National Research Center (CO, USA)

The efficiency of marine cloud brightening in cooling Earth's surface temperature is investigated using an ensemble of simulations with the Community Earth System Model version 2 (CESM2). We employ a susceptibility‐based cloud seeding strategy, previously developed under the Community Climate System Model version 3 (CCSM3) to counteract the warming of CO2 doubling, in which we target the regions of the ocean most easily brightened, to determine what area extent will be required to induce 1°C cooling under SSP2‐4.5. The results indicate that cloud seeding over 5% of the ocean area is capable of achieving this goal in CESM2. Under this seeding scheme, cloud seeding is mainly deployed over lower latitudes which leads to a La Niña‐like pattern of response which is a major unintended consequence. Potential mechanisms behind such side effects are presented and discussed. The simulations also reveal that the 5% cloud seeding scheme induces an overall reduction in global precipitation, with an increase over land and a decrease over the ocean.

Microbial isolates from sugar crop processing facilities were tested for sensitivity to several industrial antimicrobial agents to determine optimal dosing. Hydritreat 2216 showed broad spectrum activity against all bacterial isolates as well as Saccharomyces cerevisiae. Sodium hypochlorite showed broad spectrum activity against all isolates, but at much higher effective concentrations. Hops BetaStab XL was effective against Gram-positive isolates. Magna Cide D minimal inhibitory concentration was lowest for S. cerevisiae and Zymomonas mobilis but was less effective against Gram-positive bacterial strains. Based on laboratory experiments, factory losses of sucrose from a single microbial species in the absence of antimicrobials could range from 0.13 to 0.52 kg sucrose per tonne of cane. Additional improvements in sugar yield are anticipated from agents with broad spectrum activity. A cost analysis was conducted considering sucrose savings due to antimicrobial application to provide estimates for break-even costs, which ranged from approximately $0.50 to$2.00 per L for a given antimicrobial agent.

The combination of wastewater monitoring and targeted clinical testing enabled detection and containment of SARS-CoV-2 outbreaks in university dormitories. This integrated approach contributed to smart resource allocation and lower positivity rates.

This paper investigates the day‐to‐day global tidal variability in the ionosphere/thermosphere system due to fluctuations in the strength of the northern hemisphere stratospheric polar vortex. Using COSMIC‐2 (Constellation Observing System for Meteorology, Ionosphere, and Climate‐2) Global Ionospheric Specification data, ionospheric tides are derived, with the Northern Annular Mode (NAM) index indicating polar vortex variability. The semidiurnal migrating solar tide shows the largest response, with relative electron density in the F‐region significantly higher (∼ ${\sim}$ 60%) under a weak vortex and lower (∼ ${\sim}$ 20%) under a strong vortex, correlated at −0.58 with the NAM index. The study compares solar/geomagnetic forcing and vortex impacts using SD‐WACCM‐X (Specified Dynamics Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension) model runs. Findings suggest tidal modulation of the E‐region dynamo as the coupling mechanism. Our study can potentially improve ionospheric space weather predictability because the NAM index can be known a few days in advance.

Hydroclimate and terrestrial hydrology greatly influence the local community, ecosystem, and economy in Alaska and Yukon River Basin. A high‐resolution simulation of the historical climate in Alaska can provide an important benchmark for climate change studies. In this study, we utilized the Regional Arctic System Model (RASM) and conducted coupled land‐atmosphere modeling for Alaska and Yukon River Basin at 4‐km grid spacing. In RASM, the land model was replaced with the Community Terrestrial Systems Model (CTSM) given its comprehensive process representations for cold regions. The microphysics schemes in the Weather Research and Forecast (WRF) atmospheric model were manually tuned for optimal model performance. This study aims to maintain good model performance for both hydroclimate and terrestrial hydrology, especially streamflow, which was rarely a priority in coupled models. Therefore, we implemented a strategy of iterative testing and optimization of CTSM. A multi‐decadal climate data set (1990–2021) was generated using RASM with optimized land parameters and manually tuned WRF microphysics. When evaluated against multiple observational data sets, this data set well captures the climate statistics and spatial distributions for five key weather variables and hydrologic fluxes, including precipitation, air temperature, snow fraction, evaporation‐to‐precipitation ratios, and streamflow. The simulated precipitation shows wet bias during the spring season and simulated air temperatures exhibit dampened seasonality with warm biases in winter and cold biases in summer. We used transfer entropy to investigate the discrepancy in connectivity of hydrologic and energy fluxes between the offline CTSM and coupled models, which contributed to their discrepancy in streamflow simulations.

Background Patients with transfemoral amputation experience socket-related problems and musculoskeletal overuse injuries, both of which are exacerbated by asymmetric joint loading and alignment. Bone-anchored limbs are a promising alternative to treat chronic socket-related problems by directly attaching the prosthesis to the residual limb through an osseointegrated implant; however, it remains unknown how changes in alignment facilitated through a bone-anchored limb relate to loading asymmetry. Questions/purposes What is the association between femur-pelvis alignment and hip loading asymmetry during walking before and 12 months after transfemoral bone-anchored limb implantation? Methods Between 2019 and 2022, we performed 66 bone-anchored limb implantation surgeries on 63 individuals with chronic socket-related problems. Of those, we considered those with unilateral transfemoral amputation as potentially eligible for this study. Based on that, 67% (42 of 63) were eligible, a further 55% (23 of 42) were excluded because they had incomplete datasets either at baseline (such as an inability to ambulate with a socket prosthesis) or did not complete the 12-month follow-up data collection. This resulted in 19 participants being included in this retrospective longitudinal analysis (9 males and 10 females, mean ± age 51 ± 11 years, mean BMI 28 ± 4 kg/m2). As part of standard clinical care, hip-to-ankle radiographs and motion capture data during overground walking were collected at two timepoints: 2 days before (preimplantation) and 12 months after bone-anchored limb implantation (postimplantation). Femur-pelvis skeletal alignment was measured from the radiographs (femoral abduction angle, residual femur length ratio, and pelvic obliquity). Symmetry indices of hip internal hip moment impulses (flexion/extension, abduction/adduction, internal/external rotation) were calculated from the motion capture data. Differences in alignment and internal joint moment impulse symmetry indices were compared across timepoints using paired t-tests with self-selecting walking speed as a covariate. Associations between skeletal alignment and hip moment impulse symmetry indices were computed at both timepoints using Spearman rank correlation with 5000 bootstrapped resamples. Results Twelve months after bone-anchored limb implantation, a comparison of preimplantation and postimplantation measurements showed reductions in the femoral abduction angle (-8° ± 10° versus 3° ± 4°, mean difference 11° [95% confidence interval (CI) 7° to 16°]; p < 0.001) and the residual femur length ratio (57% ± 15% versus 48% ± 11%, mean difference -9% [95% CI -12% to -5%]; p < 0.001). Additionally, a comparison of preimplantation and postimplantation calculations showed that the internal hip moment symmetry was improved in the sagittal and frontal planes (flexion symmetry index: 30 ± 23 versus 11 ± 19, mean symmetry index difference -19 [95% CI -31 to -6]; p = 0.03; extension symmetry index: 114 ± 70 versus 95 ± 63, mean symmetry index difference -19 [95% CI -42 to 4]; p = 0.03; abduction symmetry index: -54 ± 55 versus -41 ± 45, mean symmetry index difference 13 [95% CI -15 to 40]; p = 0.03). A larger length ratio of the residual limb relative to the intact limb was moderately associated with hip moment impulse symmetry in all three anatomical planes of motions both before and 12 months after transfemoral bone-anchored limb implantation, with strong associations observed between postimplantation hip extension and external rotation moment impulse symmetry (extension: ρ = -0.50 [95% CI -0.72 to -0.07]; p = 0.03; internal rotation: ρ = 0.64 [95% CI 0.25 to 0.85]; p = 0.004). Conclusion The associations between residual femur length and hip loading symmetry in patients with transfemoral bone-anchored limbs suggest that those with shorter residual limbs will demonstrate more asymmetric joint loading when using a bone-anchored limb. Thus, these findings could potentially be used to better inform targeted interventions based on residual limb morphology, including continued gait training in rehabilitation to promote joint loading symmetry and surgical considerations surrounding limb length changes in those with shorter limbs. Future studies might also examine joint loading symmetry during other activities of daily living after bone-anchored limb implantation to further expand knowledge of how residual limb anthropometry is associated musculoskeletal health after bone-anchored limb implantation. Level of Evidence Level III, therapeutic study.

Plain Language Summary Solar radiation ionizes the atmosphere to produce the ionosphere. However, ionospheric electron density in the midlatitude of the winter hemisphere has been observed to increase at night with the absence of photoionization, which is referred to as winter nighttime enhancement (WNE). Many studies have suggested that the plasma causing WNE comes from the overlying plasmasphere via downward diffusion, but so far the global distribution of ionospheric topside diffusive flux has not been systematically examined because it cannot be measured directly. In this study, the topside O+ ${O}^{+}$ diffusive flux is derived based on observational data. The flux is downward at night and varies with geographical location and local time. These characteristics are similar to those of WNE. Furthermore, the theoretical model Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) is used to conduct a modeling of WNE, with the upper boundary condition modified by incorporating the derived diffusive flux. WNE is well reproduced, providing direct evidence that downward plasma diffusion is the major mechanism of WNE. This study provides new insight into the physical processes in the nighttime ionosphere, and has implication for future development and improvement of ionospheric models.

Emerging high‐resolution global ocean climate models are expected to improve both hindcasts and forecasts of coastal sea level variability by better resolving ocean turbulence and other small‐scale phenomena. To examine this hypothesis, we compare annual to multidecadal coastal sea level variability over the 1993–2018 period, as observed by tide gauges and as simulated by two identically forced ocean models, at ∼1° ${\sim} 1{}^{\circ}$ (LR) and ∼0.1° ${\sim} 0.1{}^{\circ}$ (HR) horizontal resolution. Differences between HR and LR, and misfits with tide gauges, are spatially coherent at regional alongcoast scales. Resolution‐related improvements are largest in, and near, marginal seas. Near attached western boundary currents, sea level variance is several times greater in HR than LR, but correlations with observations may be reduced, due to intrinsic ocean variability. Globally, in HR simulations, intrinsic variability comprises from zero to over 80% of coastal sea level variance. Outside of eddy‐rich regions, simulated coastal sea level variability is generally damped relative to observations. We hypothesize that weak coastal variability is related to large‐scale, remotely forced, variability; in both HR and LR, tropical sea level variance is underestimated by ∼ ${\sim}$50% relative to satellite altimetric observations. Similar coastal dynamical regimes (e.g., attached western boundary currents) exhibit a consistent sensitivity to horizontal resolution, suggesting that these findings are generalizable to regions with limited coastal observations.

Crucial to the assessment of future water security is how the land model component of Earth System Models partition precipitation into evapotranspiration and runoff, and the sensitivity of this partitioning to climate. This sensitivity is not explicitly constrained in land models nor the model parameters important for this sensitivity identified. Here, we seek to understand parametric controls on runoff sensitivity to precipitation and temperature in a state‐of‐the‐science land model, the Community Land Model version 5 (CLM5). Process‐parameter interactions underlying these two climate sensitivities are investigated using the sophisticated variance‐based sensitivity analysis. This analysis focuses on three snow‐dominated basins in the Colorado River headwaters region, a prominent exemplar where land models display a wide disparity in runoff sensitivities. Runoff sensitivities are dominated by indirect or interaction effects between a few parameters of subsurface, snow, and plant processes. A focus on only one kind of parameters would therefore limit the ability to constrain the others. Surface runoff exhibits strong sensitivity to parameters of snow and subsurface processes. Constraining snow simulations would require explicit representation of the spatial variability across large elevation gradients. Subsurface runoff and soil evaporation exhibit very similar sensitivities. Model calibration against the subsurface runoff flux would therefore constrain soil evaporation. The push toward a mechanistic treatment of processes in CLM5 have dampened the sensitivity of parameters compared to earlier model versions. A focus on the sensitive parameters and processes identified here can help characterize and reduce uncertainty in water resource sensitivity to climate change.

Future flood risk assessment has primarily focused on heavy rainfall as the main driver, with the assumption that projected increases in extreme rain events will lead to subsequent flooding. However, the presence of and changes in vegetation have long been known to influence the relationship between rainfall and runoff. Here, we extract historical (1850–1880) and projected (2070–2100) daily extreme rainfall events, the corresponding runoff, and antecedent conditions simulated in a prominent large Earth system model ensemble to examine the shifting extreme rainfall and runoff relationship. Even with widespread projected increases in the magnitude (78% of the land surface) and number (72%) of extreme rainfall events, we find projected declines in event‐based runoff ratio (runoff/rainfall) for a majority (57%) of the Earth surface. Runoff ratio declines are linked with decreases in antecedent soil water driven by greater transpiration and canopy evaporation (both linked to vegetation greening) compared to areas with runoff ratio increases. Using a machine learning regression tree approach, we find that changes in canopy evaporation is the most important variable related to changes in antecedent soil water content in areas of decreased runoff ratios (with minimal changes in antecedent rainfall) while antecedent ground evaporation is the most important variable in areas of increased runoff ratios. Our results suggest that simulated interactions between vegetation greening, increasing evaporative demand, and antecedent soil drying are projected to diminish runoff associated with extreme rainfall events, with important implications for society.

Leveraging the unique perspective enabled by Global‐scale Observations of the Limb and Disk, we examined the characteristics of equinox transitions in the thermospheric column integrated ratio of atomic oxygen to molecular nitrogen (O/N2) in the Northern Hemisphere. We found that the timing of the O/N2 equinox transition from winter to summer or vice versa exhibits a progression with latitude, particularly, near spring equinox. The O/N2 equinox transition is far slower during spring compared to fall, leading to a remarkable seasonal asymmetry. Ionospheric Connection Explorer observed a prominent asymmetry in the summer‐to‐winter circulation in the middle to upper thermosphere, implying that the inter‐hemispheric circulation plays a crucial role in the O/N2 equinox transition. Additionally, since the wave‐driven meridional circulation in the lower thermosphere displays a seasonal asymmetry between the northward‐to‐southward and southward‐to‐northward transitions, we would anticipate that the O/N2 equinox transition is also influenced by the lower atmospheric forcing.

The African easterly jet (AEJ) and the West African Monsoon (WAM) can largely modulate high‐impact weather over Africa and the tropical Atlantic. How these features will change with a warming climate is just starting to be addressed due to global climate model limitations in resolving convection. We employ a novel regional setup for an atmospheric convection‐permitting model alongside the pseudo‐global warming (PGW) approach to address climate change impacts on the weather‐climate system of Africa during a short period of high‐impact weather. Our findings indicate that the AEJ and WAM may intensify in a future warming climate scenario. Precipitation is shown to increase over Guinea Highlands and Cameroon Mountains and shift southward due to a latitudinal expansion and increase of deep convection closer to the equator. This has relevant ramifications for the livelihood of communities that depend on water‐fed crops in tropical Africa.

Increasing the albedo of urban surfaces, through strategies like white roof installations, has emerged as a promising approach for urban climate adaptation. Yet, modeling these strategies on a large scale is limited by the use of static urban surface albedo representations in the Earth system models. In this study, we developed a new transient urban surface albedo scheme in the Community Earth System Model and evaluated evolving adaptation strategies under varying urban surface albedo configurations. Our simulations model a gradual increase in the urban surface albedo of roofs, impervious roads, and walls from 2015 to 2099 under the SSP3‐7.0 scenario. Results highlight the cooling effects of roof albedo modifications, which reduce the annual‐mean canopy urban heat island intensity from 0.8°C in 2015 to 0.2°C by 2099. Compared to high‐density and medium‐density urban areas, higher albedo configurations are more effective in cooling environments within tall building districts. Additionally, urban surface albedo changes lead to changes in building energy consumption, where high albedo results in more indoor heating usage in urban areas located beyond 30°N and 25°S. This scheme offers potential applications like simulating natural albedo variations across urban surfaces and enables the inclusion of other urban parameters, such as surface emissivity.

Recent observations show very near‐Earth reconnection (∼8–13RE) could efficiently power the ring current during the main phase of geomagnetic storms, but whether the recovery phase might be contributed remains unclear. During the recovery phase of the May 2024 major geomagnetic storm, intense auroral brightening and geomagnetic disturbances were observed at midnight, indicative of particle injections. Current wedges observed by mid‐latitude ground magnetometers around midnight suggest dipolarizing flux bundles (DFBs). The latitude of the auroral brightening was clearly lower than usual, suggesting near‐Earth reconnection (NERX) was closer to Earth than during substorms (∼20–30RE). GOES‐18 at midnight detected magnetic field and plasma signatures consistent with DFBs, following an extremely thin current sheet likely compressed by strong upstream dynamic pressure. These results indicate NERX could have been close enough for resultant DFBs to penetrate geosynchronous orbit and contribute to the ring current during the recovery phase. This scenario deserves further examination in future.

Precipitation efficiency (PE) relates cloud condensation to precipitation and thus reflects how much of the total atmospheric condensate reaches the surface as precipitation. Because the PE in convective storms is directly linked to their updraft and downdraft dynamics, it is a helpful metric to identify convective processes that influence precipitation. However, km‐scale model simulations do not properly resolve convective processes such as individual updrafts and entrainment, which raises the question if such simulations can accurately represent PE. Here, we present two methods to derive PE from standard model output because condensation is usually not available as an output variable. The first method estimates PE from the state variables vertical velocity, temperature, and pressure, whereas the second method estimates PE from ice water path (IWP) and precipitation. We validate the proposed methods with the explicitly calculated PE using a set of idealized Weather Research and Forecast model simulations of organized midlatitude convective storms at different horizontal grid spacings. We show that PE can be reliably estimated from state variables with an error of less than 5%, partly due to error cancellation effects. Additionally, PE can be simulated by km‐scale models within ∼15% accuracy compared to large‐eddy simulations (LESs). The IWP method is slightly less accurate with a stronger grid spacing dependency of the error, but since it is based on observable quantities, it allows for a validation of simulated PE with satellite observations. Finally, we analyze the grid spacing dependency of the climate change signal of PE and find that future decreases in PE in LESs are robustly captured by km‐scale models.

In the past decade, dynamical downscaling using “pseudo‐global‐warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)‐simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic‐scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large‐scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic‐scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

The Whole Atmosphere Community Climate Model with thermosphere‐ionosphere eXtension (WACCM‐X) is used to investigate the impact of the upward propagating migrating diurnal (DW1) and semidiurnal (SW2) tides on the seasonal variability in the ionosphere and thermosphere. In the lower thermosphere, the tides induce a westward acceleration that obtains maximum values of 10–20 ms−1 ${\text{ms}}^{-1}$ around solstice. The tidal dissipation also changes the meridional circulation and leads to a ∼ ${\sim}$ 5 K cooling of the lower thermosphere. These changes result in a decrease in atomic oxygen in the lower thermosphere that maximizes during local winter. In the lower thermosphere, the DW1 has a greater impact around December solstice, while the SW2 has a greater impact around June solstice. The DW1 and SW2 induced changes in the lower thermosphere composition lead to changes in the thermosphere column integrated atomic oxygen to molecular nitrogen ratio (O/N2 ${\mathrm{N}}_{2}$). This leads to a reduction in the thermosphere annual variation at middle to high latitudes. The DW1 and SW2 also reduce the thermosphere neutral mass density. In the ionosphere, the DW1 and SW2 decrease the zonal and diurnal mean total electron content by ∼ ${\sim}$ 20% globally, which is primarily attributed to the reduction in thermosphere O/N2 ${\mathrm{N}}_{2}$. The SW2 is found to have a greater influence on the low latitude ionosphere compared to the DW1 due to the SW2 having a greater impact on the equatorial electrodynamics. The results demonstrate that the upward propagating DW1 and SW2 both have significant effects on the ionosphere and thermosphere, including influencing the seasonal variability.

Atmospheric turbulence poses a major risk to aviation. Besides airframe damage, it can cause injuries of passengers and crew when encountered unexpectedly. The Singapore Airlines flight SQ321 was on its way from London to Singapore when severe turbulence was encountered over Myanmar on 21 May 2024. In this study, it is analyzed how well the turbulence was predicted by the turbulent eddy dissipation rate (EDR) forecast index of the ECMWF integrated forecasting system (IFS). It was found that ECMWF IFS was able to predict the convection and associated turbulence 24 hr in advance. The state‐of‐the‐art probabilistic EDR forecasts based on IFS ensemble members predicted probabilities for EDR >0.18 ${ >} 0.18$ m2/3 ${\mathrm{m}}^{2/3}$ s−1 ${\mathrm{s}}^{-1}$ between 10% and 40% over Myanmar with higher values for shorter lead time (8‐hr forecast). Individual members predicted EDR >0.3 ${ >} 0.3$ m2/3 ${\mathrm{m}}^{2/3}$ s−1 ${\mathrm{s}}^{-1}$. Knowledge about the characteristics of convection in the IFS forecasts is required to make proper use of the probabilities determined from the ensemble for such cases.

Climate change is a pressing global issue, potentially driven by LULC changes including deforestation, urbanization, and some other anthropogenic activities. The goal of our study was to evaluate the effectiveness of Ten Billion Tree Tsunami Project (TBTTP) in improving LULC and on regional climate change using machine learning. In this study, we utilized the Google Earth Engine platform, integrating multiple data sources such as Landsat 8 satellite imagery and Terra Climate datasets. A Random Forest machine learning classifier was employed to process the data, incorporating Landsat bands, vegetation indices (NDVI, EVI, NDWI), and environmental variables (precipitation, PDSI, slope). The impacts of TBTTP on Land Use Land Cover Changes (LULCC) and regional climate were analyzed for the pre-project (2015–2018) and post-project (2019–2023) periods. Our results indicated a significant 3.36% increase in forest area, demonstrating the effectiveness of coordinated reforestation projects in mitigating climate change and restoring ecological balance. Average annual LST rose by 0.137 °C during the pre-TBTTP period but fell by −0.0875 °C post-TBTTP. Some districts, such as Dera Ismail Khan, with the highest LST and least vegetation fractional area, clearly indicate a need for more forest land in that region. Post-TBTTP, precipitation increased by 15.33% and ET by 5.52%, indicates that the project successfully enhanced vegetation cover and forest health. These eco-friendly efforts have led to consistent forest growth, highlighting the need for better land use management, although more work is still required in districts like Bannu and Dera Ismail Khan. Therefore, the research findings provide a viable foundation to promote qualified reforestation projects such as TBTTP and also recognize the value of GEE in detecting long-term trends and promoting sustainable development.

Implicit time‐stepping for advection is applied locally in space and time where Courant numbers are large, but standard explicit time‐stepping is used for the remaining solution which is typically the majority. This adaptively implicit advection scheme facilitates efficient and robust integrations with long time‐steps while having negligible impact on the overall accuracy, and achieving monotonicity and local conservation on general meshes. A novel and important aspect for the efficiency of the approach is that only one iteration is needed each time the linear equation solver is called for solving the advection equation. The demonstration in this paper uses the second‐order Runge‐Kutta implicit/explicit time integration in combination with a second/third‐order finite‐volume spatial discretization and is tested using deformation flow tracer advection on the sphere and a fully compressible model for atmospheric flows. Tracers are advected over the poles of highly anisotropic latitude‐longitude grids with very large Courant numbers and on quasi‐uniform hexagonal and cubed‐sphere meshes with the same algorithm. Buoyant flow simulations with strong local updrafts also benefit from adaptively implicit advection. Stably stratified compressible flow simulations require a stable combination of implicit treatment of gravity and acoustic waves as well as advection in order to achieve long time‐steps.