Surface anticyclones connected to the ridge of an upper-tropospheric Rossby wave are the dynamical drivers of mid-latitude summer heatwaves. It is, however, unclear to which extent an anomalously low zonal phase speed of the wave in the upper troposphere is necessary for persistent temperature extremes at the surface. Here, we use spectral analysis to estimate a categorical phase speed for synoptic-scale waves. A composite analysis of ERA5 reanalysis data reveals how a meridional shift in the Rossby wave packet envelope associated with a change in phase speed alters the geographically phase-locked stationary wave pattern. In both composites for amplified low or high phase speed waves, respectively, the ridges and troughs of these temporal-mean wave trains show enhanced and reduced heatwave frequency. The phase speed of synoptic-scale waves is, hence, crucial for where, but less important for whether heatwaves occur.

Polar stratospheric chemistry is highly sensitive even to minor disruptions in water vapor or temperature. Unusual behavior in temperature and water vapor has been identified in the southern polar winter stratosphere in 2023. The potential correlation between the post-Hunga-Tonga eruption elevation of water vapor (detected in the tropics), temperature changes, and ozone anomalies is under discussion, as these parameters play a crucial role in stratospheric chemistry and dynamics. In the winter of 2023 in the Southern Hemisphere, an unexpected decrease in ozone levels and the emergence of a substantial ozone hole were observed. This event marked one of the most significant ozone decreases in the past 15 years, with an unusually large ozone hole occurring during this period, and it appears to be at least partly associated with the Hunga Tonga eruption.

Stable water isotopes in inland Antarctic ice cores are powerful paleoclimate proxies; however, their relationship with dynamical atmospheric circulations remains controversial. Using a water isotope climate model (MIROC5-iso), we assessed the influence of the Last Glacial Maximum (LGM; ~21,000 years ago) sea surface temperatures (SST) and sea ice (SIC) on Antarctic precipitation isotopes (δ18Op) through atmospheric circulation. The results revealed that the synoptic circulation mostly maintained southward moisture transport, reaching inland Antarctica. The steepened meridional SST gradient in the mid-latitudes increased δ18Op in inland Antarctica by enhancing the baroclinic instability and synoptic moisture transport. In contrast, enhanced SIC reduced the atmospheric humidity around Antarctica and lowered δ18Op through extensive surface cooling and transport from the ocean. These findings elucidate the isotopic proxies and enable us to constrain the southern hemisphere atmospheric circulation, including the westerlies, using ice cores during past climates, including the LGM.

White Dwarf stars are one of the densest form of matter following neutron star and black holes. A typical White Dwarf is as massive as our Sun has radius comparable to the Earth. This paper reviewed the Fermi gas model Equation of State of White Dwarf and numerical computation of Mass-radius and pressure density profile. A section in brief has been included for the calculation of average speed of electrons in the White Dwarf environment.

A document by Daniel White. Click on the document to view its contents.

A document by Brady Jones. Click on the document to view its contents.

A document by Nicholas Christensen. Click on the document to view its contents.

Satellite-derived velocity data products and mass loss estimates can be problematic when applied to slow-moving systems with smaller magnitude changes such as the accumulation zone of the Llewellyn Glacier of the Juneau Icefield. As a result, inter-annual variability may be systematically over or under predicted. Ground survey data has the potential to provide a long term, higher resolution record of slow but significant changes in the accumulation zones of glaciers. Here we compare satellitebased velocity data with GPS data collected in a 2010 ground survey across the Llewellyn Glacier.

The increasing movement and deformation of Arctic sea ice cover results in pronounced drag sheltering effects behind sea ice pressure ridges. This needs to be accounted for in the parameterization of the form drag of ridges, thereby posing a challenge to evaluate the ice–ocean dynamic feedback. Laboratory experiments were conducted in a water tank to explore the sheltering effect between adjacent ridges of various geometries. The form drag forces on the keel models were measured, and the particle image velocimetry (PIV) system was employed to capture the flow fields surrounding the models to explain the variations in the drag force. The key sheltering parameters were the ratio between keel spacing and keel depth L/H, flow velocity u, and keel slope angle α. The results showed that the drag force F1 on the upstream keel was close to the value of the single keel case, while the drag force F2 on the downstream keel was lower, for L/H ≤ 10 even opposite to the flow direction. Having changed from negative to positive, the sheltering coefficient Г = F1/F2 increased with increasing L/H. Г decreased remarkably with steepening α and was independent of u. To fully incorporate the effects of the L/H and α , we propose a new sheltering function fitted with the experimental results:Г =[1-1.56exp(sL/H)]*1.20α-0.08, s=0.001α-0.15. This function is compared with the previous sheltering functions and the actual ice conditions in the Arctic Ocean, pointing the way to obtain the final sheltering functions applicable to sea ice dynamics models.

Marine heatwave (MHW), a prolonged period of anomalously warm seawater, has a catastrophic repercussion on marine ecosystems. With global warming, MHWs have become increasingly frequent, intense, and prolonged. To avoid irreversible damages from such extreme events, net-zero carbon emissions by the 2050s, called carbon neutrality, were proposed. Here, we evaluate the impact of carbon neutrality on MHWs in the late 21st century using multi-model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP)1-1.9 and SSP3-7.0 scenarios. It is found that if the current regional rivalry over carbon emissions continues (i.e., SSP3-7.0), the MHWs in the late 21st century will become stronger and longer than historical ones, especially in the western boundary current and equatorial current regions. Approximately 68% of the global ocean will be exposed to permanent MHWs, regionally 93% in the Indian Ocean, 76% in the Pacific Ocean, 68% in the Atlantic Ocean, 65% in the Coastal Ocean, and 48% in the Southern Ocean. Such MHWs can be significantly reduced by achieving carbon neutrality (i.e., SSP1-1.9). In particular, the spatial proportion of the ocean exposed to permanent MHWs can be reduced to as low as 0.02 to 0.07%, depending on the regions. This result underscores the critical importance of ongoing efforts to achieve net-zero carbon emissions to reduce the potential ecological risks induced by extreme MHWs.

This Work has been submitted to < Weather, Climate, and Society >. Copyright in this Work may be transferred without further notice.

Ocean Island Basalts (OIBs) are generated by mantle plumes, with their geochemistry controlled by a combination of source composition, temperature, and thickness of overlying lithosphere. For example, OIBs erupting onto thicker, older oceanic lithosphere are expected to exhibit signatures indicative of higher average melting pressures. Here, we quantitatively investigate this relationship using a global dataset of Neogene and younger OIB compositions. Local lithospheric thicknesses are estimated using theoretical plate-cooling models and Bayes factors are applied to identify trends. Our findings provide compelling evidence for a correlation between OIB geochemistry and lithospheric thickness, with some variables SiO2,  Al2O3, FeO, Lu, Yb and λ2) showing linear trends that can be attributed to increasing average melting pressure, whereas others (λ0 and λ1, CaO) require a bi-linear fit with a change in gradient at ~55 km. Observed variations in highly incompatible elements are consistent with melt fractions that decrease with increasing lithospheric thickness, as expected. Nevertheless, at thicknesses beyond ~55 km, the implied melt fraction does not decrease as rapidly as suggested by theoretical expectations. This observation is robust across different lithospheric thickness estimates, including those derived from seismic constraints. We interpret this result as weak plumes failing to effectively thin overlying lithosphere and/or producing insufficient melt to erupt at the surface, in combination with a 'memory effect' of incomplete homogenisation of melts during their ascent. This view is supported by independent estimates of plume buoyancy flux, indicating that OIB magmatism on older lithosphere may be biased towards hotter plumes.

Reactive Transport Models (RTMs) are essential for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent RTMs integrate hydrological and biogeochemical interactions between land surface and subsurface. These emergent, watershed-scale RTMs are often spatially explicit and require large amount of data and extensive computational expertise. There is however a pressing need to create parsimonious models that require less data and are accessible to scientists with less computational background. Here we introduce BioRT-HBV 1.0 (hereafter BioRT), a watershed-scale, hydro-biogeochemical model that builds upon the widely used, bucket-type HBV model (Hydrologiska Bryåns Vattenavdelning), known for its simplicity and minimal data requirements. BioRT uses the conceptual structure and hydrology output of HBV to simulate processes including solute transport and biogeochemical reactions driven by reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. This paper presents the model structure and governing equations, demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, when constrained by data, BioRT can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous-to-measure subsurface, and their connections to observed solute export in streams and rivers. We posit that such parsimonious models increase model accessibility to users without in-depth computational training. It also can serve as an educational tool that promote pollination of ideas across different fields and foster a more diverse, equal, and inclusive user community.

Observations of far-ultraviolet (FUV) dayglow by the Global-scale Observations of Limb and Disk (GOLD) mission provide an opportunity for quantifying the global-scale response of the thermosphere to solar extreme-ultraviolet (EUV) variability and geomagnetic activity. Relative temperature changes can be measured by monitoring changes in the rotational structure observed in molecular nitrogen Lyman-Birge-Hopfield (LBH) band emissions. We present a new technique for deriving neutral temperatures from GOLD FUV observations using optimal estimation fits to spectra containing LBH band emissions. We provide an overview of the theoretical basis for the GOLD Level 2 neutral temperature algorithm. Effects on derived neutral temperatures from instrument artifacts and particle background are reviewed. We also discuss GOLD Level 1C DAY and Level 2 TDISK data products and present representative examples of each. We show that neutral temperatures vary with local time, exhibit a strong seasonal dependence, and correlate strongly with geomagnetic and solar activity. Finally, we present results from a preliminary data product validation that show good agreement with coincident GOLD exospheric temperatures and predictions from a global reference atmospheric model.

Convective Quasi-Equilibrium (CQE) is often adopted as a useful closure assumption to summarize the effects of unresolved convection on large-scale thermodynamics, while existing efforts to observationally validate CQE largely rely on specific spatial domains or sites rather than the source of CQE constraints—deep convection. This study employs a Lagrangian framework to investigate leading temperature perturbation patterns near deep convection, of which the centers are located by use of an ensemble of satellite measurements. Temperature perturbations near deep convection with high peak precipitation are rapidly adjusted towards the CQE structure within the two hours centered on peak precipitation. The top 1% precipitating deep convection constrains the neighboring free-tropospheric leading perturbations up to 8 degrees. Notable CQE validity beyond a 1-degree radius is observed when peak precipitation exceeds the 95th percentile. These findings suggest that only a small fraction of deep convection with extreme precipitation shapes tropical free-tropospheric temperature patterns dominantly.

Using model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). We introduce a new definition of ToE that accounts for observational limitations (e.g., data gaps, gridding, changes in instrumentation, retrieval algorithms, etc), and show the potential for significant corrections to achieve the same statistical confidence as would be afforded by omniscient knowledge. We also show how our method can inform future observational needs and observing systems design.

The sea-ice cover in the Barents and Kara Seas (BKS) displays pronounced interannual variability. Both atmospheric and oceanic drivers have been found to influence sea-ice variability, but their relative strength and regional importance remain under debate. Here, we use the Liang-Kleeman information flow method to quantify the causal influence of oceanic and atmospheric drivers on the annual sea-ice cover in the BKS in the Community Earth System Model large ensemble and reanalysis. We find that atmospheric drivers dominate in the northern part, ocean heat transport dominates in the central and northeastern part, and local sea-surface temperature dominates in the southern part. Furthermore, the large-scale atmospheric circulation over the Nordic Seas drives ocean heat transport into the Barents Sea, which then influences sea ice. Under future sea-ice retreat, the atmospheric drivers are expected to become more important.

Accurate fog prediction in densely urbanized cities poses a challenge due to the complex influence of urban morphology on meteorological conditions in the urban roughness sublayer. This study implemented a coupled WRF-Urban Asymmetric Convective Model (WRF-UACM) for Delhi, India, integrating explicit urban physics with Sentinel-updated USGS land-use and urban morphological parameters derived from the UT-GLOBUS dataset. When evaluated against the baseline Asymmetric Convective Model (WRF-BACM) using Winter Fog Experiment (WiFEX) data, WRF-UACM significantly improved urban meteorological variables like diurnal variation of 10-meter wind speed, 2-meter air temperature (T2), and 2-meter relative humidity (RH2) on a fog day. UACM also demonstrates improved accuracy in simulating temperature and a significant reduction in biases for RH2 and wind speed under clear sky conditions. UACM reproduced the nighttime urban heat island effect within the city, showing realistic diurnal heating and cooling patterns that are important for accurate fog onset and duration. UACM effectively predicts the onset, evolution, and dissipation of fog, aligning well with observed data and satellite imagery. Compared to WRF-BACM, WRF-UACM reduces the cold bias soon after the sunset, thus improving the fog onset error by ~4 hours. This study underscores the UACM’s potential in enhancing fog prediction, urging further exploration of various fog types and its application in operational settings, thus offering invaluable insights for preventive measures and mitigating disruptions in urban regions.