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Precipitation extremes intensify in most regions in climate model projections. Changes in vertical velocities contribute to the changes in intensity of precipitation extremes but remain poorly understood. Here, we find that midtropospheric vertical velocities in extratropical precipitation extremes strengthen overall in simulations of twenty-first-century climate change. For each extreme event, we solve the quasigeostrophic omega equation to decompose this strengthening into different physical contributions. We first consider a dry decomposition in which latent heating is treated as an external forcing of upward motion. Much of the positive contribution to upward motion from increased latent heating is offset by negative contributions from increases in dry static stability and changes in the horizontal length scale of vertical velocities. However, taking changes in latent heating as given is a limitation when the aim is to understand changes in precipitation, since latent heating and precipitation are closely linked. Therefore, we also perform a moist decomposition of the changes in vertical velocities in which latent heating is represented through a moist static stability. In the moist decomposition, changes in moist static stability play a key role and contributions from other factors such as changes in the depth of the upward motion increase in importance. While both dry and moist decompositions are self-consistent, the moist dynamical perspective has greater potential to give insights into the causes of the dynamical contributions to changes in precipitation extremes in different regions.

Following the interdecadal shift of El Niño–Southern Oscillation (ENSO) properties that occurred in 1976/77, another regime shift happened in 1999/2000 that featured a decrease of variability and an increase in ENSO frequency. Specifically, the frequency spectrum of Niño-3.4 sea surface temperature shifted from dominant variations at quasi-quadrennial (∼4 yr) periods during 1979–99 to weaker fluctuations at quasi-biennial (∼2 yr) periods during 2000–18. Also, the spectrum of warm water volume (WWV) index had almost no peak in 2000–18, implying a nearly white noise process. The regime shift was associated with an enhanced zonal gradient of the mean state, a west ward shift in the atmosphere–ocean coupling in the tropical Pacific, and an increase in the static stability of the troposphere. This shift had several important implications. The whitening of the subsurface ocean temperature led to a breakdown of the relationship between WWV and ENSO, reducing the efficacy of WWV as a key predictor for ENSO and thus leading to a decrease in ENSO prediction skill. Another consequence of the higher ENSO frequency after 1999/2000 was that the forecasted peak of sea surface temperature anomaly often lagged that observed by several months, and the lag increased with the lead time. The ENSO regime shift may have altered ENSO influences on extratropical climate. Thus, the regime shift of ENSO in 1999/2000 as well as the model default may account for the higher false alarm and lower skill in predicting ENSO since 1999/2000.

Based on the outputs of 30 models from Coupled Model Intercomparison Project Phase 5 (CMIP5), the fractional changes in the amplitude interannual variability ( σ ) for precipitation ( P ′) and vertical velocity ( ω ′) are assessed, and simple theoretical models are constructed to quantitatively understand the changes in σ ( P ′) and σ ( ω ′). Both RCP8.5 and RCP4.5 scenarios show similar results in term of the fractional change per degree of warming, with slightly lower inter-model uncertainty under RCP8.5. Based on the multi-model median, σ ( P ′) generally increases but σ ( ω ′) generally decreases under global warming but both are characterized by non-uniform spatial patterns. The σ ( P ′) decrease over subtropical subsidence regions but increase elsewhere, with a regional averaged value of 1.4% K − 1 over 20°S–50°N under RCP8.5. Diagnoses show that the mechanisms for the change in σ ( P ′) are different for climatological ascending and descending regions. Over ascending regions, the increase of mean state specific humidity contributes to a general increase of σ ( P ′) but the change of σ ( ω ′) dominates its spatial pattern and inter-model uncertainty. But over descending regions, the change of σ ( P ′) and its inter-model uncertainty are constrained by the change of mean state precipitation. The σ ( ω ′) is projected to be weakened almost everywhere except over equatorial Pacific, with a regional averaged fractional change of − 3.4% K − 1 at 500 hPa. The overall  reduction of σ ( ω ′) results from the increased mean state static stability, while the substantially increased σ ( ω ′) at the mid-upper troposphere over equatorial Pacific and the inter-model uncertainty of the changes in σ ( ω ′) are dominated by the change in the interannual variability of diabatic heating.

The ideal environment for extratropical cyclone development includes strong vertical shear of horizontal wind and low static stability in the atmosphere. Arctic sea ice loss enhances the upward flux of energy to the lower atmosphere, reducing static stability. This suggests that Arctic sea ice loss may facilitate more intense storms over the Arctic Ocean. However, prior research into this possibility has yielded mixed results with uncertain cause and effect. This work has been limited either in scope (focusing on a few case studies) or resolution (focusing on seasonal averages). In this study, we extend this body of research by comparing the intensification rate and maximum intensity of individual cyclones to local sea ice anomalies. We find robust evidence that reduced sea ice in winter (December—March) strengthens Arctic cyclones by enhancing the surface turbulent heat fluxes and lessening static stability while also strengthening vertical shear of horizontal wind. We find weaker evidence for this connection in spring (April—June). In both seasons, lower sea ice concentration also enhances cyclone-associated precipitation. Although reduced sea ice also weakens static stability in September/October (when sea ice loss has been especially acute), this does not translate to stronger storms because of coincident weakening of wind shear. Sea ice anomalies also have little or no connection to cyclone-associated precipitation in these months. Therefore, future sea ice reductions (e.g., related to delayed autumn freeze-up) will likely enhance Arctic cyclone intensification in winter and spring, but this relationship is sensitive to simultaneous connections between sea ice and wind shear.

The properties and structure of electrically stressed ionic liquid menisci experiencing ion evaporation are simulated using an electrohydrodynamic model with field-enhanced thermionic emission in steady state for an axially symmetric geometry. Solutions are explored as a function of the external background field, meniscus dimension, hydraulic impedance and liquid temperature. Statically stable solutions for emitting menisci are found to be constrained to a set of conditions: a minimum hydraulic impedance, a maximum current output and a narrow range of background fields that maximizes at menisci sizes of 0.5–3 ${\\rm \\mu}{\\rm m}$ in radius. Static stability is lost when the electric field adjacent to the electrode that holds the meniscus corresponds to an electric pressure that exceeds twice the surface tension stress of a sphere of the same size as the meniscus. Preliminary investigations suggest this limit to be universal, therefore, independent of most ionic liquid properties, reservoir pressure, hydraulic impedance or temperature and could explain the experimentally observed bifurcation of a steady ion source into two or more emission sites. Ohmic heating near the emission region increases the liquid temperature, which is found to be important to accurately describe stability boundaries. Temperature increase does not affect the current output when the hydraulic impedance is constant. This phenomenon is thought to be due to an improved interface charge relaxation enhanced by the higher electrical conductivity. Dissipated ohmic energy is mostly conducted to the electrode wall. The higher thermal diffusivity of the wall versus the liquid, allows the ion source to run in steady state without heating.

This research focuses on developing the optimal machine learning (ML) based predictive model for calculating the factor of safety ( FS MP ) for finite slopes using the Morgenstern-Price method of slices. The ML models utilize geometric and geotechnical parameters, including slope angle, friction angle, cohesion, slope height, unit weight, horizontal seismic acceleration coefficient, and the ratio of horizontal to vertical seismic acceleration coefficients. A comprehensive dataset of 19,128 data points is generated using in-house MATLAB code. These data points are trained with the ML models to learn the underlying correlations for the prediction of FS MP . Various ML predictive models, such as multiple linear regression, support vector regression, Gaussian process regression, random forest, extreme gradient boosting, and artificial neural networks, are considered for constructing the optimal model. The objective is to develop a tailored framework for arriving at the best-performing predictive model for replication of pseudo-static stability analysis of soil slopes in geotechnical engineering. Comparison of different data-driven models are also presented. The study also utilized interpretable machine learning models with Shapley values to mitigate the inherent “black box” nature of ML models. The study also establishes a physically interpretable error validation model to assess model predictions. The findings illustrate the effectiveness and precision of the Gaussian process regression (GPR) model, as evidenced by R 2 error metric values of 99.9% and 99.8% for the training and test sets, respectively. Further, the error metric for the artificial neural network (ANN) achieved values of 99.7% and 99.6% for the training and test sets, respectively. The GPR model offers conservative results over ANN, making it the preferred predictive model for safe FS MP predictions. It serves as an efficient estimation tool for field practitioners, can be integrated into smartphones and above all integrated into the performance function for uncertainty quantification in the otherwise computationally expensive Monte Carlo simulations. Design charts are also generated using the selected optimal model for depicting the generalizability of this model, enabling geotechnical engineers to determine FS MP without complex calculations. This research showcases the potential of ML techniques for complex geotechnical problems, advancing conventional slope stability analysis and opening avenues for their practical and reliable use in geotechnical engineering.

The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics, nutrient loads, meteorology) as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal timescales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic–ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37 year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an optimization algorithm to improve the fit between observed and simulated data. We calculated stability indices (Schmidt stability, Birgean work, stored internal heat), identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the interannual variation in summer anoxia, we applied a random-forest classifier and multiple linear regressions to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production). Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50–60 d. The summer heat budget, the timing of thermal stratification, and the gross primary production in the epilimnion prior to summer stratification were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. Interannual variability in anoxia was largely driven by physical factors: earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. A measured step change upward in summer anoxia in 2010 was unexplained by the GLM-AED2 model. Although the cause remains unknown, possible factors include invasion by the predacious zooplankton Bythotrephes longimanus. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region.

Influence of the stratospheric quasi-biennial oscillation (QBO) on the Madden–Julian oscillation (MJO) and its statistical significance are examined for austral summer (DJF) in neutral ENSO events during 1979–2013. The amplitude of the OLR-based MJO index (OMI) is typically larger in the easterly phase of the QBO at 50 hPa (E-QBO phase) than in the westerly (W-QBO) phase. Daily composite analyses are performed by focusing on phase 4 of the OMI, when the active convective system is located over the eastern Indian Ocean through the Maritime Continent. The composite OLR anomaly shows a larger negative value and slower eastward propagation with a prolonged period of active convection in the E-QBO phase than in the W-QBO phase. Statistically significant differences of the MJO activities between the QBO phases also exist with dynamical consistency in the divergence of horizontal wind, the vertical wind, the moisture, the precipitation, and the 100-hPa temperature. A conditional sampling analysis is also performed by focusing on the most active convective region for each day, irrespective of the MJO amplitude and phase. Composite vertical profiles of the conditionally sampled data over the most active convective region reveal lower temperature and static stability around the tropopause in the E-QBO phase than in the W-QBO phase, which indicates more favorable conditions for developing deep convection. This feature is more prominent and extends into lower levels in the upper troposphere over the most active convective region than other tropical regions. Composite longitude–height sections show similar features of the large-scale convective system associated with the MJO, including a vertically propagating Kelvin response.

An intermediate complexity general circulation model is used to isolate the effect of vertical resolution and gravity wave parameterization on the simulated monthly quasi‐biennial oscillation (QBO)‐tropical precipitation linkage. For low vertical resolution, the model is able to simulate QBO in the lowermost stratosphere, and its impact on the tropical upper troposphere‐lower stratosphere (UTLS) and precipitation, only after optimizing the gravity wave parameterization. For increased vertical resolution, the impact of the QBO on UTLS static stability is stronger. However, the tropical precipitation response is qualitatively different from that at low resolution. The precipitation response contains a substantial zonal and meridional structure that differs qualitatively between low and high vertical resolution. Two factors appear to explain this difference: the meridional width of the QBO, and the presence of a warmpool in the West Pacific. These results have implications for the ability of comprehensive models to simulate a tropical response to the QBO.

Accurate measurement of vertical air motion is essential for improving weather forecasts and climate models. VHF stratosphere–troposphere radars, like the 46.5 MHz Middle and Upper atmosphere (MU) radar at the Shigaraki MU Observatory in Japan, are possible tools for quantifying vertical air velocities in the tropo-stratosphere. This study examines vertical air velocity measurements taken over 38 years (1987–2024) using the MU radar at altitudes ranging from ~ 2 to ~ 20 km. The analysis uses three methods: direct vertical measurements ( W ), and calculations derived from two pairs of oblique beams ( WNS and WEW ), each oriented 10 degrees off zenith in the North–South and East–West directions. Statistical parameters, such as mean, standard deviation, skewness, kurtosis, percentiles, and Gini coefficient, were computed. Except for the average vertical velocity, the higher-order moments show consistent patterns across all three estimates and altitudes. Below 10 km, the profiles of W,WNS , and WEW show minimal differences, whereas above 10 km, slight variations appear, potentially related to increased static stability. A notable kurtosis dependence on horizontal wind speed confirms data integrity. Numerical simulations, based on the observed characteristics of W frequency spectra from MU radar, suggest that this relationship is due to filtering effects from horizontal wind advection, rather than gravity wave properties. This effect, however, does not align with the expected properties of gravity waves.