Feed aggregator

Abstract

The discussion about the origin of the zebra pattern has been going on for more than 50 years. In many papers it is usually postulated that the double plasma resonance mechanism always works in the presence of fast particles in the magnetic trap. Due to a number of difficulties encountered by this mechanism, works on its improvement began to appear, mainly in a dozen papers by Karlický and Yasnov, where the whole discussion is based on variability of the ratio of the magnetic field and density height scales and the assumption of some plasma turbulence in the source. Here we show possibilities of an alternative model of the interaction between plasma waves and whistlers. Several phenomena were selected in which it is clear that the ratio of height scales does not change in the magnetic loop as the source of the zebra pattern. It is shown that all the main details of the sporadic zebra pattern in the phenomenon of August 1, 2010 (and in many other phenomena), can be explained within the framework of a unified model of zebra patterns and radio fibers (fiber bursts) in the interaction of plasma waves with whistlers. The main changes in the zebra pattern stripes are caused by scattering of fast particles by whistlers leading to switching of the whistler instability from the normal Doppler effect to the anomalous one. In the end, possibilities of laboratory experiments are considered and the solar zebra pattern is compared with similar stripes in the decameter radio emission of Jupiter.

Abstract

During the expansion phase of a substorm, the poleward jump of auroras (breakup) and the expansion of the auroral bulge are observed. The expansion is accompanied by a negative magnetic bay under the aurora and a positive magnetic bay at mid-latitudes. The magnitude of the negative bay is characterized by the auroral AL-index. The Mid-Latitude Positive Bay index (MPB-index) was previously proposed in order to characterize the positive bay. In this article, the statistical relationship of the MPB-index with the geomagnetic activity at different latitudes and with the parameters of the solar wind and interplanetary magnetic field is investigated. It is shown that all extremely high values of the MPB-index (above 10 000 nT2) are observed during strong geomagnetic storms (when the Dst-index falls below –100 nT), all extremely strong geomagnetic storms (when the Dst-index falls below –250 nT) are accompanied by extremely high values of the MPB-index. Statistically, the MPB-index increases with increasing geomagnetic activity at any latitude. On average, the MPB-index increases with increasing interplanetary magnetic field magnitudes and any of its components. However, for the Bz-component, large values of the MPB-index are observed at its southward orientation. For the plasma parameters of the solar wind, the MPB-index increases most strongly with the increase of its speed. The dependence on the dynamic pressure and on the value of the EY-component of the electric field of the solar wind is also strong. However, the MPB-index weakly depends on the density and temperature of the solar wind.

Abstract

Ionospheric disturbances that accompanied the moderate magnetic storm on January 14–20, 2022, are analyzed. The work is based on data obtained from vertical and oblique ionospheric sounding in the northeastern region of Russia and supplemented by observations at HF radars and magnetic observatories. It has been revealed that the amplitudes of positive and negative ionospheric disturbances accompanying this storm are comparable to those observed on other days of January during weak magnetic storms and disturbances. The specific features of the disturbances observed only during the storm in question are as follows: (1) a midnight–morning increase in the maximum observed frequency of one-hop mode of HF radio wave propagation on the paths Norilsk–Tory and Magadan–Tory on 14 January; (2) enhancement of nighttime fluctuations of the critical frequency in the F2 layer in Irkutsk and the maximum observed frequency of one-hop mode on the path Magadan–Tory on January 15; and (3) morning–midday Es layers with limiting frequencies reaching 7 MHz that were observed in mid-latitudes at the end of the first day and beginning of the second day of the storm recovery phase.

Abstract

In this work the problem of reconstructing the vector anomalous magnetic field from single-component data was solved by means of artificial neural networks. For training an artificial neural network a database of anomalous magnetic field components \({{B}_{x}}\) , \({{B}_{y}}\) , \({{B}_{z}}\) was created using a set of point magnetic dipoles lying under the field measurement plane. Using a synthetic example, the work of a trained neural network was shown in comparison with a well-known numerical algorithm for restoring a vector field from data of one component. Further, according to the data of the vertical component of the anomalous geomagnetic field the horizontal components of the anomalous geomagnetic field were restored using artificial neural networks in the territory of 58°–85° E, 52°–74° N with a grid step of 2 arc minutes.

Abstract

Events of induced proton precipitations from the inner radiation belt have been detected. They accompanied almost a half (11) of 25 anomalous electron precipitations recorded onboard the Meteor-M No. 2 satellite in 2014−2022 in Oceania at low latitudes in the morning hours of local time under quiet geomagnetic conditions. It is surmised that such events could be provoked by proton fall into cyclotron resonance with low-frequency radiation stimulated by a mobile ionospheric heater. The observed effects in anomalous electron precipitations which may be interpreted in the framework of the mobile ionospheric heater conception are also discussed.

Abstract

The article presents the results of a comparative analysis of the solar proton event on March 30, 2022, which has an unusual time profile of solar proton fluxes, and the previous and subsequent solar proton events (March 28, 2022, and April 02, 2022). Increases in energetic proton fluxes in the interplanetary and near-Earth space are associated with successive solar X-ray flares M4.0, X1.3, and M3.9 and three halo-type coronal mass ejections. The study was based on experimental data obtained from spacecraft located in the interplanetary space (ACE, WIND, STEREO A, and DSCOVR), in a circular polar orbit at an altitude of 850 km (Meteor-M2) and in geostationary orbit (GOES-16, Electro-L2). An explanation has been proposed for the specific features of the energetic proton flux profile in the solar proton event on March 30, 2022: protons accelerated in the flare on March 30, 2022 were partially screened by an interplanetary coronal mass ejection, the source of which was the explosive processes on the Sun on March 28, 2022; late detection of maximum proton fluxes, simultaneous for particles of different energies, is due to the arrival of particle fluxes inside an interplanetary coronal mass ejection. The spatial distribution of solar protons in near-Earth orbit was similar to the distribution at the Lagrange point L1 but with a delay of ~50 min.

Abstract—

Attempts have been made repeatedly to investigate the effect of the geomagnetic activity on the equatorial plasma bubble (EPB) generation. At the moment, it is generally accepted that the geomagnetic activity tends to suppress the EPB generation and evolution in the pre-midnight sector. As for the post-midnight sector, it is believed that the EPB occurrence probability will increase after midnight as the geomagnetic activity increases. Moreover, the growth rates of the EPB occurrence probability will strongly depend on the solar activity: at the solar activity minimum, they will be the most significant. A sufficient amount of the observations is required to confirm these ideas. For this purpose, the EPB observations obtained on board the ISS-b satellite (~972–1220 km, 1978–1979) in the pre- and post-midnight sectors are best suited. The data were considered in two latitudinal regions: the equatorial/low-latitude (±20°) and mid-latitude ±(20°–52°) regions. The LT- and Kp-variations of the EPB occurrence probability were calculated for both groups. (1) It was revealed that the occurrence probability maximum of the EPBs recorded at the equator and low latitudes is observed in the premidnight sector. The EPB occurrence probability decreases with increasing the Kp-index with a delay of 3 and 9 h before the EPB detection. (2) However, the occurrence probability maximum of the EPBs recorded at the mid-latitudes occurs in the post-midnight sector. Their occurrence probability increases slightly with the increase of the Kp-index taken 9 h before the EPB detection. Thus, the idea of the ionospheric disturbance dynamo (IDD) influence on the post-midnight EPB generation has been confirmed. The IDD mechanism “switched on” after some hours of the enhanced geomagnetic activity and favors the generation. However, its influence is weakened during the years of increased solar activity.

Abstract

Positioning, navigation and time are the cornerstones of satellite navigation. These aspects are frequently affected by ionospheric variations caused by solar flares (SF). In this study, we have attempted to predict the range error (RE) caused by ionospheric delay in Global Positioning System (GPS) signals during six different X-class SF that occurred in the 25th solar cycle using two different approaches, namely, a recurrent neural network (RNN) and the ordinary Kriging-based surrogate model (OKSM). The total electron content (TEC) collected from Hyderabad station along with other input parameter includes the Planetary A and K index (Ap and Kp), solar sunspot number (SSN), disturbance storm time index (Dst), and radio flux measured at 10.7 cm (F10.7) were used for prediction. The OKSM uses the previous six days of datasets to predict the RE on the seventh day, whereas the RNN model uses the previous 45 days of datasets to predict the RE on the 46th day. The performance of both models is evaluated using statistical parameters such as root mean square error (RMSE), normalized root mean square error (NRMSE), Pearson’s correlation coefficient (CC), and symmetric mean absolute percentage error (sMAPE). The results indicate that the OKSM performs well in adverse space weather conditions when compared to RNN.

Abstract

The induction and momentum equations are simplified to a dynamical system for the kinetic and magnetic energies in Earth’s core. Stable stationary points of this system give a geomagnetic field of ~10 mT and the cosecant of the angle between the magnetic field vector and fluid velocity vector is on average about 500 at a known speed of ~1 mm/s and a generally accepted dynamo power of ~1 TW. With a generally known typical geomagnetic time on the order of 1000 years, harmonic secular variations on the order of several decades and rapid exponential changes on the order of several months, possibly associated with jerks, were obtained. All this agrees well with dynamo theory, paleomagnetic reconstructions, numerical modeling, and observations. A geomagnetic energy of ~10 mJ/kg is four orders of magnitude greater than the kinetic energy. Under conditions of such dominant magnetic energy, an analytical solution was obtained, which over time converges to stable stationary points. Apparently unlikely catastrophes with virtually zero magnetic energy near partially stable stationary points are discussed.

Abstract

The study estimates the contribution of middle-scale solar wind structures (variations recorded by a spacecraft during ~10 min intervals) in turbulence development in the transition region behind the bow shock. The analysis is based on simultaneous measurements of plasma and/or magnetic field parameters in the solar wind, in the dayside magnetosheath, and on the flanks. The study adopts measurements by Wind, THEMIS, and Spektr-R spacecraft. The properties of the magnetic field and ion flux fluctuation spectra are analyzed in the 0.01–4 Hz frequency range, which corresponds to the transition from MHD to kinetic scales. The dynamics of turbulence properties in the magnetosheath is governed by large-scale disturbances, while structures with smaller scales have an effect in the absence of large-scale structures.

Abstract

The results of identifying trends in the annual average ionospheric indices ΔIG and ΔT are presented, obtained after excluding from IG and T the dependence of these indices on the annual average solar activity indices. The solar activity indices were F10, Ly-α, and MgII—solar radiation fluxes at 10.7 cm, in the Lyman-alpha line of hydrogen (121.567 nm), and the ratio of the central part to the flanks in the magnesium emission band 276–284 nm. Two time intervals (in years) are considered: 1980–2012 and 2013–2023. It was found that in 1980–2012, all analyzed linear trends were negative: the ΔIG and ΔT values decreased over time; they were very weak and insignificant. Fluctuations of ΔIG and ΔT with respect to trends for Ly-α were almost twice as large as for F10 and MgII. In the interval of 2013–2023, all analyzed linear trends intensified and became significant: the rate of decrease in ΔIG and ΔT over time increased. For MgII this rate was almost twice as high as for F10. For 2013–2023, the MgII index overestimated the contribution of solar radiation to ionospheric indices, especially during the growth phase of solar cycle 25, which began at the end of 2019. As a result, in the growth phase of solar cycle 25, the F10 index became a more adequate solar activity indicator for ionospheric indices than MgII. In the interval of 1980–2012, the F10 and MgII indices changed almost synchronously. The growth phase of solar cycle 25 was the first case this synchrony was disrupted for the entire period of MgII measurements.

Abstract

Accurate diagnosis of regional atmospheric and surface energy budgets is critical for understanding the spatial distribution of heat uptake associated with the Earth’s energy imbalance (EEI). This contribution discusses frameworks and methods for consistent evaluation of key quantities of those budgets using observationally constrained data sets. It thereby touches upon assumptions made in data products which have implications for these evaluations. We evaluate 2001–2020 average regional total (TE) and dry static energy (DSE) budgets using satellite-based and reanalysis data. For the first time, a consistent framework is applied to the ensemble of the 5th generation European Reanalysis (ERA5), version 2 of modern-era retrospective analysis for research and applications (MERRA-2), and the Japanese 55-year Reanalysis (JRA55). Uncertainties of the computed budgets are assessed through inter-product spread and evaluation of physical constraints. Furthermore, we use the TE budget to infer fields of net surface energy flux. Results indicate biases < 1 W/m2 on the global, < 5 W/m2 on the continental, and ~ 15 W/m2 on the regional scale. Inferred net surface energy fluxes exhibit reduced large-scale biases compared to surface flux data based on remote sensing and models. We use the DSE budget to infer atmospheric diabatic heating from condensational processes. Comparison to observation-based precipitation data indicates larger uncertainties (10–15 Wm−2 globally) in the DSE budget compared to the TE budget, which is reflected by increased spread in reanalysis-based fields. Continued validation efforts of atmospheric energy budgets are needed to document progress in new and upcoming observational products, and to understand their limitations when performing EEI research.

Abstract

In the tropics, deep convection, which is often organized into convective systems, plays a crucial role in the water and energy cycles by significantly contributing to surface precipitation and forming upper-level ice clouds. The arrangement of these deep convective systems, as well as their individual properties, has recently been recognized as a key feature of the tropical climate. Using data from Africa and the tropical Atlantic Ocean as a case study, recent shifts in convective organization have been analyzed through a well-curated, unique record of METEOSAT observations spanning four decades. The findings indicate a significant shift in the occurrence of deep convective systems, characterized by a decrease in large, short-lived systems and an increase in smaller, longer-lived ones. This shift, combined with a nearly constant deep cloud fraction over the same period, highlights a notable change in convective organization. These new observational insights are valuable for refining emerging kilometer-scale climate models that accurately represent individual convective systems but struggle to realistically simulate their overall arrangement.

Abstract

As observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) missions, global terrestrial water storage (TWS), excluding ice sheets and glaciers, declined rapidly between May 2014 and March 2016. By 2023, it had not yet recovered, with the upper end of its range remaining 1 cm equivalent height of water below the upper end of the earlier range. Beginning with a record-setting drought in northeastern South America, a series of droughts on five continents helped to prevent global TWS from rebounding. While back-to-back El Niño events are largely responsible for the South American drought and others in the 2014–2016 timeframe, the possibility exists that global warming has contributed to a net drying of the land since then, through enhanced evapotranspiration and increasing frequency and intensity of drought. Corollary to the decline in global TWS since 2015 has been a rise in barystatic sea level (i.e., global mean ocean mass). However, we find no evidence that it is anything other than a coincidence that, also in 2015, two estimates of barystatic sea level change, one from GRACE/FO and the other from a combination of satellite altimetry and Argo float ocean temperature measurements, began to diverge. Herein, we discuss both the mechanisms that account for the abrupt decline in terrestrial water storage and the possible explanations for the divergence of the barystatic sea level change estimates.

Abstract

This study uses an oceanic energy budget to estimate the ocean heat transport convergence in the North Atlantic during 2005–2018. The horizontal convergence of the ocean heat transport is estimated using ocean heat content tendency primarily derived from satellite altimetry combined with space gravimetry. The net surface energy fluxes are inferred from mass-corrected divergence of atmospheric energy transport and tendency of the ECMWF ERA5 reanalysis combined with top-of-the-atmosphere radiative fluxes from the clouds and the Earth’s radiant energy system project. The indirectly estimated horizontal convergence of the ocean heat transport is integrated between the rapid climate change-meridional overturning circulation and heatflux array (RAPID) section at 26.5°N (operating since 2004) and the overturning in the subpolar north atlantic program (OSNAP) section, situated at 53°–60°N (operating since 2014). This is to validate the ocean heat transport convergence estimate against an independent estimate derived from RAPID and OSNAP in-situ measurements. The mean ocean energy budget of the North Atlantic is closed to within ± 0.25 PW between RAPID and OSNAP sections. The mean oceanic heat transport convergence between these sections is 0.58 ± 0.25 PW, which agrees well with observed section transports. Interannual variability of the inferred oceanic heat transport convergence is also in reasonable agreement with the interannual variability observed at RAPID and OSNAP, with a correlation of 0.54 between annual time series. The correlation increases to 0.67 for biannual time series. Other estimates of the ocean energy budget based on ocean heat content tendency derived from various methods give similar results. Despite a large spread, the correlation is always significant meaning the results are robust against the method to estimate the ocean heat content tendency.

Abstract

In 1979, Herbert Riehl and Joanne Simpson (Malkus) analytically estimated that 1600–2400 undilute convective cores vertically transport energy to the tropopause at any given time within a region where upper-tropospheric energy is only exported from the tropics. The focus of this paper is to update this estimate using modern satellite observations, compare hot tower frequency and intensity characteristics to all deep convective cores that reach the upper troposphere, and document hot tower spatiotemporal variability in relation to precipitation and high cloud properties within the tropical trough zone (between 13 °S and 19 °N). Cloud vertical profiles from CloudSat and CALIPSO measurements supply convective core diameters and proxies for intensity and convective activity, and these proxies are augmented with brightness temperature data from geostationary satellite observations, precipitation information from IMERG, and cloud radiative properties from CERES. Less than 35% of all deep cores are classified as hot towers, and we estimate that 800–1700 hot towers occur at any given time over the course of a day, with the mean maximum core and hot tower frequency occurring at the time of year when peak convective intensity and precipitation occur. Convective objects that contain hot towers frequently contain multiple cores, and the largest systems with five or more distinct cores most frequently occur in regions where organized mesoscale convective systems and the highest climatological mean rain rates are known to occur. Analysis of co-located radar and infrared brightness temperatures reveals that passive observations alone are not sufficient to unambiguously distinguish hot towers using simple brightness temperature thresholds.

Abstract

This study aims to revisit the classic “hot tower” hypothesis proposed by Riehl and Simpson (Malkus) in 1958 and revisited in 1979. Our investigation centers on the convective mass flux of hot towers within the tropical trough zone, using geostationary (GEO) satellite data and an innovative analysis technique, known as ML16, which integrates various data sources, including hot tower heights, ambient profiles, and a plume model, to determine convective mass flux. The GEO-based ML16 approach is evaluated against collocated ground-based radar wind profiler observations, showing broad agreement. Our GEO-based estimate of hot tower convective mass flux, 2.8 × 1011–3.4 × 1011 kg s−1, is similar to the revisited estimate in Riehl and Simpson (1979), 2.6–3.0 × 1011 kg s−1. Additionally, our analysis gives a median count of around 550 hot towers with a median size of about 11 km, in contrast to the previous estimates of 1600–2400 hot towers, each characterized by a fixed size of 5 km. We discuss the causes of these discrepancies, emphasizing the fundamental differences between the two approaches in characterizing tropical hot towers. While both approaches have various uncertainties, the evidence suggests that greater credibility should be placed on results derived from direct satellite observations. Finally, we identify future opportunities in Earth Observations that will provide more accurate measurements, enabling further evaluation of the role played by tropical hot towers in mass transport.

Abstract

The global seasonal cycle of energy in Earth’s climate system is quantified using observations and reanalyses. After removing long-term trends, net energy entering and exiting the climate system at the top of the atmosphere (TOA) should agree with the sum of energy entering and exiting the ocean, atmosphere, land, and ice over the course of an average year. Achieving such a balanced budget with observations has been challenging. Disagreements have been attributed previously to sparse observations in the high-latitude oceans. However, limiting the local vertical integration of new global ocean heat content estimates to the depth to which seasonal heat energy is stored, rather than integrating to 2000 m everywhere as done previously, allows closure of the global seasonal energy budget within statistical uncertainties. The seasonal cycle of energy storage is largest in the ocean, peaking in April because ocean area is largest in the Southern Hemisphere and the ocean’s thermal inertia causes a lag with respect to the austral summer solstice. Seasonal cycles in energy storage in the atmosphere and land are smaller, but peak in July and September, respectively, because there is more land in the Northern Hemisphere, and the land has more thermal inertia than the atmosphere. Global seasonal energy storage by ice is small, so the atmosphere and land partially offset ocean energy storage in the global integral, with their sum matching time-integrated net global TOA energy fluxes over the seasonal cycle within uncertainties, and both peaking in April.

Abstract

Since the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrievals have been developed. The new global long-term cloud datasets show, in general, similar results to those of the previous assessment. A notable exception is the reduced cloud amount provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Science Team, resulting from an improved aerosol–cloud distinction. Height, opacity and thermodynamic phase determine the radiative effect of clouds. Their distributions as well as relative occurrences of cloud types distinguished by height and optical depth are discussed. The similar results of the two assessments indicate that further improvement, in particular on vertical cloud layering, can only be achieved by combining complementary information. We suggest such combination methods to estimate the amount of all clouds within the atmospheric column, including those hidden by clouds aloft. The results compare well with those from CloudSat-CALIPSO radar–lidar geometrical profiles as well as with results from the International Satellite Cloud Climatology Project (ISCCP) corrected by the cloud vertical layer model, which is used for the computation of the ISCCP-derived radiative fluxes. Furthermore, we highlight studies on cloud monitoring using the information from the histograms of the database and give guidelines for: (1) the use of satellite-retrieved cloud properties in climate studies and climate model evaluation and (2) improved retrieval strategies.