Regional validation of the solar irradiance tool SolaRes in clear-sky conditions, with a focus on the aerosol module
Thierry Elias, Nicolas Ferlay, Gabriel Chesnoiu, Isabelle Chiapello, and Mustapha Moulana
Atmos. Meas. Tech., 17, 4041–4063, https://doi.org/10.5194/amt-17-4041-2024, 2024
In the solar energy application field, it is key to simulate solar resources anywhere on the globe. We conceived the Solar Resource estimate (SolaRes) tool to provide precise and accurate estimates of solar resources for any solar plant technology. We present the validation of SolaRes by comparing estimates with measurements made on two ground-based platforms in northern France for 2 years at 1 min resolution. Validation is done in clear-sky conditions where aerosols are the main factors.
Low-frequency solar radio type II bursts and their association with space weather events during the ascending phase of solar cycle 25
Theogene Ndacyayisenga, Jean Uwamahoro, Jean Claude Uwamahoro, Daniel Izuikedinachi Okoh, Kantepalli Sasikumar Raja, Akeem Babatunde Rabiu, Christian Kwisanga, and Christian Monstein
Ann. Geophys., 42, 313–329, https://doi.org/10.5194/angeo-42-313-2024, 2024
This article reports the first observations of 32 type II bursts in cycle 25 from May 2021 to December 2022. The impacts of space weather on ionospheric total electron content (TEC) enhancement, as measured by the rate of change of TEC index (ROTI), are also studied. According to the current analysis, 19 of 32 type II bursts are connected with imminent space weather occurrences, such as radio blackouts and polar cap absorption events, indicating a high likelihood of space weather disturbance.
Author(s): Ricardo L. M. Bazarin, Christian Naaktgeboren, Silvio L. M. Junqueira, Paulo Cesar Philippi, and Luiz Adolfo Hegele, Jr.
We propose alternative discretization schemes for improving the lattice Boltzmann pseudopotential model for incompressible multicomponent systems, with the purpose of modeling the flow of immiscible fluids with a large viscosity ratio. Compared to the original model of Shan-Chen [Phys. Rev. E 47, 18…
[Phys. Rev. E 110, 015303] Published Mon Jul 08, 2024
Abstract
This study investigates the impact of dust on radiation over the Arabian Peninsula (AP) during the reported high, low, and normal dust seasons (March–August) of 2012, 2014, and 2015, respectively. Simulations were performed using the Weather Research and Forecasting model coupled to a Chemistry module (WRF-Chem). The simulated seasonal horizontal and vertical dust concentrations, and their interannual distinctions, match well with those from two ground-based AERONET observations, and measurements from MODIS and CALIOP satellites. The maximum dust concentrations over the dust-source regions in the southern AP reach vertically upto 700 hPa during the high dust season, but only upto 900–950 hPa during the low/normal dust seasons. Stronger incoming low-level winds along the southern Red Sea and those from Iraq bring in higher-than-normal dust during the high dust summers. We conducted a sensitivity experiment by switching-off the dust module to assess the radiative perturbations due to dust. The results suggest that active dust-module improved the fidelity of simulated radiation fluxes distributions at the surface and top of the atmosphere vis-à-vis Clouds and the Earth's Radiant Energy System (CERES) measurements. Dust results in a 26 Wm−2 short-wave (SW) radiative forcing in the tropospheric-column over the AP. The SW radiative forcing increases by another 6–8 Wm−2 during the high dust season due to the increased number of extreme dust days, which also amplifies atmospheric heating. During extreme dust days, the heating rate exhibits a dipolar structure, with cooling over the Iraq region and warming of 40%–60% over the southern-AP.
Flood exposure of environmental assets
Gabriele Bertoli, Chiara Arrighi, and Enrica Caporali
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-105,2024
Preprint under review for NHESS (discussion: open, 1 comment)
Environmental assets are crucial to sustain and fulfil life on Earth through ecosystem services. Assessing their flood risk is thus seminal, besides required by several norms. Even though, this field is not yet sufficiently developed. We explored the exposure component of the flood risk, and developed an evaluating methodology based on the ecosystem services provided by the environmental assets, to discern assets and areas more important than others with metrics suitable to large scale studies.
As climate change advances, the ocean's overturning circulation is predicted to weaken substantially. With such a slowdown, scientists estimate the ocean will pull down less carbon dioxide from the atmosphere.
Abstract
Magnetotelluric (MT) impedances from 62 sites in southern South Island of Aotearoa New Zealand have been used to model geomagnetically induced currents (GIC) in four transformers during two solar storms. Induced electric fields during the storms are calculated from the MT impedances using the magnetic fields measured at the Eyrewell (EYR) geomagnetic observatory, approximately 200 km north of the study area. Calculated GIC during the sudden storm commencements (SSC) give a generally good match to GIC measured by the network operator, Transpower New Zealand. Long period GIC (periods longer than about 10,000 s) are less well modeled. Calculations based on thin-sheet modeling, which has restrictions on the shortest period of variation which can be modeled, perform less well for the GIC associated with SSC, but are equally good, if not better, at modeling longer period GIC. Consistent underestimation of large GIC at one transformer (HWBT4) near Dunedin are likely to be the result of uncertainty in the assumed values of line, transformer, and earthing resistances. The assumption of a spatially uniform magnetic field across the study area, which is implied by use of the magnetic field measured at EYR as a basis for calculation, may also lead to incorrect calculation of GIC. For one storm use of magnetic field data from a magnetometer within the study area leads to much improved modeling of the observed GIC. This study compares modeled and measured GIC using specifically measured MT impedance data.
Abstract
The high-precision prediction of total ionospheric electron content (TEC) is of great significance for improving the accuracy of global navigation satellite systems. There are two problems with the current prediction of TEC: (a) The existing TEC prediction models mainly based on stacked structure, which has insufficient predictive ability when the network has fewer layers, and loss of fine-grained features when there are more layers, resulting in a decrease in predictive performance; (b) The existing research on ionospheric TEC prediction mainly focuses on building deep learning prediction models, while there is little research on optimizing the hyper-parameters of TEC prediction models. Optimization can help find a better quasi-optimal hyperparameter combination and improve the performance of the model. This paper proposed an automatic deep learning framework for global TEC map prediction, named MAOOA-Residual-Attitude-BiConvLSTM. This framework includes a TEC prediction model, Residual-Attention-BiConvLSTM, which can simultaneously consider both coarse-grained and fine-grained spatiotemporal features. It also includes an optimization algorithm, MAOOA, for optimizing the hyper-parameters of the model. We conducted comparative experiments between our framework and C1PG, ConvLSTM, ConvGRU, and ED-ConvLSTM during high solar activity years, low solar activity years, and a magnetic storm event. The results indicate that in all cases, the framework proposed in this paper outperforms the comparative models.
Abstract
Ionospheric delay, as one of the largest error sources in radio propagation, can only be corrected for this error using the ionospheric delay correction model for Global Navigation Satellite System (GNSS) single-frequency users. In this paper, the 2021 geomagnetic storm event is selected, and based on the measured ionospheric data from the GNSS observatory, the perturbation of the ionosphere by the geomagnetic storm event is analyzed, and it is found that the response of the ionosphere to the geomagnetic storm has obvious differences in the response characteristics and response time in different latitude regions. The performance of the global ionospheric map (GIM), the empirical model, and the broadcast ionospheric model during the geomagnetic storm-induced ionospheric perturbation is analyzed and the change in the accuracy of each ionospheric model during the geomagnetic storm-induced ionospheric perturbation is investigated, using the measured electron content of the GNSS as a benchmark. The results show that there is good agreement between the GIM products and the measured electron content during the period of ionospheric calm and the period of ionospheric perturbation. It is worth noting that geomagnetic storms do not necessarily lead to a decrease in the accuracy of ionospheric delay-correction models, and in some cases, the models that were originally under-accurate show a tendency to improve their accuracy during the period of perturbation instead. Neither the broadcast ionospheric model nor the electron content of the empirical model output responds to geomagnetic storm-induced ionospheric perturbations.
Abstract
Ultra-low frequency (ULF) waves transfer energy and momentum into the ionosphere-thermosphere system. To quantify this energy, this paper first presents a new method to quantitatively detect ULF waves in Incoherent Scatter Radar (ISR) data based on 2D fast-Fourier transforms and subsequent reconstruction of the wave. In parallel with other data sets, including optical, magnetometer, satellite, and models, we present the first full ionospheric energy dissipation rates for a ULF wave, split into electromagnetic (EM) and kinetic fluxes. The EM energy deposition is calculated from the use of the Poynting theorem, looking at Joule and frictional heating rates, where both rates show the same order of magnitude (1.24 × 1013 and 7.3 × 1012 J) respectively when integrated over the wave lifetime of 2 hr 15 min and an area of 4° magnetic latitude × 74° magnetic longitude. However, contrary to the common assumption that the EM flux is dominant, we determined the kinetic flux, to be almost equal in magnitude (8.7 × 1012 J). This indicates that previous papers might have underestimated the total energy dissipation by ULF waves. Compared to the substorm energy budget, we find that locally, the ULF wave event studied here makes up approximately 10% of a typical substorm cycle budget.
Abstract
For the first time, characteristics of the geographical and seasonal distribution of the quasi-diurnal lunar O1 tide were derived from a time series of ionospheric total electron content (TEC) maps provided by International Global Navigation Satellite System Service (IGS). The data analysis is focused on solar minimum in 2008 and 2009 where disturbing influences of geomagnetic and solar activity were minimal. We found that the magnitude of the O1 tide is as strong as the “dominant” semidiurnal lunar M2 tide. Relative amplitudes of 10% and larger are observed in some regions for the O1 component in TEC. The O1 component is particularly strong in northern hemispheric winter over the west coast of South America. There, two maxima occur which are northward and southward of the magnetic equator in the Equatorial Ionization Anomaly (EIA) crest regions. Following Yamazaki et al. (2017, https://doi.org/10.1002/2017ja024601), it might be assumed that a longitudinal anomaly of ionospheric conductivities in the Peruvian sector leads to a stronger modulation of the equatorial electrojet by the lunar tides. Electrodynamic lifting of plasma and transport to the EIA crests may explain the variations of the O1 component in TEC. Contrary to many studies, we find the O1 component (period 25.82 hr) more important than the M1 component (period 24.84 hr, a lunar day). We show that the geographical distribution of the O1 component is totally different from that of the M1 component which is smaller. The seasonal variation of O1 shows maximal amplitudes in northern hemispheric winter and minimal amplitudes in southern hemispheric winter.
Abstract
When solar wind and interplanetary magnetic field (IMF) disturb, thermospheric winds change accordingly. Among the momentum forces driving high-latitude thermospheric winds, ion drag is supposed to greatly affect wind variations through ion-neutral coupling when abrupt and strong changes in ion drifts occur. However, due to the great inertia of thermospheric winds it needs a certain period of time for the wind changes to be prominent both in speed and direction. How long the neutral winds take to change from one steady state to another through the ion-neutral coupling process is currently still a controversial issue. In this paper, we examine the high latitudinal ion-neutral coupling time scale based on the Thermosphere Ionosphere Electrodynamics General Circulation Model simulations, which can determine whether wind variations are dominantly driven by ion drag by analyzing the relative contribution of each momentum force. It is found that the spatial variation of ion-neutral coupling time scale is primarily determined by local electron density, but also varies with neutral density and ion-neutral collision frequency. Simulations during periods of medium solar activity at ∼250 km altitude show that the ion drag-dominated region is generally located at the dayside convection inverse boundary and the coupling time scale (e-folding time) is ∼1 hr when IMF B
y
is the dominant component of the IMF and changes direction. Meanwhile, the southward component of IMF B
z
enlarges the ion drag-dominated region. When IMF B
z
is southward with a large magnitude, ion drag-dominated region is primarily located in the nightside auroral oval with ∼2 hr coupling time scale.
Abstract
Energetic particle injections are commonly observed in Jupiter's magnetosphere and have important impacts on the radiation belts. We evaluate the roles of electron injections in the dynamics of whistler-mode waves and relativistic electrons using Juno measurements and wave-particle interaction modeling. The Juno spacecraft observed injected electron flux bursts at energies up to 300 keV at M shell ∼11 near the magnetic equator during perijove-31. The electron injections are related to chorus wave bursts at 0.05–0.5 f
ce frequencies, where f
ce is the electron gyrofrequency. The electron pitch angle distributions are anisotropic, peaking near 90° pitch angle, and the fluxes are high during injections. We calculate the whistler-mode wave growth rates using the observed electron distributions and linear theory. The frequency spectrum of the wave growth rate is consistent with that of the observed chorus magnetic intensity, suggesting that the observed electron injections provide free energy to generate whistler-mode chorus waves. We further use quasilinear theory to model the impacts of chorus waves on 0.1–10 MeV electrons. Our modeling shows that the chorus waves could cause the pitch angle scattering loss of electrons at <1 MeV energies and accelerate relativistic electrons at multiple MeV energies in Jupiter's outer radiation belt. The electron injections also provide an important seed population at several hundred keV energies to support the acceleration to higher energies. Our wave-particle interaction modeling demonstrates the energy flow from the electron injections to the relativistic electron population through the medium of whistler-mode waves in Jupiter's outer radiation belt.
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, 2024
Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, 2024
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Abstract
In this paper, we propose a solution of designing a topside broadcast ionospheric model to enable the future low earth orbit (LEO) navigation augmentation (LEO-NA) services. Considering the lack of global station observations to develop the LEO-NA ionosphere model, we utilize abundant global navigation satellite system (GNSS) data from LEO satellites to determine the topside global broadcast ionospheric delay. This delay can be combined with existing GNSS broadcast ionospheric delay correction models to determine LEO-NA ionospheric delay. First, the performance of the different-order spherical harmonic (SH) model is evaluated in generating a global topside ionospheric map. The results indicate that by increasing the order from 1 to 2, the internal and external accuracy of the model improves significantly. However, increasing the order from 2 to 8 leads to a decrease in accuracy of 0.10 and 0.11 TECU (total electron content unit) for the internal and external root mean square error. Taking into account compatibility with the Beidou global ionospheric delay correction model, limited data capacity in the navigation message, ionospheric model accuracy, and computational efficiency, we select the second-order SH model as the topside ionosphere broadcast model and outline the strategy for calculating broadcast coefficients. Finally, the accuracy of the topside global broadcast ionospheric delay correction model is evaluated during periods of high and low solar activity. The mean values of root mean square in 2009 and 2014 are 1.49 and 1.88 TECU, respectively. The model in 2009 and 2014 can correct for 67.30% and 72.49% of the ionospheric delay, respectively.
Nature Geoscience, Published online: 08 July 2024; doi:10.1038/s41561-024-01484-4
Nitrogen deposition in China decreased by 14% between 2010 and 2020, with greater declines in nitrogen from industrial than agricultural sources, according to decadal observations of atmospheric deposition of different forms of reactive nitrogen.
AbstractMining operations result in changes of the subsurface stress field that can lead to the occurrence of microseismic events. The development of strategies for forecasting and avoidance of significant events is crucial for safe and efficient operations of mines. One such example, discussed here is the observed induced microseismicity in soft rock potash mines. It is primarily driven by the rock excavations but can also be triggered by preceding events or can result from the delayed effects of plastic creep of soft rocks. Therefore, it is important from seismic hazard assessment and risk mitigation points of view to understand the statistical aspects of microseismicity in potash or other types of mines. In this study, the temporal evolution of the induced microseismicity from a potash mine in Saskatchewan is analyzed and modeled. Specifically, the epidemic type aftershock sequence (ETAS) model is used to approximate the occurrence rate of the induced mining microseismicity. The estimated parameters signify that the microseismicity displays swarm-type characteristics with limited inter-event triggering. Moreover, the Bayesian predictive framework is used to compute the probabilities of the occurrences of the largest expected events above a certain magnitude for prescribed forecasting time intervals during the evolution of the sequence. This approach for computing the probabilities allows one to incorporate fully the uncertainties of the model parameters. The Markov Chain Monte Carlo (MCMC) sampling of the posterior distribution are used to generate parameter chains to quantify their variability. Furthermore, several statistical tests are conducted to assess the credibility of the obtained retrospective forecasts compared to the observed microseismicity. The obtained results show that the developed approach can accurately forecast the number of events and intensity of the sequence. It also provides a framework for computing the probabilities for the largest expected events.
Abstract
Both historical observations and recent modeling studies reveal a faster warming in the Arctic compared to the Antarctic. To understand the role of the Antarctic Circumpolar Circulation (ACC) in this warming asymmetry, we simulate the climate mean state and climate response to doubled CO2 under different climate mean ACC states by closing or opening the Drake Passage (DP) with the Community Earth System Model. From closed to open DP, a stronger climate mean ACC leads to a stronger climate mean Atlantic Meridional Overturning Circulation (AMOC), as well as a colder Antarctic but a warmer Arctic in the climate mean state. The less climate mean sea ice coverage in a warmer Arctic implies less extensive sea ice melting under global warming. This causes a reduced asymmetry in warming between the two poles in response to the doubled CO2.
Abstract
The Great Arctic Cyclone 2012 (AC12) is used to understand the role of initial condition errors in the predictability at 2–3-day forecast range of a high-impact summer Arctic Cyclone (AC). Ensemble sensitivity analysis (ESA) is first performed to identify potentially sensitive regions of the cyclone evolution using an ensemble baseline forecast with conventional in situ observations assimilated. A pseudo-observation method is then introduced to investigate impacts of hypothetical observations in these sensitive but unobserved regions. In the baseline experiments with in situ observations assimilated, the forecasted AC12 reaches its peak intensity 18 hr earlier than in the verifying Global Forecast System Analysis (GFS-ANL) and the cyclone track is biased toward the southwest. Using ESA, the time of peak intensity and the cyclone track error are identified to be sensitive to the upstream trough, downstream ridge, and the tropopause polar vortex (TPV) to the northeast (NE TPV) of the AC12. These features were not observed by the in situ observation networks. To examine the impact of the observation gaps, pseudo-observations drawn from GFS-ANL are assimilated. Pseudo-observations sample the three features separately to study the impact of the initial condition error on the predictability of AC12. The cyclone peak intensity timing error and track error are greatly reduced when the initial condition error is reduced near the NE TPV. A southward expansion of the NE TPV and the corresponding southward shifting low-level front lead the forecasted AC12 to progress to the east, which better agrees with the verifying GFS-ANL.
