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In this contribution we report the first systematic study of zircon U‐Pb geochronology and δ18O‐εHf(t) isotope geochemistry from 10 islands of the hot‐spot related Galapagos Archipelago. The data extracted from the zircons allow them to be grouped into three types: (a) young zircons (0–∼4 Ma) with εHf(t) (∼5–13) and δ18O (∼4–7) isotopic mantle signature with crystallization ages dating the islands, (b) zircons with εHf(t) (∼5–13) and δ18O (∼5–7) isotopic mantle signature (∼4–164 Ma) which are interpreted to date the time of plume activity below the islands (∼164 Ma is the minimum time of impingement of the plume below the lithosphere), and (c) very old zircons (∼213–3,000 Ma) with mostly continental (but also juvenile) εHf(t) (∼−28–8) and δ18O (∼5–11) isotopic values documenting potential contamination from a number of sources. The first two types with similar isotopic mantle signature define what we call the Galápagos Plume Array (GPA). Given lithospheric plate motion, this result implies that GPA zircon predating the Galápagos lithosphere (i.e., >14–164 Ma) formed and were stored at sublithospheric depths for extended periods of time. In order to explain these observations, we performed 2D and 3D thermo‐mechanical numerical experiments of plume‐lithosphere interaction which show that dynamic plume activity gives rise to complex asthenospheric flow patterns and results in distinct long‐lasting mantle domains beneath a moving lithosphere. This demonstrates that it is physically plausible that old plume‐derived zircons survive at asthenospheric depths below ocean islands. Key Points Our data define the Galápagos Plume Array defined by mantle εHf(t) and δ18O values in the range ∼0–164 Ma This finding allows dating back plume activity to, at least, early Middle Jurassic (∼164 Ma) Numerical experiments confirm it is plausible that old Plume‐derived zircons survive in the asthenosphere for extended periods of time

On 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extreme event through a set of sensitivity numerical experiments. The control simulation followed the operational configuration used daily by the Center for Weather and Climate Forecasting Studies of Minas Gerais (CEPreMG). Additional experiments tested the use of different microphysics schemes (WSM3, WSM6, WDM6), initial and boundary conditions (GFS, GDAS, ERA5), and surface datasets (sea surface temperature and soil moisture from ERA5 and GDAS). The model’s performance was evaluated by comparing the simulated variables with those from various datasets. We primarily focused on the representation of the spatial precipitation pattern, statistical metrics (bias, Pearson correlation, and Kling–Gupta Efficiency), and atmospheric instability indices (CAPE, K, and TT). The results showed that none of the simulations accurately captured the amount and spatial distribution of precipitation over the region, likely due to the complex topography and convective nature of the studied event. However, the WSM3 microphysics scheme and the use of ERA5 SST data provided slightly better representation of instability indices, although these configurations still underperformed in simulating the rainfall intensity. All simulations overestimated the instability indices compared to ERA5, although ERA5 itself may underestimate the convective environments. Despite some performance limitations, the sensitivity experiments provided valuable insights into the model’s behavior under different configurations for southeastern Brazil—particularly in a convective environment within mountainous terrain. However, further evaluation across multiple events is recommended.

The present study mainly focuses on the effect of temperature enhancement on local weather due to the heat emitted from anthropogenic sources with a numerical weather prediction model. In this study, anthropogenic heat (AH) flux is mainly considered as heat generated due to industrial action in the urban area. Angul district located between 20.41–21.80°N latitude and 84.55–85.30°E longitude in the Odisha state of India is chosen as the study region. In this location, a heavy rain event on 16 August 2008, and a light rain event on 22 March 2008 were identified. In the first part of this study, numerical simulations are performed using the mesoscale weather research and forecasting (WRF) model for both the rain events, based on which the near-surface rain rate is simulated. The simulated rainfall is compared against tropical rainfall measuring mission (TRMM) precipitation radar observations qualitatively for validation purposes. The comparative study throws a lot of insight based on different physics options available in the WRF model. The study found that the WRF double moment, 6-class microphysics scheme is better in capturing both the rain events in 2008. The TRMM validated WRF simulation now constitutes the control run against which comparisons for other cases are made. In the second part, a numerical experiment is performed to understand the effect of AH on local weather for the same region. The temperature at the surface level is perturbed by increasing it by 10 K near the industrial site and exponentially decreasing with a height up to the atmospheric boundary layer. The design of the numerical experiment is such that the sensible heat, latent heat and moisture parameters are affected by changing the temperature parameter alone. The result shows that the rainfall rate increases locally for both the events due to the increase in temperature at the industrial site. The rate of increase in heavy rain event is nearly twice whereas, in light rain, it was found to increase by 1.7 times. In the third and final part of the study, the flow pattern at the near-surface level is studied in and around the industrial zone, and the same is then compared with the perturbed case for both the rain events. In the perturbed cases, the difference in temperature in and around the region causes pressure differential leading to the formation of stronger wind.

The intensity of tropical cyclones (TCs) is controlled by their environmental conditions. In addition to the sea surface temperature, tropospheric temperature lapse rate and tropopause height are highly variable. This study investigates the sensitivity of the intensity and structure of TCs to environmental static stability with a fixed sea surface temperature by conducting a large ensemble of axisymmetric numerical experiments in which tropopause height and tropospheric temperature lapse rate are systematically changed based on the observed environmental properties for TCs that occurred in the western North Pacific. The results indicate that the intensity of the simulated TCs changes more sharply with the increase in the temperature lapse rate than with the increase in the tropopause height. The increases in the intensity of TCs are 1.3–1.9 m s−1 per 1% change of the lapse rate and 0.1–0.5 m s−1 per 1% change of the tropopause height. With the increase in the intensity of TCs, supergradient wind at low levels and double warm core structures are evident. Specifically, the formation of the warm core at the lower levels is closely tied with the intensification of TCs, and the temperature excess of the lower warm core becomes larger in higher lapse rate cases.

The results of numerical experiments on setting the NEMO model during its preparation for the assimilation of oceanographic data are presented. The modeling of ocean circulation and sea ice characteristics is performed with two different configurations of NEMO with a 1° horizontal resolution and with two versions of the sea ice model LIM2 and LIM3. The sensitivity of simulation results to the variations in the vertical resolution of the model grid and to the selection of the methods for describing ice processes is studied. It is shown that the increased vertical resolution and the calculations with several ice thickness gradations lead to a better agreement between model simulations and observations. The model configuration used for simulations with the corresponding setting parameters is suitable for its inclusion to the ocean data assimilation system.

An efficient numerical scheme based on the scalar auxiliary variable (SAV) and marker and cell (MAC) scheme is constructed for the Navier–Stokes equations. A particular feature of the scheme is that the nonlinear term is treated explicitly while being unconditionally energy stable. A rigorous error analysis is carried out to show that both velocity and pressure approximations are second-order accurate in time and space. Numerical experiments are presented to verify the theoretical results.

To get insights into the effects of sea ice change on the Arctic climate, a polar atmospheric regional climate model was used to perform two groups of numerical experiments with prescribed sea ice cover of typical mild and severe sea ice. In experiments within the same group, the lateral boundary conditions and initial values were kept the same. The prescribed sea ice concentration (SIC) and other fields for the lower boundary conditions were changed every six hours. 10-year integration was completed, and monthly mean results were saved for analysis in each experiment. It is shown that the changes in annual mean surface air temperature have close connections with that in SIC, and the maximum change of temperature surpasses 15 K. The effects of SIC changes on 850 hPa air temperature is also evident, with more significant changes in the group with reduced sea ice. The higher the height, the weaker the response in air temperature to SIC change. The annual mean SIC change creates the pattern of differences in annual mean sea level pressure. The degree of significance in pressure change is modulated by atmospheric stratification stability. In response to reduction/increase of sea ice, the intensity of polar vortex weakens/strengthens.

A 3D, two-time-level, σS-z-σB hybrid-coordinate Marine Science and Numerical Modeling numerical ocean circulation model (HyMOM) is developed in this paper. In HyMOM, the σ coordinate is employed in the surface and bottom regions, and the z coordinate is used in the intermediate layers. This method can overcome problems with vanishing surface cells and minimize the unwanted deviation in representing bottom topography. The connection between the σ and z layers vertically includes an expanded “ghost” method and the linear interpolation. The governing equations in the σS-z-σB hybrid coordinate based on the complete Reynolds-averaged Navier-Stokes equations are derived in detail. The two-level time staggered and Eulerian forward and backward schemes, which are of second-order of accuracy, are adopted for the temporal difference in internal and external mode, respectively. The computation of the baroclinic gradient force is tested in an analytic test problem; the errors for two methods in HyMOM, which are relatively large only in the bottom layers, are obviously smaller than those in the pure σ and z models in almost all of the vertical layers. A quasi-global climatologic numerical experiment is constructed to test the simulation performance of HyMOM. With the monthly mean Levitus climatology data as reference, the HyMOM can improve the simulating accuracy compared with its pure z or σ coordinate implementation.

Recent studies suggest that cold dark matter subhalos are hard to disrupt and almost all cases of subhalo disruption observed in numerical simulations are due to numerical effects. However, these findings primarily relied on idealized numerical experiments, which do not fully capture the realistic conditions of subhalo evolution within a hierarchical cosmological context. Based on the Aquarius simulations, we identify clear segregation in the population of surviving and disrupted subhalos, which corresponds to two distinct acquisition channels of subhalos. We find that all of the first-order subhalos accreted after redshift 2 survive to the present time without suffering from artificial disruption. On the other hand, most of the disrupted subhalos are sub-subhalos accreted at high redshift. Unlike the first-order subhalos, sub-subhalos experience preprocessing and many of them are accreted through major mergers at high redshift, resulting in very high mass loss rates. We confirm these high mass loss rates are physical through both numerical experiments and semianalytical modeling, thus supporting a physical origin for their rapid disappearance in the simulation. Even though we cannot verify whether these subhalos have fully disrupted or not, their extreme mass loss rates dictate that they can at most contribute a negligible fraction to the very low mass end of the subhalo mass function. We thus conclude that current state-of-the-art cosmological simulations have reliably resolved the subhalo population.

Realistic wind information is critical for accurate forecasts of landfalling hurricanes. In order to provide more realistic near-surface wind forecasts of hurricanes over coastal regions, high-resolution land–sea masks are considered. As a leading hurricane modeling system, the National Centers for Environmental Prediction (NCEP) Hurricane Weather Research Forecast (HWRF) system has been widely used in both operational and research environments for studying hurricanes in different basins. In this study, high-resolution land–sea mask datasets are introduced to the nested domain of HWRF, for the first time, as an attempt to improve hurricane wind forecasts. Four destructive North Atlantic hurricanes (Harvey and Irma in 2017; and Florence and Michael in 2018), which brought historic wind damage and storm surge along the Eastern Seaboard of the United States and Northeastern Gulf Coast, were selected to demonstrate the methodology of extending the capability to HWRF, due to the introduction of the high-resolution land–sea masks into the nested domains for the first time. A preliminary assessment of the numerical experiments with HWRF shows that the introduction of high-resolution land–sea masks into the nested domains produce significantly more accurate definitions of coastlines, land-use, and soil types. Furthermore, the high-resolution land–sea mask not only improves the quality of simulated wind information along the coast, but also improves the hurricane track, intensity, and storm-size predictions.