Climate models often face challenges in accurately simulating the daily precipitation cycle over tropical land areas, particularly in the Amazon. One contributing factor may be the incomplete representation of the diurnal evolution of shallow cumulus (ShCu) clouds. This study aims to enhance the understanding of the diurnal cycles of ShCu clouds—from formation to maturation and dissipation—over the central Amazon (CAMZ). Using observational data from the Green Ocean Amazon 2014 (GoAmazon) campaign and large-eddy simulation (LES) modeling, we analyzed the diurnal cycle of six selected pure ShCu cases and their composite behavior. Our results reveal a well-defined cycle, with cloud formation occurring between 10-11 local time (LT), maturity from 13-15 LT, and dissipation by 17-18 LT. The vertical extent of the liquid- water mixing ratio, and the intensity of updraft mass flux were closely associated with increases in turbulent kinetic energy (TKE), enhanced buoyancy flux within the cloud layer, and reduced large-scale subsidence. We further analyzed the diurnal cycles of convective available potential energy (CAPE), convective inhibition (CIN), the Bowen ratio (BR), and vertically integrated TKE in the mixed layer (ITKE-ML), exploring their relationships with cloud base mass flux (Mb) and cloud depth across six ShCu cases. ITKE-ML and Mb exhibited similar diurnal trends, peaking at approximately 14-15 LT. However, no consistent relationships were found between CAPE (or BR) and Mb. Similarly, comparisons of cloud depth with CAPE, BR, ITKE-ML, CIN, and Mb revealed no clear relationships. Smaller ShCu clouds were sometimes linked to higher CAPE and lower CIN. It is important to emphasize that these findings are preliminary and based on a limited sample of ShCu cases. Further research involving an expanded dataset and more detailed analyses of the TKE budget and synoptic conditions is necessary. Such efforts can yield a more comprehensive understanding of the factors influencing ShCu clouds’ vertical development.

An increasing number of legacy petroleum wells are reported to suffer integrity failure, releasing methane (CH4) into the subsurface and atmosphere. Subsurface released methane is reactively transported towards ground surface with a portion converted to carbon dioxide by soil microbes. Currently, the extent to which fugitive CH4 oxidation occurs, including microbial taxa responsible and controlling parameters are poorly understood. Here, we examined fugitive CH4 leakage at a legacy well in the Montney region of British Columbia, Canada and find up to 90% is oxidised at rates as high as 230 g of CH4 /m2 of soils/day during summer. Meanwhile, a profound difference in microbiome between soils at the wellhead and background was observed, while modelling suggests that prevailing seasonal temperature will moderate CH4 oxidation extent. Overall, we find that filtration of fugitive CH4 through natural soils can significantly reduce emissions of CH4 and mitigate climate impacts from such sources

This work explores the density-driven overturning circulation of the ocean using a process-oriented three-dimensional hydrodynamic model with a free sea surface. As expected, dense-water formation in polar regions creates a deep western boundary current (DWBC) spreading southward ward along the continental slope. Near the equator, the DWBC releases its water eastward into the ambient ocean to form a large upwelling zone. This upwelling is coupled with a slow westward surface recirculation feeding into a swift surface return flow along the western boundary that closes the mass budget. This recirculation pattern, which is fundamentally different to the Stommel-Arons model, is a consequence of geostrophic adjustment to anomalies of the surface pressure field that form under the influence of both coastal and equatorial Kelvin waves and Rossby waves. Based on the findings, the author presents a revised model of the ocean’s meridional overturning circulation to supersede earlier, incorrect suggestions.

A document by Ray Nassar. Click on the document to view its contents.

• Earth system models (ESMs) have many tunable parameters that are difficult to estimate and weakly constrained by theory. • Kalman filter-based approaches are attractive options, but existing implementations require expensive offline hyperparameter selection. • We propose a new Kalman filter algorithm that estimates model parameters and its hyperparameter simultaneously.

 Wide convective cell depth responds most to available instability, while narrow cell depth responds most to mid-level relative humidity.  Entrainment-driven reduction of buoyancy decreases as updraft width increases, causing disparate narrow and wide cell depth responses.  A convection-permitting simulation with 3-km horizontal grid spacing generally reproduces observed relationships.

A document by Mike Coughlan. Click on the document to view its contents.

• Time-frequency analysis of the the total solar irradiance (TSI) dataset recoreded by the FY3E/JTSIM/DARA • DARA observations (in WRR scale) on average higher than measurements recorded with other instruments: ∼ 2.2 Wm −2 (VIRGO/PMO6), ∼ 1.2 Wm −2 (TIM/TSIS-1) and ∼ 1 Wm −2 (SIAR). • Analysis of the integration of the new JTSIM-DARA dataset into the 43 year long TSI composite time series

Hydrologic processes in snowmelt dominated systems are traditionally measured and understood at the point scale. However, snowmelt, sublimation, and snowfall rates exhibit significant spatial variability across larger landscapes. These variations are influenced by local atmospheric and terrain characteristics, which control the deviations between small-scale measurements and areally averaged responses to spatially heterogeneous mass and energy inputs. Appropriate upscaling relations are needed to translate small-scale descriptions of snow processes into constitutive relationships that are applicable at larger scales. As a proof of concept, this study examines the temporal and spatial variability of sublimation and snowmelt fluxes in a drainage basin in the Canadian Rockies using machine learning methods. Raven, a hydrological model, generates high-resolution fluxes and state variables used to train a random forest algorithm. The random forest (RF) algorithm is then applied to estimate coarse resolution fluxes. This study involves estimating spatially averaged results from discretized fine-scaled models without explicit knowledge of detailed local response, both with and without low-order statistics of state (e.g., the standard deviation of snow water equivalent). A series of experiments are used to verify that the upscaling methodology can successfully represent the impact of heterogeneity within the system. Spatially averaged forcing estimated from the scale-appropriate machine learning model is then incorporated into a mass balance equation at a coarse resolution to demonstrate the efficacy of this upscaling methodology.

Predicting the occurrence of coherent blocking structures in synoptic weather systems remains a challenging problem that has taxed the numerical weather prediction community for decades. The underlying factor behind this difficulty is the so-called "loss of hyperbolicity" known to be linked with the alignment of dynamical vectors characterizing the growth and decay of flow instabilities. We introduce measures that utilize the close link between hyperbolicity, the alignment of Lyapunov vectors, and their associated growth and decay rates to characterize the dynamics of persistent synoptic events in the mid-troposphere of the Southern Hemisphere. These measures reveal a general loss of hyperbolicity that typically occurs during onset and decay of a given event, and a gain of hyperbolicity during the persistent mature phase. Facilitating this analysis in a high-dimensional system first requires the extraction of the relevant observed coherent structures, and the generation of a reduced-order model for constructing the tangent space necessary for dynamical analysis. We achieve this through the combination of principal component analysis and a non-parametric, temporally regularized, vector auto-regressive clustering method. Analysis of the primary blocking sectors reveals hyperbolic dynamics that are consistent between metastable states and whose dynamics span the tangent subspace defined by the leading physical modes. We show that these diverse synoptic features are manifest via common spatially dependent attractors as determined by tangent space dynamics. Our results are not only important for dynamical approaches applicable to high-dimensional multi-scale systems, but are also relevant for the development of modern operational ensemble numerical weather prediction systems.

The martian tropical water ice spatial and temporal distribution was characterized using impact crater ejecta type, location, size, and age in one of two epochs, <=3.4 Ga and $>3.4 Ga, using statistical models designed for spatial and temporal correlation structures. The indicator thought to identify the presence of ice is craters with layered ejecta, while the indicator thought to identify no ice is craters with radial ejecta. These indicators imply the location (longitude and latitude) and, potentially, depth (crater diameter as a proxy) of ice, and when the ice was present. The spatial and temporal distribution of layered ejecta versus radial ejecta may inform on the geography and evolution of ice. A statistical spatial point analysis was conducted on a 54-sample data set (craters with diameters 2.77 km to 10.00 km) for an equatorial region (0o to -30o S, and 10o E to 340o W. The analysis shows there is insufficient evidence to support a non-random spatial and temporal distribution of tropical ice.

In Distributed Acoustic Sensing (DAS), a fiber-optic cable is used as a distributed seismic sensor, with channels representing successive short sections of the fiber, spaced at defined intervals along the 1D fiber axis. Typically, the positions of these channel are assumed to be known and to coincide with the cable´s position. In reality, a fiber-optic cable contains many fibers that are not perfectly straight and are thus longer than the cable itself. Additionally, the cable may feature some degree of curvature even though it was deployed with the intention of a straight line. Consequently, the real channel spacing differs from the theoretical one and may vary alongside the cable axis. On land usually a tap test is carried out before the start of the DAS acquisition to determine the exact channel locations. DAS with marine horizontal cables has recently been used for various offshore applications including seismic imaging. To avoid errors in the seismic image, a precise receiver location is required. For many marine fiber optic cables, the position is known to some extent but may be subject to inaccuracies. In this paper, we propose a traveltime-based inversion workflow to determine a more accurate fiber position on the seafloor. Moreover, we show that we can resolve an unknown time shift, between the acquisition and the recording system, in addition to the fiber position.

Incoherent scatter radar measurements rely on the application of a priori parameters from empirical models to initialize the analysis of incoherent scatter spectra. Currently, there is a need to transform ionosphere models to enable reliable space weather predictions through data assimilation of observations. Very often the data assimilation relies on electron densities measured with incoherent scatter radars. Erroneous a priori parameters would lead to the assimilation of flawed and physically inconsistent data depending on the ionospheric model. It might therefore be beneficial to assimilate the entire radar spectrum and infer the plasma parameters from the assimilated spectrum by applying the a priori parameters as given by the model. To assess the potential assimilation of incoherent scatter spectra into models, we investigate synthetic EISCAT incoherent scatter spectra calculated from TIE-GCM results. At F1 region altitudes, the atomic-to-molecular ion ratio strongly affects the shape of the incoherent scatter spectrum. Since the vertical profiles of the atomic-to-molecular ion ratio are distinctly different in the EISCAT a priori model and TIE-GCM, the assimilation of single plasma parameters induces additional, unbalanced forces into the model. A similar problem arises in the E region due to different ion-neutral collision frequency profiles. These problems could be solved by assimilation of the entire incoherent scatter spectrum followed by an in-model evaluation of the plasma parameters. We demonstrate the effect of different a priori profiles on the spectral analysis and how the derived plasma parameters are changing when leveraging a more comprehensive approach of using forward modeling with TIE-GCM.

Subsurface characterization remains a pivotal challenge in geology, hindered by the inherent complexity and nonstationarity of geological processes. Conventional geostatistical methods, relying on two-point statistics and kriging, often fall short in capturing the spatial heterogeneity and transitional dynamics of subsurface materials. This study introduces a novel three-dimensional lithofacies characterization method that incorporates manifold embedding and a transition probability-based spatial estimation technique, significantly deviating from conventional approaches. The proposed method addresses existing limitations by providing a robust framework for capturing the nonstationary nature of geological processes, utilizing data such as pole-to-plane orientations and lithological transitions for structural and juxtapositional information. Through hypothetical scenarios and simulations, the performance of the proposed method is demonstrated, showcasing its capability to model complex geological formations and accurately estimate subsurface characteristics. The study underscores the importance of considering nonstationarity in geological estimations and highlights the potential impact on hydrogeological modeling. Accurate lithological distribution estimation is crucial for reliable groundwater flow and solute transport modeling. This study advances the methodological toolkit for subsurface characterization and paves the way for future research, including empirical validation with real-world data and exploration of the method's applicability in early-stage site characterization, where data scarcity and quality are pressing concerns.

Super magnetic storm occurred on October 10, 2024, and a super substorm occurred at the beginning of the storm just after the shock arrival at 1520 UT. As a result, red aurora were photographed at multiple points over wide region of Japan from 1700 UT. A new Bayesian analysis enables us to estimate the time variation of the most probable height and latitude of the red aurora based on the citizen science dataset in combination of POES/MetOp satellite datasets of electron precipitation boundary. We found that the top height of red aurora extended to ~850 km and the red aurora shifted toward low latitude according to the storm development. The ultra-high altitude of the red aurora can be evidence of rapid atmospheric heating and the atmospheric expansion.

Magnetic reconnection, an essential mechanism in plasma physics that changes magnetic topology and energizes charged particles, plays a vital role in the dynamic processes of the Jovian magnetosphere. The traditional Vasyliūnas cycle only considers the effect of magnetic reconnection at the nightside magnetodisk. Recently, magnetic reconnection has been identified at the dayside magnetodisk in Saturn's magnetosphere and can impact dayside auroral processes. In this study, we provide the first evidence that the dayside magnetodisk reconnection can also occur at Jupiter. Using data from the Galileo and Voyager 2 spacecraft, we have identified 18 dayside reconnection events with radial distances in the range of 30–60 Jupiter radii (RJ). We analyzed the particle (electron and ion) flux, energy spectra, and characteristic energy of these dayside events and compared them to the nightside events. The statistical results show that the energy spectra and characteristic energy of electrons/ions in dayside and nightside magnetic reconnection events are comparable. On average, the characteristic energy of ions on the dayside is higher than that on the nightside. Based on the limited data set, we speculate that the occurrence rate of dayside magnetodisk reconnection should be significant. The dayside Jovian magnetodisk reconnection seems to have a comparable effect on providing energetic particles as that at nightside and to be one of the key processes driving dynamics within the Jovian magnetosphere.

Extreme climate events (ECEs) like heavy rainfall and heatwaves significantly impact society, and climate change is altering their frequency. Generalised Extreme Value (GEV) distributions help quantify these ECEs and guide human system design (e.g., return value of extreme wind gust sets construction codes at specific locations). We train a machine learning (ML) model using GEV distributions to determine the sample size required to estimate return values with specific uncertainties. For ECEs like heatwaves (with negative GEV shape parameters), fewer samples are needed to estimate the return value with specific uncertainty than rainfall extremes (positive shape parameters). For the heatwave example, a sample size of more than 20 times the annual recurrence interval is typically required to estimate the return value to ±10% uncertainty. A 1-in-20-year heatwave requires 400 samples, equating to 20 different 20-year simulations. Achieving such quantities will require extensive climate downscaling efforts, potentially aided by ML-based downscaling methods.

Local vortex-structured auroral spiral and a large-scale transpolar arc (TPA) were contemporaneously observed by the Polar ultraviolet imager (UVI), when a substorm almost recovered. The TPA grew along the dawnside auroral oval from the nightside to the dayside (oval-aligned TPA), and a chain of multiple auroral spots and spiral were located azimuthally near the poleward edge of the nightside auroral oval. Contemporaneous appearances of the TPA and the auroral spiral can be seen after the spiral appeared alone. Polar also detected the oval-aligned TPA and another dawnside TPA with the nightside end distorted toward the premidnight sector (J-shaped TPA) before and after the spiral’s formation, respectively. To examine these associated magnetotail structures, we performed global magnetohydrodynamic (MHD) simulations, based on two different types of code, BAT-S-RUS and improved REPPU, and examined how the field-aligned current (FAC) profiles varied in association with changes of the auroral form to TPA and/or auroral spiral. Global MHD simulations with the two different types of code can reproduce the TPAs and the associated FAC structures in the magnetotail. The auroral spiral and its nightside FAC profile, however, were not formed in both simulations, suggesting that its formation process cannot be treated within an MHD framework but is closely related to some kinetic process. When the J-shaped TPA and the auroral spiral contemporaneously appeared, the two MHD simulations could not reproduce the TPA, spiral and their associated magnetotail FAC structures, also advocating that a kinetic effect related to the spiral formation might prevent the TPA occurrence.