The solar radio flux at 10.7 cm, known as F10.7, is a critical operational space weather index. However, without a clear backup, any interruption to the service can result in substantial errors in model outputs. In this paper we show the impact of one such outage in March 2022 and present a number of alternative solutions for any future outages. The approach resulting in the smallest reconstruction error of F10.7 uses the solar radio flux observations at alternative wavelengths (the best giving a percentage error of 3.1%). Alternatively, use of Sunspot Number, a regular, robust alternative observation, results in a mean percentage error of 8.2% and is also a reliable fallback solution. Additionally, analysis of the error on the use of the conversion between the 12-month rolling sunspot number (R12) and its conversion to F10.7 as used by the IRI is included.
The influences of subauroral polarization streams (SAPS) on storm-enhanced density (SED) and tongue of ionization (TOI), an important topic in the field of magnetosphere-ionosphere-thermosphere coupling, however, remain undetermined. The Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) with/without an empirical SAPS model has been used to investigate the impacts of SAPS on SED and TOI. The modeled TEC and ion drift velocities agree reasonably well with the observations of GNSS and DMSP satellites on 17 March 2013. The TIEGCM simulations show that SAPS can significantly affect the electron density of SED and TOI depending on the relative location of SAPS and SED. SAPS reduces the electron density at the eastward edge of SED where they are overlapped, and enhances SED at its westward edge. A term-by-term analysis of the O+ ion continuity equation in the F-region shows that the electron density depletions at the eastward edge of SED are mainly due to increased local plasma loss rates because of SAPS elevated plasma-neutral temperatures and O/N2 reduction because of thermosphere upwelling. The electron density enhancements in the westward edge of SED are mainly due to SAPS-induced westward plasma E×B transports and O/N2 increment because of thermospheric downwelling. Moreover, SAPS-induced electron depletions in the throat region weaken TOI as plasmas undergo anti-sunward convection into the polar cap.
This study finds that sea level height in Arctic marginal sea in melting season enters an accelerated rise period since the beginning of the 21st century. It is found that precipitation is the dominant factor affecting the change of sea level height in melting season in 1979-1998. Polar vortex and Arctic Oscillation become dominant factors since the accelerated rise period, especially in Norwegian Sea, Barents Sea and Kara Sea. Main reason for the change of dominant factors may be that a clockwise surface wind anomaly in strong polar vortex year became more significant in these regions during the accelerated rise period. The strong wind anomaly affects distribution of sea water through processes such as surface wind stress. Specifically, a polar vortex-wind-sea level height mechanism is strengthened, thus affecting the change of sea level height. CESM2 future scenario simulation results show that sea level height will rise by 0.4m by 2100.
We performed wind tunnel studies of sand–bed collisions with natural sand particles and found an impact angle of 10.5o over a loose bed, and calculated the critical impact velocity (vic ≅ 1.2027 m s-1). The number of splashing particles (Ns) increased linearly with vi, but the coefficient of restitution CoR decreased linearly with vi. The momentum lost through frictional processes αlost was insensitive to vi, with a value of 0.2466. The mean splash velocity increased with vi for vi < 7 m s-1, and gradually reached its maximum value (0.7534 m s-1) at vi = 7 m s-1, whereas decreased slowly with vi for vi> 7 m s-1 and gradually approached a constant (0.6137 m s-1). In addition, we developed a probability distribution model for liftoff velocity. Our results emphasize the crucial role of the impact angle and have significant consequences for modeling sand–bed collisions in a natural environment.
Atmospheric aerosol radiative effects regulate surface air pollution (O3 and PM2.5) via both the aerosol–photolysis effect (APE) and the aerosol–radiation feedback (ARF) on meteorology. Here, we elucidate the roles of APE and ARF on surface O3 and PM2.5 in the heavily polluted megacity, Delhi, India by using a regional model (WRF-Chem) with constraints from available and limited observation. While APE reduces surface O3 (by 6%) and PM2.5 concentrations (by 2.4% via impeding the secondary aerosol formations), ARF contributes to a 17.5% and 2.5% increase in surface PM2.5 and O3, respectively. The synergistic APE and ARF impact contributed to ~1 % of the total concentrations of O3 and PM2.5. Hence, the reduction of PM2.5 may lead to O3 escalation due to weakened APE. Sensitivity experiments indicate the need and effectiveness of reducing VOC emission for the co-benefits of mitigating both O3 and PM2.5 concentrations in Delhi.
In 2021, the World Health Organization (WHO) ranked Nigeria among the most polluted nations in the world, an indication of a deteriorating air quality, especially in the major urban areas of the country, which might pose adverse human health impacts. In this study, the Integrated Source Apportionment Method (ISAM) tool in the Community Multiscale Air Quality (CMAQ) model (CMAQ-ISAM) was employed to quantify the contributions of eight emissions sectors to fine particulate matter (PM2.5) and its major components in Lagos during a prolonged severe atmospheric pollution episode (APE) in January 2021. The influence of meteorological conditions on the formation and dispersion of PM2.5 during the APE was also elucidated. Spatially, elevated PM2.5 concentrations were found in the northwestern region of Lagos, an urban area with larger anthropogenic emissions. Residential and industry were the two major sources of PM2.5. Residential contributed the most to total PM2.5 (~40 μg/m3), followed by industry (~20 μg/m3). High concentrations of secondary inorganic aerosols (SIA) at the northwest and upper northern areas of Lagos were majorly attributed to residential and industry sectors. In addition, sulfate accounted for the largest fraction of PM2.5, with residential, industry, and energy being its major sources. Residential, industry, and on-road sectors dominated the contributions to nitrate, while residential and industry were the major contributors to ammonium. Furthermore, the elevated PM2.5 concentrations during the APE were greatly enhanced by unfavorable meteorological conditions. This study provides insights for designing effective emissions control strategies to mitigate future severe PM2.5 pollution episode in Lagos.
Rossby Wave packets (RWPs) are atmospheric perturbations located at upper levels in mid-latitudes which, in certain cases, terminate in Rossby Wave Breaking (RWB) events. When sufficiently persistent and spatially extended, these RWB events are synoptically identical to atmospheric blockings, which are linked to heatwaves and droughts. Thus, studying RWB events after RWPs propagation and their link with blocking is key to enhance extreme weather events detection 10-30 days in advance. Hence, here we assess (i) the occurrence of RWB events after the propagation of RWPs, (ii) whether long-lived RWPs (RWPs with a lifespan above 8 days, or LLRWPs) are linked to large-scale RWB events that could form a blocking event, and (iii) the proportion of blocking situations that occur near RWB events. To do so, we applied a tracking algorithm to detect RWPs in the Southern Hemisphere during summertime between 1979-2020, developed a wave breaking algorithm to identify RWB events, and searched for blocking events with different intensities. Results show that LLRWPs and the other RWPs displayed large-scale RWB events around 40% of the time, and most RWB events in both distributions last around 1-2 days, which is not long enough to identify them as blocking situations. Nearly 17% of blockings have a RWB event nearby, but barely 5% of blockings are linked to RWPs, suggesting that propagating RWPs are not strongly linked to blocking development. Lastly, large-scale RWB events associated with RWPs that lasted less than 8 days are influenced by the Southern Annular Mode and El Niño-Southern Oscillation.
This study derives radiatively-active hydrometeors frequencies (HFs) from CloudSat-CALIPSO satellite data to evaluate cloud fraction in present-day simulations by CMIP5 models. Most CMIP5 models do not consider precipitating and/or convective hydrometeors but CESM1-CAM5 in CMIP5 has diagnostic snow and CESM2-CAM6 in CMIP6 has prognostic precipitating ice (snow) included. However, the models do not have snow fraction available for evaluation. Since the satellite-retrieved hydrometeors include the mixtures of floating, precipitating and convective ice and liquid particles, a filtering method is applied to produce estimates of cloud-only HF (or NPCHF) from the total radiatively-active HF (THF), which is the sum of NPCHF, precipitating ice HF and convective HF. The reference HF data for model evaluation include estimates of liquid-phase NPCHF from CloudSat radar-only data (2B-CWC) and ice-phase THF from CloudSat-CALIPSO 2C-ICE combined radar/lidar data. The model evaluation results show that cloud fraction from CMIP5 multi-model mean (MMM) is significantly underestimated (up to 30 %) against the total HF estimates, mainly below the mid-troposphere over the extratropics and in the upper-troposphere over the midlatitude lands and a few tropical convective regions. The CMIP5 cloud fraction biases are reduced dramatically when compared to the cloud-only HF estimates, but the area of overestimates expands from the tropical convective regions to mid-latitudes in the lower and upper troposphere. There is no CMIP5 standard output snow fraction available for comparison against CloudSat-CALIPSO estimate. The implications of these results show that hydrometeors frequency estimates from CloudSat-CALIPSO provide a reference for GCM’s cloud fraction from stratiform and convective form.
Assessing space weather modeling capability is a key element in improving existing models and developing new ones. In order to track improvement of the models and investigate impacts of forcing, from the lower atmosphere below and from the magnetosphere above, on the performance of ionosphere-thermosphere models, we expand our previous assessment for 2013 March storm event [Shim et al., 2018]. In this study, we evaluate new simulations from upgraded models (Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model version 4.1 and Global Ionosphere Thermosphere Model (GITM) version 21.11) and from NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) version 2.2 including 8 simulations in the previous study. A simulation of NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model version 2 (TIE-GCM 2) is also included for comparison with WACCM-X. TEC and foF2 changes from quiet-time background are considered to evaluate the model performance on the storm impacts. For evaluation, we employ 4 skill scores: Correlation coefficient (CC), root-mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (Yield), and timing error(TE). It is found that the models tend to underestimate the storm-time enhancements of foF2 (F2-layer critical frequency) and TEC (Total Electron Content) and to predict foF2 and/or TEC better in the North America but worse in the Southern Hemisphere. The ensemble simulation for TEC is comparable to results from a data assimilation model (Utah State University-Global Assimilation of Ionospheric Measurement (USU-GAIM)) with differences in skill score less than 3% and 6% for CC and RMSE, respectively.
Laterite is a red weathering crust developed with various rocks and Quaternary loose sediments as its parent material in the tropics and subtropics regions of the world, and it is also the most widely distributed Quaternary earthy accumulation in China. Since the 1930s, most researchers have believed that the fluvial reticulated laterite in southern China was influenced by the warm and humid climate of the Middle Pleistocene. In recent years, the remains of Paleolithic human activities are often found in the reticulated laterite of southern China. However, the study of laterite chronology is sporadic or there is no critical chronological analysis, which causes uncertainty in the identification and discussion of the ages of reticulated laterite and Paleolithic sites in South China. In this study, a paleolithic site found in fluvial reticulated laterite in South China was systematically tested by quartz optical luminescence dating and geomorphic process analysis. The results show that, (1) The T3 terrace, an archive of hominin activity in the study area, primarily formed between 56 and 11 ka. (2) Reticulated laterite cannot be used simply to determine the ages of the Paleolithic sites found in this stratum, and typical reticulated laterite cannot be used as a marker for climatic stratigraphy and chronostratigraphy. The fluvial reticulated laterite in the southern tropics, under suitable hydrothermal conditions, can form within tens of thousands of years or even within 10 ka. (3) Human activities can also lead to an inversion in the age of reticulated red soil.
Atmospheric gravity waves (GWs) span a broad range of length scales. As a result, the un-resolved and under-resolved GWs have to be represented using a sub-grid scale (SGS) parameterization in general circulation models (GCMs). In recent years, machine learning (ML) techniques have emerged as novel methods for SGS modeling of climate processes. In the widely-used approach of supervised (offline) learning, the true representation of the SGS terms have to be properly extracted from high-fidelity data (e.g., GW-resolving simulations). However, this is a non-trivial task, and the quality of the ML-based parameterization significantly hinges on the quality of these SGS terms. Here, we compare three methods to extract 3D GW fluxes and the resulting drag (GWD) from high-resolution simulations: Helmholtz decomposition, and spatial filtering to compute the Reynolds stress and the full SGS stress. In addition to previous studies that focused only on vertical fluxes by GWs, we also quantify the SGS GWD due to lateral momentum fluxes. We build and utilize a library of tropical high-resolution ($\Delta x =3~km$) simulations using weather research and forecasting model (WRF). Results show that the SGS lateral momentum fluxes could have a significant contribution to the total GWD. Moreover, when estimating GWD due to lateral effects, interactions between the SGS and the resolved large-scale flow need to be considered. The sensitivity of the results to different filter type and length scale (dependent on GCM resolution) is also explored to inform the scale-awareness in the development of data-driven parameterizations.
This study develops a new AI-based Self-Adaptive DPC (SADPC) system based on stepwise inference combing with genetic algorithm optimization technologies, including a filtered-clustering inference prediction model (FCI simulator), a stepwise inference controller (SI emulator), a model predictive control controller (MPC controller), a 1st-stage optimizer, and a 2nd-stage optimizer. This system effectively reflects the dynamics and complexity of the biodegradation process and realizes the control for the remediation system based on the feedback information. To achieve this goal, a statistical model for simulating the bioremediation process through the FCI simulator is proposed, which can predict the resulting contamination situation based on the previous contamination situation and control action. Then a bridge between control actions and contamination situations is established through the SI emulator, which can generate a control action based on a given contamination situation. Through running the SADPC system, the desired control action can be identified. Results show that The SADPC system increases the removal rate of benzene and arrives at the remediation goal earlier than other systems. This suggested decision makers that guidelines and policies on remediation-oriented SADPC systems could be tentatively investigated, developed, and applied in the future effort.
The wetting properties of pore walls have a strong effect on multiphase flow through porous media. However, the fluid flow behaviour in porous materials with both complex pore structures and non-uniform wettability are still unclear. Here, we performed unsteady-state quasi-static oil- and waterflooding experiments to study multiphase flow in two sister heterogeneous sandstones with variable wettability conditions (i.e. one natively water-wet and one chemically treated to be mixed-wet). The pore-scale fluid distributions during this process were imaged by laboratory-based X-ray micro-computed tomography (micro-CT). In the mixed-wet case, we observed pore filling events where the fluid interface appeared to be at quasi-equilibrium at every position along the pore body (13% by volume), in contrast to capillary instabilities typically associated with slow drainage or imbibition. These events corresponded to slow displacements previously observed in unsteady-state experiments, explaining the wide range of displacement time scales in mixed-wet samples. Our new data allowed us to quantify the fluid saturations below the image resolution, indicating that slow events were caused by the presence of microporosity and the wetting heterogeneity. Finally, we investigated the sensitivity of the multi-phase flow properties to the slow filling events using a state-of-the-art multi-scale pore network model. This indicated that pores where such events took place contributed up to 19% of the sample’s total absolute permeability, but that the impact on the relative permeability may be smaller. Our study sheds new light on poorly understood multiphase fluid dynamics in complex rocks, of interest to e.g. groundwater remediation and subsurface CO2 storage.
Optimization models for minimizing pollutant exposure from groundwater resources require time and resources that many communities might not have ready access to due to their economic conditions. In such cases, it might be useful to develop a “rule of thumb” approach for suggestions in case of uncertainties and inadequate means to address these uncertainties. Monte Carlo analysis was performed for a simplified groundwater system and the effects of extraction patterns, distance to pollution source, dispersivity, pollutant pulse period, pore water velocity and decay were examined for minimizing the high pollutant exposure risk from the extracted groundwater. Results indicate that, in a high uncertainty scenario, the best bet for minimizing the risk of high pollutant exposure would be to adopt a frequent extraction pattern and supply the water as a mixture of extractions from multiple wells spread over an area. These findings can be used as a “rule of thumb” wherever time and resources might be the limiting factors.
Stream networks are highly abundant across Earth’s surface, reflecting the tectonic and climatic history under which they have developed. Recent studies suggest that branching angles are strongly correlated with climatic aridity. However, the impact of tectonic forcing, especially in tectonically active regions, remains ambiguous. Here we analyze the branching angles of major stream networks on the eastern Tibetan Plateau, a region with complex tectonics, variable climate, and diverse landscapes. We find that spatial variations in tectonic uplift (as reflected in channel gradients) shape the branching geometry of stream networks on the steep eastern margin while in the flat interior of the eastern Tibetan Plateau, branching angles are mainly controlled by climatic aridity. This leads to the conclusion that, in the steep margin of the eastern Tibetan Plateau, climatic impacts on branching angles are overprinted by stronger tectonic controls.
This paper reports on the standing whistler waves upstream of Mercury’s quasi-perpendicular bow shock. Using MESSENGER’s magnetometer data, 36 wave events were identified during interplanetary coronal mass ejections (ICMEs). These elliptic or circular polarized waves were characterized by: (1) a constant phase with respect to the shock, (2) propagation along the normal direction to the shock surface, and (3) rapid damping over a few wave periods. We inferred the speed of Mercury’s bow shock as ~31 km/s and a shock width of 1.76 ion inertial length. These events were observed in 20% of the MESSENGER orbits during ICMEs. We conclude that standing whistler wave generations at Mercury are generic to ICME impacts and the low Alfvén Mach number (MA) collisionless shock, and are not affected by the absolute dimensions of its bow shock. Our results further support the theory that these waves are generated by the current in the shock.