WCP event followed by continuous weak ones are conducive to the low-temperature-precipitation disaster in Southern China

The global area and distribution of shallow water ecosystems (SWEs), and their projected responses to climate change, are fundamental for evaluating future changes in their ecosystem functions, including biodiversity and climate change mitigation and adaptation. Whereas previous studies have focused on a few SWEs, we modelled the global distribution of all major SWEs (seagrass meadows, macroalgal beds, tidal marshes, mangroves, and coral habitats) from current conditions (1986−2005) to 2100 under the RCP2.6 and RCP8.5 emission scenarios. Our projections show that global coral habitat shrank by as much as 75% by 2100 with warmer ocean temperatures, but macroalgal beds, tidal marshes, and mangroves remained about the same because photosynthetic active radiation (PAR) depth did not vary greatly (macroalgal beds) and the shrinkage caused by sea-level rise was offset by other areas of expansion (tidal marshes and mangroves). Seagrass meadows were projected to increase by up to 11 % by 2100 because of the increased PAR depth. If the landward shift of tidal marshes and mangroves relative to sea-level rise was restricted by assuming coastal development and land use, the SWEs shrank by 91.9% (tidal marshes) and 74.3% (mangroves) by 2100. Countermeasures may be necessary for coastal defense in the future; these include considering the best mix of SWEs and coastal hard infrastructure because the significant shrinkage in coral habitat could decrease wave energy. However, if appropriate coastal management is achieved, the other four SWEs, which relatively have high CO2 absorption rates, can help mitigate the climate change influences.