The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5 degC) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we use the LGM global temperature from geological proxies as a benchmark to examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time-step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed-phase clouds, which leads to more cloud ice content and a weaker shortwave cloud feedback over mid-to-high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate-calibrated CESM2 (PaleoCalibr), which simulates well the observed 20th century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (~4 degC) and a 20% weaker aerosol-cloud interaction than CESM2. PaleoCalibr represents a physically and numerically better treatment of cloud microphysics and, we believe, is a more appropriate tool than CESM2 in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

The East China Sea (ECS) seasonally receives a high organic input due to the terrestrial organic matter influx, which is controlled by the East Asian Summer Monsoon (EASM), and the increased productivity driven by upwelling of the subsurface Kuroshio Current (KC). Changes in benthic foraminiferal assemblage composition in combination with paleoceanographic proxy data (CaCO3 (%), TOC (%), δ13Cpf, and δ18Obf) are used to reconstruct bottom water oxygenation and organic export flux variability over the last 400 kyr in the ECS. Multivariate analyses of benthic foraminiferal census data identified six biofacies characteristic of varying environmental conditions. These results suggest that enhanced EASM precipitation and KC upwelling directly influenced organic export flux and bottom water oxygen content in the ECS. The ECS bottom water was suboxic during Marine Isotope Stage (MIS) 11 to 8; suboxic to dysoxic between MIS 7 and 6, strongly dysoxic between mid-MIS 5 and 4, and exhibited high variability between MIS 3 and 1. Spectral analysis of relative abundances of representative genera Quinqueloculina (oxic), Bulimina (suboxic), and Globobulimina (dysoxic) reveals a robust 23 kyr signal, which we attribute to precessionally-paced changes in surface productivity and bottom water oxygenation related to EASM and KC variability over the past 400 kyr.

Fault-zones significantly influence the migration of fluids in the subsurface and can be important controls on the local as well as regional hydrogeology. Hence, understanding the evolution of fault porosity-permeability is critical for many engineering applications (like geologic carbon sequestration, enhanced geothermal systems, groundwater remediation, etc.) as well as geological studies (like sediment diagenesis, seismic activities, hydrothermal ore deposition, etc.). The highly heterogeneous pore structure of fault-zones along with the wide range of hydrogeochemical heterogeneity that a fault-zone can cut through make conduit fault-zones a dynamic reactive transport environment that can be highly complex to accurately model. In this paper, we present a critical review of the possible ways of modeling reactive fluid flow through fault-zones, particularly from the perspective of chemically driven “self-sealing” or “self-enhancing” of fault-zones. Along with an in-depth review of the literature, we consider key issues related to different conceptual models (e.g. fault-zone as a network of fractures or as a combination of damaged zone and fault core), modeling approaches (e.g. multiple continua, discrete fracture networks, pore-scale models) and kinetics of water-rock interactions. Inherent modeling aspects related to dimensionality (e.g. 1D vs 2D) and the dimensionless Damköhler number are explored. Moreover, we use a case-study of the Little Grand Wash Fault-zone from central Utah as an example in the review. Finally, critical aspects of reactive transport modeling 2 like multiscale approaches and chemo-mechanical coupling are also addressed in the context of fault-zones.

This study develops a surrogate-based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near-surface air temperature (T2m). Average physics uncertainties are determined to be 1.5°C for LST and T2m over land, and 1.9°C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations are the dominant sources of uncertainty for both LST and T2m, and there is a substantial atmosphere-lake physics interaction component. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model’s surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model. Last, we show that the deduced physics uncertainty of T2m is statistically smaller than a regional warming perturbation exceeding 0.5°C.

A document by Sanjit Kumar Jena. Click on the document to view its contents.

In this study, based on the OI135.6 nm night airglow data of the FY-3D Ionospheric Photometer (IPM) during the 2018-2021 geomagnetically quiet period, the global wavenumber 4 longitudinal structure of the equatorial ionization anomaly (EIA) at 2:00 local time was discovered, and the component of the wavenumber 4 was extracted from these structures. Compared with the OI135.6 nm night airglow data of the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) F18 during 2011-2014, there were significant differences in the variation pattern of the relative amplitude of the two versus solar activity and the seasonal variation in the proportion of the component of the wavenumber 4. Based on the neutral wind speed observation results of Global High-Resolution Thermospheric Imaging (MIGHTI) on board the Ionospheric Connection Explorer (ICON) from 2020-2021, the longitudinal structures of the 4 ionospheric waves after midnight are related to the cross-equatorial meridional wind. We believe that the wavenumber 4 longitudinal structures after midnight originate from the eastward nonmigrating tidal semidiurnal wave (SE2) with a wavenumber of 2 in the cross-equatorial neutral wind rather than the eastward nonmigrating tidal semidiurnal wave (DE3) with a wavenumber of 3 in from the zonal wind, which modulates the daytime wavenumber 4 longitudinal structures.

While not specifically designed as a planetary mission, NASA’s Parker Solar Probe (PSP) mission uses a series of Venus gravity assists (VGAs) in order to reduce its perihelion distance. These orbital maneuvers provide the opportunity for direct measurements of the Venus plasma environment at high cadence. We present first observations of kinetic scale turbulence in the Venus magnetosheath from the first two VGAs. In VGA1, PSP observed a quasi-parallel shock, $\beta\sim1$ magnetosheath plasma, and a kinetic range scaling of $k^{-2.9}$. VGA2 was characterised by a quasi-perpendicular shock with $\beta\sim 10$, and a steep $k^{-3.4}$ spectral scaling. Temperature anisotropy measurements from VGA2 suggest an active mirror mode instability. Significant coherent waves are present in both encounters at sub-ion and electron scales. Using conditioning techniques to exclude these electromagnetic wave events suggests the presence of developed sub-ion kinetic turbulence in both magnetosheath encounters.

Wildfires are increasingly impacting social and environmental systems in the United States. The ability to mitigate the adverse effects of wildfires increases with understanding of the social, physical, and biological conditions that co-occurred with or caused the wildfire ignitions and contributed to the wildfire impacts. To this end, we developed the FPA FOD-Attributes dataset, which augments the sixth version of the Fire Program Analysis-Fire Occurrence Database (FPA FOD v6) with nearly 270 attributes that coincide with the date and location of each wildfire ignition in the United States. FPA FOD v6 contains information on location, jurisdiction, discovery time, cause, and final size of >2.3 million wildfires from 1992-2020 in the United States. For each wildfire, we added physical (e.g., weather, climate, topography, infrastructure), biological (e.g., land cover, normalized difference vegetation index), social (e.g., population density, social vulnerability index), and administrative (e.g., national and regional preparedness level, jurisdiction) attributes. This publicly available dataset can be used to answer numerous questions about the covariates associated with human- and lightning-caused wildfires. Furthermore, the FPA FOD-Attributes dataset can support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including development of machine learning models.

This report contains an overview of the spatial distribution of paddle boat registrations in Ohio between January 2016 and March 2019. Its purpose is to provide empirical evidence that can support decision making by the Ohio Department of Natural Resources in its efforts to improve education and recreational opportunities at Ohio's scenic rivers. The original data used in the analysis was provided by the ODNR Scenic Rivers Program.

Seismic hazard due to fluid invasion in hydraulic fracturing, wastewater disposal, and enhanced geothermal systems have become a concern for industry and nearby residents. Some of the challenges associated with the fluid-induced seismic hazard are the estimation of the spatial effects of these industry operations as well as the presence or absence of aftershock triggering. In some cases (e.g. Geysers, California, Hoadley gas field of Alberta), aftershocks triggering do occur, while in other cases (e.g. Soultz‐sous‐Forêts, France), this is not the case. First, to address the spatial effects, using several previously published high-resolution well-log data, we first show that there is a tendency that porosity within the basement resembles fractional Gaussian noise (fGn), while above the basement it resembles fractional Brownian motion (fBm). Based on this observation, we introduce a novel conceptual model of the fluid-induced seismicity in disordered porous media by integrating the notion of fluid diffusion and invasion percolation with spatially correlated permeability and porosity. We find that our model does not only capture the observed variations in frequency-magnitude distribution of seismic events but it also exhibits a much slower decay in seismic activity at large distances for fBm compared to fGn. Second, to address the presence of aftershock triggering, we also introduce nonlinear viscoelastic effects in our model to augment the failure mechanics. This allows us to test whether the presence or absence of aftershocks is coupled to the validity of a time scale separation between fluid dynamics and nonlinear viscoelastic response, for example. Our findings can be directly incorporated in the seismic hazard assessment related to fluid injections.

We report the radiocarbon age, chemistry, and mineralogy of sinter deposits from Castle and Giant Geyser in the Upper Geyser Basin of Yellowstone National Park. At each geyser, we sampled following the stratigraphy of the older terrace and younger cone. We analyzed 15 samples with x-ray diffraction, x-ray tomography, x-ray fluorescence, scanning electron microscopy, thin section microscopy, 3D imaging, and loss on ignition. Castle Geyser's terrace and Giant Geyser's cone are composed of more increasingly more mature sinter. The concentrations of Na, K, Cs, and Ga decrease in the sinter with decreasing H2O and increasing SiO2, therefore water and trace element concentrations correlate with stratigraphic position, and sinters exhibit progressive dehydration with increasing age. However, radiocarbon dates resulted in stratigraphically out-of-sequence ages. This suggests both physical mixing and the influence of magmatically dead carbon. By isolating and dating individual pieces of externally sourced organic material, we report ages as upper bounds---increasing the known age of Castle Geyser cone to 2,000 yr BP. Additionally, we demonstrate that Castle Geyser's shield is mineralogically distinct from and at least 1,000 years older than it's cone.

Coronal holes (CH) are dark areas in EUV images that are generally associated with open magnetic field regions on the Sun. CHs detected over the entire Sun can be used to estimate the open magnetic flux in the heliosphere by overlaying them on magnetic field measurements. Making accurate estimates is difficult due to many factors, including limited instrument coverage, uncertainties in the observations, and challenges in reliable detection of CH boundaries. One such CH detection challenge stems from the fact that EUV line-of-sight observations essentially flatten the three-dimensional structure in the low corona, which can cause nearby bright structures to obstruct CHs. Here we introduce a mitigation strategy for avoiding the effects of CH obscuration. Using a global thermodynamic MHD model of the corona, we first generate synthetic EUV images for a multitude of observer locations (chosen to mimic the view of SDO over the solar rotation) and combine them into a full-Sun synoptic EUV map. A CH map is then extracted using an established detection algorithm. The resulting open flux estimates are computed and compared to the model’s true open flux. The mitigation strategy (called “minimum intensity disk merge (MIDM)”) is applied by changing the way multiple EUV disk images are combined. Instead of using central strips, full disk images are used by taking the minimum intensity in all overlapping regions. This allows any CH area observed at any vantage point to be seen in the final map. We compare the resulting open flux and CH areas to those using the standard synoptic method. We apply the MIDM method to SDO AIA 193 observational data for the same rotation, and the resulting EUV and CH maps (with corresponding open flux estimates) are compared. Issues such as CH evolution over the rotation, and synchronizing the effective EUV image height to the height of the magnetic field values are discussed.

The Colorado Rockies were initially raised during the Laramide Orogeny ca. 70-45 Ma. But consensus exists that the range experienced a second, post-Laramide episode of surface uplift; the timing and cause of that post-Laramide surface uplift event remains enigmatic. Low-temperature thermochronologic studies conducted by us and others using apatite (U-Th)/He (AHe), apatite fission track (AFT), and zircon (U-Th)/He (ZHe) techniques reveal that a dome of kilometer-scale exhumation occurred in Colorado’s Elk and West Elk mountains between ca. 18-6 Ma. We call this feature the “Gothic Dome” because it is centered on Gothic Mountain, near the town of Crested Butte. We suggest the ~100-km-diameter Gothic Dome likely experienced Miocene surface uplift, which triggered the dome-shaped exhumation pattern documented by the low-temperature thermochronometry. The exhumation magnitude exceeds 4 km in the center of the dome (as revealed by a 16 Ma ZHe date on an Oligocene pluton) and diminishes toward its perimeter. This diminution of exhumation magnitude toward the perimeter is revealed by progressively older AHe, AFT, and ZHe dates in all directions away from Gothic Mountain. AHe dates for samples that lie outside the perimeter are Laramide-age or older, further documenting the dome-shaped nature of this Miocene exhumation event and illustrating the low magnitude of Miocene to recent exhumation outside the dome’s perimeter. Outcrops of ca. 11 Ma basalt surround the Gothic Dome to the north, west, and south, requiring that Miocene exhumation outside the dome’s perimeter was minimal. A suite of alkaline, low-volume, felsic plutons and ultramafic lamprophyres intruded the Gothic Dome between ca. 18-12 Ma. This alkalic magmatism began either immediately prior to or contemporaneous with the onset of Gothic Dome exhumation, hinting that the same root cause might be responsible for both. Workers elsewhere, including Tibet, the Altiplano, and California’s Sierra Nevada mountains, have attributed small-volume alkalic magmatism, surface uplift, and exhumation to the activity of lithospheric drips. We offer that Miocene activity of such a drip beneath Colorado’s Elk and West Elk mountains is an appealing mechanism to explain the near simultaneity of those same phenomena here.

Himalaya glaciers are invariably covered by supra-glacial debris. Of the glaciers, the Chhota Shigri Glacier (CSG) in the western Himalaya is basically debris-free yet has the highest melt rate compared to other central and eastern Himalayan glaciers. Here, utilizing osmium isotopic composition and major and trace element geochemistry of cryoconite — a dark-colored aggregate of mineral and organic materials —and glacial surface materials on the ablation zone of the CSG, we show that the surface of CSG is essentially free of anthropogenically emitted particles, contrary to many previous findings. Given this and the lack of debris, we conclude that the high melting rate in CSG is primarily related to the increase of the Earth’s near-surface temperature in direct response to global warming. Thus, monitoring the ice mass loss is further critical given the water source to millions of people.

Although the Brown mathematical model is the standard model for waveform retracking over open oceans, coastal waveforms usually deviate from open ocean waveform shapes due to inhomogeneous surface reflections within altimeter footprints, and thus cannot be directly interpreted by the Brown model. Generally, the two primary sources of heterogeneous surface reflections are land surfaces and bright targets such as calm surface water. The former reduces echo power, while the latter often produces particularly strong echoes. In previous studies, sub-waveform retrackers, which use waveform samples collected from around leading edges in order to avoid trailing edge noise, have been recommended for coastal waveform retracking. In the present study, the peaky-type noise caused by fixed-point bright targets is explicitly detected and masked using the parabolic signature in the sequential along-track waveforms (or, azimuth-range echograms). Moreover, the power deficit of waveform trailing edges caused by weak land reflections is compensated for by estimating the ratio of sea surface area within each annular footprint in order to produce pseudo-homogeneous reflected waveforms suitable for the Brown model. Using this method, Jason-2 altimeter waveforms are retracked in several coastal areas. Our results show that both the correlation coefficient and root mean square difference between the derived sea surface height anomalies and tide gauge records retain similar values at the open ocean (0.9 and 20 cm) level, even in areas approaching 3 km from coastlines, which is considerably improved from the 10 km correlation coefficient limit of the conventional MLE4 retracker and the 7 km sub-waveform ALES retracker limit. These values, however, depend on the coastal topography of the study areas because the approach distance limit increases (decreases) in areas with complicated (straight) coastlines.

AbstractSeveral flood-generating mechanisms could produce high flows in catchments however, AMS/POT sampling is not considering these hydrological processes. Grouping the floods into homogenous samples (in terms of process) has many potential advantages, such as better estimation of return level. This study aims to develop methods to classify and group floods, based on the simple flood hydrograph characteristics, from the daily discharge data. This approach is based on the underlying hypothesis that similar hydrological and catchment conditions lead to similar hydrological responses. We used the Dresden gauge station on the Elbe river, Germany (1950-2019). Flood separation follows four steps: 1. Identification of peaks, i.e., points with a higher streamflow value than its prior and next values, 2. Pruning based on 90th percentile threshold value, 3. Application of independence criterion, 4. Identification of flood starting and ending position. From the separated flood events, six features are extracted for clustering, i.e., peak, volume, timescale, rise to duration ratio, occurrence season and the existence of multi peaks. Extracted flood features include both numerical and categorical variables thus, to deal with these mixed feature datasets, we employed the K-medoids technique for clustering. Further, various cluster validation indices robustly help to identify the optimal number of clusters. We also performed the feature relevancy analysis to understand the hydrograph features’ relative importance. Since hydrometeorological variables are not used for classification, we used the magnitude of the precipitation and snowmelt during the flood duration to characterize the various clusters. Clustering results show that the employed methods are effective in classifying the flood events driven by different flood drivers.Keywords: Flood classification, Flood separation, Flood frequency analysis

The California Current System (CCS) supports a wide array of ecosystem services with hypoxia historically occurring in near-bottom waters. Limited open ocean data coverage hinders the mechanistic understanding of CCS oxygen variability. We compared three models with different horizontal resolutions and complexities and found that regions of high dissolved oxygen (DO) variability deepened with distance to the coast, mainly driven by water mass variation in the surface 100 meters with remineralization important below 200 meters. We illustrate how oxygen anomalies are transported from the coastal areas into the open ocean where they are downwelled to 200-400 m and propagated Southwest on decadal timescales as part of the large-scale circulation. Pacific Decadal Oscillation was the climate variability mode most closely linked to DO anomalies. We suggest that increased sampling at subsurface near the shelf break and within the regions of water mass formation would help further elucidate mechanisms driving DO anomalies.

It has been four decades since Apollo 16 returned the first wide-field UV imagery of the Earth and revealed the vast extent of exospheric hydrogen (H) atoms around the planet. Since that time, appreciation has grown regarding the significance of this outermost atmospheric layer, whose charge exchange interaction with ambient ions dissipates magnetospheric energy, generates the energetic neutral atoms (ENAs) widely used for remote sensing of the ring current dynamics during geomagnetic storms, and accelerates gravitational escape and thus permanent atmospheric evolution. Despite the importance of Earth’s H exosphere to the solar-terrestrial system, however, current understanding of its global structure and dynamical evolution is insufficient, such that the origin of persistent discrepancies between measurements and models remains unresolved. Remote sensing of UV emission from geocoronal H atoms, generated through resonant scattering of solar radiation at 121.6 nm (Lyman-alpha) is the only empirical means available to investigate the terrestrial exosphere. In this work, we present robust tomographic-based techniques we have developed in recent years to estimate the 3-D, global and time-dependent H-density distributions during quiet and storm-time from observations of its optically thin emission at Lyman-α acquired from the Lyman-alpha detectors onboard the NASA TWINS satellites. Several examples of recent 2D and 3D data analyses will be used to demonstrate the current state-of-the-art, reveal surprising exospheric phenomenon, and motivate future work.